Project Summary
Large-scale networks of the human brain can be measured non-invasively using functional Magnetic Resonance
Imaging (fMRI). While most previous work has focused on group descriptions of functional networks, recent
findings suggest that the study of highly-sampled single participants can reveal novel aspects of brain
organization specific to an individual. Here, we focus on atypical locations where an individual’s functional
networks do not match the group, which we call network variants. Preliminary data demonstrates that network
variants are present across all individuals, but differ in location, number, and network assignment. Variants are
most often associated with systems of the brain linked to goal-directed “controlled” processing. This observation
is intriguing, given that individual differences in control functions are known to be large and heritable, and in
extreme cases can be central contributions to pathology in disorders such as schizophrenia. Based on these
preliminary findings, we develop a model, wherein we suggest that stable factors (e.g., genetics, long-term
experience) reprioritize the functions of cortical areas, leading to the creation of network variants, altered task
activations, and behavior. Our goal is to test this model by examining the sources and consequences of variants.
Given that variants are most associated with regions related to controlled tasks, we focus our tests on control-
related activations and behavior. We will test the following hypotheses: (Aim 1) variants represent stable,
heritable, endophenotypes for individual differences in brain organization, (Aim 2) variants relate to individual
differences in brain activations in control tasks, and (Aim 3) variants relate to individual differences in behavior
in control tasks. In Aim 1 we propose addressing the trait-like nature of variants by measuring variant stability
across states, and the similarity of variant patterns across unrelated individuals, mono-, and dizygotic twins. In
Aim 2, we propose using a precision fMRI approach to measure variant activations across a range of control-
related task contexts. Finally, in Aim 3 we propose examining whether variants are related to differences in
control-related behavior. This proposal is innovative: it adopts cutting-edge methods for reliably characterizing
networks in single individuals to study atypical components of brain networks (rather than group descriptions)
and provides a new window into possible mechanisms underlying individual differences in brain organization,
activations, and behavior. This proposal will impact (1) basic science, by expanding our understanding of
individual variability in brain networks and their relationship to brain function and behavior, and (2) translational
research, by laying groundwork for the study of extreme forms of individual differences in control found in
psychopathology, potentially with future utility in personalized medicine. Thus, this proposal addresses RDoC
goals by investigating (1) individual differences at multiple levels (brain organization, physiology, and behavior),
(2) genetic and environmental sources for individual differences, and (3) potential biomarkers of dimensional
individual differences linked to psychopathology.
