fNIRS Archives - BIOPAC Blog

Neuroergonomics: Measuring Cognitive Workload in Real-World Tasks

In some high-stakes jobs, the pressure can feel overwhelming. From air traffic controllers tracking dozens of aircraft simultaneously to surgeons guiding robotic instruments through delicate procedures, many modern occupations require people to process extraordinary amounts of information while maintaining accuracy and focus. As workplaces become more automated and technologically sophisticated, understanding how the brain and body respond to these demands has become a central challenge for ergonomics researchers. A growing area of study, known as neuroergonomics, combines neuroscience, physiology, and human factors research to better understand how people perform in complex real-world environments.

In human factors research, neuroergonomics conintues to gain traction by offering a more comprehensive picture of cognitive workload than traditional measures. Two individuals may perform a task equally well while experiencing dramatically different levels of mental effort. Excessive cognitive workload can contribute to fatigue, stress, errors, and reduced situational awareness, while insufficient workload can lead to disengagement and decreased vigilance. Researchers are therefore concentrating attention on measuring not only what people do but also how their brains and bodies respond as they do it.

Among the most valuable tools for studying cognitive workload are physiological signals that provide objective measurements of mental state. Electroencephalography (EEG) can reveal changes in neural activity associated with attention and cognitive effort, while functional near-infrared spectroscopy (fNIRS) measures changes in cortical blood oxygenation linked to mental workload. Electrocardiography (ECG) and heart rate variability (HRV) offer insight into autonomic nervous system activity, and eye-tracking measures such as pupil diameter and gaze behavior can indicate shifts in attention and cognitive demand. More often, researchers are combining multiple synchronized signals to create a more complete view of how people interact with demanding tasks and environments.

A team of researchers from Drexel University and Lockheed Martin investigated how multiple physiological signals can be combined to measure cognitive workload across a range of mental activities. Participants completed tasks involving working memory, vigilance, risk assessment, attention shifting, situation awareness, and inhibitory control while researchers simultaneously monitored EEG, fNIRS, ECG, photoplethysmography (PPG), electrooculography (EOG), and eye tracking. Brain activity was measured using an fNIR Devices system alongside other physiological monitoring technologies. The researchers found that different physiological measures varied in their sensitivity to specific task demands, with neuroimaging measures providing particularly valuable insight into changes in workload. The findings demonstrate the value of combining signals from the brain, heart, and eyes to create a broader perspective of cognitive effort in complex environments.

Researchers at Loughborough University in the United Kingdom examined how rising task complexity influences cognitive workload in modern manufacturing environments. Participants performed a series of assembly tasks while researchers recorded pupil diameter with Tobii eye-tracking and measured HRV with wearable ECG sensors. By comparing physiological responses across low-, medium-, and high-complexity tasks, the team identified significant changes in both pupillometry and cardiac indicators of cognitive load. Their findings suggest that physiological monitoring can provide an objective means of evaluating cognitive ergonomics in highly digitalized manufacturing environments and may help support the design of more sustainable, human-centered workplaces.

Another important challenge in neuroergonomics is determining which physiological measurements provide the most reliable indicators of mental workload. A collaborative team of researchers from France investigated how physiological measurements can be used to establish standardized levels of mental workload during aviation-inspired tasks. Using the Multi-Attribute Task Battery (MATB-II), participants performed simulated flight-related tasks under varying levels of demand while researchers measured EEG, eye-tracking, electrodermal activity, and cardiac activity. ECG and EDA signals were acquired using a BIOPAC data acquisition and analysis system running AcqKnowledge software. The study found that several cardiac, ocular, and electroencephalographic measures successfully distinguished high-workload conditions and correlated with subjective workload ratings. The researchers found that several physiological measures, particularly EEG, eye tracking, and cardiovascular metrics, reliably distinguished between different workload levels and closely tracked participants’ subjective assessments of task difficulty. Their findings suggest that multimodal physiological monitoring could support the development of adaptive systems that detect cognitive overload in real time, improving both performance and safety in demanding operational environments.

These studies highlight the increasingly multimodal nature of neuroergonomics research. Eye tracking provides insight into attention and visual processing, cardiovascular measures reveal how the autonomic nervous system responds to mental demands, and brain-imaging techniques such as EEG and fNIRS offer direct windows into neural workload. By combining these complementary perspectives, researchers are moving beyond simple measures of task performance toward a deeper understanding of how people think, adapt, and perform in complex environments. As workplaces continue to evolve alongside automation and intelligent technologies, neuroergonomics is helping researchers design systems that better support human capabilities, improve safety, and reduce the hidden costs of cognitive overload.

