Biology subjects

Esterman, M.

Publications and source records attributed to Esterman, M..

5 recordsLinked to original sources

bioRxiv2024

Generalizable Neural Models of Emotional Engagement and Disengagement

Emotional experiences are never static but continuously evolve in response to internal and external contexts. Little is known about how neural patterns change as a function of these experiences, particularly in response to complex, real-world stimuli. This study aimed to identify generalizable neural patterns as individuals collectively engage and disengage from emotions dynamically. To do so, we analyzed functional magnetic resonance imaging (fMRI) along with subjective emotional annotations from two independent studies as individuals watched negative and neutral movie clips. We used predictive modeling to test if a model trained to predict a group emotional signature response in one study generalizes to the other study and vice versa. Disengagement patterns generalized specifically across intense clips. They were supported by connections within and between the sensorimotor and salience networks, maybe reflecting the processing of feeling states as individuals regulate their emotions. Prediction success for the engagement signature was mixed, but primarily linked to connections within the visual and between the visual and dorsal attention networks, maybe supporting visual attention orienting as emotions intensify. This work offers potential pathways for identifying generalizable neural patterns contributing to future affective research and clinical applications aiming to better understand dynamic emotional responses to naturalistic stimuli.

neuroscience↗

bioRxiv2021

Generalizable prediction of stimulus-independent, task-unrelated thought from functional brain networks

Neural substrates of "mind wandering" have been widely reported, yet experiments have varied in their contexts and their definitions of this psychological phenomenon, limiting generalizability. We aimed to develop and test the generalizability, specificity, and clinical relevance of a functional brain network-based marker for a well-defined feature of mind wandering--stimulus-independent, task-unrelated thought (SITUT). Combining functional MRI (fMRI) with online experience sampling in healthy adults, we defined a connectome-wide model of inter-regional coupling--dominated by default-frontoparietal control subnetwork interactions--that predicted trial-by-trial SITUT fluctuations within novel individuals. Model predictions generalized in an independent sample of attention-deficit/hyperactivity disorder (ADHD) adults. In three additional resting-state fMRI studies (total n=1,115), including healthy and ADHD populations, we demonstrated further prediction of SITUT (at modest effect sizes) defined using multiple trait-level and in-scanner measures. Our findings suggest that SITUT is represented within a common pattern of brain network interactions across time scales, populations, and contexts.

neuroscience↗

bioRxiv2020

The missing role of gray matter in studying brain controllability

1Brain controllability properties are normally derived from the white matter fiber tracts in which the neural substrate of the actual energy consumption, namely the gray matter, has been widely ignored. Here, we study the relationship between gray matter volume of regions across the whole cortex and their respective control property derived from the structural architecture of the white matter fiber tracts. The data suggests that the ability of white fiber tracts to exhibit control at specific nodes not only depends on the connection strength of the structural connectome but additionally strongly depends on gray matter volume at the host nodes. Our data indicates that connectivity strength and gray matter volume interact with respect to the brains control properties, such that gray matter exerts the great impact in regions with high structural connectivity. Disentangling effects of the regional gray matter volume and connectivity strength, we found that frontal and sensory areas play crucial roles in controllability. Together these results suggest that structural and regional properties of the white matter and gray matter provide complementary information in studying the control properties of the intrinsic structural and functional architectural of the brain.

neuroscience↗

bioRxiv2020

Two dominant brain states reflect optimal and suboptimal attention

Attention is not constant but fluctuates from moment to moment. Previous studies dichotomized these fluctuations into optimal and suboptimal states based on behavioral performance and investigated the difference in brain activity between these states. Although these studies implicitly assume there are two states, this assumption is not guaranteed. Here, we reversed the logic of these previous studies and identified unique states of brain activity during a sustained attention task. We demonstrate a systematic relationship between dynamic brain activity patterns (brain states) and behavioral underpinnings of sustained attention by explaining behavior from two dominantly observed brain states. In four independent datasets, a brain state characterized by default mode network activity was behaviorally optimal and a brain state characterized by dorsal attention network activity was suboptimal. Thus, our study provides compelling evidence for behaviorally optimal and suboptimal attentional states from the sole viewpoint of brain activity. We further demonstrated how these brain states were impacted by motivation, mind wandering, and attention-deficit hyperactivity disorder. Within-subject level modulators (motivation and mind wandering) impacted the optimality of behavior in the suboptimal brain state. In contrast, between-subject level differences (ADHD vs healthy controls) impacted the optimal brain state character, namely its frequency.

neuroscience↗

bioRxiv2018

Anticorrelated inter-network electrophysiological activity varies dynamically with attentional performance and behavioral states

The default mode network (DMN) is thought to exhibit infraslow anticorrelated activity with dorsal attention (DAN) and salience (SN) networks across various behavioral states. To investigate the dynamics of activity across these networks on a finer timescale, we used human intracranial electroencephalography with simultaneous recordings within core nodes of the three networks. During attentional task performance, the three sites showed dissociable profiles of high-frequency broadband activity. Anticorrelated infraslow fluctuations of this activity were found across networks during task performance but also intermittently emerged during rest and sleep in concert with the expression of task-like network-level topographic patterns. Critically, on a finer timescale, DAN and SN activations preceded DMN deactivations by hundreds of milliseconds. Moreover, greater lagged, but not zero-lag, anticorrelation between DAN and DMN activity was associated with better attentional performance. These findings have implications for interpreting antagonistic network relationships and confirm the behavioral importance of time-lagged inter-network interactions.

neuroscience↗