All posts by Anirudh Singhal

Alzheimer’s patients now also have access to Transcranial Pulse Stimulation (TPS) in Munich

News

Alzheimer’s patients now also have access to Transcranial Pulse Stimulation (TPS) in Munich – one of the leading medical cities in Germany. In July 2021, a NEUROLITH system was installed in the private practice Schleicher & Brückl. It is the first NEUROLITH in the capital of Bavaria, the largest German state.

Dr Peter Schleicher, who runs the practice together with his daughter, has been a convinced shock wave user for many years. Based on the available studies and previous treatment results, he has now also included TPS, which is also based on shock waves, in his range of therapies.

As a result of the installation in Munich, Alzheimer’s patients and their relatives now have access to 10 TPS treatment centres in Germany.

 

Klinikum Wahrendorff and private practice in Hamburg opt for the NEUROLITH

News

In early May 2021, two more NEUROLITH systems were installed in Germany. Both the renowned Klinikum Wahrendorff in Sehnde near Hanover and the private practice of Prof. Dr Musa Citak in Hamburg are expanding their range of therapies with Transcranial Pulse Stimulation (TPS).

Prof. Dr Marc Ziegenbein, Medical Director and Chief Physician (right) &
Oliver Rosenthal, Senior Physician

The Klinikum Wahrendorff, led by chief physician Prof. Dr Marc Ziegenbein opened in May 2021 a new, modern treatment centre specifically for the early stimulation/maintenance of the mental abilities of people with Alzheimer’s disease. Transcranial Pulse Stimulation (TPS) with the NEUROLITH is part of the special therapy offer.

In addition, patients with Alzheimer’s dementia can now also be treated with the NEUROLITH system in Hamburg. Prof. Dr Citak was one of the first doctors in northern Germany to opt for the TPS system. »The first few patients are making very good progress. Relatives are very surprised and pleased by the positive effect,« says Prof. Dr Citak. In his private practice, the shock wave expert also uses various shock wave systems as well as a system for Extracorporeal Magnetotransduction Therapy (EMTT) from STORZ MEDICAL.

About TPS treatment
In 2018, Transcranial Pulse Stimulation (TPS) with the NEUROLITH system was the first, and hitherto only, procedure of its kind to obtain market authorization for the »treatment of the central nervous system of patients with Alzheimer’s disease«. TPS can stimulate deep cerebral regions, reaching as much as 8 cm into the brain.

Studies conducted at the University of Vienna under the direction of Prof. Dr Roland Beisteiner demonstrated a significant increase in cognitive performance in the CERAD test and a decrease in the Becks Depression Index in patients with mild to moderate dementia.(1) In addition, a significant correlation between neuropsychological improvement and cortical thickness increase in AD-critical brain areas was found after TPS treatment.(2)

In an ongoing study, Prof. Dr Beisteiner is investigating the effect of TPS therapy on the course of the disease in patients with Parkinson’s.

Sources:

1. Beisteiner, R. et. al., Adv Sci (Weinh). 2019 Dec 23;7(3):1902583. doi: 10.1002/advs.201902583.

2. Popescu, T. et al., Alzheimers Dement (N Y). 2021 Feb 25;7(1):e12121. doi: 10.1002/trc2.12121.

All new CGX Quick headsets with live impedance measurement by means of LEDs now available

News, Product Updates

Since introducing the CGX Quick systems into our portfolio in 2020, several updates have been made to improve your overall experience with this dry electrode headset. Whether you are conducting research in neuromarketing, neuroergonomics, mobile applications or other fields where an easy to apply headset is needed, the updates recently made to the Quick Systems are sure to enhance the experience of both the researcher and the participant.

What’s new? 

The new Quick-32r and Quick-20r v2 have been updated to include on-board impedance checking by means of LEDs, a Brain Products’ patented technology which is implemented in our actiCAP slim electrodes. This handy feature eases your set-up as you can directly see the range of the electrode’s impedance at each site in real-time without having to check the recording software. BrainVision Recorder for CGX not only allows online impedance checking and has an LSL outlet, but is also compatible with RecView to perform online analysis.

CGX Quick-20r v2 and Quick-32r

CGX Quick-20r v2 (left) and Quick-32r (right)

Powered by AA batteries, you can get up to 8 hours of recording time with your new CGX Quick system. These attributes help reduce your set-up time and provide you with all the tools necessary to conduct your research studies.

Moreover, with the participants’ experience in mind, sensors were redesigned for faster set-up through the hair and increased comfort, for up to 60-minute recording sessions. This new and improved design has clear benefits for both the research technician, as well as the participant. As we’ve shown in previous webinars, the CGX headset can be self-donned, meaning that it is easy enough for the participant to apply all on their own without the assistance of a research technician.

For a closer look at getting started with the new Quick Systems, check out this video.

Are you thinking of upgrading?

Whether you recently purchased a Quick system from CGX or your local distributor, or were one of the early adopters of these headsets, we have attractive loyalty and trade-in offers to facilitate your upgrade to the newest product bundle. If your system (Quick-30 or Quick-20r) is less than 3 years old and you wish to upgrade, your newly purchased Quick-32r or Quick-20r v2 will be discounted. Similarly, you can trade in any Quick-30 or Quick-20r, regardless of condition, if you are ordering a new Quick-32r or Quick-20r v2. Trade-in pricing is determined based on the age of the Quick system.

If you’d like to know more about this product and these exceptional upgrade options, please contact us (via email, contact form or chat) or your local distributor for more information or a product demo. Be sure to register for our upcoming webinar on introducing the new Quick systems and stay tuned for other upcoming online events.

R-Nets with infants: a walkthrough

News, Product Updates

What happens in the brain of infants is especially interesting to developmental and neurocognitive psychologists. Up to now using EEG on infants, however, was a scientifically risky process with lots of dropout due to the long and – for the infant – uncomfortable preparation of the measurement. With the new R-Net system, the preparation time can be reduced to about five minutes – giving the scientists more time to collect good data.

In this guide, we provide a detailed walkthrough showing how to use the R-Net in studies with infants.

Overview

1. Before the participant arrives
a. Provide sufficient information to the caregivers 
b. Preparation of materials 

2. When the participant arrives
a. Inform the caregivers and make sure the infant is fine 
b. Fit the R-Net 
c. Adjust the cables 
d. Check impedances 

3. Starting the measurement
a. Instruct caregivers 
b. Record video of the experiment 

4. After the experiment
a. Show signal to caregiver 
b. Clean the equipment 

1. Before the participant arrives

a. Provide sufficient information to the caregivers

Often caregivers are not familiar with the EEG measurement and are afraid to participate in EEG experiments with their infants. When inviting the families, always make sure to provide an information sheet in which you explain the technique, state possible risks such as skin irritations, and list possible counter indications. You can also include pictures of an infant with the cap (make sure to have the consent of the family for this) so the caregivers know what to expect.

Some caregivers expect that bringing their infant to an EEG measurement will provide them with medical information about the infant. Thus, it is important to state that the measurement does not have a diagnostic purpose and that you cannot deliver any medical information.

In contrast to EEG measurements with adults, infants do not need to come with their hair washed. As they have little and thin hair, the measurement works well without it. With the R-Nets, the infants also do not need their hair to be washed after the experiment. It only gets a little wet, but you can easily rub it dry with a towel or use a hair dryer.

If you do not have the possibility to measure the head circumference of the infant yourself before the EEG measurement, you can use the pre-testing information to ask for it. Infants regularly visit the doctor and have their head circumference measured there – if the last measurement is not more than four weeks ago, you can use that number. Heads do not grow as fast as the rest of the body.

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b. Preparation of materials

Make sure to have the materials you need during the testing prepared. This should include:

  • an interesting toy for the infant in case you need distraction
  • a selection of infant-friendly videos you can play during the preparation
  • hook and loop fasteners or other material to fix the cap’s cables
  • a measurement band

You can already prepare the solution needed to prepare the R-Net. For this, fill the measurement cup labelled “electrolyte/water” with 1.5 liters of distilled water and add 1 teaspoon of potassium chloride (KCl) per liter (i.e. 1.5 spoons). Also, add a couple of drops of baby shampoo. Mix the solution.

 Tip: This video shows how to prepare the solution.

If you know the head circumference of the infant, you can put the R-Net of the correct size into the mix already. You know the size of the net from a small label close to the white plastic bar (this is called the “clamping block”). Take the size that is closest to the head circumference of the infant. If the circumference is in between two cap sizes, take the larger one so that the infant’s ears fit nicely into the cap. When you put the net in the solution, make sure to cover the splitter boxes with a towel, so they do not get wet. You can also store them on a shelf above the measurement cup to make sure no water drips on them. Make sure that the whole R-Net is within the solution. The net needs to soak for a minimum of 15 minutes but not more than 30 minutes. For example, you can put it into the solution 15 minutes before the scheduled appointment and set a timer for 30 minutes so that you know when to take it out of the solution if the family is running late. If you have other experimental tasks planned before the EEG measurement (something we would not recommend), make sure to plan the soaking time accordingly.

You can already prepare the disinfection solution. For this and for cleaning the R-Net, Brain Products officially recommends using distilled water; however, we’ve been using filtered water instead and so far, everything works fine in our lab with this alternative solution. (Be aware that this may increase corrosion of the material). Fill 1.5 liters of distilled/filtered water in the measurement cup labelled “disinfection”. Add the appropriate amount of your disinfectant and stir the solution.

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2. When the participant arrives

a. Inform the caregivers and make sure the infant is fine

When the families arrive, make sure to bring them to the experimental room as soon as possible and inform them there. This way, the infant can already get used to the experimental conditions that might be very unfamiliar (i.e., many distracting cables and equipment being around, different lighting conditions, etc.).

Put a nice, comfortable chair for the caregiver to sit on in front of the screen. Letting the infant sit on the caregiver’s lap might increase movement artefacts in comparison to letting them sit in an infant’s chair. However, the infant might feel more comfortable on the caregiver’s lap and be less fussy. Decide how to arrange infant and caregiver depending on the specific experiment. If you let the infant sit on the caregiver’s lap, make sure to have some pillows available to make it more comfortable for the caregiver if necessary. This way you can at least reduce movements from the caregiver.

If you do not have the head circumference of the infant yet, make sure to measure it and prepare the R-Net. As you best have two experimenters ready for the whole experiment, one can continue informing the caregivers, while the other is preparing the cap.

We usually bring a cap in a different size to show the caregivers the cap and explain again how it works. In the meantime, you can give the infant an interesting toy.

Ask the caregiver if they think the infant is fine. Offer the possibility to feed the infant. Often caregivers think that the infant will make it through the experiment, and they will feed the infant afterwards. However, it is better to have the infant as happy as possible before the experiment.

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b. Fit the R-Net

After 15 minutes of soaking, take the net out of the electrolyte solution and make sure to dry excess water. You do not need to be afraid that the cap will not work if it seems dry from the outside, if the sponges are soaked with the solution. On the contrary, having the cap too wet will lead to bridges easily. Wring out the chinstraps of the cap. They usually are also soaked with the solution, but them being wet is uncomfortable for the infant. So, make sure to get them as dry as possible.

During the preparation, play some infant-friendly videos so the infant is distracted and does not realize the cap immediately. This way you will also have the infant look straight, which will make it easier to fit the cap correctly.

At best, you should have two people fitting the cap. One will kneel in front of the infant and make sure to fit the cap close to the eyebrows of the infant. The other one will hold the back of the cap and make sure to place it over the head of the infant. It is particularly important to fit the cap as fast as possible, so the process does not bother the infant. It is worth training the team of experimenters on a Styrofoam head a couple of times before they start testing real infants, to make sure everyone exactly knows what to do. Changes in the team always worsen the results for some time as insecurities easily transfer to the mood of the infant.

Close the chinstraps of the cap and make sure that the white plastic bar (i.e. the clamping block) is approximately at the jaw of the infant. You might need to cut the foremost tube on the plastic bar as this might tickle the infant near the mouth, raising its attention towards the cap.

 Tip: This video shows how to exchange tubes of the R-Net to optimize its fit.

After you fit the R-Net, make sure that all the electrodes are straight and in contact with the head, meaning that it should be symmetrical on both sides. Cz should be centered between Nasion-Inion and the preauricular points. Especially the electrodes on top of the head are prone to being twisted; probably you need to adjust them manually.

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c. Adjust the cables

In your lab environment, make sure to be able to place the cables and boxes of the cap behind the infant. Anything that is in sight of the infant will provoke the infant to grab it. For example, you can lay the cable over the shoulder of the caregiver and fix it there. Fixing the cable will also limit the movement possibilities of the infant, leading to less movement artifacts.

R-Nets with Infants Setup

Image showing the typical setup in our lab at LMU Munich

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d. Check impedances

Plug in the amplifier cables into the boxes and start the impedance measurement. The R-Nets are capable to tolerate high impedances up to 150 kOhm. However, the BrainAmp amplifiers only can measure up to 100 kOhm. Therefore, you can work on the impedances until they are below 100 kOhm.

To work on the impedances, you can massage the cap with your hands. This way the infant does not attend to the cap as much as if you apply additional solution. In addition, as they have little hair, this often is enough.

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3. Starting the measurement

a. Instruct caregivers

Before finally starting the measurement, instruct the caregiver about their expected behavior during the measurement. You probably cannot stop the infant from moving but ask the caregiver to remain as still as possible. If the infant does not need their hands during the task, ask the caregiver to gently hold onto the infant’s hands. This way you reduce the possibility for the infant to grab and pull the R-Net.

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b. Record video of the experiment

R-Net with Infants Video Recording

Screenshot from Video Recording

Make sure to record a video of the infant during the experiment. In the best case, the video is already time-locked to your EEG recording.

For example, you can use BrainVision Recorder with a video recording add-on to simultaneously record a video and the EEG signal. This way you can easily code whether the infant was attentive to the screen in the respective trials. You can also monitor the infant’s attention live and trigger attention getters or breaks during the experiment.

The regular use of attention getters during the experiment is extremely helpful. Usually, right after the attention getters, the infant is attentive and still for a couple of seconds, giving you a much better signal for this period.

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4. After the experiment

a. Show signal to caregiver

If possible, you can show the EEG signal to the caregiver after the experiment. They will not see much in it of course, but knowing how it looks like is mostly interesting to the caregivers. You can also offer screenshots of the video you recorded so that they have a picture of the infant with the cap. This will increase the compliance to your study, lab and further experiments.

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b. Clean the equipment

After taking the cap off the infant, wrap the splitter boxes in a towel and put the cap into the measurement cup labelled “disinfection” that you already prepared before the experiment. Make sure all of the cap is completely under water and let it sit for about 10 minutes. In the meantime, you can already clean the measurement cup labelled “electrolyte/water” and fill it with one liter of distilled water. After the disinfection, place the cap into this measurement cup and wait for one more minute. Move the cap around a little bit to make sure that all disinfectant solution is washed out of the cap. This way you can reduce the risk of skin irritations with the next use. Put the cap for another minute into fresh water for two more times. Afterwards, hang the cap to dry. Make sure that the boxes are stored higher than the cap so that no water can drip into the boxes.

Extend your BrainVision Analyzer 2 to its full potential with Solutions

News, Product Updates

Are you looking for extensions for BrainVision Analyzer 2? They are called Solutions! Scientists from various fields of research use them to tweak Analyzer to their needs. Analysis of non-EEG sensor data, sleep data, single trials and time-frequency domain exports are only some examples where users can benefit from our solutions.

In the following we present our most popular solutions and show how they add valuable functionality to Analyzer 2. We will start with general remarks and installation instructions and continue with some selected use-cases dedicated to specific analysis needs. At the end we present generally useful solutions that many of our users can profit from.

General remarks and installation instructions

BrainVision Analyzer 2BrainVision Analyzer 2 is appreciated for its easy-to-use yet powerful signal processing ability. Analysis pipelines created from the rich collection of Transformations cover most analysis needs while being extremely memory efficient. As scientific methodology is rapidly evolving, occasionally researchers will miss a function or method that is not implemented as a transformation. At Brain Products Scientific Support, we offer a variety of extensions to Analyzer 2 that fill in this gap. We call them Solutions.  They are usually created in first response to a frequently needed functionality and over time, we have grown a significant library of them. Solutions are free of charge for any Analyzer 2 user. Once they are installed you can use them almost as any other transformation.

Most popular solutions can be directly downloaded from our website. You have the option to download all of them at once or only individual ones. Either way you only need to run the installer and open Analyzer 2 to have them in your Solutions ribbon menu (see below).

Solutions Ribbon Menu in BrainVision Analyzer

If Analyzer 2 was already open, click Solutions > Help > Refresh Solutions to see them. Under the Solutions Help menu you will find the documentation for each of them. You can read more about how to use the Solutions Help Explorer in the Support Tip “Have you located the Solutions help documentation for Analyzer 2?”. If you are struggling with a certain task in Analyzer 2, our Scientific Support is always happy to help. We might send you a solution that is not available on our website, in this case you receive a solutions file (*.vaso), that you need to add to a subfolder of the Solutions directory on your Analyzer 2 installation path. The default path is: C:\Vision\Analyzer2\Solutions.

One word on macros – yes, solutions are basically compiled macros. You can add your own functions to Analyzer 2 by writing a Sax Basic macro and running it through the Macro ribbon menu. This topic will not be covered in this article. You can find more information on it on our website.

Solutions to help with specific analyses

Sensor Data

If you are working with signals from non-EEG sensors, we offer a range of solutions that you might find useful. For instance, you can analyze acceleration data, ECG profiles, EMG or GSR Peaks, Pulse transit times and width with the help of solutions. We have recently described how you can do that in our Support Tip “Offline analysis of sensor data in BrainVision Analyzer”.

Sleep

If you are a sleep researcher, you might be interested to know how to score and use sleep stages in Analyzer 2. Our Sleep Scoring solution allows you to manually score your data or inspect and edit imported sleep scores. For this purpose, we introduced the SleepStage marker dedicated to sleep research. Its description indicates the type of physiological state i.e., sleep stage N1, N2, N3, N4, REM, or Wake or the absence of a score (None). The Sleep Scoring solution recognizes these markers and allows you to edit them.

You can navigate the sleep data in steps of the desired scoring interval (typically 30 seconds). The frequency-spectra or topography can be displayed simultaneously to support the scorer. A full night hypnogram displaying all scores can be opened in a Microsoft Excel® sheet. Once scoring is finished, a Sleep Report can be generated. It summarizes important sleep parameters such as sleep latency, sleep efficiency, duration of stages and composition of sleep cycles. The approved scores remain as markers in the dataset and can be used for Segmentation in a sleep-informed analysis in Analyzer 2. This solution is available on request.