Are you planning a multimodal neuroergonomics study? Our team of experts can help you plan your research and identify the tools that will provide the best possible data.

Under the Skin: Digging Deeper into the Physiology of Fear

From the thrill of cinematic jump scares to debilitating phobias that can turn daily life for some into a waking nightmare, our sense of fear can feel like both a blessing and a curse. Fear is one of the most fundamental human emotions, serving as a necessary safeguard for recognizing and responding to danger. Despite its primal origins, the mechanisms of fear remain complex. For decades, psychophysiologists have studied fear using measures such as the startle reflex and skin conductance, building a deep understanding of how the body reacts to threats. Today, however, researchers are beginning to look beyond these traditional markers. Technologies such as virtual reality (VR) expand how researchers can stimulate the fear response. At the same time, a broad range of signals and techniques can measure not only the body’s autonomic responses, but also how people allocate attention to threats and how the brain processes fear-related information.

One reason fear remains such a compelling topic is that it sits at the intersection of cognition, emotion, memory, and physiology. Fear responses can be observed through changes in sweating, heart activity, breathing patterns, pupil size, neural activity, and even social behavior. As researchers seek to gain a better understanding of anxiety disorders, phobias, post-traumatic stress disorder (PTSD), and related conditions, they increasingly rely on multiple synchronized signals to capture a more complete picture of how fear is learned, remembered, and generalized.

Among the most widely used measures is electrodermal activity (EDA), often recorded as skin conductance response (SCR), which reflects changes in sympathetic nervous system arousal. More recently, eye tracking and pupillometry have emerged as valuable tools for measuring vigilance and attention, while functional near-infrared spectroscopy (fNIRS) has enabled monitoring of changes in cortical activity during fear-related tasks in more naturalistic settings. Together, these approaches help researchers move beyond viewing fear as a single physiological reaction and toward understanding it as a coordinated brain-body process.

A team of researchers at South China Normal University in China explored how the duration of memory retrieval influences the reconsolidation and extinction of fear memories. Using a four-day fear-conditioning paradigm, participants were conditioned to associate visual cues with mild electric shocks. Simultaneously, skin conductance responses were recorded using an MP36 running Biopac Student Lab System. The experiment was designed and implemented with E-Prime stimulus presentation software. The team found that briefly reactivating a fear memory before training participants to view the stimulus as safe was most effective at preventing the fear from returning. Longer periods of memory reactivation produced weaker effects. The study highlights how electrodermal activity can reveal subtle changes in fear-memory processing and may ultimately contribute to improved behavioral interventions for anxiety-related disorders.

A study conducted at the University of Würzburg in Germany examined how anxiety sensitivity influences attention and memory during threat and safety learning. Participants learned associations between neutral faces and aversive outcomes while researchers recorded both electroencephalography (EEG) and pupil diameter. Pupillometry data were acquired using a Tobii eye tracker, allowing researchers to measure moment-to-moment changes in attention. Individuals with higher anxiety sensitivity showed larger pupil responses and enhanced neural markers of attention when viewing both threatening and safe cues, reflecting a generalized pattern of hypervigilance. Interestingly, this heightened attentional engagement did not translate into better memory performance. The findings suggest that pupillometry provides a valuable window into how anxious individuals process potential threats and may help researchers better understand mechanisms underlying pathological anxiety.

Another perspective on fear comes from research at Sichuan Normal University in China, where investigators look at how trait anxiety influences observational fear learning. Unlike traditional conditioning studies, participants learned about danger by watching another person experience threat-related events. Researchers measured skin conductance using a BioNomadix wireless EDA plus data acquisition and analysis system and monitored prefrontal brain activity using fNIRS. The study found that individuals with high trait anxiety exhibited stronger physiological fear responses and increased medial prefrontal cortex activation, even when observing threats indirectly. The work demonstrates that fear can be acquired socially and that neural measures such as fNIRS can reveal aspects of fear processing that are not readily captured by autonomic measures alone. These findings may have important implications for understanding how fear and anxiety spread through social environments and how vulnerability to anxiety disorders develops.

These studies illustrate how fear research leverages multimodal approaches to incorporate multiple physiological perspectives. Skin conductance continues to provide valuable information about autonomic arousal, while pupillometry reveals how attention is divided between threat and safety cues, and fNIRS offers insight into the neural processes involved in fear learning and regulation. As multimodal research platforms become increasingly accessible, researchers are gaining unprecedented insight into how fear is acquired, maintained, and modified. By combining signals from the body, the eyes, and the brain, modern psychophysiology is shining a light on the shadowy labyrinth that is one of humanity’s most powerful and important emotions. To learn more about how to construct a fear stimulation lab for your next fear-conditioning research project, check out our webinar on the subject.

