We empower neurophysiological research with state-of-the-art hardware and software from world-leading manufacturers.

Even if it is not central to the hypothesis, eye tracking can elevate neurophysiological (EEG, fNIRS, peripheral physio, etc) research into a more comprehensive brain and behavioral investigation. By providing objective metrics on visual attention, cognitive load and stimulus prioritization, eye tracking strengthens interpretability and adds scientific rigor to any study.

Transcranial magnetic stimulation (TMS) uses electromagnetic coils to induce brief electrical activation of brain cells in specific cortical regions. Depending on the stimulation pattern, duration, and frequency, the effects of TMS can be either short-lived or longer-lasting (i.e., repetitive TMS, rTMS), making it an attractive modality for researchers interested in studying brain modulation without surgery or electrode implantation. TMS is generally well-tolerated by participants and has demonstrated efficacy in the treatment of major-depressive disorder, obsessive compulsive disorder, and smoking cessation, making it among the first noninvasive brain stimulation modalities to receive FDA-approval. TMS is a great tool for studying brain circuitry and connectivity (i.e., temporarily exciting one area of the cortex and observing how cognitive and motoric processes are affected). Combining TMS with EEG allows researchers to better examine changes in the brain’s electrical activity following electromagnetic stimulation. Traditionally, many researchers who have combined TMS with EEG have limited their experiments to blocked designs (e.g., EEG-TMS-EEG) because the strength of the TMS pulse often results in saturation of the EEG amplifier and/or a long-lasting electromagnetic artifact that contaminates the underlying EEG signal. However, recent advances in amplifier technology have made it possible to record EEG concurrently during a TMS pulse. We are proud to offer an unparalleled solution for TMS-EEG experiments that can recover from a TMS pulse within 2ms.

Functional near infrared spectroscopy (fNIRS) uses different wavelengths of near infrared light to measure changes in blood oxygenation and deoxygenation (i.e., the hemodynamic response) across the cortex, which is often considered to be a correlate of brain activation. With fNIRS, specialized optodes are placed on the head, and their positions are secured in a grid-like fashion by caps or other headgear. Near infrared light is then emitted through one set of optodes and directed towards the scalp. Light that is not absorbed by the cortex is measured by surrounding detector optodes. This technique allows researchers to make inferences about brain activation without the need for magnetic fields or currents. Given its portability, fNIRS is versatile and can be used to answer a variety of questions about brain activation under more ecologically valid conditions (i.e., while participants are engaged in real-world activities). Similar to fMRI, it can also be combined with EEG; however, it is limited to cortical brain activation. Compared with EEG, fNIRS is a newer methodology and many labs previously developed homegrown solutions for measuring the hemodynamic response of the brain. We have partnered with leading fNIRS companies to offer cutting-edge, professional solutions that are backed by expert-level support.

Mobile brain/body imaging (MoBI) is a rapidly evolving area taking neuroscience research out of the lab and into the real world. MoBI research measures fNIRS, eyetracking, peripheral physio, EEG, and more on free moving participants in real and VR environments to capture more naturalistic behavior. Find out how you could take your next experiment out of the lab!

Virtual reality involves placing participants in simulated computerized environments. Often, participants wear a headset with goggles that project 3D images or videos onto their retinas, creating the sensation of immersion in the environment. Virtual reality allows cognitive scientists and psychophysiologists to address novel questions about the brain and behavior in controlled settings that may range from fantastic (e.g., riding a roller coaster or teleporting to different realms) to realistic (e.g., solving puzzles or walking through mazes). Advances in mobile brain and body imaging (MoBI) technologies have incentivized researchers to combine virtual reality with electroencephalography (EEG). Being able to wear an EEG system and freely move around while engaging with the virtual reality environment allows for the collection of data that is more ecologically valid. We offer several options for lightweight wireless EEG amplifiers that are perfect for use in virtual reality settings. We also offer caps that have built-in harnesses for the virtual reality goggles – simply remove the headset and attach the goggles directly to your EEG cap. This process maximizes participant comfort (i.e., eliminating added pressure of the headset on the electrode positions) without sacrificing electrode density and scalp coverage.

Electroencephalography (EEG) is the measurement of the electrical activity of the brain through specialized electrodes placed on the head. We offer passive, active, gel-based, saline, and dry-electrode technologies, so researchers have flexibility in choosing the right recording electrode for their signals of interest. Often these electrodes are placed on the surface of the scalp and their positions are secured by caps, nets, or headgear. In special cases, electrodes may be placed underneath the scalp or directly on the surface of the brain in a form of electrophysiological monitoring known as electrocorticography (ECoG). Regardless of the approach taken, these electrodes measure the summation of post-synaptic potentials from many brain cells (i.e., neurons) and the resulting waveforms are amplified, digitized, and recorded to better understand brain function under a variety of conditions. We specialize in providing reliable and robust solutions to streamline the measurement and recording of EEG so that researchers can confidently deploy this methodology to address their scientific questions.

