802-Cognitive & social neuroscience-Characterizing Misophonia-Related Brain Activity Using fNIRS ?? A feasibility study
Misophonia is characterized by decreased tolerance to specific sounds that elicit strong negative emotional, physiological, and behavioral responses. While fMRI has explored these mechanisms, loud scanner noise and enclosed environments confound neural measurements and heighten anxiety. We evaluated functional near-infrared spectroscopy (fNIRS), a quiet, portable optical neuroimaging modality, to study misophonia. We recorded fNIRS, Photoplethysmography (PPG), and Electrodermal Activity (EDA) in 10 healthy adults during trigger, unpleasant, and neutral sounds. Unpleasant and trigger sounds elicited greater cortical activation than neutral sounds. Unpleasant sounds also induced heart rate deceleration. This study validated the feasibility of using fNIRS to study misophonia. Continue reading
804-Brain Health (clinical and preclinical)-Cerebral Neurovascular Networks May Serve as Potential Targets for Identifying Disorders of Consciousness: A Synchronous EEG-fNIRS Study
Multimodal EEG-fNIRS enhances differentiation between minimally conscious state (MCS) and unresponsive wakefulness syndrome (UWS) in disorders of consciousness. Resting-state data from 13 brain regions revealed significantly higher neurovascular coupling and EEG beta-band power in premotor and frontopolar cortices for MCS than UWS. Combining these features achieved >90% classification accuracy, outperforming single modalities. This noninvasive, portable approach offers robust diagnostic and prognostic biomarkers, addressing behavioral scale limitations and enabling longitudinal monitoring. Continue reading
807-Brain Health (clinical and preclinical)-fNIRS-Based Machine Learning for Parkinson??s Motor Subtype Classification
Parkinson??s disease includes tremor-dominant and akinetic-rigid subtypes that differ in pathophysiology and treatment response but are difficult to distinguish objectively. This study presents a machine learning??based classifier using functional near-infrared spectroscopy (fNIRS) recorded during upper-limb fine motor tasks. fNIRS data from 20 patients and 20 controls were preprocessed, and time- and frequency-domain features were extracted and selected using signal-processing procedures. Twenty-two classification models were evaluated in a multiclass setting. The Ridge Classifier achieved the best performance, with balanced accuracies of 75% in training and 83.33% in testing. These findings support fNIRS and machine learning for objective Parkinson??s subtype classification. Continue reading
817-Brain Health (clinical and preclinical)-Investigating and Enhancing Motor Imagery Brain-Computer Interface Performance: A Series of fNIRS Studies on Training Protocols and Neuromodulation
This series of studies utilizes functional Near-Infrared Spectroscopy (fNIRS) to investigate optimize Motor Imagery Brain-Computer Interface (MI-BCI) performance. We examined the effects of training frequency on cortical plasticity, the impact of MI-BCI on post-stroke attention deficits, and the efficacy of rTMS targeting the DLPFC in enhancing BCI response rates. Results demonstrate that high-frequency training and rTMS neuromodulation significantly improve BCI accuracy and cortical connectivity. Furthermore, MI-BCI training effectively enhances cognitive functions in stroke patients. These findings provide a scientific basis for standardized clinical MI-BCI protocols and highlight fNIRS as a vital tool for monitoring neural recovery. Continue reading
818-Neurodevelopment-Network Dynamics Underlying Early Speech Discrimination
This study investigated neonatal language processing using dynamic functional connectivity. Moving beyond localized hemodynamic responses, we analyzed fNIRS data from 92 neonates to capture large-scale network fluctuations during forward and reversed speech. Using a sliding-window approach and k-means clustering, we identified three distinct brain states with graded increases in functional connectivity strength. Crucially, state occurrence rates differed between speech conditions. These findings suggest that early speech discrimination relies on rapid, transient shifts in global arousal networks rather than solely localized temporal or frontal activation, emphasizing the critical role of network dynamics in early cognitive maturation. Continue reading
821-Cognitive & social neuroscience-Resting-state functional connectivity reveals age-dependent networks of affective and cognitive emapthy
Empathy comprises affective and cognitive components, yet little is known about how their neural correlates vary across adulthood. Using resting-state fMRI, we examined associations between empathy and functional connectivity (FC) in 32 younger and 33 older adults. Empathy was assessed with the Interpersonal Reactivity Index, and FC was estimated using a 264-node whole-brain parcellation. Affective empathy showed age-dependent connectivity patterns: older adults exhibited stronger positive FC, whereas younger adults showed predominantly negative correlations. In contrast, cognitive empathy showed largely negative associations with FC across both groups. Shared involvement of default mode and salience networks suggests common neural substrates underlying empathic processing across adulthood. Continue reading
822-Neuroscience for everyday life (including hyperscanning, VR, etc.)-Mismatch in Social Anxiety Impairs Interpersonal Neural Synchronization During Social Interaction: An fNIRS Hyperscanning Study
This study used functional near-infrared spectroscopy hyperscanning to examine inter-brain neural synchronization (INS) in dyads with matched or mismatched levels of social anxiety??low??low (LL), high??high (HH), and low??high (LH) dyads??during a closeness-generation task. LH dyads showed reduced INS in the right superior temporal gyrus and prefrontal regions compared with matched dyads. INS was differentially associated with perceived closeness and post-event processing across dyad types. Dynamic network analysis revealed LH dyads showed longer mean dwell time in intermediate-efficiency state and lower transition probability from low-efficiency state to intermediate-efficiency state. Continue reading
825-Cognitive & social neuroscience-The Effect of Collaborative Scripts in Engineering Design: Unraveling Neural Underpinnings using fNIRS hyperscanning study
Engineering design within STEM education serves as a vital pathway for cultivating innovative talent. To unravel the neural underpinnings of how scripts affect this process, this study employed fNIRS hyperscanning to examine the within-group inter-brain synchrony (IBS) during the engineering design progress with and without the support of a project-based collaborative script. Results revealed that the script significantly enhanced IBS in the r-TPJ and it positively predicted task performance of engineering design tasks. The findings demonstrate that structured scripts align cognitive-behavioral processes and IBS as a potential biomarker for interaction quality. Continue reading
829-Cognitive & social neuroscience-Neural correlates of evaluative bias against AI-labeled versus human-labeled artworks
Generative AI creates art rivaling humans??, yet public acceptance is uncertain. This study (two pre-registered studies, N=125) used EEG, fNIRS and LASSO regression-based machine learning to examine people??s evaluative biases toward AI-labeled paintings. We found that participants rated AI-labeled works lower. Neural data showed higher P300/alpha power, elevated right angular gyrus activity and stronger IFG-angular gyrus connectivity for human-labeled art, with LASSO regression validating these neural differences. These biases reflect human creativity preference, urging bias mitigation for AI acceptance. Continue reading
830-Neuroscience for everyday life (including hyperscanning, VR, etc.)-Cascade Transmission of Neural Coupling in Live Ensemble Performance: An fNIRS Hyperscanning Study
Live ensemble performance involves performer??performer (PP) coordination, performer??audience (PA) communication, and audience members?? perceptual integration, unfolding concurrently in a shared environment. Current research examines each process in isolation, leaving their potential interplay unexplored. Using fNIRS hyperscanning with a 3-performer and 6-audience setting across 4 live performances, we characterized PP and PA inter-brain coupling (IBC) and audience intra-brain (intraA) coupling, and tested a cascade transmission hypothesis (PP???PA???intraA). We found that PP IBC predicted PA IBC, which in turn influenced intraA coupling, with the indirect effect moderated by PP IBC level. These findings provide novel evidence for understanding live ensemble performance. Continue reading