If you are planning a multimodal fear conditioning study, our staff can help identify the right equipment and software for stimulus presentation and data recording and analysis.

The Nose Knows: Brain-Body Research and the Science of Olfactory Cognition

“Smell is a potent wizard that transports you across thousands of miles and all the years you have lived.” — Helen Keller

There is something uniquely intimate about the sense of smell. Unlike vision or hearing, olfactory signals travel a remarkably direct neural route from receptors in the nasal epithelium through the olfactory bulb, and straight into the brain’s limbic system, the seat of emotion and memory. A single scent can transport us instantly to a childhood kitchen, sharpen our alertness, or dissolve stress within seconds. Yet for all its power, olfaction has historically been one of the most understudied human senses. That landscape is changing. A new generation of multimodal brain-body research platforms, capable of simultaneously recording signals from the brain and the body, is giving scientists insight into how smell shapes thought, emotion, and cognition.

The olfactory system is the only sensory system that bypasses the thalamus, the brain’s central relay station, and connects directly to the amygdala and hippocampus, two structures critical to emotional processing (affect) and memory. This anatomical shortcut explains why odors are so potent at triggering emotional memories, often more vividly than visual or auditory cues. Beyond memory, researchers are increasingly interested in how odor exposure alters measurable physiological and neurological states in real time, ranging from modulating cognitive performance and stress to the early detection of neurodegenerative disease, in which olfactory dysfunction often appears years before other symptoms emerge.

What makes this research technically challenging is also what makes it scientifically rich: the olfactory experience simultaneously engages the central nervous system and the autonomic nervous system, meaning that studying it well requires capturing signals from both brain and body at once. Electroencephalography (EEG) provides direct data on the brain’s electrical activity with millisecond-level temporal resolution, making it well-suited to detecting rapid shifts in cognition and arousal following odor exposure. Functional near-infrared spectroscopy (fNIRS) offers a complementary picture, using near-infrared light to detect changes in cortical oxygenation, a measure of the brain’s metabolic response to stimulation. Wearable and tolerant of movement, fNIRS is particularly well-suited to naturalistic experimental designs. Electrodermal activity (EDA), or skin conductance, captures the autonomic nervous system’s arousal response through sweat gland activity, while electrocardiography (ECG) and heart rate variability (HRV) add a cardiovascular layer that can distinguish sympathetic from parasympathetic activity in fine detail. Today’s lab setups use a range of sophisticated scent delivery systems to integrate precise, controllable olfactory stimuli into experiments. The real power of modern multimodal platforms lies in their ability to synchronize all these channels within a single setup, time-locking each physiological response to a specific odor event and revealing the full brain-body picture that no single signal could show alone.

A research team at the All India Institute of Medical Sciences in Jodhpur investigated whether citrus odor could buffer the cognitive and physiological impact of working memory load. Thirty participants completed a demanding working memory test under both control and citrus-odor conditions, with the odor delivered via an aroma diffuser. ECG, photoplethysmography (PPG), and EDA were recorded using a BIOPAC data acquisition system with AcqKnowledge software for analysis, and dual-signal BioNomadix wireless EDA and PPG module. For EDA recording, disposable silver/silver chloride disc electrodes were applied to the hypothenar and thenar eminences, and the PPG sensor was placed on the index finger. Citrus odor significantly improved task accuracy while suppressing the rise in skin conductance typically associated with cognitive load. HRV measures, including pNN50, RMSSD, and HF power, shifted toward parasympathetic dominance, indicating a calmer, more regulated physiological state. The findings, published in the Annals of Neurosciences, suggest that citrus odor acts as a cognitive stress buffer and point to practical applications in educational, occupational, and clinical settings with high sustained cognitive demands.

A counterintuitive question motivated a study at Nagaoka University of Technology in Japan: could black pepper, widely known as a stimulant, actually calm the body’s stress response? A group of university students performed a 30-minute arithmetic calculation task under three aroma conditions: black pepper, ginger, and a scentless control. Scents were delivered at precise, reproducible intervals through an olfactometer. A BIOPAC data acquisition system recorded continuous ECG and skin conductance level (SCL) at 200 Hz with 16-bit resolution, with high-frequency HRV (HF-HRV) derived as a measure of cardiac parasympathetic activity. Electrodes were placed beneath the right clavicle and on the lower left abdomen following the Lead II placement protocol for ECG measurements using multi-lead ECG cables. SCL was recorded using skin conductance sensors placed on the palmar side of the middle phalanx of the index and ring fingers of the participant’s non-dominant hand. The results, published in the Journal of Physiological Anthropology, found that black pepper aroma reduced the stress-induced rise in heart rate by 38.9% compared to the scentless control, attenuated the decline in HRV by 32.9%, and blunted the increase in SCL compared to ginger. Crucially, subjective stress ratings did not differ across conditions, demonstrating that the body can respond to olfactory stimuli at a physiological level even when conscious perception does not register a difference. These findings have meaningful implications for workplace wellness and aromatherapy research.