If you are interested in a demonstration of the solution, feel free to watch the recording of our webinar about  “Sleep Research and Sleep Scoring Solution”.

Analyzer Solutions: Figure 1 Sleep Scoring in Analyzer 2 with the display of the frequency data of the current scoring interval.

Figure 1. Sleep Scoring in Analyzer 2 with the display of the frequency data of the current scoring interval.

Single trial analysis

Analyzer 2 was originally designed for ERP analysis. Many ERP studies need to extract features of ERP components only after performing an Average across trials. Analyzer’s transformations and exports are designed for this approach and offer feature extraction from averaged data. Solutions add the possibility to also perform single trial analysis.

Analyzer Solutions: Figure 2 Stacked Plot view: the solution utilizes the time-frequency view in Analyzer to show multiple stacked trials. For this reason, the label of the ordinate is showing Hz instead of trial number.

Figure 2. Stacked Plot view: the solution utilizes the time-frequency view in Analyzer 2 to show multiple stacked trials. For this reason, the label of the ordinate is showing Hz instead of trial number.

The Peak Detection transformation for example, detects peaks on averaged data and the MinMax Marker solution on a single trial level. It allows you to place Peak markers at the maximum and/or minimum in a certain interval of each segment.

Likewise, where Area Information and Peak Information Export modules work on averaged datasets, you can export data from single trials with the solutions described in the section Solutions for exports below. There are solutions for time, frequency, or time-frequency domain exports.

Before the detection and export of peaks, it often makes sense to assess the ERP on a single trial level. For example, to estimate the variability of components across segments or to visually inspect a set of trials at once. You can do this with the Stacked Plot solution. It will display all segments stacked on top of each other (see Figure 2). The solution is using the time-frequency view in Analyzer 2 to display trial number on the ordinate and time on the abscissa. Amplitude is shown on a color scale that can be configured through the view settings.

Solutions for exports

Our most popular solutions are exports. These provide exports of time, frequency or time-frequency domain data from averaged or single-trial history nodes. For a detailed overview about exports please read our Support Tip “Exports for all occasions – A selective overview of Analyzer 2’s most useful export options”.

Peak Export: Despite its name the solution exports not only various peak measures such as amplitude, latency, peak-to-peak distance and the area under the curve but also average amplitudes within a time interval. This is the go-to solution if you need to export single trial, time domain data.

Analyzer Solutions: Figure 3 Interface of the Wavelet Data Export solution.

Figure 3. Interface of the Wavelet Data Export solution.

FFT Band Export: Like the Peak Export this solution can be used to export single-trial data from a selected frequency range. It allows you to export individual values as well as many aggregation options such as area under curve measures, average or the raw sum.

Wavelet Data Export: If you are using Wavelets to decompose your data into the time-frequency domain this solution is essential. You can specify a time and frequency range (see Figure 3) and then export the sum or average of this area to a text file. It is applicable for both real (e.g. power) or complex values. It is now also possible to export into a file with comma separated values (*.csv), making the transfer to other software even easier.

Create MAT File: Complementary to the Matlab transformation, that interfaces directly with the application, this solution allows you to create a MATLAB® compatible file (*.mat) with the data of the current history node. For each channel a separate variable is created. Note that time-frequency domain data cannot be exported with this solution.

Solutions for parameter extraction

Analyzer Solutions: Figure 4 Example output of the Write Markers solution.

Figure 4. Example output of the Write Markers solution.

The Write Markers solution has found many useful applications despite its simplicity. It collects basic information of selected markers and writes them to an external text file. Marker information includes Description, Type, Position, Duration and Amplitude at the marker position. An example file is shown in Figure 4. It is generated from a continuous dataset and only includes selected output information. If the dataset is segmented, each row in the file corresponds to a segment. If it is continuous, you can specify a marker that will trigger a new line or row. In this example the “S_20” marker was used. In the exported file, the position of this marker is reset to zero. The position of all other markers in the same row is exported as the distance to the previous “S_20” marker. This feature allows you to inspect marker placement and to plan a marker-based segmentation before actually implementing it.

This export is also quite useful to extract:

Reaction time from markers

Often the distance between a Stimulus marker and a following Response Marker indicates reaction time. In the example export in Figure 4 the Stimulus marker triggers a new row and the position of the following Response marker indicates reaction time. Note that the Position can be exported in milliseconds or in data points.

Peak frequency

Analyzer Solutions: Figure 5 Example of the MinMax Marker solution applied to FFT (frequency domain) data to identify peak frequencies.

Figure 5. Example of the MinMax Marker solution applied to FFT (frequency domain) data to identify peak frequencies.

For most spectral analysis, frequencies of interest must be defined. For example, when the individual alpha frequency (iAF) is of interest, the peak of the alpha band of each subject needs to be detected and exported. The peak of the alpha band or another frequency band can be exported when the solution is used in combination with the MinMax Marker solution (see Figure 5). The MinMax Marker solution finds the largest (or smallest) value in a dedicated frequency band and inserts a Peak marker. The Write Markers solution exports the Magnitude and Frequency of the Peak marker. Both solutions can be applied to segmented or averaged frequency domain data.

List rejected segments

A common preprocessing step for EEG or ERP analysis is the detection and rejection of data containing an artifact. In Analyzer 2, a Bad Interval marker is used to indicate them. You can detect artifacts with Raw Data Inspection or Artifact Rejection automatically. Segments that contain Bad Interval markers can be rejected directly within Segmentation or can be automatically ignored by other transformations such as the Average. Often it is important for researchers to get an overview of segments that contain artifacts and are rejected from the result. Such a list can be exported with the Write Markers solution by exporting the Bad Interval markers.

Other popular solutions

Recode Markers: If you are interested to explore the relationship between the behavioral response and the EEG, this solution might be worth noticing. It allows you to select a group of segments based on the temporal distance between markers. Typically, the distance between a Stimulus and Response marker is used to reflect the reaction time. Available groupings are Median/Mean Split, Mean ± SD, Upper/Lower percentages, Middle fraction and more. It is also possible to define your own fractions in percentage or time range. The inserted marker (Type “Comment”) can be used within Segmentation to create a group ERP. Additionally, statistics such as the Mean, Median and Standard Deviation (SD) of the marker distances (e.g. reaction time) are reported in the Operation Infos of the Marker Recode history node.

Set Markers: Have you ever been in need to add a marker to your dataset? Maybe because you realized only after recording that it is needed or because it was simply forgotten. Of course, you can add or edit markers with Edit Markers transformation, but if you need to place a marker in a fixed distance to another existing marker this solution will help. It allows you to insert markers with a fixed or randomized temporal distance to all markers of a selected Type and Description. This solution is available on request.

Read Coordinates: If your dataset is lacking electrode coordinates but they are available in an external file, you can load it with this solution. You can specify the type of coordinates used (cartesian or spherical) and instruct the solution where to find the information in the file. This makes it possible to read from any electrode coordinate file if it is in a compatible text form. The solution also converts coordinates. In Analyzer 2 only spherical coordinates are used and if yours are specified in cartesian it will convert them. This solution is available on request.

Moving Average: Some analyses require to estimate the envelope of the signal, for example in EMG analysis. The Moving Average solution can be used to smooth the data, similar to a low-pass filter. Each value is replaced with the average of a time-window centered on the current data point. It offers some extra options such as rectification before or subtraction instead of replacing with the average.

Concluding remarks

To grasp the full processing power and skill of Analyzer 2 it is good to know Solutions and the range of functionality that they add to it. This article provides a glimpse of the full spectrum that is available with the solutions that are useful for most researchers. If you are stuck with your analysis and need to advance your pipeline beyond what you can do with transformations our tip is: browse through our solutions and find out whether they can help you. If you don’t find anything that fits your pipeline, contact us, we have more! Please get in touch with us via support@brainproducts.com and we will do our best to find a solution for you.

Combining EEG and eye tracking: a workflow for your lab experiment

News, Publications

Combining EEG and eye tracking can open new possibilities for your EEG analysis. If you would like to add eye tracking to your EEG setup but are unsure how to implement this, we have great news for you: Thanks to our new cooperation with Tobii Pro, Brain Products now offers complete out-of-the-box solutions for simultaneous EEG and eye tracking!

Abstract

This article intoduces how you can combine your EEG measurements with simultaneous eye tracking. We offer a full example workflow for a specific lab-based setup, while pointing to generally important aspects for a successful combination of EEG and eye tracking. For our setup, we are using the software Tobii Pro Lab for experimental control, the Tobii Pro Spectrum for recording eye tracking data, and the actiCHamp Plus to record EEG data in combination with our Photo Sensor. In the workflow, we describe how you can design your experiment while setting up shared event markers, how to perform the combined recordings, and how to merge both data streams in BrainVision Analyzer 2.

Boost your EEG research with simultaneous eye tracking!

In the last decade, the combination of eye tracking with measures of brain activity like EEG or fMRI has increased. But why would we want to take a closer look at the eyes when investigating brain activity?

Eye tracking offers two major sources of information:

The position of a person’s gaze gives us insight into the “open” focus their attention, and this information can be highly valuable for EEG research. With this gaze information, you will be able to tell if participants are focusing their attention on a target, when exactly their focus arrives and for how long it stays until shifting elsewhere. This will let you identify trials in which the participant was not paying attention and discard them from your analyses. Most importantly though, you gain precise timing information for your EEG analysis. Event-related potentials (ERPs) can, for example, be calculated with respect to the fixation on a stimulus (i.e., Fixation-Related Potentials), instead of the mere stimulus appearance on the screen. Research addressing topics like attentional processes, visual search, reading or social perception can highly benefit from gaze information.

Changes in pupil size can inform about cognitive and emotional experiences. The pupil reacts with short dilations (in the second range) to different stimuli. These “pupil responses” are a very sensitive physiological measure, and their magnitude reflects the intensity of the undergoing cognitive/emotional processes. Thereby, stimuli that are more emotionally arousing, or that demand higher cognitive effort cause larger pupil responses. By analyzing them, you may be able to check if your experimental manipulation was successful, or to even follow cognitive or emotional processes dynamically throughout your experiment. In combination with EEG, you could, for example, use the magnitude of pupil responses to weigh or categorize different trials in your experiment.

Adding eye tracking to your EEG setup will hence open a range of new possibilities for your research!

Figure 1. Combined EEG and eye tracking setup in a laboratory setting

Figure 1. Combined EEG and eye tracking setup in a laboratory setting

A workflow for your lab-based EEG & eye tracking experiment

Combining two different measures like EEG and eye tracking can be technically challenging, especially if they should be temporally aligned and analyzed together. The key here is setting up shared event markers/triggers that will appear in both the EEG and the eye tracking data at the same time. Note that not all trigger signals need to be shared. It is enough to have a few (at least two) shared event markers to align the data sets after recording. It is however crucial that an equal number of the shared events appear in both data sets, and that they mark common points in time. Therefore, we need to plan our setup and experiment with these shared trigger events in mind.

Event markers are usually generated by the software used for experimental control (like E-Prime®, Presentation®, Psychtoolbox or Tobii Pro Lab‘s Designer module). There are many ways to pass them on to your EEG and eye tracking recordings. The best setup for you will depend on your experimental software and the properties of the computer, EEG amplifier and eye tracker you are using.

Here, we want to show you one concrete example for setting up simultaneous EEG and eye tracking recordings. We are going to explain how you can record high-quality data in a lab-based setup using:

Figure 2. Example workflow for simultaneous EEG and eye tracking recordings

Figure 2. Example workflow for simultaneous EEG and eye tracking recordings

1. Design your experiment and set up shared event markers

Naturally, the workflow needs to start with designing and planning your experiment. If you use the Tobii Pro Lab software for the experimental design, it will allow you to set up the timeline of your experiment in a very intuitive way. Make sure the timeline always starts with a calibration and validation routine to accurately map and record gaze data. Next, you can add all sorts of stimuli to the timeline, e.g., pictures, text elements, videos, or groups of stimuli. You can find an introduction video on how to create a screen-based study with Tobii Pro Lab here, and further useful information here.

When designing your experiment, you need to set up shared event markers that will allow you to temporally align EEG and eye tracking data after recording. Note that you will need at least two markers of the same type appearing at the same time in both data streams. For example, you can send the first synchronization marker a few seconds before your task begins, and the last one a few seconds after the task finishes. This way your synchronization markers span the whole experiment, and you can align the EEG and eye tracking data sets completely.

(a) Marking events in the eye tracking data

The Pro Spectrum eye tracker can receive TTL trigger signals. However, in this specific example, we are using Tobii Pro Lab not only to present stimuli, but also to record eye tracking data. Therefore, all presented stimuli will be marked automatically as “Events” in the eye tracking data and you don’t need to worry about triggers.

(b) Marking events in the EEG data

To mark stimulus events in the EEG data, TTL hardware triggers are usually the preferred solution because they offer highly accurate timing. Tobii Pro Lab can send TTL pulses to mark stimulus events if your computer has a parallel port card available. However, for this scenario we will assume that you are working with a laptop that has no parallel port.

With a small workaround, you can still precisely record the stimulus timing in your EEG data by using a Photo Sensor. This small accessory detects changes in brightness that can be recorded alongside your EEG data. Simply attach the Photo Sensor to one corner of the presentation screen and modify your stimuli in a way that they differ in brightness in this very corner (see Figure 3). This way, the photo sensor will detect a change in brightness every time the next stimulus is presented. During later analysis, you can identify the stimulus onsets from the Photo Sensor signal. The timing of this solution is very precise because stimuli are detected by the Photo Sensor exactly when they appear on the screen.

 Tip: If you want to directly generate trigger events from your Photo Sensor, you can combine it with the Brain Products StimTrak! The StimTrak can convert the Photo Sensor signal into trigger pulses and pass them on to your EEG recording where they will appear as event markers. See this article for more information.

 Tip: If you want to identify different kinds of stimuli from your Photo Sensor signal, you can modify your stimuli with different shades of grey (this article offers a more detailed description).

Figure 3. Using a Photo Sensor to detect stimulus onsets. In this example, two checkerboard stimuli (A and B) are shown alternatingly on the presentation screen. Only Stimulus A displays a bright square in one corner. If the Photo Sensor is attached in this corner of the presentation screen, it will detect the change in brightness at every onset and offset of Stimulus A. During later data analysis, the photo sensor signal can be used to derive stimulus markers with very precise timing

Figure 3. Using a Photo Sensor to detect stimulus onsets. In this example, two checkerboard stimuli (A and B) are shown alternatingly on the presentation screen. Only Stimulus A displays a bright square in one corner. If the Photo Sensor is attached in this corner of the presentation screen, it will detect the change in brightness at every onset and offset of Stimulus A. During later data analysis, the Photo Sensor signal can be used to derive stimulus markers with very precise timing.

Here are a few additional options for alternative setups:

 Find a support article here about sending TTL trigger pulses, or read about our TriggerBox for sending trigger signals via USB port.

 If your EEG amplifier and your eye tracker have trigger ports and you can send TTL pulses, you can share the exact same triggers among both devices. Either split the trigger signal with a Y-cable, or use the practical trigger mirroring function of our actiCHamp Plus: this amplifier can receive 8-bit triggers and can immediately pass them on to your eye tracker!

 If you are using E-Prime® for presenting your experiment and have a screen-based Tobii eye tracker, you may be interested in the E-Prime extension for Tobii Pro Lab.

2. Prepare the eye tracking recordings

To set up your eye tracking recording, your Spectrum eye tracker needs to be connected and correctly set up in Tobii Pro Lab (find more information here). Once this is done, you will find everything you need in the “Record” tab of Tobii Pro Lab. Here, you should pay special attention to the sampling rate (or “sampling frequency”) with which you are recording the eye tracking data (click on the eye tracker symbol in the top left corner). Higher sampling rates allow you to assess not only fixations, saccades and even micro-saccades (see this article), but they also allow you to record the stimulus events with more temporal precision. Therefore, higher sampling rates are better for a more precise synchronization with the EEG data.

It is also important to set up the stimulus markers in Pro Lab with the highest temporal precision. You may encounter delays between the stimulus marker being registered in Pro Lab, and the stimulus actually appearing on the presentation screen. To reduce such delays, please make sure that the computer running Pro Lab matches the required specifications, and carefully follow these important tips to optimize your stimulus timing in Pro Lab. To find how you can determine this delay in your setup, and how you can account for it during recording, you can take a look at this Timing Guide.

Before recording data with an actual participant, you will need to run at least one test recording of your final task and make sure your current setup and the available stimulus events let you analyze everything of interest in Pro Lab’s “Analyze” tab. If all events are marked in Pro Lab and you are satisfied with their timing, you are all set for the eye tracking recordings.


3. Prepare the EEG Recordings

To prepare your EEG recordings, you will need to set up the actiCHamp Plus with the PowerUnit, and connect the Photo Sensor to one of the amplifier’s AUX channels. When preparing your workspace in BrainVision Recorder, make sure to also set up the respective AUX channel for recording the Photo Sensor signal. For the EEG data, we can use a higher sampling rate (for example 2000 Hz) to have a high temporal precision of the signal and a good synchronization with the eye tracking data.

When everything is set up, you will need to identify the correct position for the Photo Sensor on the presentation screen. For this, briefly start a test run of your experiment and attach the Photo Sensor to the monitor with an adhesive ring. Next, run a test EEG recording to make sure you can identify all necessary stimulus events in the recorded Photo Sensor signal. Present the full experiment while recording, then load the data in BrainVision Analyzer 2. If your setup contains the Photo Sensor in combination with a StimTrak, the stimulus events should already be marked in your EEG data. Otherwise, you can now use the “Level Trigger” transformation. Here, you can identify the optimal threshold value for your Photo Sensor data and extract the stimulus events from the Photo Sensor channel (see Figure 4).

Figure 4. Identify the stimulus onsets from the photo sensor channel with the Level Trigger transformation.

Figure 4. Identify the stimulus onsets from the photo sensor channel with the Level Trigger transformation.

Keep in mind that the shared synchronization events need to appear at the same time in both EEG and eye tracking data, and that there need to be an equal number of synchronization events present in both data sets. If necessary, you can use the “Edit Markers” transformation to rename or modify some events in your EEG data.

