Collecting neural or physiological data like brain activity or heart rate is a key part of many fields of research. You may want to collect this type of data to support your behavioural data, or it may be your core dependent variable and you need something to present stimuli. Either way, you'll likely need to use Gorilla in combination with an external device.
This page gives a brief guide to how to combine external devices with Gorilla, bringing together neuroimaging, physiological, and behavioural data.
Anything you use during data collection that isn't the device the participant is using Gorilla on! Examples are functional near-infrared spectroscopy (fNIRS) caps to measure brain activity, or wrist sensors to measure heart rates.
The short answer is, if the external device can connect via USB/Bluetooth, then it might be possible to integrate it with Gorilla.
The longer answer is that it's less about what's compatible with Gorilla and more what's compatible with the browser in general.
So, if it's a tool that you already can manipulate/use via a browser like Firefox/Chrome, then it should be possible. If it's a tool that connects to a device via USB or Bluetooth, then it might be possible - there are basic APIs available in Chrome and Firefox which allow for connecting to devices via USB/Bluetooth. Importantly though, it is only Chrome and Firefox. Currently, Safari (and Apple products more broadly) doesn't support these APIs.
However, if it connects via serial port, ethernet or any other kind of connector, then there's no way to do this natively within the browser. To integrate these devices with Gorilla, you need to write a browser plugin/ desktop application to act as a go-between, communicating information from the device to the browser and vice versa. While this is possible, we cannot offer support on how to do this.
If connecting the device directly with Gorilla is not possible, there are other routes you can take to synchronise data collection between Gorilla and your external device:
To see how other researchers have succeeded with integrating external devices while using Gorilla, check out the devices listed on the menu!
Have you run a study using Gorilla and an external device at the same time? Get in touch with us at info@gorilla.sc - we'd love to share your research with our community!
Functional near-infrared spectroscopy (fNIRS) is a method to measure brain activity through optical sensors placed on the surface of the scalp.
Read on for case studies from researchers who have successfully collected Gorilla data and fNIRS data at the same time!
Kew and colleagues (2025) used fNIRS and Gorilla at the same time to learn more about the neural basis of our perceptions of taste and smell of plant proteins.
The researchers used Gorilla's timing controls to provide participants with instructions of when to exactly try the samples. After trying the sample, participants then rated it on the texture attributes of astringency, roughness, creaminess, sweetness and thickness. To align the timings between Gorilla and the fNRIS device used, experimenters in the room placed markers at the start of each new sample.
Kew, B., Burke, M.R., Stieger, M. et al. (2025). Unveiling plant protein astringency perception through neural and cellular responses. Scientific Reports, 15, 39184. https://doi.org/10.1038/s41598-025-23836-9
Levy and colleagues (2026) used fNIRS to investigate brain activity when participants generated visual or olfactory mental images in response to semantic cues (odor-related words) or perceptual cues (abstract color patterns) that were presented via Gorilla.
The researchers used Gorilla to create a 2x2 factorial design and applied their own pseudorandomisation. To align timings, synchronization timestamps were recorded as part of the data collection. The researchers also collected electrocardiographic (ECG) activity and galvanic skin response (GSR) through a patch on the participants' skin.
Levy, A., Boot, E., Jacquot, M., Gaeta, G., Parkkinen, E., Mari, T., & Tachtsidis, I. (2026). Shedding light on imagined scents: An fNIRS feasibility study of olfactory mental imagery and semantic cueing. Frontiers in Neuroscience, 20, 1825171. https://doi.org/10.3389/fnins.2026.1825171
An electrocardiogram (ECG) records the rhythm, rate, and electrical activity of the heart.
Read on for a case study from researchers who have successfully collected Gorilla data and ECG data at the same time!
This research used ECGs as a 'ground-truth' to validate remote photoplethysmography - the measurement of heart rate via video by tracking subtle changes in skin colouration. By recording participants' video on Gorilla in-person, video data was collected in a similar way to how it would be with online recruitment. The researchers concluded that both methods of heart rate recordings (remote photoplethysmography and ECG) had excellent agreement, paving the way for remote heart rate collection in online research.
To align timings across Gorilla and the ECG recordings, a photodiode (a light-sensitive semiconductor) was used. The photodiode was controlled with an Arduino Uno. At the start and the end of each trial, the researchers used Gorilla to make a 2 × 2 cm black square appeared in the bottom right corner of the screen. The photodiode, placed on the screen, detected changes in light intensity caused by the appearance of the square. Then the Arduino triggered an event marker, enabling precise alignment of the ECG data with the start and end of each video recording.
Finotti, G., Di Lernia, D., & Tsakiris, M. (2026). Validation of web-based remote photoplethysmography for heart rate measurement using standardized online infrastructure against ECG benchmarks. Behavior Research Methods, 58, 252. https://doi.org/10.3758/s13428-026-03098-7
Wearable devices such as smart watches can play an important role in social science research by monitoring heart rate, blood pressure, electrodermal activity, temperature, and much more.
Read on for a case study from researchers who have successfully collected data on Gorilla data and from a wearable device at the same time!
Investigating whether audio or visual stories are more engaging, Richardson and colleagues presented participants with narratives either as video or audio files on Gorilla. By using Gorilla, the researchers were able to easily counterbalance the order of different blocks within the experiment.
Participants were fitted with an Empatica E4 wrist sensor, which captured their heart rate, electrodermal activity, wrist temperature and acceleration. This physiological data were aligned to stimulus and condition information and trimmed to trial durations using the Universal Time Coordinates that were recorded by the Empatica sensors and the Gorilla system.
Richardson, D.C., Griffin, N.K., Zaki, L. et al. (2020). Engagement in video and audio narratives: contrasting self-report and physiological measures. Scientific Reports, 10, 11298. https://doi.org/10.1038/s41598-020-68253-2