A French consortium of researchers from the Université Bourgogne Franche-Comté and the Université Grenoble Alpes tested whether music, lavender odor, or their combination would accelerate autonomic recovery following acute cognitive stress. Ninety-nine participants completed a battery of cognitively demanding tasks. They were then randomly assigned to one of four 30-minute recovery conditions: silence, relaxing classical music, lavender essential oil, or music and lavender together. A data acquisition system running AcqKnowledge continuously recorded ECG and EDA using Ag-AgCl finger electrodes, with HF-HRV as an index of parasympathetic activity and EDA as a measure of sympathetic arousal. Published in Psychophysiology, the study found that both music and lavender independently facilitated autonomic recovery. The surprising finding, however, was the absence of any multisensory advantage: combining the two stimuli produced no greater benefit than either alone, suggesting that when multiple sensory channels converge on the same relaxation goal, they may share rather than combine their neural resources. The study underscores both the value of multimodal physiological recording in parsing the mechanisms of stress recovery and the importance of rigorously testing assumptions about how the senses work together.

These studies illustrate how much remains to be discovered at the intersection of smell, brain, and body, and how essential it is to measure all three at once. As synchronized multimodal platforms continue to evolve, the science of olfactory cognition continues to shape our fundamental understanding of how the brain works and the development of practical tools to support cognitive health and wellbeing. To learn more about the convergence of olfaction with brain-body research, be sure to check out our webinar on how scents influence cognition.

If you are planning a brain-body study that integrates multimodal data collection with stimulus presentation like scent delivery, our expert staff is ready to help find everything you need to get started.

Muscles in Motion: Electromyography in Physiological Research

When we think about the human muscular system, movement often comes to mind. Activities such as running, lifting, and maintaining posture all rely on coordinated skeletal muscle activity, while cardiac muscle drives circulation and smooth muscle supports essential functions like digestion. Yet muscles do more than move us from point A to B; they also reflect what is happening inside the body. Patterns of muscle activation can reveal information about physical effort, fatigue, coordination, and recovery, as well as emotional expression, stress, and cognitive engagement. Electromyography (EMG) is a widely used technique for measuring the electrical signals generated by muscles during contraction, providing researchers with a direct and objective means to study both physiological function and the links among the nervous system, behavior, and mental state. By capturing muscle activity that may be too subtle to observe visually, EMG enables precise investigation of processes ranging from motor control and performance to emotional and stress-related responses.

There are several types of EMG, each suited to different research needs. Surface EMG (sEMG) uses small sensors placed on the skin to detect activity from nearby muscles and is the most common approach in behavioral and human performance studies. Intramuscular EMG involves inserting a fine-needle electrode directly into a muscle to record activity from specific muscle fibers, often used in clinical or specialized research settings. Facial EMG (fEMG), a form of surface EMG, focuses on facial muscles. By measuring muscle activity associated with smiling or frowning, fEMG allows researchers to study emotional responses, even when those responses are subtle or not consciously expressed.

One of the key strengths of EMG is its ease of integration with other physiological measurements. In many studies, EMG is recorded alongside electrocardiography (ECG), which measures heart activity; electroencephalography (EEG), which records electrical activity in the brain; functional near-infrared spectroscopy (fNIRS), which tracks changes in brain oxygenation; and eye tracking, which monitors visual attention and gaze patterns. By synchronizing these signals in time, researchers can better understand how different systems in the body work together. For example, combining EMG with EEG can reveal how brain activity leads to muscle movement, while pairing EMG with ECG can show how physical effort relates to heart responses during stress or exercise. This multimodal approach is central to advancing research in areas such as emotion, cognition, and human performance.

EMG also has important real-world applications. In rehabilitation, it helps clinicians monitor muscle recovery after injury. In ergonomics, it provides objective data about muscle strain in the workplace. In sports science, EMG helps optimize training and performance by identifying how and when muscles are activated. Increasingly, EMG is also used in human–machine interfaces, such as systems that allow people to control prosthetic limbs using their muscle signals. Its ability to detect fine-grained changes in muscle activity makes EMG a valuable tool across both research and applied settings.