4. Record EEG and eye tracking data simultaneously

Now you are ready for the real data acquisition! Set up the EEG system and cap, use the prepared workspace and the Photo Sensor. To get ready for the eye tracking recordings, load the correct experiment in Tobii Pro Lab. Then have the participant sit in front of the eye tracker and presentation screen at the optimal distance. After double-checking that all settings are correct (see section “2. Prepare the eye tracking recordings” above), you can enter a name for your participant, and the “Record data” button will become available in Tobii Pro Lab.

When starting the recording in Tobii Pro Lab, follow the calibration and validation procedure until you are satisfied with accuracy and precision. Before you start the actual task, make sure to start your EEG recordings in time for the Photo Sensor to capture the first synchronization marker. Always keep an eye on the data streams in BrainVision Recorder and Tobii Pro Lab to make sure all data is recorded smoothly. When the task is finished, again make sure the Photo Sensor captured the last synchronization event before stopping the EEG recording.

 Tip: Make sure you do not stop or pause the EEG recordings before the task is fully finished, so you can later align the EEG and eye tracking data sets!

5. Analyze the eye tracking data

Now it’s time to analyze your eye tracking data in Tobii Pro Lab’s “Analyze” tab. It is good practice to start with some quality control (reviewing the recording and checking for data loss). Then you will be able to perform all kinds of analyses, export metrics or create graphics from your recorded gaze data. What may be most relevant for your combined EEG and eye tracking analysis is to identify times of interest or fixations in areas of interest in your eye tracking data.

When you are done with your eye tracking analysis, you can export the gaze and pupil data together with all identified event markers and import them into your EEG data. For this, use the “Data Export” option in Pro Lab and export the data in the Pro Lab Output File (PLOF) format.

6. Identify the event markers in your EEG data

After a brief quality control, you can extract all stimulus events from the Photo Sensor channel by using the “Level Trigger” transformation with the previously tested settings (see section “3. Prepare the EEG recordings” above). If necessary, modify the resulting markers so you can clearly identify the synchronization events that should be shared with the eye tracking recording.

 Tip: Be careful with segmenting your EEG data before importing the eye tracking data to make sure you don’t lose important synchronization markers!

7. Merge both data sets for combined EEG and eye tracking analysis

Finally, you can import the eye tracking data and the events you identified in your eye tracking analysis into your EEG recordings. At this time point, the sampling rates and the length of both data sets will likely be different, but BrainVision Analyzer 2 will now use the shared synchronization events to bring both data streams to the same timeline.

To merge the EEG and eye tracking data, open the EEG data containing the identified synchronization events. Next, use Analyzer’s Add Channels transform and select the previously exported eye tracking file under Import files. In the next window, you will need to select the shared synchronization markers which will be used to align both data sets. For the EEG data, they can be selected from the Markers in Active Node list, for the eye tracking data from the Markers in Import File list. If you click on the Details button, you will see if there is an equal number of synchronization markers in both data sets.

In the following dialogs, you will be able to select the specific channels and markers you would like to import. Finally, when you finish the Transformation, the eye tracking channels will appear underneath your EEG channels, and all selected event markers will be imported.

 Tip: You can find a full description of how to use the Add Channels transform in the BrainVision Analyzer 2 User Manual, and more information about its latest enhanced features here. However you can also always contact our Scientific Support team if you need help with BrainVision Analyzer 2.

Now that both data streams are temporally aligned, you can start analyzing them together! As mentioned in the introduction, you can discard data during which the subject was not focusing on areas of interest. Finally, you can also segment your EEG data based on fixations or other events you identified in your eye tracking analysis, and you can calculate Fixation-Related Potentials.

Conclusion

We hope this article provided you with helpful guidelines for your lab-based EEG and eye tracking setup, and that we could walk you through the most important steps for your recordings and analysis. Keep your eyes open for more articles as well as dedicated online events about our new eye tracking solutions!

Introducing Tobii hardware and software: the perfect complement to your EEG and eye tracking research

News, Product Updates

To provide solutions for neurophysiological researchers, we are always staying current and up to date on integrating EEG with complementary methods to equip scientists with the most comprehensive solution for understanding the relationship between brain and behaviour. These combined methods have been a focus for Brain Products, whether it be via extra physiological measures, EEG-fMRI solutions or EEG-fNIRS combinations. As an extension of our multimodal offering, we’ve partnered with Tobii Pro to offer you high-grade screen-based and wearable eye tracking systems for your combined EEG & eye tracking research.

Are you interested in adding eye tracking to your EEG experiments? Whether you are conducting research in cognitive psychology, vision sciences or real-world applications, we offer a range of devices to fit your research needs.

Screen-based eye trackers

For stationary experiments with the actiCHamp Plus or BrainAmp, we are pleased to offer a range of screen-based eye trackers. Capturing gaze data up to 1200Hz, the Tobii Pro Spectrum offers advanced triggering options with superior data quality. It’s designed for lab-based research in the vision sciences, as well as studying eye movements from fixation-based studies to micro-saccades. Another high precision eye tracker, which can track the pupil in both light and dark conditions, the Tobii Pro Fusion, is designed to collect data in a variety of environments (e.g. hospitals, libraries, schools etc). A much smaller and lightweight screen-based eye tracker, which is designed for fixation-based studies, the Tobii Pro Nano, is fully portable and provides the ideal setup for educational and teaching purposes.

Tobii Pro screen-based eye trackers

From left to right: Tobii Pro Spectrum, Tobii Pro Fusion and Tobii Pro Nano

Wearables

Perfectly paired with our mobile LiveAmp, the wearable Tobii Pro Glasses 3 allow you to conduct behavioural EEG and eye tracking research in a variety of real-world settings. Delivering accurate gaze data from naturally moving participants, these glasses come equipped with 4 cameras, 16 illuminators, and a full HD resolution scene camera with 106° field of view. This sleek setup, together with our low-profile, actiCAP slim, electrodes provide an outstanding solution for all of your mobile EEG and eye tracking research applications, whether it be MoBI, neuromarketing or sports psychophysiology.

Tobii Pro wearable eye tracker

Tobii Pro Glasses 3

Software

Together with Tobii Pro eye trackers, Tobii Pro Lab software provides the complete solution for researching human behaviour. A user interface and dedicated software features efficiently guide and support you through all the phases of an eye tracking experiment from test design to recording and subsequent analysis. Once your EEG and eye tracking data are recorded, use the new Add Channels transform in BrainVision Analyzer 2.2.1 to synchronize and align your data streams before further analysis.

Tobii Pro Lab Software

Tobii Pro Lab Software

BESA Research 7.1 March 2021 released

News, Product Updates

BESA Research 7.1 March 2021 is a maintenance release. All customers with a valid license for BESA Research version 7.1 are eligible for a free update to this version.

This release features a lot of improvements and bug fixes. Please make sure to update to this version as soon as possible on www.besa.de/downloads/besa-research/besa-research-7-1/.

Data review and pre-processing:

  • Batch commands – Many new or enhanced batch commands are available, including improvements for automated pattern search, visualizing results, drawing maps, saving screen shots, scaling of data, etc.
  • Data export improvements
  • New source montages including the new 25 source standard (cf. Scherg et al., Front. Neurol., 20 August 2019, https://doi.org/10.3389/fneur.2019.00855), and atlas-based source montages (see picture above for an example of atlas region sources).

Source Analysis:

  • The time-domain beamformer can now be used to compare two conditions. The target and control conditions can be selected in the dialog of the ERP module that initiates the beamformer calculation.
  • A single dipole fit can now be started directly using the Start Fit button, without having to place a dipole source first.
  • The Bayesian source imaging method SESAME is now available for all head models. Before, it was restricted to spherical models.
  • Beamformer and DICS can now be used with MEG finite element and boundary element models.
  • It is now possible to add noise sources to a solution, in order to generate source montages. They can be selected from several pre-defined source configurations, and only sources with a certain distance from existing sources will be added in order to describe brain activity that is unrelated to the activity of interest. The functionality is available from the Solution menu.

The full list of improvements and bug fixes can be seen on https://www.besa.de/downloads/besa-research/besa-research-7-1/ in the section on New Features and Bug Fixes.

Is it all in the knee?

News, Publications

Patellofemoral pain (PFP) is considered a mechanistic pain syndrome, originating from kinetic, anatomic or biomechanical dysfunction leading to nociceptive pain.

However, some data shows that not all pain expressions in patients with PFP can be causatively connected to a biomechanical impairment.

Researchers from the School of Health and Rehabilitation Sciences, The University of Queensland, Australia, have endeavored to clarify whether patients suffering from PFP have local or centrally altered sensory profiles.

Profiling patients vs. controls

One-hundred-and-fifty patients with PFP were recruited along with sixty one controls.
Quantitative sensory testing (QST) was performed on the most painful knee and on a remote site: the contralateral lateral epicondyle of the elbow. QST consisted of: mechanical and thermal sensory and pain thresholds, pressure pain thresholds (PPT), as well as mechanical temporal summation and conditioned pain modulation (CPM) with PPTs as test stimuli and cold pressor as the conditioning stimulus.

Medoc’s Pathway ATS, TSA2’s predecessor, was utilized for all thermal thresholds.

Questionnaires on kinesiophobia (TSK), self-efficacy (FESQ), catastrophizing (PCS), and anxiety and depression (HADS) were administered.

What was found

Interestingly, cold and heat pain thresholds were significantly lower for the patient group compared to the controls, both at the knee and the elbow, hinting at central sensitization. There were similar findings for the mechanical pain and pressure pain thresholds, but not for the sensory thermal/mechanical thresholds.
In pain modulation measures of temporal summation and CPM only temporal summation was significantly increased for the patient group.

Additional to this, higher prevalence of anxiety, depression and pain catastrophizing was found in the patient group as compared to the controls.

To conclude

The authors conclude that “Our discovery of thermal hyperalgesia offers new insight in terms of PFP mechanisms. Multi-modal hyperalgesia locally and at a remote site (elbow), reflected by greater sensitivity to heat, cold and pressure pain in our PFP group, could be construed as evidence of nociplastic pain.”
Physicians, physiotherapists and other clinicians treating patients with patellofemoral pain should take into account physiological, pain modulatory, and psychological changes, in order to holistically treat their patients.

Reference:

Maclachlan, L. R., Collins, N. J., Hodges, P. W., & Vicenzino, B. (2020). Psychological and pain profiles in persons with patellofemoral pain as the primary symptom. European Journal of Pain, 24(6), 1182-1196.

Transcranial Pulse Stimulation (TPS): first NEUROLITH system installed in Switzerland

News, Product Updates

Transcranial Pulse Stimulation (TPS®) for the treatment of Alzheimer’s patients is now also  available for patients in Switzerland. In early February 2021, the first NEUROLITH® system was successfully installed in the Praxis Alexander Russ in Zurich.

The NEUROLITH® practice A. Russ has already treated the first patients and reports that TPS® is in high demand: »We have numerous appointment requests from patients from the greater Zurich area, but also from the entire Lake Constance region and neighbouring southern Germany.«

In addition to Switzerland, TPS® is already available in Germany, Austria, Spain, France, Denmark, Portugal, England, Kuwait, Hong Kong, China and Canada. Another 15 installations are firmly planed until the middle of this year.

About TPS® treatment
In 2018, Transcranial Pulse Stimulation (TPS®) with the NEUROLITH® system was the first, and hitherto only, procedure of its kind to obtain market authorization for the »treatment of the central nervous system of patients with Alzheimer’s disease«.

TPS® can stimulate deep cerebral regions, reaching as much as 8 cm into the brain. Owing to the short duration of the TPS® stimulation, tissue heating is avoided. The pulses applied to the treatment area thus develop their maximum clinical effectiveness. TPS® treatment is performed through the closed skull. In studies, TPS® treatment has been shown to significantly improve CERAD test performance and to reduce Beck’s depression index in patients with mild to moderate dementia.

thermal taster

Do you know what your thermal taster status is?

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Thermal taster status (TTS) is a phenomenon in which thermal stimulation of specific areas of the tongue, causes a sensation of a distinct taste in the absence of a gustatory stimulus. Reports vary on what percentage of the general population is a thermal taster, occurrence of thermal tasters in research cohorts of between 20% and 50% has been reported.

thermal taster

Not all Thermal Tasters taste alike

Even within the group of thermal tasters, there are subgroups. These groups differ from one another in responsiveness to thermal stimuli in different areas of the tongue and the phantom taste that each type of stimulation arouses. Green and George report that “thermal sweetness” is a common taste occurring in half the thermal tasters in response to warming after the tongue was cooled, while Skinner et al. reported 25% of tasters tasting “bitter” while another 25% tasting “sour” in cooling trials.

How to assess Thermal Taste

In general, TTS is assessed by applying a thermode with a warming and a cooling stimulus, as each temperature change direction and specific temperatures elicits a different taste sensation in thermal tasters. Thermal taste is classically tested on the tip of the tongue, and some studies report findings from areas lateral of the tip or the back of the tongue. Several studies on thermal tasters have used Medoc’s Pathway 16*16 mm thermode or the Intra-oral thermode. An example of a testing protocol for TTS could be found in Eldeghaidy et al.’s study in which both warming trials and cooling trials were applied. A warming trial would start at 35°C, cooled down to 15°C and go up to 40°C, and held there for 10 sec., with a ramp of 1 °C/sec.

Tongue taste innervation

In Thermal tasters, the anterior part of the tongue, innervated by the chorda tympani nerve, shows a typical reaction to heating and to cooling, while the posterior part of the tongue, innervated by the glossopharyngeal nerve, reacts less typically, Cruz and Green found[7]. Thermal taster status, along with another measure, 6-npropylthiouracil (PROP) taster status, form the taste phenotype.

Do fungiform papillae matter?

A hypothesis existed that the fungiform papillae of the tongue would be responsible for thermal taste because of their high density at the tip of the tongue, and their dual role: as they contain both taste buds and mechanoreceptors that are innervated by gustatory and trigeminal nerve fibers. Eldeghaidy et al. found that TTS did not seem to be correlated to fungiform papillae density in contrast to PROP taster status, and thus must have a different mechanism. The taste phenotype as a whole, and the thermal taster status specifically, increasingly allure both neurology researchers and the food and beverage industry alike. Temperature may be actively integrated as a contributor in the totality of the gustatory experience when new taste product are planned to be released to market.

The Association Between Preoperative Pain Catastrophizing and Chronic Pain After Hysterectomy – Secondary Analysis of a Prospective Cohort Study

All, Publications
    Hon Sen Tan,1 Rehena Sultana,2 Nian-Lin Reena Han,3 Chin Wen Tan,1,4 Alex Tiong Heng Sia,1,4 Ban Leong Sng1,4
    1Department of Women’s Anaesthesia, KK Women’s and Children’s Hospital, Singapore; 2Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore; 3Division of Clinical Support Services, KK Women’s and Children’s Hospital, Singapore; 4Anesthesiology and Perioperative Sciences Academic Clinical Program, SingHealth-Duke-NUS Medical School, Singapore
    Correspondence: Ban Leong Sng
    Department of Women’s Anaesthesia, KK Women’s and Children’s Hospital, 100 Bukit Timah Road 229899, Singapore
    Tel +65 6394 1077
    Email sng.ban.leong@singhealth.com.sg
    Purpose: Hysterectomy is associated with a high incidence of chronic post-hysterectomy pain (CPHP). Pain catastrophizing, a negative cognitive-affective response to pain, is associated with various pain disorders but its role in CPHP is unclear. We aimed to determine the association of high preoperative pain catastrophizing with CPHP development and functional impairment 4 months after surgery.
    Patients and Methods: Secondary analysis of a prospective cohort study of women undergoing abdominal/laparoscopic hysterectomy to investigate the association between high pain catastrophizing (pain catastrophizing scale, PCS≥ 20) with CPHP and associated functional impairment (defined as impairment with standing for ≥ 30 minutes, sitting for ≥ 30 minutes, or walking up or down stairs). CPHP and functional impairment were assessed via 4- and 6-month phone surveys.
    Results: Of 216 patients, 72 (33.3%) had high PCS, with mean (SD) of 30.0 (7.9). In contrast, 144 (66.7%) patients had low PCS, with mean (SD) of 9.0 (4.7). At 4 months, 26/63 (41.3%) patients in the high PCS group developed CPHP, compared to 24/109 (22.0%) in the low PCS group. At 6 months, 14/53 (26.4%) high PCS patients developed CPHP, compared to 10/97 (10.3%) patients with low PCS. High PCS was independently associated with CPHP at 4 months (OR 2.49 [95% CI 1.27 to 4.89], p=0.0082) and 6 months (OR 3.12 [95% CI 1.28 to 7.64], p=0.0126) but was not associated with functional impairment. High PCS≥ 20, presence of evoked mechanical temporal summation (MTS), and history of abdominal/pelvic surgery predict CPHP at 4 months with area under the curve (AUC) of 0.69. Similarly, PCS≥ 20 and increasing MTS magnitude predicted CPHP at 6 months with AUC of 0.76.
    Conclusion: High PCS was independently associated with CPHP. Future studies should identify other CPHP associated factors to formulate a risk-prediction model and investigate the effectiveness of early intervention for pain catastrophizers in improving pain-related outcomes.

Neuronavigation based 10 sessions of repetitive transcranial magnetic stimulation therapy in chronic migraine: an exploratory study

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    Abstract

    Introduction: Chronic migraine is a disease of altered cortical excitability. Repetitive transcranial magnetic stimulation provides a novel non-invasive method to target the nociceptive circuits in the cortex. Motor cortex is one such potential target. In this study, we targeted the left motor cortex using fMRI-guided neuronavigation.

    Materials and methods: Twenty right-handed patients were randomized into real and sham rTMS group. Baseline subjective pain assessments were done using visual analog scale (VAS) and questionnaires: State-Trait Anxiety Inventory, Becks Depression Inventory, and Migraine Disability Assessment (MIDAS) questionnaire. Objectively, pain was assessed by means of thermal pain thresholds using quantitative sensory testing. For corticomotor excitability parameters, resting motor thresholds and motor-evoked potentials were mapped. For rTMS total, 600 pulses in 10 trains at 10 Hz with an intertrain interval of 60 s were delivered in each session. Ten such sessions were given 5 days per week over 2 consecutive weeks. The duration of each session was 10 min. Real rTMS was administered at 70% of Resting MT. All the tests were repeated post-intervention and after 1 month of follow-up. There are no studies reporting the use of fMRI-based TMS for targeting the motor cortex in CM patients.
    Results: We observed a significant reduction in the mean VAS rating, headache frequency, and MIDAS questionnaire in real rTMS group which was maintained after 1 month of follow-up.
    Conclusion: Ten sessions of fMRI-based rTMS over the left motor cortex may provide long-term pain relief in CM, but further studies are warranted to confirm our preliminary findings.
    Keywords: Chronic pain; Cortical excitability; Headache; Motor cortex stimulation; Neuromodulation; Quantitative Sensory test.