Hyperscanning involves recording brain activity from more than one person at the same time. There are many advantages to these types of paradigms – particularly when it comes to understanding changes in cognition and behavior associated with social interactions and child development. Participant mobility, although not essential for hyperscanning studies, is helpful for recording brain activity in more real-world environments. We offer hyperscanning solutions for both electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), and the combination of the two methods. One challenge of hyperscanning paradigms is being able to synchronize the delivery of event markers across multiple devices. To address this challenge, we offer reliable trigger solutions that help eliminate the guesswork associated with verifying the timing of stimulus presentation. Another challenge of hyperscanning paradigms, particularly when relying on wireless data transmission, is the number of systems that can be in the room at the same time. Our systems allow for multiple modes of data acquisition, including the ability to save the data to a microSD card onboard the device. This ensures that no data are lost, even if the wireless transmission is interrupted.

The average person spends about one-third of their life sleeping. A good night’s sleep is positively correlated with general well-being and cognitive function, and understanding changes in brain activity during sleep may help inform many neuroscientific research questions ranging from cognitive processes to physical performance. Standard sleep studies, or polysomnography (PSG), measure brain activity (EEG), respiration, muscle tone (EMG), eye movements (EOG), and oxygenation during sleep. The resulting output is called hypnogram and consists of a graphical representation of the sleep stages over time. We recognize that there are several clinical PSG systems on the market that are used for diagnostic purposes. For sleep researchers who are interested in more flexible PSG solutions, we offer several low- and high-density portable and wireless EEG systems that can be tailored to the specific needs of the research program. For EEG / ERP researchers who are interested in adding sleep as a parameter to their existing research program, we can work with you to expand your current setup (e.g., customizing comfortable EEG caps that are ideal for long recordings, adding the necessary sensors to enable full PSG recordings, and incorporating software plugins to streamline sleep staging and hypnogram generation). We also offer an affordable, self-donning, light-weight patch that is ideal for recording sleep data from participants in their home environments.

Child development is a fascinating area of research that is often complicated by the unique requirements (e.g., excess movement, emotional responses, sensitivity to stimuli, limited attention spans, limited verbal communication) of working with newborns, infants, toddlers, and children. These unique requirements also pose a challenge for developmental researchers who study cognition, especially for those who utilize electroencephalography (EEG), where signal quality is dependent on the stability of both the participant and the contact between the recording electrodes and the participant’s head. Choosing the right electrode technology (e.g., saline/sponge vs. active gel electrodes) and headgear (e.g., net vs. cap) is crucial for obtaining usable data from babies and children. We are proud to offer several robust EEG solutions that have been optimized for use with babies and children, prioritizing speed and ease of application and participant comfort. We know that no electrode is completely baby-proof, so regardless of which electrode solution you choose, you will need no fancy tools to replace an electrode, should one fail during a recording. We also offer a video add-on solution that integrates EEG with video data for a complete child development package.

Transcranial Electrical Stimulation (tES) is a general term used to describe noninvasive brain stimulation methods in which brief pulses of low-intensity electrical current are delivered to the brain through electrodes placed on the scalp. tES may consist of direct current stimulation (tDCS), alternating current stimulation (tACS), or random noise stimulation (tRNS). Depending on the type of stimulation, the stimulation site(s), and the stimulation protocol, tES may excite or inhibit certain brain pathways and induce short-duration neuromodulation or longer-duration neuroplasticity. tES has been used to treat neuropsychiatric disorders and for neurocognitive rehabilitation following traumatic brain injury. We offer a range of cutting-edge solutions for researchers who are interested in pushing the limits of tES (including an MR-conditional setup). Recording electroencephalography (EEG) during tES (i.e., concurrent tES-EEG) is technically challenging and will result in noise in the EEG signal, especially from the EEG electrodes close to the stimulation site. These EEG artifacts can be attenuated during tDCS, but they are harder to remove during tACS or tRNS protocols. We offer an amplifier that is built to address this issue in the not-too-distant future. We also offer a complete solution for researchers who would like to combine tES with EEG for brain-state dependent experiments to precisely trigger stimulation at specific phases of ongoing brain rhythms.