Best practices for EMG data quality begin with careful electrode placement and attention to potential sources of noise. For sEMG and fEMG, electrodes should be placed over the “belly” of the target muscle, aligned with the muscle fibers, and spaced consistently to capture clean, interpretable signals. Gently cleaning the skin and, when appropriate, lightly abrading the surface helps reduce impedance and improve signal quality. In fEMG studies, precise and repeatable placement over well-defined facial muscles is critical, as these muscles are small and closely spaced. To minimize noise and artifacts, researchers should secure electrodes and cables to prevent movement, ask participants to limit unnecessary body motion, and ensure proper grounding of the recording system. Electrical interference from nearby equipment, power lines, or poor cable management can also contaminate EMG signals, so shielded cables and a controlled recording environment are recommended. Finally, synchronizing EMG with other physiological signals using a common acquisition system helps prevent timing errors and reduces the need for later corrections, resulting in cleaner data and more reliable conclusions.

Recent studies demonstrate how EMG continues to expand into new and innovative areas. In a study published in Results in Engineering, a team of researchers from China developed a low-computational method for recognizing hand gestures from EMG signals to improve prosthetic device control. The researchers extracted key features from EMG recordings and used a lightweight machine-learning model, a multilayer perceptron (MLP), to classify gestures in real time. EMG data were collected using a four-channel BIOPAC data acquisition system running Biopac Student Lab (BSL) software. Surface Ag/AgCl electrodes were placed on four forearm muscles to capture relevant muscular activity. The study showed that accurate gesture recognition can be achieved without heavy computational requirements, making the system more practical for everyday use. This work highlights how EMG can support the development of more responsive, accessible assistive technologies.

Another study, conducted by a team of researchers from Mahidol University in Thailand and presented in the Institute of Electrical and Electronics Engineers (IEEE) proceedings, explored how combining EMG with motion sensors can improve ergonomic assessments. Focusing on occupational health, the study integrated surface EMG with data from an inertial measurement unit (IMU), a sensor that tracks movement and orientation. The researchers used the IMU to calculate Rapid Upper Limb Assessment (RULA) scores—a common method for evaluating postural risk—while EMG data collected via a BIOPAC four-channel research system provided insight into muscle activity. By combining these measures, the team found that posture alone did not always reflect actual muscle strain. The inclusion of EMG revealed additional muscle stress that might otherwise go unnoticed, suggesting that multimodal approaches can lead to more accurate workplace assessments and better injury-prevention strategies.

Researchers from Louisiana State University and the Pennington Biomedical Research Center in Baton Rouge, Louisiana, examined how training experience influences muscle activation and fatigue during resistance exercise performed with and without blood flow restriction (BFR) in young men. The study, published in Physiological Reports, compared trained and untrained participants while they completed knee extension exercises under low-, medium-, and high-load conditions. The team used sEMG to measure muscle excitation and total muscle activation in the vastus lateralis, with participants fitted with a portable BIOPAC BioNomadix Wireless EMG system. EMG signals were sampled at 2000 Hz and analyzed using a data acquisition system with AcqKnowledge software, allowing the researchers to quantify both peak muscle excitation and overall activation across repetitions. The results showed that low-load exercise with blood flow restriction produced lower peak muscle excitation but substantially greater total muscle activation compared to traditional high-load exercise, regardless of training status. These findings suggest that low-load BFR training may provide an effective alternative for stimulating muscle adaptations while reducing mechanical stress, with potential applications in rehabilitation and strength training programs.

Taken together, these examples illustrate the versatility and effectiveness of EMG in neuroscience, psychophysiological research, and beyond. Whether used to study emotion, improve physical training and workplace safety, or develop assistive technologies, EMG provides a direct link between muscle activity and human behavior. When combined with other physiological measures, it offers a more comprehensive understanding of how the brain and body interact. As research tools and techniques continue to advance, EMG will remain an essential method for exploring brain-body connections. For additional information on how to design studies around EMG, best practices for gathering EMG data, and how to integrate EMG with other signals, check out our webinar on EMG acquisition and analysis.

If EMG will be part of your next physiological or psychophysiological research project, reach out to our knowledgeable staff, who are standing by to help you with each stage of the planning and design process.

Virtual Phobia: How VR is Transforming Anxiety and Fear Research

“Do the thing you fear and the death of fear is certain.”

