Network Approaches to Understand Individual Differences in Brain Connectivity: Opportunities for Personality Neuroscience.

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TitleNetwork Approaches to Understand Individual Differences in Brain Connectivity: Opportunities for Personality Neuroscience.
Publication TypeJournal Article
Year of Publication2018
AuthorsTompson, S, Falk, EB, Vettel, JM, Bassett, DS
JournalPersonal Neurosci
Volume1
Date Published2018 Jul 05
ISSN2513-9886
Abstract

Over the past decade, advances in the interdisciplinary field of network science have provided a framework for understanding the intrinsic structure and function of human brain networks. A particularly fruitful area of this work has focused on patterns of functional connectivity derived from non-invasive neuroimaging techniques such as functional magnetic resonance imaging (fMRI). An important subset of these efforts has bridged the computational approaches of network science with the rich empirical data and biological hypotheses of neuroscience, and this research has begun to identify features of brain networks that explain individual differences in social, emotional, and cognitive functioning. The most common approach estimates connections assuming a single configuration of edges that is stable across the experimental session. In the literature, this is referred to as a static network approach, and researchers measure static brain networks while a subject is either at rest or performing a cognitively demanding task. Research on social and emotional functioning has primarily focused on linking static brain networks with individual differences, but recent advances have extended this work to examine temporal fluctuations in dynamic brain networks. Mounting evidence suggests that both the strength and flexibility of time-evolving brain networks influence individual differences in executive function, attention, working memory, and learning. In this review, we first examine the current evidence for brain networks involved in cognitive functioning. Then we review some preliminary evidence linking static network properties to individual differences in social and emotional functioning. We then discuss the applicability of emerging dynamic network methods for examining individual differences in social and emotional functioning. We close with an outline of important frontiers at the intersection between network science and neuroscience that will enhance our understanding of the neurobiological underpinnings of social behavior.

DOI10.1017/pen.2018.4
Alternate JournalPersonal Neurosci
PubMed ID30221246
PubMed Central IDPMC6133307
Grant ListR01 NS099348 / NS / NINDS NIH HHS / United States
R01 MH107235 / MH / NIMH NIH HHS / United States
R01 DC009209 / DC / NIDCD NIH HHS / United States
R21 MH106799 / MH / NIMH NIH HHS / United States
R01 HD086888 / HD / NICHD NIH HHS / United States
R01 MH109520 / MH / NIMH NIH HHS / United States
R01 MH107703 / MH / NIMH NIH HHS / United States