Cognitive Training Reorganizes Network Modularity in Traumatic Brain Injury

Abstract

Background. Graph-theoretic approaches are increasingly popular for identifying the patterns of disrupted neural systems after traumatic brain injury (TBI). However, the patterns of neuroplasticity in brain organization after cognitive training in TBI are less well understood. Objective. We identified the patterns of training-induced neuroplasticity of the whole-brain network in TBI, using resting-state functional connectivity and graph theory. Methods. A total of 64 civilians and veterans with TBI were randomized into either a strategy-based cognitive training group (n = 33) or a knowledge-based training group (active control group; n = 31) for 8 weeks. The participants experienced mild to severe TBI without focal damage and persistent cognitive dysfunctions. A subset of participants complained of subclinical but residual psychiatric symptoms. We acquired their resting-state functional magnetic resonance imaging before training, immediately posttraining, and 3 months posttraining. From participants’ resting-state networks, we obtained the modularity, participation coefficient, within-module connectivity, global efficiency, and local efficiency over multiple network densities. We next performed longitudinal analyses on those measures corrected for multiple comparisons across network densities using false discovery rate (FDR). Results. Relative to the knowledge-based training group, the strategy-based cognitive training group had reduced modularity and increased participation coefficient, global efficiency, and local efficiency over time ( Pnodal FDR nodal FDR < 0.05). Conclusions. Cognitive training reorganized modular networks in TBI over the whole brain. Graph-theoretic approaches may be useful in identifying a potential brain-based marker of training efficacy in TBI.

Document Details

Document Type
Pub Defense Publication
Publication Date
Aug 22, 2019
Source ID
10.1177/1545968319868710

Entities

People

  • Daniel C Krawczyk
  • Kihwan Han
  • Sandra B. Chapman

Organizations

  • Meadows Foundation
  • United States Department of Defense
  • University of Texas at Austin
  • University of Texas at Dallas

Tags

Readers

  • Neural Network Machine Learning.
  • Neuroscience
  • Traumatic Brain Injury (TBI) and Cognitive Aging in the Guam and Border Populations Affected by Alzheimer's Disease and Tau-Associated Dementias.