These words by American poet and philosopher Ralph Waldo Emerson assert a head-on approach to overcoming life’s anxieties and phobias. It’s a strategy backed by the latest research methodology, which, thanks to technology, can leverage the relative safety of virtual environments to study how participants react to and manage anxiety.

Anxiety disorders are among the most prevalent mental health conditions and are often maintained through avoidance of fear‑provoking situations. A cornerstone of evidence‑based treatment is exposure therapy, in which individuals gradually and safely confront feared experiences to reduce anxiety over time. In recent decades, virtual reality (VR) has emerged as an effective way to deliver exposure therapy and to study anxiety under controlled conditions. Virtual reality exposure therapy (VRET) uses immersive, computer‑generated environments to recreate anxiety‑triggering situations, such as public speaking, social interaction, or medical procedures, while allowing researchers and clinicians to control intensity, pacing, and repetition.

Research shows that VRET can be as effective as traditional, real‑world exposure for many anxiety‑related conditions, including specific phobias, social anxiety, panic disorder, and symptoms of post‑traumatic stress disorder (PTSD). One of VR’s key advantages is its balance between realism and experimental control. Environments can be standardized across participants, exposure levels can be adjusted in small steps, and scenarios can be repeated across sessions without the logistical challenges of invivo exposure. At the same time, well‑designed VR experiences reliably evoke emotional and stress responses, making them valuable for both treatment and research.

The scientific impact of VR is amplified when immersive environments are combined with multimodal psychophysiological measurements—such as electrocardiography (ECG), electroencephalography (EEG), functional near‑infrared spectroscopy (fNIRS), respiration, electrodermal activity (EDA), and eye tracking. In multimodal studies, researchers gain a deeper, objective understanding of how the brain and body respond to emotional challenges. By synchronizing VR events with physiological data, researchers can observe how the body responds moment by moment as fear is triggered, maintained, and eventually reduced.

Researchers at the University of Cyprus investigated whether a single session of VR exposure could meaningfully reduce public speaking anxiety in university students. Participants were placed in a virtual auditorium and asked to give a speech in front of realistic virtual audiences. The researchers could adjust audience size and behavior, allowing them to gradually increase the social challenge while maintaining full experimental control. To capture objective stress responses, heart activity was recorded using a Lead I electrocardiogram configuration, with two disposable silver/silver‑chloride electrodes placed on the forearms. Signals were amplified with a BIOPAC ECG100C bio‑amplifier, acquired using a MP data acquisition system with AcqKnowledge software for recording and analysis. This setup enabled precise measurement of heart rate and heart rate variability (HRV) throughout the task. The virtual environment was created using the Vizard Virtual Reality Toolkit, which was integrated with the BIOPAC system so that physiological data could be synchronized with key moments in the VR experience, such as the start of the speech. Results showed significant reductions in both self‑reported anxiety and physiological arousal following a single VR exposure session, demonstrating how VR and physiological monitoring can be combined to assess rapid emotional change.

Researchers at the University of Macau examined how social rewards and emotional cues influence anxiety during interpersonal interaction. Participants engaged in a virtual reality social interaction game designed to mimic real social exchanges while allowing researchers to control feedback and outcomes. During the task, heart activity was recorded using ECG with an MP data acquisition system. By synchronizing physiological data with events in the virtual environment, the research team could examine how anxiety‑related responses evolved as social interactions unfolded. The findings suggested that anxiety responses were more strongly related to sensitivity to others’ emotional cues than to reward outcomes themselves. This study highlights how immersive VR combined with synchronized physiological recording can provide insight into the subtle emotional dynamics of social anxiety, processes that are difficult to capture using self‑report measures alone.

In a multi‑institutional effort led by researchers at the University of Toledo, researchers developed a study protocol to better understand how dental fear develops and how early exposure might help prevent it. The study uses a virtual reality dental clinic to expose participants to dental‑related sights and sounds across multiple sessions and contexts. The virtual environment was programmed using Vizard software, and participants interacted with it using an HTC Vive Pro headset and handheld controllers, allowing natural movement and exploration. Skin conductance responses (SCR) were recorded using a BIOPAC MP system paired with a wireless BioNomadix EDA transmitter, enabling participants to move freely while skin conductance and other signals are collected. This wireless, immersive setup is especially well suited for fear‑learning research, where comfort and natural movement are critical. Although the publication focuses on study design rather than completed outcomes, it demonstrates how VR combined with physiological monitoring can support translational research aimed at understanding and preventing the development of fears and anxiety.

