Biology subjects

Feusner, J. D.

Publications and source records attributed to Feusner, J. D..

6 recordsLinked to original sources

bioRxiv2026

Disrupted Higher-Order Topology in OCD Brain Networks Revealed by Hodge Laplacian - an ENIGMA Study

Brain disorders are increasingly understood as disorders of distributed brain circuits, yet functional connectivity (FC), the dominant framework for mapping them, treats the brain as a collection of pairwise relationships between regions and cannot represent pathology distributed across coordinated sets of connections. We introduce a Hodge-Laplacian topological framework that localizes higher-order "loop" (1-cycle) organization within functional connectome, maps each loop to specific edges and networks, and yields a subject-level measure of loop expression. Applied to resting-state fMRI from the ENIGMA-OCD consortium (1,024 patients and 1,028 controls across 28 sites), the framework identified 93 loop-level abnormalities in obsessive-compulsive disorder (OCD), concentrated in frontoparietal and somatomotor systems. The edges forming these loops largely showed no significant differences between groups, indicating that the abnormalities were invisible to conventional FC analysis. The frontoparietal and somatomotor loop clusters recurred across the clinical subgroups, suggesting convergence on a shared higher-order phenotype. Robustness analyses showed the loop signal reflected higher-order organization rather than an artifact of individual edges, the network backbone, or any single site. These results indicate that coordinated, multi-edge pathology exists and can be localized even when pairwise analyses fail to detect it, positioning higher-order topology as a generalizable axis for mapping circuit pathology across psychiatric and neurological disorders.

neuroscience↗

bioRxiv2025

Model-based and model-free valuation signals in the human brain vary markedly in their relationship to individual differences in behavioral control

Human action selection under reinforcement is thought to rely on two distinct strategies: model-free and model-based reinforcement learning. While behavior in sequential decision-making tasks often reflects a mixture of both, the neural basis of individual differences in their expression remains unclear. To investigate this, we conducted a large-scale fMRI study with 179 participants performing a variant of the two-step task. Using both cluster-defined subgroups and computational parameter estimates, we found that the ventromedial prefrontal cortex encodes model-based and model-free value signals differently depending on individual strategy use. Model-based value signals were strongly linked to the degree of model-based behavioral reliance, whereas model-free signals appeared regardless of model-free behavioral influence. Leveraging the large sample, we found individuals lacking both model-based behavior and model-based neural signals exhibited impaired state prediction errors, suggesting a difficulty in building or updating their internal model of the environment. These findings indicate that model-free signals are ubiquitous across individuals, even in those not behaviorally relying on model-free strategies, while model-based representations appear only in those individuals utilizing such a strategy at the behavioral level, the absence of which may depend in part on underlying difficulties in forming accurate model-based predictions.

neuroscience↗

bioRxiv2025

Functional Brain Mapping of Body Size Estimation Using a 3D Avatar

BackgroundBody size estimation--the ability to judge the size and shape of ones own body-- is a key perceptual component of body image. However, its neural basis, and the basis for inter-individual differences in accuracy, remain poorly understood, partly due to limitations in existing assessment tools. MethodsWe developed Somatomap 3D, an interactive fMRI-compatible task allowing participants to manipulate a rotatable 3D avatar by adjusting the size and shape of 26 individual body parts to match their perceived body. Twenty-eight healthy male and female adults completed the task during fMRI. Brain activity in a priori regions of interest from previous studies of body processing was modeled using a general linear model incorporating event-specific parameters and parametric modulators related to task performance. Inter-individual differences in body size estimation accuracy were calculated using multidimensional scaling of body part estimation errors, and scores were correlated with BOLD signal eigenvariates from regions of interest. ResultsTask engagement was associated with significant activation in hypothesized body-selective and multisensory regions, including bilateral extrastriate body area, right fusiform body area, right superior parietal lobule, and bilateral premotor cortex. Multidimensional scaling identified a primary subdimension reflecting distortions in body part girths, which was significantly associated with neural responses in the superior parietal lobule. No other brain regions showed significant associations with inter-individual differences in estimation accuracy. ConclusionsThese results suggest that body size estimation engages a distributed network of visual, motor, and parietal regions. Among these, only the superior parietal lobule showed a significant association with inter-individual variation in body size estimation accuracy for body part girths, supporting its role as a candidate neural substrate for altered body representation in psychiatric conditions such as eating disorders and body dysmorphic disorder.

neuroscience↗

bioRxiv2024

Visual system structural and functional connections during face viewing in body dysmorphic disorder

