Biology subjects

Stolk, A.

Publications and source records attributed to Stolk, A..

5 recordsLinked to original sources

bioRxiv2024

Social Anxiety Alters Theory of Mind Activation and Intersubject Neural Variability During Movie Viewing

Social anxiety is characterized by an intense fear of judgment in social situations, yet the underlying mechanisms driving this condition remain poorly understood. One hypothesis holds that specific alterations in Theory of Mind (ToM) affect the ability to interpret others thoughts and emotions. Another hypothesis proposes that broader interpretive biases lead individuals to perceive social cues as overly significant, even in neutral settings. We investigated these possibilities by measuring brain activity, pupil responses, and heart rates in socially anxious individuals and matched controls as they viewed Partly Cloudy, an animated film known to engage the ToM network during specific scenes. While overall brain activity during ToM-related scenes was similar across groups, socially anxious participants exhibited reduced activation in the left posterior superior temporal sulcus (pSTS), a key area for ToM processing. Additionally, intersubject correlation analysis revealed a distinct neural response pattern in the socially anxious group, marked by uniform responses in sensory regions and heightened variability in higher-order cortical areas. This pattern persisted throughout the film and occurred without changes in heart rate or pupil responses, indicating a neural processing bias that manifests even in non-evaluative settings. These findings provide a neural basis for ToM alterations and broader interpretive biases in social anxiety, supporting cognitive-behavioral models and suggesting novel targets for intervention.

neuroscience↗

bioRxiv2024

Preserved spontaneous mentalizing amid reduced intersubject variability in autism during a movie narrative

Individuals with autism may perform well in structured Theory of Mind (ToM) tasks that assess their ability to infer mental states, yet encounter challenges in everyday social interactions. Using fMRI and pupillometry, we investigated whether this discrepancy stems from reduced spontaneous mentalizing or broader difficulties in unstructured environments. Autistic adults and neurotypical controls viewed a nonverbal animated movie featuring events known to evoke mental state inferences. Both groups exhibited similar ToM network activations and pupil responses to these events, alongside comparable verbal accounts of the mental states portrayed. However, intersubject correlation analysis revealed a significant reduction in response variability among autistic participants throughout the movies complex visual narrative, affecting brain regions beyond the ToM network. We suggest that the primary challenge for individuals with autism may lie in the idiosyncratic exploration of narratives in unstructured settings, regardless of whether mental state inferences are involved.

neuroscience↗

bioRxiv2023

Integrating stereotypes and factual evidence in interpersonal communication

Stereotypes can exert a powerful influence on our interactions with others, potentially leading to prejudice when factual evidence is ignored. Here, we identify neuroanatomical and developmental factors that influence the real-time integration of stereotypes and factual evidence during live social interactions. The study uses precisely quantified communicative exchanges in a longitudinal cohort of seventeen-year-olds followed since infancy, testing their ability to moderate stereotype tendencies toward children as contrary evidence accumulates. Our results indicate that the impact of stereotypes on communicative behavior is linked to individual variations in gray matter density and cortical thickness in the right anterior cingulate gyrus. In contrast, the ability to moderate stereotype tendencies is influenced by developmental exposure to social interactions during the initial years of life, beyond the effects of familial environment and later experiences. These findings pinpoint a key brain structure underlying stereotype tendencies and suggest that early-life social experiences have lasting consequences on how individuals integrate factual evidence in interpersonal communication.

neuroscience↗

bioRxiv2019

Electrocorticographic dissociation of alpha and beta rhythmic activity in the human sensorimotor system

This study uses electrocorticography in humans to assess how alpha- and beta-band rhythms modulate excitability of the sensorimotor cortex during movement selection, as indexed through a psychophysically-controlled movement imagery task. Both rhythms displayed effector-specific modulations, tracked spectral markers of action potentials in the local neuronal population, and showed spatially systematic phase relationships (traveling waves). Yet, alpha- and beta-band rhythms differed in their anatomical and functional properties, were weakly correlated, and traveled along opposite directions across the sensorimotor cortex. Increased alpha-band power in the somatosensory cortex ipsilateral to the selected arm was associated with spatially-unspecific inhibition. Decreased beta-band power over contralateral motor cortex was associated with a focal shift from relative inhibition to excitation. These observations indicate the relevance of both inhibition and disinhibition mechanisms for precise spatiotemporal coordination of neuronal populations during movement selection. Those mechanisms are implemented through the substantially different neurophysiological properties of sensorimotor alpha- and beta-band rhythms.

neuroscience↗

bioRxiv2017

Integrated analysis of anatomical and electrophysiological human intracranial data

The exquisite spatiotemporal precision of human intracranial EEG recordings (iEEG) permits characterizing neural processing with a level of detail that is inaccessible to scalp-EEG, MEG, or fMRI. However, the same qualities that make iEEG an exceptionally powerful tool also present unique challenges. Until now, the fusion of anatomical data (MRI and CT images) with the electrophysiological data and its subsequent analysis has relied on technologically and conceptually challenging combinations of software. Here, we describe a comprehensive protocol that addresses the complexities associated with human iEEG, providing complete transparency and flexibility in the evolution of raw data into illustrative representations. The protocol is directly integrated with an open source toolbox for electrophysiological data analysis (FieldTrip). This allows iEEG researchers to build on a continuously growing body of scriptable and reproducible analysis methods that, over the past decade, have been developed and employed by a large research community. We demonstrate the protocol for an example complex iEEG data set to provide an intuitive and rapid approach to dealing with both neuroanatomical information and large electrophysiological data sets. We explain how the protocol can be largely automated, taking under an hour to complete, and readily adjusted to iEEG data sets with other characteristics.

neuroscience↗