Literature DB >> 31434528

Cognitive Training Reorganizes Network Modularity in Traumatic Brain Injury.

Kihwan Han1, Sandra B Chapman1, Daniel C Krawczyk1,2.   

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 < .05; qFDR < 0.05). Brain behavior analysis revealed that the participation coefficient and global efficiency within the strategy-based cognitive training group correlated with trail-making scores in the context of training (Pnodal < .05; qFDR < 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.

Entities:  

Keywords:  brain network; functional connectivity; graph theory; intervention; neuroplasticity; resting-state

Year:  2019        PMID: 31434528     DOI: 10.1177/1545968319868710

Source DB:  PubMed          Journal:  Neurorehabil Neural Repair        ISSN: 1545-9683            Impact factor:   3.919


  9 in total

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2.  Brain dysfunction underlying prolonged post-concussive syndrome: A systematic review.

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3.  Efficacy of Cognitive Training When Translated From the Laboratory to the Real World.

Authors:  Leanne R Young; Jennifer E Zientz; Jeffrey S Spence; Daniel C Krawczyk; Sandra B Chapman
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4.  Cognitive Training for Mild Traumatic Brain Injury and Posttraumatic Stress Disorder.

Authors:  Kristin W Samuelson; Krista Engle; Linda Abadjian; Joshua Jordan; Alisa Bartel; Margaret Talbot; Tyler Powers; Lori Bryan; Charles Benight
Journal:  Front Neurol       Date:  2020-11-26       Impact factor: 4.003

5.  Eight-week multi-domain cognitive training does not impact large-scale resting-state brain networks in Parkinson's disease.

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6.  The Effect of Repetitive Transcranial Magnetic Stimulation (rTMS) on Cognition in Patients With Traumatic Brain Injury: A Protocol for a Randomized Controlled Trial.

Authors:  Han Zhang; Yu Zhao; Yun Qu; Yunyun Huang; Zhu Chen; Hong Lan; Yi Peng; Hongying Ren
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7.  Connectomic assessment of injury burden and longitudinal structural network alterations in moderate-to-severe traumatic brain injury.

Authors:  Yusuf Osmanlıoğlu; Drew Parker; Jacob A Alappatt; James J Gugger; Ramon R Diaz-Arrastia; John Whyte; Junghoon J Kim; Ragini Verma
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Review 8.  Prospective memory impairment in neurological disorders: implications and management.

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9.  Low-Frequency Repetitive Transcranial Magnetic Stimulation Restores Dynamic Functional Connectivity in Subcortical Stroke.

Authors:  Yin Qin; Xiaoying Liu; Xiaoping Guo; Minhua Liu; Hui Li; Shangwen Xu
Journal:  Front Neurol       Date:  2021-12-07       Impact factor: 4.003

  9 in total

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