Stepwise increasing sequential offsets cannot be used to deliver high thermal intensities with little or no perception of pain

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Abstract

Offset analgesia (OA) is the disproportionate decrease in pain experience following a slight decrease in noxious heat stimulus intensity. We tested whether sequential offsets would allow noxious temperatures to be reached with little or no perception of pain. Forty-eight participants continuously rated their pain experience during trials containing trains of heat stimuli delivered by Peltier thermode. Stimuli were adjusted through either stepwise sequential increases of 2°C and decreases of 1°C or direct step increases of 1°C up to a maximum of 46°C. Step durations (1, 2, 3, or 6 s) varied by trial. Pain ratings generally followed presented temperature, regardless of step condition or duration. For 6-s steps, OA was observed after each decrease, but the overall pain trajectory was unchanged. We found no evidence that sequential offsets could allow for little pain perception during noxious temperature presentation.

NEW & NOTEWORTHY Offset analgesia is the disproportionate decrease in pain experience following a slight decrease in noxious heat stimulus intensity. We tested whether sequential offsets would allow noxious temperatures to be reached with little or no perception of pain. We found little evidence of such overall analgesia. In contrast, we observed analgesic effects after each offset with long-duration stimuli, even with relatively low-temperature noxious stimuli.

INTRODUCTION

Offset analgesia (OA) was first described by Grill and Coghill (2002) and was defined as a disproportionate decrease in pain experience following a slight decrease in heat stimulus intensity. In a typical OA experiment, three successive periods (T1, T2, T3) each contain a continuous noxious stimulus. The first and last stimuli are of equal intensity, but the middle stimulus is slightly more intense (e.g., 45°C, 46°C, 45°C). The OA effect is revealed by a greater fall in reported pain intensity following a step back to the original noxious stimulus temperature compared with delivery of a continuous noxious stimulus temperature (e.g., 45°C, 45°C, 45°C).

MagVenture receives FDA clearance for OCD

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FDA has cleared MagVenture TMS Therapy® for adjunct treatment of Obsessive-Compulsive Disorder (OCD). This marks MagVenture’s second indication in the US. MagVenture TMS Therapy  is already FDA cleared for the treatment of major depressive disorder.

MagVenture TMS Therapy is an adjunct treatment to existing OCD therapies which may involve pharmaceutical and behavioral therapy. It is an out-patient procedure with no systemic side effects. The treatment specifically targets the networks in the brain which are known to be particularly affected by OCD, including the deeper-lying structures.

“We have worked closely with brain researchers for well over 25 years, providing numerous TMS solutions to help advance the field of neuroscience – both basic and applied. Expanding the treatment options to include other indications than major depressive disorder, such as OCD, is one more important step towards helping more adult patients improve their mental health,” says VP of Sales, MagVenture Inc, Kerry Rome.

MagVenture TMS Therapy for OCD

  • OCD treatment coil specifically designed to reach deeper cortical structures
  • Easily integrated with your current MagVenture TMS Therapy® system
  • To be used as an adjunct to current medical or behavioral therapy
  • A technology which precisely targets the area in the brain your need to reach

Additional highlights

  • MagVenture has most FDA cleared treatment options:
    • 3, 19, and 37 minute MDD protocols
    • 18 minute OCD protocol
  • Allows you to do deep or focal TMS
  • Shortest FDA cleared TMS protocol for major depressive disorder available: 3 minute Express TMS  which has the same proven efficacy as the standard, longer protocols
  • Dedicated staff for ongoing support: technical, clinical, reimbursement and marketing

What is OCD?
OCD is a mental health disorder characterized by unreasonable thoughts and fears (obsessions) which lead to repetitive behavior (compulsions). OCD can severely affect one’s daily life and routines and cause distress or even functional impairment. Although pharmaceutical and psychological interventions are available, some OCD patients experience limited results from these and need more therapeutic options.

    Transcranial Magnetic Stimulation (TMS) uses magnetic pulses to stimulate a specific area in the brain in order to improve the OCD symptoms. TMS is a well-established, FDA cleared option for people suffering from treatment-resistant Major Depressive Disorder and available throughout the US at numerous psychiatric practices and hospitals. MagVenture TMS Therapy® was FDA cleared for depression in 2015 and the first company to receive FDA clearance for the 3-minute Express TMS® – the shortest TMS treatment currently available.
    MagVenture TMS Therapy® FDA clearances: “As an adjunct for the treatment of adult patients suffering from Obsessive-Compulsive Disorder (OCD)” and “Treatment of Major Depressive Disorder in adult patients who have failed to receive satisfactory improvement from prior antidepressant medication in the current episode.”

Please note, the OCD treatment is currently only approved in the US by the FDA. The usage of TMS for any other purpose than the cleared indication, in the country in which the product is intended to be used, is considered investigational.

Medoc Thermodes

Fit to a T(hermode)

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Medoc Thermodes

We are often asked by our customers: “what thermode should I use?” Our answer is usually: “it depends”.

This is one of the most common questions we are asked when a customer approaches us, intending to buy a thermal quantitative sensory testing (QST) device.

The thermode is the probe that is attached to the participants’ skin, that on command of the computer program changes its temperature to hot or cold.

There are several types of thermodes; which one fits you best, depends mostly on your intended use.

Let’s start with the basics:

Comparing and contrasting

The classic thermode size is the 30mm by 30mm contact surface thermode, or for short: the 30*30. This thermode size has been around for decades and has therefor gathered quite the following.

Most of the normative data that has been gathered with Medoc devices around the world, and specifically by the German Research Network on Neuropathic Pain, the DFNS, has been gathered with this 30*30 thermode[1],[2],[3]. If you intend to compare your QST results to normative values that have been collected from healthy participants, you may want to consider using the 30*30.

Another quite common thermode size is the 16*16. This thermode has been in use with researchers and clinicians who wish to stimulate smaller areas, like the face[4] or the tongue[5], or perform QST on children[6].

Need for speed

One of the most asked-about thermodes is the CHEPS thermode. This thermode is special, because its technology allows working at very high speeds, for both heat and cold stimulation.

These high speeds are especially important for researchers who want to use a fast thermal stimulation in order to record Contact Heat Evoked Potentials (CHEPs)[7],[8],[9] or Cold Evoked Potentials (CEPs)[10]. Others may be interested in an application called: phasic heat temporal summation, in which very fast noxious heat pulses are applied in order to test for the wind-up phenomenon[11],[12].

Visualizing pain

The above thermode types (30*30, 16*16, CHEPS) are also available in fMRI versions. fMRI thermodes are different from normal thermodes for having additional 10 meters cable length, allowing the device to be placed outside the magnetic chamber and only the thermode to pass through the waveguide, reducing noise artifacts and insuring safety. These thermodes have undergone thorough testing and validation in different MRI environments.

Thermal stimulation is used in many trials that examined psychology (including reward processing, mindfulness, and more)[13],[14] and pain neurophysiology[15],[16].

Not your run of the mill thermode..

Then there are the specialized thermodes. Some quantitative sensory testing has been conducted on the most uncommon places in the body, to elucidate specific issues.

Intra-oral testing is conducted with a small diameter Intraoral thermode for varying purposes like; tooth sensitivity[17],[18], pain disorders involving the mouth or the face[19]and thermal taster status.

Medoc’s Intravaginal thermode, formerly known as the Genito-sensory-analyzer (GSA) is utilized in studies which seek to assess somatosensory function and pain of the genital area in women[20],[21],[22] and men[23].

 

References: [1]Hafner, J., Lee, G., Joester, J., Lynch, M., Barnes, E. H., Wrigley, P. J., & Ng, K. (2015). Thermal quantitative sensory testing: a study of 101 control subjects. Journal of Clinical Neuroscience, 22(3), 588-591. [2] Blankenburg, M., Boekens, H., Hechler, T., Maier, C., Krumova, E., Scherens, A., … & Zernikow, B. (2010). Reference values for quantitative sensory testing in children and adolescents: developmental and gender differences of somatosensory perception. PAIN®, 149(1), 76-88. [3]Yarnitsky, D., & Sprecher, E. (1994). Thermal testing: normative data and repeatability for various test algorithms. Journal of the neurological sciences, 125(1), 39-45. [4] Sampaio, F. A., Sampaio, C. R., Cunha, C. O., Costa, Y. M., Alencar, P. N., Bonjardim, L. R., … & Conti, P. C. (2019). The effect of orthodontic separator and short‐term fixed orthodontic appliance on inflammatory mediators and somatosensory function. Journal of oral rehabilitation, 46(3), 257-267. [5] Yang, Q., Dorado, R., Chaya, C., & Hort, J. (2018). The impact of PROP and thermal taster status on the emotional response to beer. Food Quality and Preference, 68, 420-430. [6] Hainsworth, K. R., Simpson, P. M., Ali, O., Varadarajan, J., Rusy, L., & Weisman, S. J. (2020). Quantitative Sensory Testing in Adolescents with Co-occurring Chronic Pain and Obesity: A Pilot Study. Children, 7(6), 55. [7] Rosner, J., Hostettler, P., Scheuren, P. S., Sirucek, L., Rinert, J., Curt, A., … & Hubli, M. (2018). Normative data of contact heat evoked potentials from the lower extremities. Scientific reports, 8(1), 1-9. [8] Jutzeler, C. R., Rosner, J., Rinert, J., Kramer, J. L., & Curt, A. (2016). Normative data for the segmental acquisition of contact heat evoked potentials in cervical dermatomes. Scientific reports, 6, 34660. [9] Granovsky, Y., Anand, P., Nakae, A., Nascimento, O., Smith, B., Sprecher, E., & Valls-Solé, J. (2016). Normative data for Aδ contact heat evoked potentials in adult population: a multicenter study. Pain, 157(5), 1156-1163. [10]Hüllemann, P., Nerdal, A., Binder, A., Helfert, S., Reimer, M., & Baron, R. (2016). Cold‐evoked potentials–Ready for clinical use?. European Journal of Pain, 20(10), 1730-1740. [11]Staud, R., Weyl, E. E., Riley III, J. L., & Fillingim, R. B. (2014). Slow temporal summation of pain for assessment of central pain sensitivity and clinical pain of fibromyalgia patients. PloS one, 9(2), e89086. [12]Bar-Shalita, T., Vatine, J. J., Yarnitsky, D., Parush, S., & Weissman-Fogel, I. (2014). Atypical central pain processing in sensory modulation disorder: absence of temporal summation and higher after-sensation. Experimental brain research, 232(2), 587-595. [13] Elman, I., Upadhyay, J., Langleben, D. D., Albanese, M., Becerra, L., & Borsook, D. (2018). Reward and aversion processing in patients with post-traumatic stress disorder: functional neuroimaging with visual and thermal stimuli. Translational psychiatry, 8(1), 1-15. [14] Harrison, R., Zeidan, F., Kitsaras, G., Ozcelik, D., & Salomons, T. V. (2019). Trait mindfulness is associated with lower pain reactivity and connectivity of the default mode network. The Journal of Pain, 20(6), 645-654. [15]Russo, A., Tessitore, A., Esposito, F., Di Nardo, F., Silvestro, M., Trojsi, F., … & Tedeschi, G. (2017). Functional changes of the perigenual part of the anterior cingulate cortex after external trigeminal neurostimulation in migraine patients. Frontiers in neurology, 8, 282. [16] Grahl, A., Onat, S., & Büchel, C. (2018). The periaqueductal gray and Bayesian integration in placebo analgesia. Elife, 7, e32930 [17] Baad-Hansen, L., Lu, S., Kemppainen, P., List, T., Zhang, Z., & Svensson, P. (2015). Differential changes in gingival somatosensory sensitivity after painful electrical tooth stimulation. Experimental Brain Research, 233(4), 1109-1118 [18] Rahal, V., Gallinari, M. D. O., Barbosa, J. S., Martins-Junior, R. L., Santos, P. H. D., Cintra, L. T. A., & Briso, A. L. F. (2018). Influence of skin cold sensation threshold in the occurrence of dental sensitivity during dental bleaching: a placebo controlled clinical trial. Journal of Applied Oral Science, 26. [19] Mo, X., Zhang, J., Fan, Y., Svensson, P., & Wang, K. (2015). Thermal and mechanical quantitative sensory testing in chinese patients with burning mouth syndrome–a probable neuropathic pain condition?. The journal of headache and pain, 16(1), 84. [20] Gruenwald, I., Mustafa, S., Gartman, I., & Lowenstein, L. (2015). Genital sensation in women with pelvic organ prolapse. International urogynecology journal, 26(7), 981-984. [21]Reed, B. D., Sen, A., Harlow, S. D., Haefner, H. K., & Gracely, R. H. (2017). Multimodal vulvar and peripheral sensitivity among women with vulvodynia: a case-control study. Journal of lower genital tract disease, 21(1), 78. [22] Lesma, A., Bocciardi, A., Corti, S., Chiumello, G., Rigatti, P., & Montorsi, F. (2014). Sexual function in adult life following Passerini-Glazel feminizing genitoplasty in patients with congenital adrenal hyperplasia. The Journal of urology, 191(1), 206-211. [23] Chen, X., Wang, F. X., Hu, C., Yang, N. Q., & Dai, J. C. (2018). Penile sensory thresholds in subtypes of premature ejaculation: implications of comorbid erectile dysfunction. Asian journal of andrology, 20(4), 330.

Ergonomic Analysis of Workers During Cannabis Cultivation Activities to Reduce Musculoskeletal Injury

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Winner: Lockheed Martin Best Project Award

Project Summary

Overview

The National Cannabis Risk Management Association (NCMRA) is interested in minimizing the strain undergone by cannabis workers, specifically at the trimming station, to reduce repetitive motion injuries and ensure worker safety. The team determined that creating an ergonomic table would best improve worker safety.

Objectives

– Characterize worker motion during cannabis trimming for the purpose of assessing musculoskeletal strain and to identify areas in need of improved methods and equipment.

– Propose and design standardized equipment (chair type and height, table shape and height, and clipper design) and methods to reduce musculoskeletal strain during trimming.

Approach

– Participate in weekly advisor and sponsor calls to gather information on the industry and discuss the plan of action.

– Research cannabis and ergonomic literature to familiarize with the current workplace setup.

– Use general workspace postural data to create the drawings and a Solidworks model of the ergonomic table.

– Design a two factor two-level experiment to analyze the standard and ergonomic table as well as the curved/straight blade trimmers.

– Collect data from the NCRMA that was collected using Noraxon’s software via sensors on various parts of the test subject’s body throughout the study.

– Analyze the anatomical angles and EMG activity collected for the standard and ergonomic table as well as the two trimmers.

Outcomes

The ergonomic table has shown improvements in the cervical spine, pelvis, and elbow flexion angles:
– The cervical spine showed a 50% decrease in average angle looking down (cervical flexion).

– The pelvic tilt decreased causing a reduction in noticeable lower back pain in the test subject.

– The elbow flexion angles are within the safe region 100% of the time when using the ergonomic table.

– The impact of straight blade trimmers and curved blade trimmers showed mixed results, but further studies would be more conclusive.

What fMRI equipment do I need to do an fMRI scan?

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In this article, you will get an overview of what equipment you need to be able to perform an fMRI exam. To perform  an fMRI exam four main components are required:

  1. MR scanner with EPI pulse sequence,
  2. Stimulus
  3. Peripheral fMRI equipment
  4. Post-processing and analysis software.

MR scanner with EPI pulse sequence

First, in order to acquire fMRI data, an MR scanner with fMRI specific pulse (Echo Planar Imaging) sequence is required. Most higher filed strength magnets (1.5T -3T) have the EPI sequence built into them.

The most common MR vendors are –

*All NordicNeuroLab products are compatible with all above.

Stimulus

Second, a library of paradigms designed to increase metabolic activity in the area of the brain responsible for a particular sensorimotor process is required. These tasks need to be presented to the patient while inside the MR scanner.

NordicNeuroLab can provide you with the stimulus presentation software nordicAktiva

Peripheral fMRI equipment

Third, and most importantly, MR-compatible hardware is needed to present auditory and visual stimulus to the patient. A response device is necessary to record patient responses, and a synchronization device is required to ensure precise timing between MR image acquisition with the onset of the stimuli.

Visual Stimulus equipment

NordicNeuroLab offers two types of visual stimulus hardware

Turnkey Solution

NordicNeuroLab provides a turnkey solution for clinical fMRI. It is a complete and user-friendly system for simplifying and standardizing implementation of functional MRI in clinical environments.

Post-processing and analysis software

Fourth, once the data is collected, a software is required to perform statistical analysis of fMRI data and overlay it on the high resolution anatomical MR images.

Additional equipment

Eye-tracking

The combination of fMRI and eye-tracking is a very powerful tool in neuroscience and has led to many advances in neuropsychology, neuropsychiatric, neurophysiology, and basic science (Bonhage et al. 2015; Tylen et al. 2012; Hausler et al. 2016; Kalpouzos et al. 2010; Kim et al. 2020)

The NordicNeuroLab VSHD are the only MR compatible goggles with integrated binocular eye-tracking. The video-based PCCR eye-tracking
technology uses two active glint points and an adjustable camera focus for precise and reliable tracking of each eye.

Icone

Asia’s ageing population drives development of rehabilitation technologies targeting elderly disabilities

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Heaxel srl., a company that designs and commercializes technologies for robot-mediated rehab, is also slated to showcase their icone® system at MFA 2020. CE Marked and FDA registered, icone® is the world’s first neurorehabilitation robot for the upper limbs, delivering intense rehabilitation via interactive games to help the brain heal itself and regain control of the arm after a stroke. The portable plug-and-play system may also be used outside of hospitals, such as in patients’ homes, making it more convenient for healthcare practitioners to monitor patients’ progress remotely.

Icone

 

“We aim to develop clinically tested and proven robotic systems that help doctors and therapists deliver effective rehabilitation treatments which are affordable and improve the quality of life of neurological patients,” said the CEO and Founder of Heaxel srl. Maria Teresa Francomano.

