Cohesive network reconfiguration accompanies extended training
| Autor: | Qawi K. Telesford, Nicholas F. Wymbs, Jean M. Vettel, Danielle S. Bassett, Scott T. Grafton, Arian Ashourvan |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Connectomics Theoretical computer science Computer science graph theory Neuropsychological Tests Brain mapping 03 medical and health sciences 0302 clinical medicine Neural Pathways medicine Humans Learning Radiology Nuclear Medicine and imaging connectomics Set (psychology) Research Articles Network model Brain Mapping Communication Neuronal Plasticity Radiological and Ultrasound Technology medicine.diagnostic_test business.industry dynamic networks Brain Control reconfiguration Graph theory functional magnetic resonance imaging Magnetic Resonance Imaging 030104 developmental biology Neurology Motor Skills Neurology (clinical) Anatomy Functional magnetic resonance imaging business Motor learning motor learning 030217 neurology & neurosurgery Research Article |
| Zdroj: | Human Brain Mapping |
| ISSN: | 1097-0193 1065-9471 |
| Popis: | Human behavior is supported by flexible neurophysiological processes that enable the fine‐scale manipulation of information across distributed neural circuits. Yet, approaches for understanding the dynamics of these circuit interactions have been limited. One promising avenue for quantifying and describing these dynamics lies in multilayer network models. Here, networks are composed of nodes (which represent brain regions) and time‐dependent edges (which represent statistical similarities in activity time series). We use this approach to examine functional connectivity measured by non‐invasive neuroimaging techniques. These multilayer network models facilitate the examination of changes in the pattern of statistical interactions between large‐scale brain regions that might facilitate behavior. In this study, we define and exercise two novel measures of network reconfiguration, and demonstrate their utility in neuroimaging data acquired as healthy adult human subjects learn a new motor skill. In particular, we identify putative functional modules in multilayer networks and characterize the degree to which nodes switch between modules. Next, we define cohesive switches, in which a set of nodes moves between modules together as a group, and we define disjoint switches, in which a single node moves between modules independently from other nodes. Together, these two concepts offer complementary yet distinct insights into the changes in functional connectivity that accompany motor learning. More generally, our work offers statistical tools that other researchers can use to better understand the reconfiguration patterns of functional connectivity over time. Hum Brain Mapp 38:4744–4759, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. |
| Databáze: | OpenAIRE |
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