Biology subjects

Mentch, J.

Publications and source records attributed to Mentch, J..

3 recordsLinked to original sources

bioRxiv2026

Pregistered movie-fMRI analyses reveal altered visual feature encoding in autism in pSTS

Sensory-perceptual differences are widely reported in autism, yet their underlying mechanisms remain unclear. We tested preregistered hypotheses using stacked encoding models applied to naturalistic movie-viewing fMRI from children and adolescents with and without an autism diagnosis from the Healthy Brain Network. We mapped cortical responsiveness to low- and high-level auditory and visual feature spaces. Contrary to enhanced perceptual functioning predictions, autism was not associated with increased low-level encoding in primary sensory cortices. Instead, autistic children and adolescents had reduced high-level visual representations and a relative shift toward low-level over high-level feature encoding in integration and social brain regions including the pSTS and adjacent face/social areas. In pSTS, this high-low weighting tracked Social Responsiveness Scale (SRS) scores. By contrast, audio-visual modality preference and sensory dominance were broadly conserved across groups. Developmentally, encoding exhibited strong, lateralized, modality-congruent age effects. Together, these findings favor weak central coherence accounts over early sensory enhancement, constrain mechanisms to altered visual feature weighting within social/multisensory networks, and demonstrate the value of naturalistic stimuli and encoding models for characterizing sensory-perceptual neurodevelopmental differences.

neuroscience↗

bioRxiv2022

Neuroscout, a unified platform for generalizable and reproducible fMRI research

Functional magnetic resonance imaging (fMRI) has revolutionized cognitive neuroscience, but methodological barriers limit the generalizability of findings from the lab to the real world. Here, we present Neuroscout, an end-to-end platform for analysis of naturalistic fMRI data designed to facilitate the adoption of robust and generalizable research practices. Neuroscout leverages state-of-the-art machine learning models to automatically annotate stimuli from dozens of naturalistic fMRI studies, allowing researchers to easily test neuroscientific hypotheses across multiple ecologically-valid datasets. In addition, Neuroscout builds on a robust ecosystem of open tools and standards to provide an easy-to-use analysis builder and a fully automated execution engine that reduce the burden of reproducible research. Through a series of meta-analytic case studies, we validate the automatic feature extraction approach and demonstrate its potential to support more robust fMRI research. Owing to its ease of use and a high degree of automation, Neuroscout makes it possible to overcome modeling challenges commonly arising in naturalistic analysis and to easily scale analyses within and across datasets, democratizing generalizable fMRI research.

neuroscience↗

bioRxiv2020

Active Vision in Immersive, 360° Real-World Environments

Vision is an active process. Humans actively sample their sensory environment via saccades, head turns, and body movements. Yet, little is known about active visual processing in real-world environments. Here, we exploited recent advances in immersive virtual reality (VR) and in-headset eye-tracking to show that active viewing conditions impact how humans process complex, real-world scenes. Specifically, we used quantitative, model-based analyses to compare which visual features participants prioritize over others while encoding a novel environment in two experimental conditions: active and passive. In the active condition, participants used head-mounted VR displays to explore 360{o} scenes from a first-person perspective via self-directed motion (saccades and head turns). In the passive condition, 360{o} scenes were passively displayed to participants within the VR headset while they were head-restricted. Our results show that signatures of top-down attentional guidance increase in active viewing conditions: active viewers disproportionately allocate their attention to semantically relevant scene features, as compared with passive viewers. We also observed increased signatures of exploratory behavior in eye movements, such as quicker, more entropic fixations during active as compared with passive viewing conditions. These results have broad implications for studies of visual cognition, suggesting that active viewing influences every aspect of gaze behavior - from the way we move our eyes to what we choose to attend to - as we construct a sense of place in a real-world environment. Significance StatementEye-tracking in immersive virtual reality offers an unprecedented opportunity to study human gaze behavior under naturalistic viewing conditions without sacrificing experimental control. Here, we advanced this new technique to show how humans deploy attention as they encode a diverse set of 360{o}, real-world scenes, actively explored from a first-person perspective using head turns and saccades. Our results build on classic studies in psychology, showing that active, as compared with passive, viewing conditions fundamentally alter perceptual processing. Specifically, active viewing conditions increase information-seeking behavior in humans, producing faster, more entropic fixations, which are disproportionately deployed to scene areas that are rich in semantic meaning. In addition, our results offer key benchmark measurements of gaze behavior in 360{degrees}, naturalistic environments.

neuroscience↗