In addition to commercial systems built for facilities and institutions, at-home systems and products, such as Push Braces, will also make an appearance at the digital event.

Developed by Nea International B.V., Push Braces offers a diverse range of braces for different joint injuries, including the ankle, hand, knee, elbow, wrist, back, shoulder and neck. Unlike conventional taping techniques, Push Braces are clinically proven to offer the perfect balance between support and pliability, allowing patients to move without constraints as they heal.

“Push Braces are focused on the retention, recovery, and improvement of joint function. Made of durable, lightweight materials, and designed for a perfect fit, Push Braces are available in various designs for different areas of the body and are highly comfortable in shoes and under clothing, ensuring better patient compliance for effective joint repair,” said International Account Manager of Nea International BV, Jorgen Van Beem.

nBx DCE

DCE Module – nordicBrainEx is now available at the NNL Academy

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nBx2.3_DCE

About the DCE Module

The DCE analysis uses two-compartment extended Tofts modeling to generate output maps such as volume transfer constant (Ktrans), rate constant (Kep), plasma volume (Vp), fractional volume (Ve), time to peak (TTP), and area under the curve (AUC). Output maps and results including volume-of-interest statistics, tissue response curves, and histograms can be saved and exported to PACS. In addition, the Ktrans map can be thresholded and exported to neuronavigation platforms.

About nordicBrainEx

nordicBrainEx is a vendor neutral clinical, DICOM-compatible post-processing software that is designed to be user-friendly and contribute to improved neuroradiolosgist workflow and productivity. Advanced volume of interest tools, 2D/3D visualization of BOLD activation areas, DTI tractography, and perfusion maps, combined with advanced interaction tools allow clinicians to perform extensive evaluations of brain tissue surrounding pathological areas. All processed data can be saved in a comprehensive report, exported to PACS or presurgical planning and neuronavigation systems.

Read more about nordicBrainEx here

Join the NNL Academy with over 300 members

To access the tutorial you can sign-up to the NNL Academy for free. There you’ll have access to all our tutorials for nordicBrainEx, nordicICE, and nordicAktiva.

virtual reality in MR

Virtual Reality during an fMRI scan – is it possible?

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Virtual Reality has become more popular for Neuroscientist

Are you a neuroscientist interested in studying how memories are created and how we use memory to navigate in space?

Or a neurologist who would like to develop non-invasive methods for early detection of neurological disorders such as Parkinson’s disease, Alzheimer’s disease, and other forms of dementia?

Perhaps you are a neuropsychologist who would like to understand the neurophysiological manifestations of phobias and PTSD and design better treatment strategies? Or maybe a neuromarketing researcher who would like to study how our mind responds to certain stimuli on the neurophysiological and neurofunctional level to apply this knowledge to marketing applications?

The Challenge

The MR environment presents a challenge to do Virtual Reality inside an MR because the commercial VR equipment isn’t MR compatible. At CAMH (Center for Addiction and Mental Health) they are using an LCD screen for visual presentation. Recent advancements now allow participants to have a more virtual experience through the use of MR compatible goggles.

fMRI studies with Virtual Reality have been performed by presenting the VR outside of the MR environment and then doing an MRI scan.

We believe that the VisualSystem HD from NordicNeuroLab is a solution to this issue and gives the researcher the opportunity to do an immersive stimulus presentation during the scan. Not only will this enhance the immersive experience, but we believe that this will improve the quality of your results.

Combining VR, fMRI, and eye tracking

Our team of Application Scientist have created a PDF to give you an introduction to immersive technology for functional neuroimaging.

BESA statistics

BESA Statistics 2.1 released!

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The successor to the ground-breaking BESA Statistics program is there! BESA Statistics 2.1 greatly enhances the options of the previous version 2.0. As before, dedicated workflows allow you to perform t-test, one-way ANOVA, and correlation analyses of your data using the parameter-free cluster permutation statistics which so elegantly solve the multiple-test problem. We have added several input data types to this pipeline, in order to ensure that time-frequency analyses and connectivity analyses are now fully supported.

The main highlights of the new release are:

  • In all workflows, the data type Connectivity can now be used. This enables direct import of results obtained by BESA Connectivity for group statistics on connectivity results in sensor space or source space.
  • For Image data, a configurable slice view is available that displays sequences in one of three available orthogonal orientation.
  • The color theme can be adjusted between BESA White and the previous BESA Standard.
  • Several new color maps are available.
  • The data values are displayed on mouse-over in the detail windows.
  • Time-frequency data stored by BESA Connectivity with wavelet analysis can now be read with the correct (logarithmic) frequency spacing.
  • Single-trial time-frequency data can now be read in the t-test workflow (.tfcs data format).
  • There is no upper limit on the number of data files imported into the workflow.
  • A new image export format is available (.svg).
  • Screenshots and cluster summary results can now be copied to the clipboard using the right mouse popup menu.

The Pathophysiology of Acute Brain Damage

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Topics:
Characteristics of traumatic brain injury and subarachnoid hemorrhage
Preliminary data collected through the CNS Monitor

Date Recorded:
– Monday, November 30, 2020

Disclaimer:
The views and opinions expressed by the presenter and other third parties do not necessarily reflect those of Moberg Research, Inc. Moberg Research, Inc. makes no clinical claims regarding information described by the presenter and other third parties.

National CME & TMS training workshop

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The 5Th National CME and 2nd Hands-on-Training workshop is one of its kind in India delivering hands-on training in administration of rTMS Therapy. This year we welcome practitioners and researchers from across the country and world-wide to enlighten using the field of Transcranial Magnetic Stimulation.

This workshop creates a diverse platform for novel and keen individuals as well as
renowned national and international experts to collaborate together to further their knowledge.

Thus, this program not only sets up a platform to acquire skills evaluating TMS from
both clinical and research perspectives, but also sets an opportunity for networking.

The didactic sessions in program tend to cover series of topic relevant to running a
TMS clinical service or rTMS based research project, including:

  • Introducing Neuromodulation: Beginning of Interventional Psychiatry
  • Neurophysiology of rTMS: Recent Updates
  • Clinical Applications of rTMS
  • Personalisation and Optimisation of TMS through Neuronavigation
  • COVID 19 Pandemic and Neuromodulation: What Future Beholds
  • TMS: From Books to Bed

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Apple vs. Samsung: A Neuroscientific fMRI study

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In 2007, Samsung was the world’s largest mobile device manufacturer. The same year Apple Inc introduced the iPhone to the world. The iPhone became a game-changer for the mobile device industry and the fascination for the device has had an impact on people’s lives, but also their brains.

Neuroscientists Prof. Dr. Jürgen Gallinat and Dr. Simone Kühn conducted an fMRI study to see if and how people’s brains responded differently to an Apple product vs. a Samsung product.

During this experiment, the neuroscientist was using the old VisualSystem from NordicNeuroLab to present the stimulus to the research attendees (Learn more about the new improved VisualSystem HD here)

The 25 participants attended the study and they were presented with pictures of Samsung and Apple products. Based on the fMRI results they discovered that the Samsung products stimulated the prefrontal cortex and the Apple product stimulated a part of the brain responsible for liking people.

Using fMRI for Neuromarketing

One interpretation is that Samsung is more a product for the “mind” while Apple is more a product that evokes “gut-feelings”

Prof. Dr. Jürgen Gallinat

How do we make our buying decisions? Do we make decisions consciously based on facts, reason, and logic? Or do we actually make decisions unconsciously based on emotions, feelings, and intuition?

For instance, what do you prefer? Coca Cola or Pepsi? Most importantly: why?

This is what Neuromarketing is trying to answer, and therefore neuroscientist use techniques such as fMRI, and stimulus presentation tools like VisualSystem HD, to understand how our brains respond to different advertising, products, and how they affect our buying decisions.

 

How playing an instrument benefits your brain.

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Your brain on fire

In the last few decades, neuroscientist have made enormous breakthroughs in understanding how our brains work by monitoring them in real time. One of the techniques being used is functional magnetic resonance imaging (fMRI).

Usually, the participants are given tasks through fMRI equipment like the InroomViewingDevice or VisualSystem HD. These tasks can be language tasks or math problems.

Doing these tasks activates specific parts of the brain, but when the participants listened to music, multiple parts of the brain was activated.

Playing music is the brain’s equivalent of a full-body workout

Someone took it a step further by creating instruments with materials that weren’t magnetic and played the instrument while doing an functional MRI scan.

Playing a musical instrument engages practically every area of the brain at once, especially the visual, auditory, and monitor cortices.

Anita Collins – TED-Ed

Learn to play

Learning to play any instrument has great benefits. At NordicNeuroLab we have several of our employees who play instrument on a regular basis. And we encourage each other to pick up a new song or an instrument, simply because it’s good for the brain.

Learning new songs, or new instruments is always hard but it is also equally rewarding.

Trond Ytrøy – VPO at NordicNeuroLab

Nordic Neurolab

NordicNeuroLab Supports The Best Global Universities for Neuroscience and Behavior

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Based on the latest ranking of the best global universities for Neuroscience and Behavior, we are proud to announce that nine of the top ten list are NordicNeuroLab customers.

Our journey, as a company, started in Bergen, Norway in 2001. Since then we’ve had over 2000 installations in 70+ countries, and we are still growing.

Best Global Universities for Neuroscience and Behavior according to U.S.News & World Report:

RANK NNL CUSTOMER UNIVERSITY NAME
1 x Harvard University
2 x University of California – San Francisco
3 x Massachusetts Institute of Technology
4 x Stanford University
5 x University College London
6 x Johns Hopkins University
7 x Columbia University
8 x University of Pennsylvania
9 Washington University in St. Louis
10 x University of Oxford

FDA clearance for MagVenture: 3 minute depression treatment

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    For people suffering from severe depression, the road to remission just became a lot shorter: The treatment is known as Transcranial Magnetic Stimulation (TMS), and MagVenture has now, as the only company in the US, received FDA clearance for a newer and much faster treatment protocol which will cut down treatment time to just 3 minutes per session*. Before that, the required treatment time per session was up to 37 minutes.
    TMS has been FDA cleared for treatment-resistant major depressive disorder since 2008. Since then, over 1,000 psychiatric clinics have emerged in the US. Most private health insurance companies also cover the treatment. The relatively long treatment sessions have, however, not only limited the treatment capacity for TMS practices but also hindered a more widespread dissemination. Until now, each session has been up to 37 minutes long, with 20-30 sessions needed in total. The new treatment form, which is known as Theta Burst Stimulation (TBS), offers one significant advantage: Time. A TBS treatment session lasts only 3 minutes and thus has the potential to revolutionize the clinical field of TMS.
    “We have named it “Express TMS®” because that’s what it is: a treatment which is just as safe and effective for the treatment of depression as conventional TMS, only much, much faster. We are happy and proud to be the first in the US to receive an FDA clearance for this revolutionary treatment which is backed up by substantial scientific evidence. Our current treatment system, MagVenture TMS Therapy, can easily be upgraded with the new Express TMS option. This will enable our many customers to treat far more patients per day without having to invest in another TMS device. For people needing treatment, this will also be a huge benefit, as treatment will now take up less of their time,” says Kerry Rome, Vice President of Sales, MagVenture Inc.
    The new FDA cleared treatment protocol is based on a new clinical study, named the THREE-D trial, and led by a partnership of three leading research hospitals in Canada (CAMH, UHN, and UBC). It is the largest, double-blinded, randomized TMS trial to date, with 414 participants suffering from major depressive disorder. Response/remission rates were 32% for those receiving the TBS protocol, whereas 49% had an improvement in their depressive symptoms. These rates are similar to the standard, longer TMS protocol.

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Drug screening platform using human induced pluripotent stem cell‐derived atrial cardiomyocytes and optical mapping

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ORIGINAL RESEARCH : Open Access

First published: 14 September 2020
https://doi.org/10.1002/sctm.19-0440

Marvin G. Gunawan, Sarabjit S. Sangha, and Sanam Shafaattalab contributed equally to this study.

Funding information: Stem Cell Network; Canada Innovation Fund; Canadian Institutes of Health Research

PDF download

Abstract

Current drug development efforts for the treatment of atrial fibrillation are hampered by the fact that many preclinical models have been unsuccessful in reproducing human cardiac physiology and its response to medications. In this study, we demonstrated an approach using human induced pluripotent stem cell‐derived atrial and ventricular cardiomyocytes (hiPSC‐aCMs and hiPSC‐vCMs, respectively) coupled with a sophisticated optical mapping system for drug screening of atrial‐selective compounds in vitro. We optimized differentiation of hiPSC‐aCMs by modulating the WNT and retinoid signaling pathways. Characterization of the transcriptome and proteome revealed that retinoic acid pushes the differentiation process into the atrial lineage and generated hiPSC‐aCMs. Functional characterization using optical mapping showed that hiPSC‐aCMs have shorter action potential durations and faster Ca2+ handling dynamics compared with hiPSC‐vCMs. Furthermore, pharmacological investigation of hiPSC‐aCMs captured atrial‐selective effects by displaying greater sensitivity to atrial‐selective compounds 4‐aminopyridine, AVE0118, UCL1684, and vernakalant when compared with hiPSC‐vCMs. These results established that a model system incorporating hiPSC‐aCMs combined with optical mapping is well‐suited for preclinical drug screening of novel and targeted atrial selective compounds.

Significance statement

Current in vitro drug screening systems for treatment of atrial fibrillation are confounded by cell type heterogeneity, specificity, and translatability to human physiology. In this study, we developed a drug screening platform using human induced pluripotent stem cell‐derived atrial cardiomyocytes (hiPSC‐aCMs) and a multiwell optical mapping system. The high‐content optical mapping system reports on membrane voltage and Ca2+ transients which serve as critical biomarkers of cardiac function in vitro. The hiPSC‐aCMs generated by this protocol possess atrial‐specific molecular profiles, functional signatures, and pharmacological response. These findings demonstrate that the platform can be readily applied as a relevant preclinical model for drug screening for atrial fibrillation therapies.

1 INTRODUCTION

The advent of human induced pluripotent stem cell‐derived cardiomyocytes (hiPSC‐CMs) has revolutionized the field of cardiac research. It has enabled the study of cardiac diseases in a patient‐specific and human‐relevant in vitro model system which provides a unique opportunity for clinical translation.1 Furthermore, the ability to differentiate chamber‐specific cardiomyocytes allows for a more precise study of cardiac disease physiology and pharmacology.

The cardiomyocytes of the lower (ventricles) and upper (atria) chambers have distinct characteristics that arise from differential developmental pathways. Previous work in vivo has shown that the expression patterns of retinoic acid and retinaldehyde dehydrogenase 2 (RALDH2) are important determinants of the atrial fate.2–5 These results were later recapitulated in a pivotal study by Lee and Protze et al6 who determined that atrial cardiomyocytes (aCMs) differentiated from human embryonic stem cells (hESCs) originate from a unique mesoderm characterized by robust RALDH2 expression. This study established an atrial differentiation protocol that included the addition of retinoic acid. Retinoic acid has also been utilized to selectively differentiate hESCs and hiPSCs into aCMs in other studies.6–10

The distinct properties of the atrial and ventricular cardiomyocytes are determined by the differential expression of unique sets of ion channels and other proteins that optimize their specific function. Drugs that target atrial ion channels selectively can therefore produce differences in pharmacological function in the two chambers. This atrial‐selective pharmacology is of utmost interest in the study and treatment of atrial‐specific diseases such atrial fibrillation (AF), which is the most common heart rhythm disorder. Investigating atrial‐selective pharmacology can assist and guide novel cardiac drug development as well as improving both safety and efficacy by avoiding potential toxic electrophysiologic effects on the ventricular chambers.

The differential pharmacology of stem cell‐derived aCMs was studied previously by Laksman et al7 who showed that flecainide can rescue the AF phenotype in a dish. Other studies have also studied the selective pharmacological effects of agents on hiPSC‐derived aCMs but have largely focused on proof‐of‐concepts using limited number of test compounds and standard measurement systems that are low in throughput.9, 10 With a focus on translation, a preclinical model platform that characterizes pharmacological activity must capture the main cardiac functional signatures that most closely mimic and predict human cardiac physiology and drug responses. As such, we established in this study an in vitro assay platform by combining hiPSC‐derived atrial cardiomyocytes (hiPSC‐aCMs) and high‐content optical mapping, a noninvasive all‐optical system that simultaneously measures membrane potential (Vm) and Ca2+ transients at a high‐resolution in a monolayer tissue format.

We first demonstrate a selective hiPSC‐aCM differentiation protocol by modifying the well characterized GiWi protocol11 through the controlled introduction of retinoic acid. The recapitulation of the human atrial phenotype of the hiPSC‐aCMs was validated with assays that measure the expression of gene transcripts and proteins, as well as functional signatures. We then demonstrate the utility of our platform as an atrial‐selective drug screening tool by using existing clinical and experimental drugs. The model established in this study adds to our current understanding of the utility of stem cell‐derived cardiomyocytes in preclinical and translational research focused on screening new pharmacological agents.

2 METHODS AND MATERIALS

A detailed methods section is available in the Supplemental Information.

2.1 Maintenance and expansion of hiPSCs

hiPSCs (WiCell, IMR90‐1) were maintained and expanded in mTeSR1 medium and feeder‐free culture using 6‐well plates coated with Matrigel. Using Versene (EDTA), hiPSCs were passaged every 4 days or ~85% confluency at 1:15 ratio. Passaged hiPSCs were cultured with mTeSR1 supplemented with 10 μM Y27632 for the first 24 hours and the mTeSR1 was exchanged daily during cell culture maintenance.

2.2 Directed differentiation of hiPSCs into atrial and ventricular subtypes

hiPSC‐derived ventricular cardiomyocytes were differentiated by employing a modified GiWi protocol11 that we previously published.12 In brief, hiPSCs were seeded at a density of 87 500 cells/cm2. At day 0, differentiation was initiated using 12 μM CHIR99021. At day 3, the cells were incubated with 5 μM IWP‐4. At day 5, the media were refreshed with RPMI‐1640 supplemented with B27 minus insulin. At day 7, the medium was replaced with cardiomyocyte maintenance media (RPMI‐1640 supplemented with B27 with insulin). Thereafter, cardiomyocyte maintenance media were replaced every 4 days. For the atrial differentiation protocol, retinoic acid (RA) addition was first optimized in pilot studies (Figure S2 and S3) and determined to be 0.75 μM RA every 24 hours from days 4‐6.

