Task-Based Core-Periphery Organization of Human Brain Dynamics

By D. Bassett, Nicholas F. Wymbs, M. P. Rombach, M. A. Porter, Peter J. Mucha, Scott T. Grafton. PLoS Comput. Biol., 2012

362 citations recorded by the source corpus.

As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated activity across a large set of brain regions. Our goal is to identify properties that enable robust learning of a motor skill. We measure brain activity during motor sequencing and characterize network properties based on coherent activity between brain regions. Using recently developed algorithms to detect time-evolving communities, we find that the complex reconfiguration patterns of the brain's putative functional modules that control learning can be described parsimoniously by the combined presence of a relatively stiff temporal core that is composed primarily of sensorimotor and visual regions whose connectivity changes little in time and a flexible temporal periphery that is composed primarily of multimodal association regions whose connectivity changes frequently. The separation between temporal core and periphery changes over the course of training and, importantly, is a good predictor of individual differences in learning success. The core of dynamically stiff regions exhibits dense connectivity, which is consistent with notions of core-periphery organization established previously in social networks. Our results demonstrate that core-periphery organization provides an insightful way to understand how putative functional modules are linked. This, in turn, enables the prediction of fundamental human capacities, including the production of complex goal-directed behavior.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/38bc733a168d3cab72fd08e227b0ff044e0e3282

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Citations in the corpus

Criticality in the brain: A synthesis of neurobiology, models and cognition. (2017, background): “The constellation of densely connected hub regions – the rich club – appear to support a slow, stable dynamic “core” whereas peripheral sensory regions introduce (rapid) stimuli-related variability in the system (Bassett et al., 2013; Gollo et al., 2015; Hasson et al., 2015).”
Two’s company, three (or more) is a simplex (2016, background): “( c) Thresholded coherence between the activity patterns of motor regions and visual regions in human fMRI data during performance of a motor-visual task (Bassett et al, 2013).”
Cognitive Network Neuroscience (2015, methodology): “Core– periphery organization could play a role in conferring robustness to the brain’s structural core (van den Heuvel & Sporns, 2011) and in enabling a balance between stability and adaptivity in brain dynamics (Bassett et al., 2013).”
Dynamic reconfiguration of frontal brain networks during executive cognition in humans (2015, background): “These highly stable modules also display relatively low flexibility across both n-back task conditions (Supporting Information), suggesting that they form a stable task-based core that supports higher order cognitive functions (40).”
Multilayer networks (2013, background): “Optimization of multislice modularity has been used in multislice representations of temporal networks to study phenomena such as political-party reorganization [237, 238], the dynamics of behavioral [362] and functional brain networks [30, 32], and the qualitative behavior of time-series output of ”
Small-World Brain Networks Revisited (2016, methodology): “There is much important recent work on topological properties like degree distribution and hubness [48], modularity [49–55], core/periphery organisation [56–58], controllability [59–61] and navigability [62] that are not simply related to small-worldness.”
The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition (2016, background): “Two recent motor learning studies focused on the contrast between stable, task-relevant core networks and flexible, peripheral networks (Bassett et al., 2013, 2015).”
Modern temporal network theory: a colloquium (2015, background): “Even though fMRI has a temporal resolution of the shortest time scale of neuronal activities, it has proven fruitful to study as a temporal network [20,21,170].”