These studies show how VR and synchronized physiological measurement are expanding the study of anxiety, stress, and fear. VR provides immersive, repeatable experiences that reflect real‑world challenges, while physiological signals reveal how the body responds beneath conscious awareness. For additional information on how to integrate VR into multimodal research, visit our Webinar page for instructive trainings on this topic and others.

If you are planning to integrate VR into your next multimodal study, reach out to our skilled sales staff who can assist you through each step of the process.

Healing Hands: EDA and Affective Touch

“Nothing eases suffering like human touch.” — Bobby Fischer

The gentle caress of a mother to her child. A reassuring pat on the shoulder from a friend. The touch of another human is one of the first forms of communication we experience in life, preceding the development of spoken language. Touch can have a remarkable effect on our emotional, psychological, and physiological states. It shapes our relationships with others and helps us build social connections.

The positive effects of touch are primarily associated with affective touch, characterized by comforting, caress-like stroking that activates C-tactile afferent (CT-afferent) neurons in the skin of mammals (including humans). Affective touch has attracted the interest of researchers seeking to decode how the sympathetic nervous system confronts and manages a variety of challenges, including pain regulation, stress management, and social interactions. The subject has drawn attention in the study of neurodevelopmental disorders, such as Autism Spectrum Disorders (ASD), where it is playing an essential role in understanding the sensory and social challenges facing individuals with atypical neurocognitive function.

While studies on touch, and affective touch specifically, utilize a range of physiological signals to gather data, electrodermal activity (EDA) has proven particularly useful in this area. Also referred to as Galvanic Skin Response (GSR), EDA provides a direct window into the sympathetic nervous system, which is responsible for emotional or affect-related arousal. When someone experiences pleasant or meaningful touch (e.g., a gentle stroke or supportive hand), the brain triggers subtle changes in sweat gland activity manifested as shifts in skin conductance. These changes occur when people aren’t fully aware of their emotional response. This makes EDA a sensitive, objective marker of how the body reacts to social and tactile experiences. In studies of affective touch, researchers track EDA to see whether a touch feels calming, engaging, or stressful, and how these responses differ across individuals or clinical groups such as autistic youth. Because EDA reflects genuine physiological arousal tied to emotional processing, it helps scientists understand the underlying autonomic mechanisms that shape how we experience social touch.

Researchers at the University of Tours in France examined how children with ASD respond to gentle, affective touch to determine whether they exhibit physiological patterns that differ from those of their neurotypical peers under the same conditions. The team measured multiple aspects of the autonomic nervous system, including EDA and electrocardiogram (ECG). These signals were collected using a BIOPAC MP36 data acquisition and analysis system to capture subtle changes in sympathetic arousal. Researchers collected EDA data using two 8 mm Ag/AgCl cup electrodes placed on the second phalanges of the index and middle fingers of the right hand. ECG was collected via two disposable vinyl electrodes placed on the sternum and on the right shoulder. The study found that autistic children exhibited atypical EDA responses, showing either blunted or inconsistent autonomic reactions relative to controls, even when their outward behavior appeared typical. These results suggest that affective touch may not regulate internal arousal in autistic children the same way it does in others, providing an essential insight for therapies and sensory-based interventions that rely on touch.

In a similar study, a team from the University of Turin in Italy explored how autistic adults process affective touch by comparing their subjective ratings of pleasantness with their physiological responses. The researchers used a BIOPAC data acquisition research system with an EDA amplifier module to record EDA. At the same time, participants received gentle, slow stroking intended to activate the brain’s affective touch pathways. The goal was to determine whether autistic adults show a mismatch between what they say they feel and how their bodies respond. The findings revealed an apparent dissociation. While autistic participants often rated the touch similarly to neurotypical participants, their EDA responses differed significantly, indicating altered sympathetic arousal. This physiological-subjective mismatch provides compelling evidence that affective touch is processed differently in ASD, which may help explain challenges with social touch and sensory integration in everyday interactions.

Researchers from the University of Liverpool and Manchester Metropolitan University examined how brief, naturalistic social touch alters brain activity, autonomic physiology, and emotion recognition performance. Although this multimodal study did not focus on an autism-only sample, it is relevant to social-touch research more broadly and provides methodological examples that apply to ASD studies. To capture changes in prefrontal cortex function, the team employed a BIOPAC fNIRS imager system, with signals sent to a data acquisition unit. Further analysis of fNIRS signals was handled via fNIRS visualization software. Both EDA and photoplethysmography (PPG) were recorded at 2 kHz, using shielded Ag/AgCl electrodes on the index and fourth fingers and a PPG sensor on the middle finger, and were acquired and analyzed in AcqKnowledge. The results showed that social touch increased prefrontal activation, modulated cardiac and vascular dynamics captured via PPG, and produced measurable changes in sympathetic arousal, as indexed by EDA. Participants also demonstrated improved emotion-recognition accuracy following touch. Together, these findings suggest that social touch engages coordinated central and peripheral systems in ways that may support social cognition and emotional understanding.

