Brain Networks

Connectivity-driven organization of infant, adolescent, and adult brains

The brain is organized into distinct, distributed intrinsic networks that can be characterized within an individual using resting state functional connectivity. These networks support information processing, and individualized networks predict individual differences in behavior, cognition, and psychopathology. My dissertation work focused on investigating network organization in newborns and adolescents (Molloy & Saygin, 2022; Molloy et al., 2023), and predicting task-based activation from network organization in adults (Molloy et al., 2024; Molloy & Osher, 2023). Currently, I am interested in the development of these networks over time, and how individual differences in developmental trajectory can predict behavior and are impacted by the environment (e.g., substance use, sleep) (Molloy et al., 2025; Molloy et al., 2026).

References

2026

Decreased sleep is linked longitudinally and directionally to alterations in the brain’s intrinsic functional architecture

M. Fiona Molloy, Aman Taxali, Mike Angstadt, Katherine Toda-Thorne, Katherine L. McCurry, Alexander Weigard, Omid Kardan, Camille Lehrmann, Joshua Vens, Cleanthis Michael, Mary M. Heitzeg, and Chandra Sripada

Developmental Cognitive Neuroscience, Apr 2026

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Previous cross-sectional studies demonstrated that reduced sleep is associated with widespread changes in the brain’s intrinsic functional architecture. The present study extends this work by clarifying links between sleep and the developing brain during adolescence both longitudinally (across two years) and directionally (does reduced sleep cause connectivity changes or are connectivity changes the cause of reduced sleep?). Our novel approach combines the Adolescent Brain Cognitive Development (ABCD) Study, a longitudinal observational study of 11,878 youth, and a second sample of 76 adult participants scanned after a typical night of sleep and after a sleep deprivation causal manipulation. First, in the ABCD dataset, we identified a robust and generalizable neurosignature of reduced sleep. Second, in an independent sample of ABCD participants, we demonstrate that greater reductions in sleep duration across two years are significantly related to greater expression of this neurosignature. Third, in the sleep deprivation dataset, we show that expression of the ABCD reduced sleep neurosignature is significantly increased within individuals following sleep deprivation, and that neurosignatures of reduced sleep from the two samples exhibit significant spatial correspondence. These results clarify links between sleep and the developing brain and provide novel evidence that changes in sleep produce characteristic brain functional connectivity changes across adolescence.

2025

Regional, but not brain-wide, graph theoretic measures are robustly and reproducibly linked to general cognitive ability

M Fiona Molloy, Aman Taxali, Mike Angstadt, Tristan Greathouse, Katherine Toda-Thorne, Katherine L McCurry, Alexander Weigard, Omid Kardan, Lily Burchell, Maria Dziubinski, Jason Choi, Melanie Vandersluis, Cleanthis Michael, Mary M Heitzeg, and Chandra Sripada

Cerebral Cortex, Apr 2025

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General cognitive ability (GCA), also called “general intelligence,” is thought to depend on network properties of the brain, which can be quantified through graph theoretic measures such as small worldness and module degree. An extensive set of studies examined links between GCA and graphical properties of resting state connectomes. However, these studies often involved small samples, applied just a few graph theory measures in each study, and yielded inconsistent results, making it challenging to identify the architectural underpinnings of GCA. Here, we address these limitations by systematically investigating univariate and multivariate relationships between GCA and 17 whole-brain and node-level graph theory measures in individuals from the Adolescent Brain Cognitive Development Study (n = 5937). We demonstrate that whole-brain graph theory measures, including small worldness and global efficiency, fail to exhibit meaningful relationships with GCA. In contrast, multiple node-level graphical measures, especially module degree (within-network connectivity), exhibit strong associations with GCA. We establish the robustness of these results by replicating them in a second large sample, the Human Connectome Project (n = 847), and across a variety of modeling choices. This study provides the most comprehensive and definitive account to date of complex interrelationships between GCA and graphical properties of the brain’s intrinsic functional architecture.