2.3 Flow cytometry

hiPSC‐aCMs and hiPSC‐vCMs at Day 20‐30 postdifferentiation were dissociated into single cells as described in the Supplemental Information. The harvested cells were fixed in 4.1% PFA solution for 25 minutes and then washed and permeabilized in Saponin/FBS. Cells were subsequently incubated overnight in primary mouse‐cTnT (1:2000) and rabbit‐MLC2V (1:1000) antibodies. Subsequently, the cells were washed and incubated in secondary goat anti mouse Alexa‐488 (1:500) and goat anti rabbit Alexa‐647 (1:2000) antibodies for 1 hour, respectively. Cells were then washed and suspended in PBS for analysis. All analyses were performed using the BDJAZZ Fluorescence Activated Cell Sorter.

2.4 mRNA expression profiling

Gene expression profiling was conducted using multiplexed NanoString and real time quantitative PCR (qPCR). Pooled total RNA was used in both assays. The extracted RNA was reverse transcribed into cDNA which was used in the qPCR assay. Oligonucleotide sequences are described in Table S7. The multiplexed mRNA profiling was conducted using NanoString Technologies (Seattle, Washington) platform with a custom Codeset containing 250 gene probes. Analysis was performed on the Sprint instrument and nSolver analysis software with the Advanced Analysis module.

2.5 Atrial natriuretic peptide measurement

The levels of atrial natriuretic peptide (ANP) of hiPSC‐aCMs and ‐vCMs were measured by a competitive enzyme‐linked immunosorbent assay (ELISA) using a commercially available kit (Invitrogen, California). The assay was conducted according to the manufacturer’s protocol and was measured using a spectrophotometric plate reader.

2.6 Cardiomyocyte enrichment

For cardiac enrichment, hiPSC‐aCMs and ‐vCMs at day 20‐30 postdifferentiation were dissociated into single cells which were then enriched using a MidiMACS PSC‐derived Cardiomyocyte Isolation Kit (Miltenyi Biotec, Germany) according to the manufacturer’s protocol. Enriched hiPSC‐CMs were seeded on Matrigel‐coated 24‐well plates at a seeding density of 600 000 cells per well.

2.7 Patch‐clamp recordings

Single hiPSC‐aCMs and ‐vCMs were plated on gelatin (0.1%) and Geltrex (1:10) at 30 000 cells per well. After 48 hours in culture, glass electrodes were used to achieve the whole‐cell configuration with single hiPSC‐CMs and only cells with gigaohm seals were used for further analysis. The formulation for internal and external recordings solutions are outlined in the Supplemental Information. Current recordings were performed using the Axon Instruments 700B amplifier and digitized at 20 kHz. All recordings were performed at 33‐35°C as maintained. For pacing at 1 Hz, gradually increasing amounts of current were injected with a 1 ms pulse width until reliable action potentials (APs) were triggered. The maximal upstroke velocity was determined by calculating the maximum derivative and the resting membrane potential was measured during a 5 second epoch without spontaneous activity 1 minute after break‐in. Further details on data analysis are found in the Supplemental Information.

2.8 Optical mapping

Optical mapping recordings were performed on enriched monolayers of hiPSC‐aCMs and ‐vCMs cultured in a 24‐well plate format at Day 45‐60 postdifferentiation. Imaging experiments were conducted using Ca2+ Tyrode’s solution (formulation found in Supplemental Information). The hiPSC‐CMs were loaded with RH‐237, blebbistatin, and Rhod‐2AM sequentially before imaging as described.12, 13 Both RH‐237 and Rhod‐2AM were excited by 530 nm LEDs. Images were acquired at a frame rate of 100 frames/second by a sCMOS camera (Orca Flash 4.0V2, Hamamatsu Photonics, Japan) equipped with an optical splitter. The cells were paced using programmable stimulation. Data collection, image processing, and initial data analysis were accomplished using custom software. The multiwell optical mapping system was custom engineered in the lab based on a system as described previously.12, 13 Further details are found in the Supplemental Information.

2.9 Pharmacological analyses

The drugs used in this study are listed Table S8. Drug stocks were further diluted in Ca2+ Tyrode’s solution prior to pharmacological testing with the final DMSO concentration in the experimental solution not exceeding 0.03% (v/v). Drug effects were studied in serum‐free conditions (ie, Ca2+ Tyrode’s and drug only) at four doses by sequentially increasing the drug concentration in the same well with recordings at 20‐minute intervals.

2.10 Statistical analysis

Further details on data and statistical analysis can be found in the Supplemental Information. Unpaired t tests were conducted to compare two groups (ie, hiPSC‐aCMs vs hiPSC‐vCMs) in the analysis of qPCR, ELISA, patch clamp recordings, and optical mapping (baseline condition and normalized drug effects). Analysis of dose‐dependent effects was performed using one‐way ANOVA and Dunnett’s post hoc test. All data are presented as mean ± SEM unless noted otherwise. Significance level for all statistical analysis was set at p < .05 with the following notation: *p < .05, **p < .01, ***p < .001.

3 RESULTS

3.1 RA treatment drives cardiac differentiation into atrial phenotype

We first optimized the atrial differentiation protocol by altering the concentration and timing of retinoic acid (RA) based on the molecular signatures of atrial phenotype as measured by qPCR and flow cytometry (Figures S2 and S3). Higher dose of RA reduced cardiac differentiation efficacy defined by the decrease in the cTnT+ proportion of the total cell population as measured by flow cytometry (Figure S2A). The finalized protocol to generate hiPSC‐aCMs included RA addition at 0.75 μM every 24 hours on days 4, 5, and 6 (Figure 1A) which was found as a balance between sufficiently driving atrial differentiation as defined by decreased ventricular marker myosin light chain 2 ‐ ventricular paralog (MLC‐2v) while having no impact cardiac differentiation efficacy Figures S2 and S3).

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FIGURE 1

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Directed differentiation of hiPSC‐derived atrial and ventricular CMs. A, Schematic depicting the atrial differentiation protocol. Doses of 0.75 μM retinoic acid (RA) were added to the cells every 24 hours on days 4, 5, and 6 with media exchanged to RPMI1640 + B27 with insulin at day 7. Cells were harvested for analysis at day 20. B, qPCR analysis of ventricular markers MYL2 and IRX4, cardiac marker NKX2.5, and atrial markers NPPA, GJA5, CACNA1D, KCNA5, and KCNJ3. n = 3, unpaired t test, *p < .05. C, Flow cytometric analysis of cardiac troponin T (cTnT) and myosin light chain 2v (normalized to cTnT expression) in hiPSC‐aCMs and ‐vCMs. n = 4, unpaired t test, ***p < .001. D, Average beating rates of hiPSC‐aCMs and ‐vCMs from the day they begin to beat until day 20. n = 4 independent differentiation batches. E, Atrial Natriuretic peptide (ANP) concentration between hiPSCs, and hiPSC‐aCMs and ‐vCMs determined by competitive ELISA. n = 3 and n = 2 hiPSC lines, unpaired t test *p < .05, **p < .01, ***p < .001. Data are presented as mean ± SEM One n represents one independent differentiation batch

Compared with hiPSC‐vCMs, hiPSC‐aCMs were found to have no significant difference in pan cardiac phenotype. Expression of the pan cardiac transcript NKX 2.5 measured by qPCR was similar between hiPSC‐aCMs and ‐vCMs (Figure 1B), as was cardiac troponin T (cTnT) protein expression measured by flow cytometry (Figures 1C and S1). The protein expression of MLC‐2v was reduced in hiPSC‐aCMs compared with hiPSC‐vCMs (8.0 ± 1.1% vs 57.0 ± 0.5%; p < .05) (Figure 1C). Furthermore, hiPSC‐aCMs displayed higher concentrations (increased by 91%) of atrial natriuretic peptide (ANP) at 65 ± 2 compared with 34 ± 6 ng/mL in hiPSC‐vCMs as measured by ELISA (p < .05).

The qPCR assay revealed that atrial‐specific transcripts such as atrial natriuretic peptide (NPPA), connexin 40 (GJA5), the calcium channel CaV1.3 (CACNA1D), and the K+ channels Kv1.5 (KCNA5) and Kir3.1 (KCNJ3) transcripts were all expressed at a significantly higher levels in hiPSC‐aCMs compared with hiPSC‐vCMs (p < .05, Figure 1B). Another ventricular marker, IRX4, also had decreased expression in hiPSC‐aCMs (Figure 1B). Furthermore, consistent with previous studies,8–10, 14, 15 hiPSC‐aCMs started beating at day 10 or earlier and exhibited an increased beating frequency relative to hiPSC‐vCMs, which started beating around day 10‐12 postdifferentiation.

3.2 Gene expression analysis of hiPSC‐aCMs

We performed an extensive gene expression analysis of hiPSC‐aCMs and ‐vCMs using NanoString technology in which each mRNA copy was digitally counted for accurate and sensitive detection of gene expression.16 Five independent differentiation batches of each cardiac subtype were included in the analysis. The unsupervised hierarchical clustering analysis showed clear grouping of hiPSC‐aCM samples that were segregated relative to hiPSC‐vCMs (Figure 2A). The gene expression profile of the hiPSC‐vCM samples were more variable with 2 samples closer in distance to the hiPSC‐aCMs while three samples displayed clear segregation (Figure 2A). The overall difference in global gene expression and lineage between hiPSC‐aCMs and ‐vCMs was also captured in the principal component analysis (PCA, Figure S4A). Out of the 250 transcripts analyzed, 200 genes were detected above background noise defined by a threshold of 50 raw digital counts as determined by the negative controls of the assay. In the hiPSC‐aCMs, 14 and 27 genes were significantly upregulated and downregulated, respectively (Figure 2C). As expected, hiPSC‐aCMs displayed significantly higher expression profiles of atrial‐specific markers including atrial‐specific K+ channel Kv1.5 (KCNA5) and transcription factors (NR2F2 and TBX18) (Figure 2C). Meanwhile, hiPSC‐vCMs displayed higher expression of ventricular‐specific genes such as those encoding for contractile proteins MYL2, MYH7, and the L‐type Ca2+ channel isoform Cav1.2 (CACNA1C) (Figure 2C). The genes encoding for the proteins in the sarcoplasmic reticulum complex such as TRDN, CASQ2, and RYR2 were expressed in significantly lower amounts in the hiPSC‐aCMs samples (Figure 2C). Meanwhile, pan‐cardiac markers NKX2‐5 and TNNT2 were expressed at similar levels in both hiPSC‐aCMs and ‐vCMs, further corroborating the efficiency of the differentiation protocol (Figure S4B).

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FIGURE 2

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Gene expression analysis of hiPSC‐aCMs and ‐vCMs using NanoString. Global gene expression pattern of hiPSC‐aCMs and ‐vCMs shown in A, heat map of the expression of the 250 genes across samples of hiPSC‐aCMs and ‐vCMs. The cluster dendrogram shows the unsupervised hierarchical clustering that was conducted using the agglomerative algorithm and the Euclidian distance criterion. B, Differentially expressed genes between hiPSC‐aCMs and ‐vCMs expressed in volcano plot shows 14 upregulated (red) and 27 downregulated (blue) genes in hiPSC‐aCMs. Solid horizontal line represents the Benjamini‐Hochberg false discovery rate (FDR) adjusted p‐value <.05 (−log10 = 1.3). Dashed vertical lines represent the arbitrary log2 fold change cut‐off of −0.5 and 0.5. C, Forty‐two differentially expressed genes identified from the statistical criteria of FDR adjusted p‐value <.05 and log2 fold change of <−0.5 and >0.5. Data are presented as mean ± SEM. n = 5 independent differentiation batches

3.3 Functional phenotyping of hiPSC‐derived atrial cardiomyocytes

We compared the electrophysiological characteristics of the differentiated hiPSC‐aCMs and ‐vCMs using whole‐cell patch clamp. Confirming our observations in tissue culture, the spontaneous beating rates were higher in the single hiPSC‐aCMs than in ‐vCMs (Figure 3A,C). Whole cell current clamp recordings demonstrated the ventricular‐like AP morphology of hiPSC‐vCMs with a clear and prolonged plateau phase while the AP of the hiPSC‐aCMs displayed atrial‐like morphology with a shorter action potential duration (APD) and a lack of prolonged plateau phase at both spontaneous beating rates (Figure 3B,D, left panel) and paced at 1 Hz (Figure 3B,D, right panel). No statistical differences were observed in the resting membrane potential and the maximum upstroke velocity of hiPSC‐aCMs and ‐vCMs. The APD at 50% (APD50) and 90% (APD90) of the peak voltage were significantly shorter in hiPSC‐aCMs than ‐vCMs at both spontaneous beating rates (APD50: 157 ± 16 ms vs 349 ± 35 ms, p‐value <.005; APD90: 249 ± 34 ms vs 484 ± 30 ms, p‐value <.005) and paced at 1 Hz (APD50: 157 ± 16 ms vs 264 ± 44 ms, p‐value <.05; APD90: 242 ± 22 ms vs 341 ± 48 ms, p‐value <.05).

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FIGURE 3

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hiPSC‐aCMs and ‐vCMs have distinct electrophysiological characteristics. Single differentiated hiPSC‐aCMs and ‐vCMs were plated on gelatin and Geltrex after 30 days in culture. A, Whole cell current clamp recordings from a spontaneously beating hiPSC‐vCM. B, Recorded action potential (APs) demonstrates typical prolonged plateau phase in both spontaneous (left) and/or paced at 1 Hz (right). C, Current clamp recording from a spontaneously beating hiPSC‐aCM. D, Single AP from hiPSC‐aCM demonstrates shortened action potential duration (APD) and lack of prolonged plateau phase, spontaneous (left), paced at 1 Hz (right). E, The first differential of voltage recordings from hiPSC‐aCMs and ‐vCMs were used to calculate the maximal upstroke velocities. F, One minute after achieving the whole‐cell configuration, the average resting membrane potential was measured. G, Spontaneously beating and 1 Hz paced APs were assessed for duration at 50% of peak (APD50), and H, 90% of peak (APD90). Statistics were performed by unpaired t test. *p < .05, ***p < .005. Data are presented as mean ± SEM. Two differentiation batches were included in this analysis

We further assessed the functional properties of hiPSC‐aCMs and ‐vCMs using optical mapping with simultaneous measurement of APs and calcium transients (CaT). Like the patch clamp recordings, optical membrane voltage measurements revealed similar atrial‐like and ventricular‐like AP morphology in the hiPSC‐aCMs and ‐vCMs, respectively (Figure 4A). AP and CaT durations were quantified at early, mid, and late repolarization (APD20, APD50, and APD80) and Ca2+ decay (CaTD20, CaTD50, and CaTD80), respectively. These stages reflect different phases of ionic currents across the plasma membrane and the extrusion of Ca2+ handling mechanics.

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FIGURE 4

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Functional phenotyping of hiPSC‐derived atrial and ventricular CMs using optical mapping. Representative average traces of A, action potential and B, Ca2+ transients of hiPSC‐aCMs and ‐vCMs electrically paced at 1 Hz. C, Electrical restitution curve measured at APD80 relative to the diastolic interval (DI). D, Quantification of early‐ (APD20), mid‐ (APD50), and late‐ (APD80) repolarization, unpaired t test, *p < .05, **p < .01. E, Quantification of early‐ (CaTD20), mid‐ (CaTD50), and late‐ (CaTD80) Ca2+ transient decay, unpaired t test, ***p < .001. F, Time to peak (TTP) of the Ca2+ transient, unpaired t test, ***p < .001. G, Time constant (τ) of Ca2+ decay, unpaired t test *p < .05. H, Maximum slope of the electrical restitution as shown in panel C, unpaired t test, *p < .05. Electrical restitution curves were measured under a variable rate pacing protocol (60‐200 bpm) as described in the Supplemental Information. n = 4 (four independent differentiation batches) and cardiac enriched hiPSC‐aCMs and ‐vCMs were analyzed in these set of experiments. Data are presented as mean ± SEM

For these experiments, both hiPSC‐aCMs and ‐vCMs were paced at 1 Hz. All measured levels of the APD were significantly shorter in hiPSC‐aCMs compared with hiPSC‐vCMs (APD20: 84 ± 8 ms vs 127 ± 6 ms, p < .05; APD50: 131 ± 12 ms vs 191 ± 8 ms, p < .01; APD80: 179 ± 16 ms vs 251 ± 12 ms, p < .05; Figure 4D). The overall CaTD of hiPSC‐aCMs was significantly shorter than that of hiPSC‐vCMs (CaTD20: 180 ± 12 ms vs 266 ± 12 ms, p < .001; CaTD50: 282 ± 18 ms vs 397 ± 16 ms, p < .001; CaTD80: 474 ± 27 ms vs 615 ± 18 ms, p < .001; Figure 4E). Compared with hiPSC‐vCMs, hiPSC‐aCMs displayed significantly faster CaT time‐to‐peak (hiPSC‐aCMs: 116 ± 7 ms vs hiPSC‐vCMs: 246 ± 10 ms, p < .05) and faster decay kinetics (τ; hiPSC‐aCMs: 350 ± 39 ms vs hiPSC‐vCMs: 671 ± 118 ms, p < .05) indicating that Ca2+ handling mechanics are accelerated in hiPSC‐aCMs (Figure 4F,G).

The direct comparison between whole‐cell patch clamp and optical mapping read‐outs paced at 1 Hz is shown in Figure S7. We observed no differences in the read‐outs of hiPSC‐aCMs at APD20 (optical: 84 ± 8 ms, patch: 98 ± 12 ms) and APD50 (optical: 131 ± 12 ms, patch: 169 ± 19 ms). However, APD80 of hiPSC‐aCMs measured by patch clamp was longer than the optical APD80 (253 ± 22 ms vs 179 ± 16 ms, p < .05). Similarly, both APD20 (216 ± 22 ms vs 127 ± 6 ms) and APD80 (393 ± 62 vs 251 ± 12 ms) of hiPSC‐vCMs measured by patch clamp were longer than the comparable optical measurements. APD50 of hiPSC‐vCMs did not show a statistical difference between the two assays (optical: 191 ± 8 ms, patch: 308 ± 60 ms).