These are just a few examples of how EDA is being used in research into affective touch. For additional information on integrating EDA in your study, see our multiple webinars on the subject.

Are you designing a study into affective touch or just planning a research project that will focus on EDA? Our customer service staff can help you streamline the process to produce best possible data.

Brain and Body: SPA-fNIRS Solves Physiological Signal Noise

Functional near-infrared spectroscopy (fNIRS) offers researchers a powerful noninvasive tool for studying brain activity by measuring changes in blood oxygen levels. These changes reflect how various brain regions respond to stimuli such as tasks that involve thinking, emotion, movement, and social interaction. These are often in natural, real-world settings that are not possible with other brain imaging methods. However, fNIRS is not without its own limitations. Systemic fluctuations in the body, such as breathing patterns, cardiovascular changes, and autonomic responses, can result in signal noise that is misinterpreted as brain activity by traditional fNIRS. The solution: a visit to the SPA.

Systemic Physiology Augmented fNIRS (SPA-fNIRS) is an advanced approach to fNIRS that goes beyond measuring local changes in cerebral oxygenation. While standard fNIRS measures cortical hemodynamics by tracking oxygenated (HbO) and deoxygenated (HbR) hemoglobin, noise originating from systemic physiological changes can corrupt those signals. Combining data from both neural and systemic physiological signals, SPA-fNIRS provides researchers with a more diverse and accurate view of how the brain and body interact in real time.

The method is being applied across various fields, including psychophysiology, cognitive neuroscience, exercise physiology, mental health, and human performance research. Studies have utilized SPA-fNIRS to investigate a range of topics, including meditation and emotional regulation, movement control, and social interaction. The broader goal is to move beyond studying the brain in isolation and to understand it as part of an integrated mind-body system. This holistic view is transforming how scientists interpret brain-function data, opening new paths for applied research in education, rehabilitation, and human-machine interface design.

Researchers in India investigated the impact of a traditional sound-based meditation technique, known as the Mind-Sound Resonance Technique (MSRT), on both brain and heart activity. Using fNIRS to track changes in oxygen levels in the prefrontal cortex, and a BIOPAC data acquisition and analysis system with AcqKnowledge software to record and analyze heart rate variability (HRV), the study employed a SPA-fNIRS design, integrating neural and physiological data in a single, synchronized dataset. HRV analysis allowed the researchers to quantify shifts in autonomic balance during and after meditation. The results showed increased oxygenation in the right prefrontal cortex and enhanced low-frequency HRV components, reflecting greater parasympathetic regulation. Together, these findings suggest that sound-based meditation not only improves brain oxygenation but also promotes calmer, more balanced heart-brain dynamics, illustrating how SPA-fNIRS methods can reveal the comprehensive physiological impact of mindfulness practices.

In her doctoral research at the Université de Lille in France, neuroscientist Aurore Guérin examined how the brain controls movement speed using a multimodal combination of fNIRS and physiological data recording systems. Participants performed repetitive arm movements at fast, natural, and slow tempos. At the same time, the study captured oxygenation in the prefrontal and motor cortices using fNIRS, alongside heart rate and respiration signals collected with a BIOPAC data acquisition system. A respiratory effort transducer measured breathing patterns, while a BioNomadix ECG module recorded cardiac activity for HRV analysis. All physiological signals were synchronized and analyzed in AcqKnowledge software, allowing the team to identify and remove systemic influences (e.g., heartbeat and breathing rhythms) from the fNIRS signals, following a SPA-fNIRS approach. The results revealed that faster movements primarily engaged motor regions, while slower, more deliberate pacing resulted in higher prefrontal activation, reflecting greater cognitive control. By integrating physiological monitoring with fNIRS, the study provided a clearer picture of how the brain and body coordinate timing and control during movement.

These studies illustrate how SPA-fNIRS is reshaping the way scientists investigate the interaction between brain and body. By combining neural and physiological data in a single synchronized system, researchers can separate brain activity from systemic noise and uncover the interplay between cognition, emotion, and autonomic regulation. For more information on this topic, watch our webinar on Multimodal SPA-fNIRS and check our our latest multimoldal fNIRS research products.

Are you planning a study that blends fNIRS with other physiological signals? Contact your local BIOPAC customer service representative to learn more about how SPA-fNIRS can benefit your research.