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Symposium Session 6 - Not Your Average Brain: Individual-Level fMRI as a Paradigm Shift for Cognitive Neuroscience

Monday, March 9, 2026, 10:00 am – 12:00 pm PDT, Salon D

Chairs: Andre Zamani¹, Jingnan Du²; ¹University of British Columbia, ²Harvard University
Presenters: Charles Lynch, Rodrigo M. Braga, Jingnan Du, Arielle Keller

For decades, cognitive neuroscience has largely relied on a group-level approach, collecting small amounts of fMRI data from many separate individuals and statistically averaging them to produce group-level effects. However, over the past decade, accumulating evidence suggests that averaging fMRI signal across individuals significantly misrepresents brain function by mixing signal across separate adjacent functional networks given the high inter-individual variability in network topography. To address this limitation, individual-level fMRI, also known as precision fMRI or precision functional mapping, has emerged as a transformative approach. It involves collecting extensive data across multiple sessions from a smaller number of individuals and analyzing each brain separately, enabling the detailed estimation of individual-level functional networks and their response properties. In the last few years, it has become clear that individual-level fMRI is not merely a methodological option, but rather, a major and potentially necessary advancement for cognitive neuroscience. This symposium demonstrates the critical advances of individual-level fMRI by featuring talks from several researchers leading groundbreaking programs of research on key emerging topics in the field, including: (i) repeating motifs of brain network topography in cortical and subcortical association regions, (ii) reliable forms of brain network variability across individuals, and (iii) linking variability in functional network shape and size to cognition, psychopathology, gene expression, and social factors. Join us as we explore this paradigm shift that is rapidly transforming cognitive neuroscience.

Presentations

Precision Functional Mapping and Dense Longitudinal fMRI Reveal Symptom-Linked Circuit Dynamics in Mood Disorders

Charles Lynch¹; ¹Weill Cornell Medicine

Mood disorders are defined by fluctuating symptoms and episodic mood state changes, yet most neuroimaging approaches rely on cross-sectional designs that are not equipped to capture within-person dynamics of brain–symptom relationships. In this presentation, I will describe how dense longitudinal sampling—serial fMRI assessments paired with weekly symptom tracking—combined with precision functional mapping (PFM) provides a powerful framework for uncovering individualized circuit mechanisms in depression and bipolar disorder. Using more than 120 multi-echo resting-state fMRI scans per individual, collected across 1.5 years from participants with major depressive disorder and bipolar disorder type II, we show that individualized network maps explain roughly twice as much variance in symptom fluctuations compared to group-average maps. These within-subject, n-of-1 analyses highlight how deviations from group-average functional architecture limit the variance explained in symptom fluctuations, largely because group maps mislocalize clinically relevant circuits, whereas PFM preserves individual network boundaries and better captures signals of interest. Together, this work demonstrates how dense sampling and individualized mapping can reveal novel insights into the temporal dynamics of brain–symptom coupling in mood disorders, advancing mechanistic models of mood state transitions and laying the groundwork for personalized neuromodulation interventions.

Shared Principles of Brain Network Organization Derived from Within-Individual fMRI

Rodrigo M. Braga¹; ¹Northwestern University

Because all brains are unique, group-averaging of fMRI data provides a distorted view of brain networks. These distortions can include the blurring together of distinct adjacent networks but also, paradoxically, the separation of regions that actually show strong connections within individuals. Here, I will summarize evidence in which the improved clarity of within-individual precision fMRI has revealed unifying organizational principles that link multiple large-scale brain networks. I will also argue that fine-scale anatomical differences which distinguish the networks, that are sometimes only appreciable in individualized maps, can help form hypotheses regarding how each network’s circuit properties support specialized cognitive functions. Finally, I will present a framework for identifying and navigating equivalent networks in different individuals, an endeavor complicated by the large inter-individual differences in network location, shape, and size. I argue that these identifying factors also hold important clues for understanding each network’s specialized role in cognition.

Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function

Jingnan Du¹; ¹Harvard University

The cerebral cortex is populated by specialized regions that are organized into networks. Using resting-state fMRI data from 15 intensively sampled participants (each scanned 8 or more times), we recently applied a multi-session hierarchical Bayesian model to delineate 15 distinct networks. Analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that linked to distant regions. Third-order networks possessed regions distributed widely throughout association cortex. Regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated across multiple cortical zones. We refer to these as supra-areal association megaclusters (SAAMs). We demonstrate these fine-grained spatial details are stable features of an individual’s brain, reproducible using only task-based functional connectivity. Further, we show that networks estimated from task-based functional connectivity can effectively predict functional specializations across multiple higher-order cognitive domains in independent task datasets; and that the same task data can simultaneously provide both within-individual network estimates and region-level functional response quantification. A complete set of atlases based for this 15-network model in both surface and volume-based formats are publicly available at https://freesurfer.net/fswiki/CorticalParcellation_DU15NET.

Person-Specific Patterns of Functional Brain Network Topography Reflect Childhood Environments, Gene Expression, and Cognitive Abilities in Youth

Arielle Keller¹; ¹University of Connecticut

Many cognitive abilities are supported by coordinated activity within and across large-scale functional brain networks. However, the size, shape, and spatial organization of these brain networks (“functional topography”) varies substantially across individuals. This poses a particular challenge for cognitive neuroimaging studies, which have historically relied on group-averaged brain atlases that obscure individual differences. Recent advances in precision functional mapping techniques now enable the definition of person-specific atlases of functional brain networks, including in youth during critical stages of cognitive neurodevelopment. In this talk, I will present recent work applying precision functional mapping in a large cohort of youth from the Adolescent Brain Cognitive Development (ABCD) Study (n=11,878). Using spatially-regularized non-negative matrix factorization, we delineate 17 large-scale functional networks that are uniquely tailored to each individual, allowing for investigation of personalized functional topography. Our findings reveal that individual differences in functional topography are robustly associated with various domains of cognitive functioning as well as affective psychiatric symptoms. These individualized network patterns exhibit sex differences aligned with cortical sex chromosome gene expression patterns and are closely tied to multidimensional features of childhood socioeconomic environments. Notably, association networks that support high-level cognitive and affective functions appear to be most variable across individuals and are most strongly linked with both genetic and environmental factors. Together, these results demonstrate how precision functional neuroimaging can offer a powerful lens to study person-specific trajectories of cognitive neurodevelopment. This person-centered approach holds particular promise for identifying novel, developmentally sensitive markers of cognitive functioning and mental well-being in youth.