Rate‐dependent properties are critical in cardiac function. A variable rate protocol (Figure S6) in which the hiPSC‐CMs were electrically paced with increasing frequency at every cycle was used to investigate the electrical restitution dynamics. The electrical restitution curve reflects the ability of the cardiac system to accommodate a higher pacing rate by progressive shortening of APD80 and is described as APD80 in relation to the diastolic interval (DI). Compared with hiPSC‐vCMs, the electrical restitution curve of the hiPSC‐aCMs displayed a flatter portion and did not show APD80 shortening at longer diastolic intervals (Figure 4F). The extensive shortening in APD80 started at shorter diastolic intervals for hiPSC‐aCMs (<275 ms) compared with hiPSC‐vCMs (<500 ms). The maximum slope of the restitution curve was higher in hiPSC‐vCMs compared with hiPSC‐aCMs (1.26 ± 0.08 vs 0.91 ± 0.04, p < .05; Figure 4G) indicating faster kinetics of APD in response to higher pacing rate.

3.4 In vitro screening for atrial‐selective pharmacology

We first established the utility of optical mapping to detect a pan‐cardiac pharmacological response by using dofetilide, a strong blocker of the rapid delayed rectifier K+ current (IKr),17 an ionic current expected to be present in both hiPSC‐aCMs and ‐vCMs.18 Dofetilide elicited a dose‐dependent response in both hiPSC‐aCMs and ‐vCMs. Compared with predrug baseline, dofetilide at 100 nM prolonged APD80 of both hiPSC‐aCMs from 182 ± 16 ms to 355 ± 24 ms (95 + 7% prolongation) and of hiPSC‐vCMs from 238 ± 20 ms to 319 ± 45 ms (34 ± 14% prolongation, p < .05; Table S1 and Figure 5C). The drug prolonged early‐repolarization (APD20) of hiPSC‐vCMs at 10 and 30 nM while having no effect on APD20 of hiPSC‐aCMs at all tested doses (Table S1). Additionally, CaTD50 and CaTD80 of both hiPSC‐aCMs and ‐vCMs were significantly prolonged in response to dofetilide (Table S1). However, hiPSC‐aCMs appeared to be more sensitive to dofetilide as the APD80 was significantly prolonged at the lowest tested dose of 3 nM (from to 182 ± 26 ms to 241 ± 26 ms, p < .05; Table S1) and displayed a larger dose‐response (Figure S8).

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FIGURE 5

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The effects of dofetilide and nifedipine on action potential and Ca2+ transient of hiPSC‐aCMs and ‐vCMs. Representative traces of action potential and Ca2+ transients illustrating the effects of A, dofetilide and B, nifedipine on hiPSC‐aCMs and ‐vCMs. Higher drug doses are presented by a progressively darker shade. The effects of C, 4‐aminopyridine and D, nifedipine on normalized (percent change from predrug baseline) action potential duration (APD) and Ca2+ transient duration (CaTD); both parameters being measured at 20%, 50%, and 80%. Dashed line is the normalized predrug control presented as 0% change. n = 6 from six independent differentiation batches. hiPSC‐derived atrial cardiomyocytes (aCMs) are shown in red while hiPSC‐derived ventricular cardiomyocytes (vCMs) are presented in blue. Data are presented as mean ± SEM. Drug effects were compared between hiPSC‐aCMs and ‐vCMs at each dose using unpaired t test, *p < .05, **p < .001, ***p < .001. NS stands for not significant

Next, we demonstrated the functional differences in the ion channel profiles of hiPSC‐aCMs and ‐vCMs. We aimed to show that the ultrarapid outward current (IKur) produced by the channel Kv1.5 (KCNA5) was functional and specific to hiPSC‐aCMs, while the inward Ca2+ current (ICa,L) produced the voltage‐dependent L‐type Ca2+ channel CaV1.2 (CACNA1C) was functional and specific to hiPSC‐vCMs. We used two relatively selective compounds, 4‐aminopyridine (4AP) and nifedipine, to dissect the presence of functional IKur and ICaL, respectively. While nifedipine is also known to block Cav1.3, it is expected to have a preferential effect at lower concentrations on CaV1.2 based on the literature which indicates ~13‐fold higher block on CaV1.2 than CaV1.3.19

At the highest tested dose (300 nM), nifedipine significantly decreased APD50 of hiPSC‐vCMs from 170 ± 14 ms to 121 ± 16 ms (28 ± 4% shortening) and decreased CaTD50 from 357 ± 10 ms to 333 ± 23 ms (30 ± 3% shortening) (Figure 5D; Table S2). We observed a trend in APD50 shortening of hiPSC‐aCMs in response to increasing the nifedipine dose, but the drug elicited a significantly stronger dose‐dependent shortening in both APD and CaTD of hiPSC‐vCMs compared with hiPSC‐aCMs (Figures S8 and S9). Observing the percent change from predrug control, nifedipine induced differential response in overall APD and CaTD between hiPSC‐aCMs and ‐vCMs at 10, 100, and 300 nM (Figure 5D).

In hiPSC‐aCMs, 4AP prolonged APD and CaTD in a dose‐dependent manner with a statistically significant change starting at 30 μM (Figure 6A,C; Table S3). 4AP significantly prolonged early‐repolarization (APD20) of hiPSC‐aCMs by 46 ± 2% and 66 ± 2% at 50 and 100 μM, respectively (APD20 at baseline: 82 ± 8, at 50 μM: 120 ± 9 ms, at 100 μM: 131 ± 9 ms, p < .05) (Figure 6C and Table S3). In contrast, 4AP prolonged APD20 of hiPSC‐vCMs by 23 ± 4% (APD20 at baseline: 138 ± 8 ms, at 100 μM: 170 ± 9 ms) at the highest tested dose of 100 μM (Figure 6C and Table S3). hiPSC‐aCMs showed greater change in APD to relative to predrug control at all concentrations of 4AP compared with hiPSC‐vCMs (Table S3), This is corroborated by the steeper trend of the dose response relationship in hiPSC‐aCMs (Figure S8). Additionally, the overall CaTD of hiPSC‐aCMs were prolonged after exposure to 4AP at 10 μM while the drug had a significant effect on CaTD of hiPSC‐vCMs at 30 μM (CaTD50 elongation from baseline: 68 ± 2% vs 12 ± 2%, p < .05) (Table S3).

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FIGURE 6

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The effects of 4‐aminopyridine (4AP) and AVE0118 on action potential and Ca2+ transient of hiPSC‐aCMs and ‐vCMs. Representative traces of action potential and Ca2+ transients illustrating the effects of A 4‐aminopyridine (4AP) and B, AVE0118 on hiPSC‐aCMs and ‐vCMs. Higher drug dose is presented by a progressively darker shade. The effects of C dofetilide and D, vernakalant on normalized (percent change from predrug baseline) action potential duration (APD), and B, Ca2+ transient duration (CaTD); both parameters being measured at 20%, 50%, and 80%. Dashed line is the normalized predrug control presented as 0% change. n = 6 from six independent differentiation batches. hiPSC‐derived atrial cardiomyocytes (aCMs) are shown in red while hiPSC‐derived ventricular cardiomyocytes (vCMs) are presented in blue. Data are presented as mean ± SEM. Drug effects were compared between hiPSC‐aCMs and ‐vCMs at each dose using unpaired t test, *p < .05, **p < .001, ***p < .001. NS stands for not significant

We then demonstrated the effectiveness of our drug screening platform in assessing the effects of experimental compounds designed to have targeted effects on atrial‐specific ion channels using AVE0118 and UCL1684.

AVE0118 is an experimental drug that blocks IKur, the G‐protein‐activated K+ current (IKAch), and the transient outward K+ current (Ito) at a similar dose range.20 Both IKur and IKAch are atrial‐specific ionic currents. AVE0118 prolonged mid‐ and late‐ repolarization (APD50 and APD80) of both hiPSC‐aCMs and ‐vCMs at the two highest tested doses (3 and 10 μM; Table S4). Similarly, AVE0118 had significant effects on CaTD50 and CaTD80 of hiPSC‐aCMs and ‐vCMs at all tested doses (Table S4). However, the APD50 and APD80 of hiPSC‐aCMs were significantly prolonged at a lower dose of 1 μM (control: 200 ± 14 ms, 1 μM: 244 ± 16 ms; Table S4). Furthermore, the atrial‐selective effects of the drug were demonstrated by a larger proportional prolongation in APD50 and APD80 of hiPSC‐aCMs compared with hiPSC‐vCMs at 1, 3, and 10 μM (APD; Figure 6D). Furthermore, AVE0118 induced a larger proportional prolongation in CaTD of hiPSC‐aCMs compared with hiPSC‐vCMs at all tested doses (Figure 6D). Early repolarization (APD20) of hiPSC‐aCMs also displayed a large dose‐dependent response (Figure S8) with a proportionally larger prolongation at 10 μM (63 ± 2% vs 43 ± 5%, p < .05; Figure 6D).

UCL1684 is purported to be a potent direct pore blocker of the small conductance Ca2+ activated K+ channel (SK channel)21 and was expected to induce a dose‐dependent atrial‐selective response. In hiPSC‐aCMs, UCL1684 treatment resulted in a significantly prolonged APD80 at 3 and 10 μM (from predrug control: 136 ± 11 ms to 3 μM: 188 ± 25 ms or 38 ± 5% prolongation, and to 10 μM: 206 ± 32 ms or 49 ± 11% prolongation, p < .05; Figure 7C and Table S5). UCL1684 prolonged CaTD80 of hiPSC‐aCMs at all tested doses (baseline: 300 ± 15 ms, at 0.3 μM: 372 ± 23 ms, at 1 μM: 387 ± 33 ms, at 3 μM: 413 ± 24 ms, at 10 μM: 416 ± 39 ms, p < .05; Table S5). In contrast, UCL1684 exposure showed no statistically significant effect on overall APD and CaTD of hiPSC‐vCMs. The sensitivity of hiPSC‐aCMs to UCL1684 was also reflected in the dose‐response relationship showing a prolongation APD80, in contrast to the minimal prolongation in APD80 of hiPSC‐vCMs (Figure S8).

image

FIGURE 7

Open in figure viewerPowerPoint
The effects of UCL1684 and vernakalant on action potential and Ca2+ transient of hiPSC‐aCMs and ‐vCMs. Representative Vm and Ca2+ transients illustrating the effects of A, UCL1684 and B, vernakalant on hiPSC‐aCMs and ‐vCMs. Higher drug doses are presented by a progressively darker shade. The effects of C, AVE0118 and D, UCL1684 on normalized (percent change from predrug baseline) action potential duration (APD) and Ca2+ transient duration (CaTD); both parameters being measured at 20%, 50%, and 80%. Dashed line is the normalized predrug control presented as 0% change. n = 6 from six independent differentiation batches. hiPSC‐derived atrial cardiomyocytes (aCMs) are shown in red while hiPSC‐derived ventricular cardiomyocytes (vCMs) are presented in blue. Data are presented as mean ± SEM. Drug effects were compared between hiPSC‐aCMs and ‐vCMs using unpaired t test at each dose, *p < .05, **p < .001, ***p < .001. NS stands for not significant

Finally, we tested the effects of vernakalant which is a multi‐ion channel blocker that blocks the fast and late inward Na+ current (INa, INaL, respectively), the IKur, and the IKAch.22 The drug is used clinically for intravenous cardioversion of patients in AF23 and was expected to induce an atrial‐specific effect due to its IKur and IKAch blocking properties.

Vernakalant elicited a positive dose‐dependent response in both APD and CaTD of hiPSC‐aCMs with minimal measurable effects on hiPSC‐vCMs (Table S6; Figures S8 and S9). Vernakalant demonstrated atrial‐selectivity with statistically significant differences between APD and CaTD of hiPSC‐aCMs and ‐vCMs at doses of 3, 10, and 30 μM (Figure 7D). Compared with APD at baseline, vernakalant at 10 μM significantly prolonged APD20, APD50, and APD80 of hiPSC‐aCMs by 84 ± 6%, 70 ± 5%, and 77 ± 4%, respectively (Figure 7D). Additionally, vernakalant at 10 μM prolonged CaTD20, CaTD50, CaTD80 of hiPSC‐aCMs by 58 ± 4%, 50 ± 3%, 35 ± 5%, respectively (Figure 7D). At clinically relevant concentrations (30 μM), vernakalant greatly affected early repolarization of hiPSC‐aCMs (APD20 prolonged by 124 ± 8%; Figure 7D). At 30 μM, vernakalant prolonged APD80 of hiPSC‐vCM by 20 ± 7% (APD80: 238 ± 22 ms at baseline vs 289 ± 30 ms at 30 μM, p < .05; Figure 7D and Table S6). Except for APD80 prolongation at 30 μM, vernakalant had no statistically significant effect on overall APD and CaTD of hiPSC‐vCMs at the lower doses (Table S6).

4 DISCUSSION

In this study, we were successful in efficiently differentiating hiPSCs into a monolayer of cardiomyocytes with an atrial phenotype by modifying the GiWi protocol.11 We used multiple phenotypic approaches such as qPCR, digital multiplexed gene expression analysis with NanoString technology, flow cytometry, ELISA, voltage measurements with current clamp electrophysiology as well as simultaneous voltage and Ca2+ transient measurements with optical mapping to demonstrate a clear and distinct atrial phenotype. Unique to our study, we completed an in‐depth pharmacological analysis with simultaneous voltage and Ca2+ measurements to demonstrate the differential responses of these chamber‐specific cardiomyocytes, and their utility as a translational model in screening for the safety and efficacy of novel atrial‐specific compounds for the treatment of AF.

Our observations support previous data in showing that atrial specification is in part mediated by RA.6, 8–10, 16 In our protocol, atrial differentiation was accomplished by adding 0.75 μM RA 24 hours after WNT inhibition, with a total exposure time of 72 hours. The generated hiPSC‐aCMs showed an atrial‐specific phenotype as validated at both protein and transcript levels with a decrease in ventricular‐specific and an increase in atrial‐specific markers. These results suggest that RA, at the dose and temporal exposure used in this study, maintains cardiac differentiation efficiency while pushing the differentiation process into an atrial lineage.

As a complementary assay, we used the NanoString digital multiplexed gene expression analysis to assess the expression of 250 genes custom‐curated from the existing literature. We found MYL2 and MYH7, markers of the ventricular phenotype, to be significantly differentially expressed between hiPSC‐aCMs and ‐vCMs, matching the gene expression pattern of native adult human right atrial and left ventricular tissues.24 Another ventricular‐specific marker KCNA425 which encodes for the Kv1.4 channel of the slow Ito was downregulated in hiPSC‐aCMs. Canonical atrial markers such as KCNA5 and NR2F2 were also confirmed to be differentially upregulated in hiPSC‐aCMs. Other markers of human atrial specificity such CXCR4, GNAO1, JAG1, PLCB1, and TBX18 as retrieved from the GTEx database26 were upregulated in our hiPSC‐aCMs further demonstrating the effect of RA on driving the differentiation pathway into an atrial lineage.

MYL7, thought to be an atrial‐specific marker, was not found to have a significantly higher expression in hiPSC‐aCMs. The differential expression of MLC‐2a may however require additional maturation of the hiPSC‐CMs. Other studies11, 27 have shown a high expression in MLC‐2a at day 20 postdifferentiation and a subsequent decrease over time in culture systems generating predominantly ventricular hiPSC‐CMs. One study has shown a higher expression of MLC‐2a in hiPSC‐aCMs analyzed at a later date (earliest at day 60).6

Electrophysiological differences between atrial and ventricular phenotypes, in terms of voltage and Ca2+ handling, define their function and are critical to the development and determination of efficacy of atrial‐specific compounds. As demonstrated by whole‐cell patch clamp and optical mapping measurements, the hiPSC‐aCMs generated in this study exhibited atrial‐like AP and Ca2+ handling properties. Namely, the AP of hiPSC‐aCMs was significantly shorter, along with a lack of a prolonged plateau phase as opposed to the AP of hiPSC‐vCMs, an observation that is aligned with native cardiomyocyte electrophysiology.28 Similarly, the CaT of hiPSC‐aCMs had faster kinetics with a faster decay time as reflected by the differential expression of Ca2+ channel isoforms, further demonstrating the differential physiology between hiPSC‐aCMs and ‐vCMs.

In terms of APD measurements, we observed a good correlation between the patch clamp and optical mapping recordings for hiPSC‐aCMs. In hiPSC‐vCMs, however, the optical AP measurements were shorter overall than patch clamp recordings. This discrepancy may be attributed to the heterogeneity of our current ventricular differentiation protocol which generated predominantly ventricular cardiomyocytes but also contain a small proportion of nonventricular phenotypes (ie, atrial myocytes and nodal cells). Thus, the optical AP signals represents an average from about 300 000 cells in each 1 cm2 region of interest.

Another hallmark of cardiomyocyte function is rate‐dependence, as described by the electrical restitution curve.29 We observed that the electrical restitution properties were different between hiPSC‐aCMs and ‐vCMs. Compared with hiPSC‐vCMs, hiPSC‐aCMs displayed a steady‐state‐like property by undergoing minimal APD80 shortening in response to the lower ranges of the pacing protocol (cycle lengths of about 400‐1000 ms) indicating full recovery of ion channel kinetics at these pacing ranges. In contrast, the hiPSC‐vCMs displayed consistent APD80 shortening at the same pacing range. It is important to note that APD restitution curves are likely different when using the standard steady‐state extra stimulus protocol compared with dynamic pacing, particularly in cardiomyocytes with immature Ca2+ handling and memory.29 In relation to dynamic pacing protocol, hiPSC‐vCMs have steeper maximum slope of the restitution curve compared with hiPSC‐aCMs as steady‐state APD is the principal determinant of the slope of the ventricular restitution curve.30

The presence of specific ion channel currents (ie, IKur, IKAch, and ICaL) explain, in part, the functional differences between the two cardiac chamber subtypes, the expressions of which were already shown in our qPCR and NanoString assays. We used a series of compounds (4‐aminopyridine, dofetilide, vernakalant, AVE0118, UCL1684, and nifedipine) to demonstrate the function of atrial‐specific ionic currents in our model system and were able to show the expected chamber specific differences between hiPSC‐aCMs and ‐vCMs.