Recording videos of participants during EEG data collection is often helpful for informing both pre-processing and interpretation of the resulting EEG signals. This is particularly useful for applications in which participants are intended to be mostly stationary (e.g., during sleep) or mobile (e.g., during extreme EEG). Video recordings are also common for researchers who work with babies and children and those who are interested in social interaction studies. Many researchers may choose to set up a video camera and record participants independently from the EEG data, with the goal of synchronizing the data offline. Because video cameras use their own clock and timing, reliable synchronization of video with EEG data is a complex task. Therefore, we aim to streamline this process by offering a compact, high-resolution video recorder kit with a software integration plugin that allows researchers to record video concurrently with EEG data. This solution allows maximum synchronization between video and EEG data with an active drift correction mechanism that works even over long duration recordings. We also offer an optional video module for BrainVision Analyzer 2 so that researchers can see the video recording advance automatically as they scroll through their EEG data.

An event-related potential (ERP) or evoked-potential (EP) is a stereotyped neurophysiological response to an internal (e.g., thought or emotion) or external (e.g., image or sound) stimulus. Often, to record a reliable ERP, a stimulus is presented multiple times (i.e., trials), and the resulting waveforms are averaged to obtain a neural signature that is time-locked to the presentation of the stimulus in question. One strength of ERP is its high temporal resolution, allowing researchers to answer questions about how the brain processes information within milliseconds of stimulus presentation. Being able to reliably measure the onset of the ERP-eliciting stimulus is central to both the collection and interpretation of ERP data. We offer several solutions to ensure that the stimulus presentation is captured and embedded within the EEG data, which streamlines data pre-processing and ERP generation. There is also increasing interest in recording ERPs with as few trials as possible. Collecting clean EEG data is critical to reducing the number of trials needed to record an ERP, and a major contributor to being able to collect clean EEG data is having the right hardware and software for your research program.

One inherent limitation of EEG & ERP data collection is that it is virtually impossible to pinpoint the underlying neural generator (e.g., source) of the electrical signal recorded from the surface of the scalp due to the folding of the cerebral cortex, which may affect the orientation of the postsynaptic potentials that are measured by the EEG electrodes. This is well-known in the EEG literature as the inverse problem. Source analysis solutions attempt to address the inverse problem by disentangling the neuronal sources that contribute to the EEG signal and helping researchers determine where and when the generator was active. Often this is done by sampling enough positions (e.g., 64 EEG channels), measuring and digitizing the locations of the EEG electrodes on the head, overlaying the electrode positions with an structural MRI (e.g., either one specific to the participant or a standardized head model), and then back-projecting the recorded electrical signals onto cortical and subcortical structures with the help of sophisticated software programs. With this approach, information pathways in the brain can be studied by using either the reconstructed activation waveforms or time-frequency analysis. Source analysis can identify the brain regions involved in different tasks and, depending on data and model quality, yield a precise localization of the generators in both space and time.

Magnetoencephalography (MEG) uses high-resolution coils coupled to superconducting quantum interference devices (SQUIDs) to measure the magnetic fields associated with the electrical currents produced by neuronal activation. Unlike EEG or fNIRS, MEG does not require the placement of sensors on the heads of participants. Rather, participants undergoing an MEG scan simply insert their heads into a helmet-like device that contains hundreds of sensor coils to capture dynamic changes in the brain’s magnetic fields. One strength of MEG is that it has both good spatial and temporal resolution for measuring neuronal activation from the cortex. Researchers may choose to combine MEG with EEG to better correlate changes in the brain’s magnetic fields with its actual electrical activity as detected by EEG electrodes placed on the head. Many MEG machines have built-in EEG amplifiers to facilitate the combination of these two modalities, and there are several technical considerations to keep in mind when combining EEG with MEG (e.g., the EEG electrodes must be degaussed to prevent interference in the MEG signal). We have many years of experience building custom EEG caps to fit with the various MEG machines on the market, and we can also provide higher-density solutions if researchers are interested in bypassing their MEG machine’s built-in EEG amplifier and using a dedicated EEG amplifier with their system.

Many researchers have teaching commitments, and we recognize the time and effort that goes into lesson planning with the goal of transferring knowledge about complex topics like electrophysiology and brain activity to a room full of students. Theoretical instruction is most effective when it is followed by practical sessions that reinforce the topics covered. Although there are several voltage / current simulators and sandbox programs available online, nothing compares to the real deal. For researchers who teach general neuroscience or cognitive science courses, being able to provide students with the opportunity to gain first-hand experience with psychophysiological data collection in the classroom setting makes the course more exciting and can improve foundational learning. Traditionally, in a classroom setting, researchers may choose to borrow equipment from their laboratory, which means that regular lab downtime is necessary if dedicated training is to be provided on an ongoing basis. To encourage education and limit downtime in the lab, we offer affordable training amplifiers and teaching licenses for many of our professional software packages. Teaching EEG has never been easier!