2024

Predicting high-level visual areas in the absence of task fMRI

M. Fiona Molloy, Zeynep M. Saygin, and David E. Osher

Scientific Reports, May 2024

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The ventral visual stream is organized into units, or functional regions of interest (fROIs), specialized for processing high-level visual categories. Task-based fMRI scans ("localizers") are typically used to identify each individual’s nuanced set of fROIs. The unique landscape of an individual’s functional activation may rely in large part on their specialized connectivity patterns; recent studies corroborate this by showing that connectivity can predict individual differences in neural responses. We focus on the ventral visual stream and ask: how well can an individual’s resting state functional connectivity localize their fROIs for face, body, scene, and object perception? And are the neural processors for any particular visual category better predicted by connectivity than others, suggesting a tighter mechanistic relationship between connectivity and function? We found, among 18 fROIs predicted from connectivity for each subject, all but one were selective for their preferred visual category. Defining an individual’s fROIs based on their connectivity patterns yielded regions that were more selective than regions identified from previous studies or atlases in nearly all cases. Overall, we found that in the absence of a domain-specific localizer task, a 10-min resting state scan can be reliably used for defining these fROIs.

2023

Effect of Extremely Preterm Birth on Adolescent Brain Network Organization

M. Fiona Molloy, Emily J. Yu, Whitney I. Mattson, Kristen R. Hoskinson, H. Gerry Taylor, David E. Osher, Eric E. Nelson, and Zeynep M. Saygin

Brain Connectivity, Sep 2023

Publisher: Mary Ann Liebert, Inc., publishers

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Introduction: Extremely preterm (EPT) birth, defined as birth at a gestational age (GA) \textless28 weeks, can have a lasting impact on cognition throughout the life span. Previous investigations reveal differences in brain structure and connectivity between infants born preterm and full-term (FT), but how does preterm birth impact the adolescent connectome? Methods: In this study, we investigate how EPT birth can alter broadscale network organization later in life by comparing resting-state functional magnetic resonance imaging connectome-based parcellations of the entire cortex in adolescents born EPT (N = 22) to age-matched adolescents born FT (GA ≥37 weeks, N = 28). We compare these parcellations to adult parcellations from previous studies and explore the relationship between an individual’s network organization and behavior. Results: Primary (occipital and sensorimotor) and frontoparietal networks were observed in both groups. However, there existed notable differences in the limbic and insular networks. Surprisingly, the connectivity profile of the limbic network of EPT adolescents was more adultlike than the same network in FT adolescents. Finally, we found a relationship between adolescents’ overall cognition score and their limbic network maturity. Discussion: Overall, preterm birth may contribute to the atypical development of broadscale network organization in adolescence and may partially explain the observed cognitive deficits.
A personalized cortical atlas for functional regions of interest

M. Fiona Molloy and David E. Osher

Journal of Neurophysiology, Nov 2023

Publisher: American Physiological Society

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2022

Individual variability in functional organization of the neonatal brain

M. Fiona Molloy and Zeynep M. Saygin

NeuroImage, Jun 2022

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The adult brain is organized into distinct functional networks, forming the basis of information processing and determining individual differences in behavior. Is this network organization genetically determined and present at birth? And what is the individual variability in this organization in neonates? Here, we use unsupervised learning to uncover intrinsic functional brain organization using resting-state connectivity from a large cohort of neonates (Developing Human Connectome Project). We identified a set of symmetric, hierarchical, and replicable networks: sensorimotor, visual, default mode, ventral attention, and high-level vision. We quantified individual variability across neonates, and found the most individual variability in the ventral attention networks. Crucially, the variability of these networks was not driven by SNR differences or differences from adult networks (Yeo et al., 2011). Finally, differential gene expression provided a potential explanation for the emergence of these distinct networks and identified potential genes of interest for future developmental and individual variability research. Overall, we found neonatal connectomes (even at the voxel-level) can reveal broad individual-specific information processing units. The presence of individual differences in neonates and the framework for personalized parcellations demonstrated here has the potential to improve prediction of behavior and future outcomes from neonatal and infant brain data.