Dofetilide (DF) served as a positive control in our optical mapping assay as a clinically relevant drug which has a strong effect on IKr in both atria and ventricular CM.31 As expected, dofetilide affected the repolarization of both hiPSC‐aCMs and ‐vCMs, confirming the presence of IKr in both cell types. At clinically relevant doses of DF (3 and 10 nM), hiPSC‐aCMs displayed greater sensitivity to the drug indicating a larger proportional contribution of IKr in the AP of hiPSC‐aCMs relative to hiPSC‐vCMs. This may partly explain the effectiveness of the drug in the clinical treatment of AF. However, clinical use of the drug to treat AF is limited due to its tendency to induce QTc prolongation. This pro‐arrhythmic risk of TdP32 which was captured by the prolongation of APD80, an in vitro surrogate of QTc, in the hiPSC‐vCMs. This finding supports the utility of our optical mapping assay in predicting the risk of ventricular proarrhythmia in vitro.

The compound 4AP has been shown to selectively block Kv1.4 (Ito) and Kv1.5 (IKur)33 and is therefore expected to elicit a response in hiPSC‐aCMs at lower doses than in hiPSC‐vCMs as IKur (Kv1.5) is a strong functional indicator of atrial phenotype. Confirmation of the atrial expression of IKur channels was demonstrated by the stronger dose‐dependent hiPSC‐aCM AP prolongation to 4AP at all tested doses (10, 30, 50 and,100 μM) suggesting selective sensitivity of hiPSC‐aCMs to 4AP due to a greater expression of Kv1.5. The inhibitory effects of 4AP were observed at higher doses (50 and 100 μM) in hiPSC‐vCMs which can be attributed to the heterogeneous population, potential off‐target effects at these high doses, as well as baseline expression of Kv1.4 (Ito).

Using nifedipine, we demonstrated the functional differences in Ca2+ handling dynamics between hiPSC‐aCMs and ‐vCMs. Nifedipine elicited a dose‐dependent response in hiPSC‐vCMs demonstrating high sensitivity at 300 nM thereby confirming the functional presence of Cav1.2. In contrast, hiPSC‐aCMs were relatively insensitive to nifedipine showing no statistically significant differences in APD at all tested doses. This finding is further corroborated by the relatively decreased expression of CACNA1C (Cav1.2) in the hiPSC‐aCMs. This suggests that Ca2+ handling in hiPSC‐aCMs may be reliant on other voltage‐gated Ca2+ channels such as Cav1.3, as this Ca2+ channel is blocked less potently by nifedipine.34 Moreover, our qPCR assay confirmed that hiPSC‐aCMs had higher expression of CACNA1D (Cav1.3).

AVE0118 is an experimental K+ channel blocker (Ito, IKur, and IKr) that was predicted to demonstrate targeted effects in hiPSC‐aCMs. However, only a nuanced atrial specificity was observed in our assay. Although the effects were proportionally larger in hiPSC‐aCMs, AVE0118 prolonged early repolarization of both hiPSC‐aCMs and ‐vCMs in a similar fashion. The drug prolonged mid‐ and late‐repolarization at a lower dose (1 μM) in hiPSC‐aCMs showing minimal atrial specific effects. Interestingly, AVE0118 greatly affected Ca2+ handling in hiPSC‐aCMs compared with hiPSC‐vCMs with larger proportional prolongation of CaTD50 at all doses. These results were unexpected as AVE0118 is thought to be highly specific to hiPSC‐aCMs due to its IKur blocking component. Perhaps the observed mixed‐effects in both cell types is due to the drug binding to Ito (IC50: 3.4 μM) and IKr (IC50: 9.6 μM)35 which prolongs APD at the tested doses of 3 and 10 μM as genes encoding the channels producing the Ito (KCNA4) and IKr (KCNH2) were expressed in our hiPSC‐vCMs. The drug was also shown to be effective in terminating certain ventricular arrhythmias36 which was predicted based on our results of prolongation in the APD of hiPSC‐vCMs.

Next, we used UCL1684, a highly specific SK channel pore blocker, to assess the presence of functional SK channels in hiPSC‐aCMs. The SK channel has three paralogs but the SK3 channel variant (KCNN3) has been shown to be atrial‐specific and has been implicated in AF pathogenesis in several studies.37, 38 In this study, UCL1684 displayed high specificity toward hiPSC‐aCMs with a strong dose‐dependent response. The drug confirmed the presence of functional SK channels in hiPSC‐aCMs at 3 μM with a positive dose‐dependent response while having no effect on hiPSC‐vCMs at all tested doses (0.3, 1, 3, and 10 μM).

Vernakalant is touted as an atrial‐selective compound clinically approved for intravenous cardioversion of AF.39 Strikingly, out of all the tested drugs, vernakalant showed the most pronounced atrial‐selective effects even though it is a blocker of multiple ion channels (INa, IKur, and IK,Ach). Vernakalant prolonged APD and CaTD of hiPSC‐aCMs at three tested doses (3, 10, 30 μM). However, no statistically significant changes were observed in hiPSC‐vCMs at early‐ and mid‐ repolarization while the slight prolongation at APD80 at the clinically relevant dose (30 μM) may be attributed to the INa blocking component of vernakalant. This result further demonstrates the sensitivity of the assay in establishing atrial‐selective drug effects.

This study has several limitations. One limitation in our findings is that we cannot directly compare the results from qPCR and NanoString as both assays have fundamental differences in technical principles and statistical methodologies. Taken together, however, both assays show the global changes in cell type specific gene markers and further validate the role of retinoic acid in directing the cardiac differentiation process toward an atrial lineage. The main limitation in this field is the maturation state of the hiPSC‐CMs as they have an overall immature phenotype with some crucial differences compared with adult cardiomyocytes.40 Nonetheless, we were able to observe the stark differences in genetic, protein, as well as functional signatures of AP and CaT in the two generated chamber‐specific cell types. Additionally, maturation stage does not explain the differences in chamber‐specific phenotype as parallel batch differentiation and time‐in‐culture were incorporated in our study design. Most importantly, we were able to capture effects of drugs that were expected to have atrial‐specific properties in hiPSC‐aCMs.

5 CONCLUSION

The ability to differentiate hiPSC‐aCMs provides a unique opportunity to study atrial physiology and its pharmacologic responses in a human‐relevant in vitro model. We demonstrated an hiPSC‐based in vitro model that recapitulates the molecular and functional characteristics of the phenotype of native atrial tissue. Our platform adds to the repertoire of cardiac drug screening and can be readily applied in future efforts of atrial‐specific drug discovery.

ACKNOWLEDGMENTS

We would like to thank Salina Kung and Jennifer Yi for their help in designing the NanoString codeset. This work was financially supported by the Canadian Institutes of Health Research (G.F.T), the Canada Innovation Fund (G.F.T), the Stem Cell Network (G.F.T and Z.L.), and the Michael Smith Foundation (Z.L.).

CONFLICT OF INTEREST

The authors declared no potential conflicts of interest.

AUTHOR CONTRIBUTIONS

M.G.G., S.S.S.: conception and design, collection and assembly of data, data analysis and interpretation, manuscript writing; S.S.: experimental design support, data interpretation, manuscript writing; E.L.: designed and built the optical mapping system (hardware and software); D.A.H.‐W.: cell culture; V.J.B.: data collection, data analysis and interpretation, manuscript writing; Z.L., G.F.T.: conception of study, manuscript writing support and review, data interpretation, financial support.

Motor neuroprosthesis implanted with neurointerventional surgery improves capacity for activities of daily living tasks in severe paralysis

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Abstract

Background Implantable brain–computer interfaces (BCIs), functioning as motor neuroprostheses, have the potential to restore voluntary motor impulses to control digital devices and improve functional independence in patients with severe paralysis due to brain, spinal cord, peripheral nerve or muscle dysfunction. However, reports to date have had limited clinical translation.

Methods Two participants with amyotrophic lateral sclerosis (ALS) underwent implant in a single-arm, open-label, prospective, early feasibility study. Using a minimally invasive neurointervention procedure, a novel endovascular Stentrode BCI was implanted in the superior sagittal sinus adjacent to primary motor cortex. The participants undertook machine-learning-assisted training to use wirelessly transmitted electrocorticography signal associated with attempted movements to control multiple mouse-click actions, including zoom and left-click. Used in combination with an eye-tracker for cursor navigation, participants achieved Windows 10 operating system control to conduct instrumental activities of daily living (IADL) tasks.

Results Unsupervised home use commenced from day 86 onwards for participant 1, and day 71 for participant 2. Participant 1 achieved a typing task average click selection accuracy of 92.63% (100.00%, 87.50%–100.00%) (trial mean (median, Q1–Q3)) at a rate of 13.81 (13.44, 10.96–16.09) correct characters per minute (CCPM) with predictive text disabled. Participant 2 achieved an average click selection accuracy of 93.18% (100.00%, 88.19%–100.00%) at 20.10 (17.73, 12.27–26.50) CCPM. Completion of IADL tasks including text messaging, online shopping and managing finances independently was demonstrated in both participants.

Conclusion We describe the first-in-human experience of a minimally invasive, fully implanted, wireless, ambulatory motor neuroprosthesis using an endovascular stent-electrode array to transmit electrocorticography signals from the motor cortex for multiple command control of digital devices in two participants with flaccid upper limb paralysis.

Interleaved TMS/fMRI

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Study human brain functionality in real-time

Stimulation of the brain with magnetic pulses while depicting what happens in the brain at the same time with  functional magnetic resonance imaging (functional MRI) That is the essense of interleaved TMS/fMRI. 

With this complete turnkey TMS/fMRI research solution, it is possible to induce neural activity safely into targeted cortical regions, directly in the MRI scanner. Features of the MagVenture TMS/fMRI solution further include: The integration of TMS with functional MRI provides researchers with a unique tool to study human brain functional connectivity in real-time and assess how it can be altered by certain interventions, behaviour, or pathologies.

Features of the MagVenture TMS/fMRI solution include:

  • Special TMS coils for use inside the MRI scanner
  • Reduced RF noise filters and controllers
  • Built-in dynamic leakage current reduction for minimizing artefacts
  • Stimulator-controlled recharge delay and parameters
  • High quality imaging
  • Ability to add inside/inbore neuronavigation
  • Full control via synchronization of TMS, scanner and peripheral equipment, incl. neuronavigation and functional data formats (Analyze, DICOM, MNI, IfTI)
  • EEG electrode localization and position export in flexible data format
  • Export of stimulation parameters (e.g. EMG, amplitude, mapping results) along  with the acquired stimulation location as functional image data
  • Open documentation format: All data stored is written in XML format for easy post processing
  • The MRI compatible solution can easily be extended to a 2-in-1 solution for navigation outside the MRI environment

Stimulate multiple sites

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Small research coils allows for stimulation at multiple sites at the same time

The small geometry of the B35 coil enables you to place multiple coils simultaneously on the head providing a focal, yet powerful stimulation. The B35 coil comes in different versions to suit your specific needs:

• MC-B35
• Cool-B35
• Cool B35-HO (with handle turning upwards for easy coil placement)
• Cool-B35 RO (Robotic edition to be used with the Axilum robot)

 Another option

Another option is the D-shaped Cool-D50 coil with the stimulation center being placed at the edge of the coil. This allows for alternating stimulation of two centers in the brain only 2-3 cm apart.

Smaller circular coils like the MMC-90 coil or MCF-75 coil are also available for less selective stimulation, but still allow for multiple coils to be placed close to one another.

Robotic TMS solutions

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Movement controlled, highly accurate TMS without compromising on safety and comfort

Head motion compensation monitors the coil’s position, orientation and contact to the head at all times and actively follows any possible head movement during TMS. It ensures a high level of repeatability between TMS sessions, is integrable with MagVenture stimulators and coils and may be piloted by a neuronavigation system from Localite.

Highlighted features

  • Maintain position, orientation and tilt of the TMS coil during the session
  • Compensate for potential head motion during the TMS session
  • Maintain contact between coil and head (integrated contact sensor)
  • Plan fully automated image-guided TMS sessions when piloted by a compatible neuronavigation system
  • Plan and execute predefined stimulation paths when piloted by a compatible neuronavigation system
  • Ensure identical setups in multi-center studies
  • Reduce inter-operator variability
  • Double-blind study support
  • Reduce interactions between operator and patient during the session (no need for coil adjustment)

Robotic solutions

There are two different robotic solutions available depending on your need: TMS-Robot and TMS-Cobot.

Clinical TMS research

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The most comprehensive solution for double-blinded TMS studies

MagVenture offers a highly flexible solution which addresses all your requirements for accuracy, reliability and consistency in clinical research and thus, ultimately, help facilitate new treatment options. This even includes the possibility to perform true randomized, double-blinded, multi-center studies.A robotic solution and/or neuronavigation may easily be added to further enhance the reproducibility of your research.

  • Coils with both active and sham sides (or with only a placebo side)
  • Software for complete study control by study master or principal investigator
  • Patient and operator codes to ensure true double-blinding
  • Sham noise generation
  • Electric masking

Active/Placebo coils

MagVenture offers a number of coils with both an active and a placebo side for true double-blinded TMS studies: Cool D-B80 A/P, MMC-140 A/P, Cool-B65 A/P and Cool-B70 A/P.
MagVenture also offers a number of placebo coils for single-blinded research: MC-P-B70, MCF-P-B70 and MCF-P-B65

Neuronavigation with Localite

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Stimulate selected brain regions with high precision and reliability every time

Plan stimulation areas, visualise the stimulation spot, and monitor and record the precise position of the research subject and coil with complete replicabibility. The turnkey solution provides full integration with MagVenture stimulators, allowing for automatic and easy exchange of all the needed information such as intensity, coil and stimulator type, MEPs, and temperature.

Our partner Localite offers a range of different neuronavigation systems (Classic, MRI Edition and Robotic Edition). They are all precise, intuitive and scalable.

 Highlighted features:

  • Easily scalable: From MR-less system to MR-based system extendable by attractive soft and hardware
  • Tracking of up to 4 coils at the same time
  • More than 30 MagVenture coils ready to use in the software
  • Import of multiple morphological and functional data formats (DICOM, MNI, NIfTI)
  • EEG electrode localization and position export in flexible data format
  • Export of stimulation parameters (e.g. EMG, amplitude, mapping results) along with the acquired stimulation location as functional image dataOpen documentation format: All data stored is written in XML format for easy post processing
  • The MRI compatible solution can easily be extended to a 2-in-1 solution for navigation outside the MRI environment

TMS Translational research

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Complete TMS solution for animal model research

MagVenture offers a specifically dedicated coil for animal model research. It provides a unique opportunity to study the effects of TMS within a wide range of fields including behavioural, metabolic, (epi) genetics, molecular, and biochemical pathways. This research solution overcomes previously known challenges pertaining to focality, overheating, shape, and size. It provides complete replicability and reliability and, due to the small coil size, it will even fit inside a PET or SPECT imaging scanner with a minimum ø120mm bore which for some research purposes is important.

Overcoming the barriers in TMS for rodents

The number of stimuli available in small coils like the Cool-40 Rat Coil is a huge barrier for performing real TMS due to the heating of the TMS coil. The Cool-40 Rat coil overcomes this barrier as it operates with the special High-Performance Cooling System. This will allow for a high number of stimuli before overheating.

The small dimensions of the rat brain compared to the human brain makes it very challenging to provide efficient TMS stimulation using human coils, as they typically lack focus of the magnetic fields and largely out-limit the dimensions of the rat’s head. Further, the smaller coils that are currently available do not induce electrical fields in the brain that are comparable to the electrical fields elicited with human coils in the patient’s brain. All of these issues have been solved with the Cool-40 Rat coil due to the special design of the windings, the High-Performance Cooling System, and the bended shape.

Spike2

The latest Spike2 updates for V10, V9 and V8, for Windows is available now

All, Product Updates

Features of version 10.07 include:

  • Video recording has a new option to fix timing problems with some cameras. It now compensates for time delays when starting to record video. It also can be used across a remote desktop. Video review has frame accurate video stepping for both MP4 and AVI files.
  • You can display axes in the data area of Time, Result and XY views. This is expected to be useful when generating figures for publication
  • In a time view you can add channels without a y axis to a group (as long as the group head has an axis). This allows you to colour the background of areas of a waveform with states and to superimpose TextMark data.
  • Many useful small improvements and fixes

“It’s so Cute I Could Crush It!”: Understanding Neural Mechanisms of Cute Aggression

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Katherine K. M. Stavropoulos* and Laura A. Alba
  • Graduate School of Education, University of California, Riverside, Riverside, CA, United States

The urge people get to squeeze or bite cute things, albeit without desire to cause harm, is known as “cute aggression.” Using electrophysiology (ERP), we measured components related to emotional salience and reward processing. Participants aged 18–40 years (n = 54) saw four sets of images: cute babies, less cute babies, cute (baby) animals, and less cute (adult) animals. On measures of cute aggression, feeling overwhelmed by positive emotions, approachability, appraisal of cuteness, and feelings of caretaking, participants rated more cute animals significantly higher than less cute animals.

There were significant correlations between participants’ self-report of behaviors related to cute aggression and ratings of cute aggression in the current study.

N200: A significant effect of “cuteness” was observed for animals such that a larger N200 was elicited after more versus less cute animals. A significant correlation between N200 amplitude and the tendency to express positive emotions in a dimorphous manner (e.g., crying when happy) was observed.

RewP: For animals and babies separately, we subtracted the less cute condition from the more cute condition. A significant correlation was observed between RewP amplitude to cute animals and ratings of cute aggression toward cute animals. RewP amplitude was used in mediation models.

Mediation Models: Using PROCESS (Hayes, 2018), mediation models were run. For both animals and babies, the relationship between appraisal and cute aggression was significantly mediated by feeling overwhelmed. For cute animals, the relationship between N200 amplitude and cute aggression was significantly mediated by feeling overwhelmed. For cute animals, there was significant serial mediation for RewP amplitude through caretaking, to feeling overwhelmed, to cute aggression, and RewP amplitude through appraisal, to feeling overwhelmed, to cute aggression. Our results indicate that feelings of cute aggression relate to feeling overwhelmed and feelings of caretaking. In terms of neural mechanisms, cute aggression is related to both reward processing and emotional salience.

Introduction

Cute aggression is defined as the urge some people get to squeeze, crush, or bite cute things, albeit without any desire to cause harm. Aragón et al. (2015) initially operationalized the phenomenon of “cute aggression” through individual self-reports while viewing cute stimuli. The authors investigated cute aggression using pictures of baby humans and animals via an online survey. Findings indicated that for infantile babies (e.g., images that had been altered to have large eyes and chubby cheeks; Sherman et al., 2013) and baby animals, there was a relationship between being overwhelmed by positive feelings and the expression of cute aggression (Aragón et al., 2015).