Researchers Decode Emotional Responses to Sound and Touch

Scientists at NYU Tandon and the Icahn School of Medicine at Mount Sinai have made significant strides in understanding how our bodies react to emotional stimuli. Their recent study, published in PLOS Mental Health, reveals that physiological signals, such as skin conductance, can provide insights into cognitive arousal—mental alertness and emotional activation—without relying on subjective reports. This research illustrates how our physiological responses often occur before we consciously register feelings.

The study, led by Rose Faghih, an Associate Professor of Biomedical Engineering at NYU Tandon, utilized skin conductance as a key indicator of autonomic nervous system activity. When sweat glands are activated, even slightly, the skin’s electrical conductivity changes. This phenomenon, known as electrodermal activity, has long been associated with emotional and cognitive states. What sets this research apart is its innovative combination of physiological modeling and statistical analysis to interpret these subtle electrical fluctuations in response to various sensory experiences.

Starting as a course project, the research involved students Suzanne Oliver and Jinhan Zhang under the mentorship of research scientist Vidya Raju and the supervision of Faghih. James W. Murrough, Professor of Psychiatry and Neuroscience at Mount Sinai, also played a key role in the project. Oliver expressed her enthusiasm, saying, “Taking Prof. Faghih’s class was a great experience, and it was exciting to see how our work could potentially improve treatment for mental health conditions in the future.”

Analyzing Skin Conductance for Emotional Insights

The researchers analyzed an existing dataset where participants’ skin conductance was continuously recorded as they experienced visual, auditory, and haptic stimuli. Participants also rated their arousal levels using the Self-Assessment Manikin, a pictorial scale for quantifying emotional states. By applying a physiologically informed computational model, the team separated the components of the skin’s electrical response, inferring when the autonomic nervous system was most active.

The analysis uncovered a significant pattern: the nervous system reacted most robustly within two seconds of exposure to a new stimulus, with haptic sensations eliciting the strongest immediate responses. Interestingly, while auditory stimuli, particularly sounds and music, were often linked to high arousal states in self-reports, physiological signals suggested haptic sensations triggered the most immediate responses.

Despite the discrepancies, when researchers processed the physiological signals into arousal estimates, the findings aligned closely with participants’ self-assessments regarding auditory stimuli. The model was successful in tracking changes in arousal levels as participants transitioned from low- to high-intensity stimuli, demonstrating accuracy beyond random chance.

When analyzing participants based on their responsiveness to different stimuli, the model effectively captured group trends in self-reports, revealing significant differences in responses to visual and haptic cues.

Applications in Health and Technology

The implications of this research extend far beyond academic interest. In clinical settings, self-reported measures have long been the gold standard for assessing mental states such as anxiety and stress. However, these measures can be subjective and unreliable. Objective metrics derived from skin conductance could provide clinicians with a more nuanced understanding of a patient’s emotional dynamics in real-time.

This approach may be particularly beneficial in monitoring recovery from conditions like depression, anxiety, or post-traumatic stress disorder, where physiological arousal often reflects symptom fluctuations. Furthermore, the study hints at promising applications in virtual reality and human-computer interaction. By quantifying user reactions to various stimuli, systems could adapt dynamically—enhancing immersion, improving focus, or reducing stress based on user needs.

The authors acknowledge the challenges of translating physiological signals into precise emotional interpretations. Factors such as stimulus duration, individual differences, and past experiences complicate understanding. While the correlation between computed arousal and self-reported ratings was modest overall, the model’s ability to consistently identify moments of heightened engagement indicates its potential as a complementary measure of internal states.

Ultimately, this study bridges the gap between physiology and perception. By grounding emotional experience in physiological signals, it opens avenues for a more continuous, data-driven understanding of how humans interact with the world. This research may eventually influence both mental health care and the development of emotionally responsive technologies.