BackgroundIndividuals with body dysmorphic disorder (BDD) perceive distortions in their appearance, which could be due to imbalances in global and local visual processing. The vertical occipital fasciculus connects dorsal and ventral visual stream regions, integrating global and local information, yet the role of this structural connection in BDD has not been explored. Here, we investigated the vertical occipital fasciculuss white matter microstructure in those with BDD and healthy controls and tested associations with psychometric measures and effective connectivity while viewing their face during fMRI. MethodsWe analyzed diffusion MRI and fMRI data in 17 unmedicated adults with BDD and 21 healthy controls. For diffusion MRI, bundle-specific analysis was performed, enabling quantitative estimation of neurite density and orientation dispersion of the vertical occipital fasciculus. For task fMRI, participants naturalistically viewed photos of their own face, from which we computed effective connectivity from dorsal to ventral visual regions. ResultsIn BDD, neurite density was negatively correlated with appearance dissatisfaction and negatively correlated with effective connectivity. Further, those with weaker effective connectivity while viewing their face had worse BDD symptoms and worse insight. In controls, no significant relationships were found between any of the measures. There were no significant group differences in neurite density or orientation dispersion. ConclusionThose with BDD with worse appearance dissatisfaction have a lower fraction of tissue having axons or dendrites along the vertical occipital fasciculus bundle, possibly reflecting impacting the degree of integration of global and local visual information between the dorsal and ventral visual streams. These results provide early insights into how the vertical occipital fasciculuss microstructure relates to the subjective experience of ones appearance, as well as the possibility of distinct functional-structural relationships in BDD.

neuroscience↗

bioRxiv2023

Stable, efficient, and typical dynamic functional connectivity patterns relate to higher general intelligence

General intelligence, referred to as g, is hypothesized to emerge from the capacity to dynamically and adaptively reorganize macroscale brain connectivity. Temporal reconfiguration can be assessed using dynamic functional connectivity (dFC), which captures the propensity of brain connectivity to transition between a recurring repertoire of distinct states. Conventional dFC metrics commonly focus on categorical state switching frequencies which do not fully assess individual variation in continuous connectivity reconfiguration. Here, we supplement frequency measures by quantifying within-state connectivity consistency, dissimilarity between connectivity across states, and conformity of individual connectivity to group-average state connectivity. We utilized resting-state fMRI data from the large-scale Human Connectome Project and applied data-driven multivariate Partial Least Squares Correlation to explore emergent associations between dynamic network properties and cognitive ability. Our findings reveal a positive association between g and the stable maintenance of states characterized by distinct connectivity between higher-order networks, efficient reconfiguration (i.e., minimal connectivity changes during transitions between similar states, large connectivity changes between dissimilar states), and ability to sustain connectivity close to group-average state connectivity. This hints at fundamental properties of brain-behavior organization, suggesting that general cognitive processing capacity is supported by the ability to efficiently reconfigure between stable and population-typical connectivity patterns. Impact StatementNovel evidence for an association between the stability, efficiency, and typicality of macro-scale dynamic functional connectivity patterns of the brain and higher general intelligence.

neuroscience↗

bioRxiv2020

Brain activation and connectivity in anorexia nervosa and body dysmorphic disorder when viewing bodies: relationships to clinical symptoms and perception of appearance

Anorexia nervosa (AN) and body dysmorphic disorder (BDD) are characterized by distorted perception of appearance, yet no studies have directly compared the neurobiology associated with body perception. We compared brain activation and connectivity in relevant networks when viewing images of others bodies and tested their relationships with clinical symptoms and subjective appearance evaluations. We acquired fMRI data from 64 unmedicated females (20 weight-restored AN, 23 BDD, 21 controls) during a matching task using photos of others bodies that were unaltered or spatial-frequency filtered. With general linear model and independent components analyses we compared brain activation and connectivity in visual, striatal, and parietal networks and performed univariate and partial least squares multivariate analyses to investigate relationships with clinical symptoms and appearance evaluations. BDD but not AN demonstrated hypoactivity in dorsal visual and parietal networks compared to controls. Yet, AN and BDD showed partially overlapping patterns of hyperconnectivity in the dorsal visual network and hypoconnectivity in parietal network compared with controls. Further, there were significant activity and connectivity differences between AN and BDD in both networks. In both groups, activity and/or connectivity were associated with symptom severity and appearance ratings of others bodies. AN and BDD demonstrate both distinct and partially overlapping aberrant neural phenotypes involved in body processing and visually encoding global features. Nevertheless, in each disorder, aberrant activity and connectivity show relationships to clinically relevant symptoms and subjective perception. Results have implications for understanding distinct and shared pathophysiology underlying perceptual distortions for appearance and may inform future novel treatment strategies.

neuroscience↗