Brain-Computer Interfaces (BCIs) consist of hardware and software solutions that use the electrical activity of the brain to interact with and/or control external devices (e.g., machines). Traditionally, BCIs were home-grown solutions that evolved depending on the needs of the researcher and/or participant. Recognizing that there is no single solution for BCI work, we have adapted our professional research-grade solutions to be ideal for BCI work, both in terms of data quality and ease of use. Specifically, our amplifiers allow for fast access to the raw data, which is critical for real-time BCI work and are integrated with all major BCI-related software pipelines (e.g., lab streaming layer, OpenViBE, BCILAB, and BCI2000). For researchers who prefer to bypass professional software packages and have simple, code-level access to the EEG data, we offer software development kits (SDKs) for several amplifiers that are written C and C++. We also have several team members with expertise in BCI and related fields, so we are well-equipped to support researchers who are interested in this application.

Auditory brainstem responses (ABR) or brainstem auditory evoked potentials (BAEP) measure the electrical activity of the brain’s auditory system in response to the presentation of acoustic stimuli (e.g., clicks, chirps, tones, or speech). ABR and BAEP are characterized by small amplitude (e.g., ≤ 1µV) and short latency (e.g., 5-7 peaks within 10ms) signals, so specialized electrodes, pre-amplifiers, and data acquisition systems with high sampling rates (e.g., ≥ 10kHz) are needed to reliably capture these signals. To facilitate generation of the ABR/BAEP during data pre-processing, it is critical to record the precise onset of acoustic stimuli that are used to activate the brain’s auditory pathway. The timing of sound files within computer operating systems is not precise enough for ABR work (and sometimes not even for normal ERP studies), so we offer a dedicated ABR solution package that helps alleviate headaches associated with timing offsets and jitter in event markers. We also offer accessories that give researchers the ability to adjust marker onset during analysis based on the actual audio signals in the recording. ABR is a valuable method on its own, and researchers may choose to combine it with EEG to answer more complex questions about audition and speech perception.

Peripheral physiology can be used to infer activation of the autonomic nervous system in response to various cognitive processes. Peripheral signals (e.g., heart rate [ECG], muscle activation [EMG], eye movements [EOG], skin conductance [GSR], respiration, acceleration, pulse oximetry, etc.) are measured by specialized electrodes and/or sensors that are placed along the body. These signals can be informative on their own, or they may be combined with EEG to inform the interpretation of the resulting waveforms. The requirements for recording clean peripheral signals often differ from those for recording clean EEG signals. For example, peripheral signals tend to be larger (e.g., on the order of mV) compared with EEG signals (e.g., on the order of µV), so there are important technical considerations to keep in mind when selecting an appropriate system for a specific research program. We offer several solutions (including amplifiers, accessories, and open-ended auxiliary cables for researchers to incorporate their own sensors) for recording peripheral physiology that can be used independently or in conjunction with EEG to answer a wide array of questions about psychophysiology. Being able to record peripheral physiology and EEG in the same data file, synchronized to the onset of specific stimuli, streamlines data pre-processing and interpretation of the results.

Functional magnetic resonance imaging (fMRI) uses rapidly oscillating magnetic fields to measure changes in blood oxygenation level dependent signaling (BOLD) throughout the brain, which is often considered to be a correlate of neural activation. One strength of fMRI is its high spatial resolution, which permits measurement of activation in small, deep brain structures, whereas EEG is often restricted to the measurement of activation in more superficial areas of the cortex. Because fMRI measures changes in blood oxygenation (i.e., the hemodynamic response), it is a slower signal (on the order of seconds) compared to EEG, which is extremely fast (on the order of milli seconds). The ability to study brain activation with both high spatial and temporal resolution allows researchers to answer more complex questions about neural activation. However, fMRI is traditionally considered to be a hostile environment for EEG. So, from a technical standpoint, it is challenging to combine these two methodologies while maintaining participant safety. We are the market leaders in EEG / fMRI solutions, and we have a dedicated team of fMRI-certified EEG experts to support researchers throughout their studies.

We offer professional software solutions for data acquisition, real-time visualization of underlying EEG signals in hostile recording environments (e.g., during fMRI recordings), data cleaning / pre-processing, and statistical analysis. Our software solutions are stable and utilize sophisticated, research-backed algorithms that researchers can trust. Working with professional-grade software solutions allows researchers to focus on what they do best (e.g., collecting EEG data or teaching EEG methodology) rather than needing to spend time writing code or programming their data pre-processing pipeline from scratch. Of course, for those researchers who want the flexibility of writing their own macros and/or processing their data in MATLAB, our flagship software solution, BrainVision Analyzer 2, does allow for these options. Furthermore, we have dedicated scientific and technical support teams to assist EEG researchers with high-level questions related to data pre-processing and data acquisition, respectively. When it comes to stimulus presentation software, we have partnered with market-leading vendors (e.g., Psychology Software Tools and Neurobehavioral Systems) in the cognitive science space to offer complete solution packages for researchers who are building a new lab or streamlining their current setup.