Task-induced subjective fatigue and resting-state striatal connectivity following traumatic brain injury

AbstractFunctional magnetic resonance imaging (fMRI) has significant potential to evaluate changes in brain network activity after traumatic brain injury (TBI) and enable early prognosis of potential functional (e.g., motor, cognitive, behavior) deficits. In this study, resting-state and task-based fMRI (rs- and tb-fMRI) were utilized to examine network changes in a pediatric porcine TBI model that has increased predictive potential in the development of novel therapies. rs- and tb-fMRI were performed one day post-TBI in piglets. Activation maps were generated using group independent component analysis (ICA) and sparse dictionary learning (sDL). Activation maps were compared to pig reference functional connectivity atlases and evaluated using Pearson spatial correlation coefficients and mean ratios. Nonparametric permutation analyses were used to determine significantly different activation areas between the TBI and healthy control groups. Significantly lower Pearson values and mean ratios were observed in the visual, executive control, and sensorimotor networks for TBI piglets compared to controls. Significant differences were also observed within several specific individual anatomical structures within each network. In conclusion, both rs- and tb-fMRI demonstrate the ability to detect functional connectivity disruptions in a translational TBI piglet model, and these disruptions can be traced to specific affected anatomical structures.

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Longitudinal Resting State Functional Connectivity Predicts Clinical Outcome in Mild Traumatic Brain Injury

Journal of Neurotrauma ◽

10.1089/neu.2018.5739 ◽

2019 ◽

Vol 36 (5) ◽

pp. 650-660 ◽

Cited By ~ 11

Author(s):

Radhika Madhavan ◽

Suresh E. Joel ◽

Rakesh Mullick ◽

Taylor Cogsil ◽

Sumit N. Niogi ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Functional Connectivity ◽

Clinical Outcome ◽

Mild Traumatic Brain Injury ◽

Resting State ◽

Resting State Functional Connectivity

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Functional Wavelet Connectivity in Resting State Reflects Consciousness Recovery in Patients with Severe Traumatic Brain Injury

Human Physiology ◽

10.1134/s0362119721020146 ◽

2021 ◽

Vol 47 (2) ◽

pp. 128-136

Author(s):

A. S. Zigmantovich ◽

L. B. Oknina ◽

M. M. Kopachka ◽

E. L. Masherow ◽

E. V. Alexandrova

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Severe Traumatic Brain Injury ◽

Resting State

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Effects of mild traumatic brain injury and post-traumatic stress disorder on resting-state default mode network connectivity

Brain Research ◽

10.1016/j.brainres.2019.01.015 ◽

2019 ◽

Vol 1711 ◽

pp. 77-82 ◽

Cited By ~ 4

Author(s):

Priya Santhanam ◽

Steffanie H. Wilson ◽

Terrence R. Oakes ◽

Lindell K. Weaver

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Mild Traumatic Brain Injury ◽

Post Traumatic Stress Disorder ◽

Traumatic Stress ◽

Resting State ◽

Stress Disorder ◽

Network Connectivity ◽

Post Traumatic Stress ◽

Post Traumatic

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Resting-state functional connectivity as a biomarker of aggression in mild traumatic brain injury

Neuroreport ◽

10.1097/wnr.0000000000001127 ◽

2018 ◽

Vol 29 (16) ◽

pp. 1413-1417 ◽

Cited By ~ 1

Author(s):

Natalie S. Dailey ◽

Ryan Smith ◽

John R. Vanuk ◽

Adam C. Raikes ◽

William D.S. Killgore

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Functional Connectivity ◽

Mild Traumatic Brain Injury ◽

Resting State ◽

Resting State Functional Connectivity

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Resting State Functional Connectivity is Directly Related to Clinical Presentation of Mild Traumatic Brain Injury

Neurology ◽

10.1212/01.wnl.0000581088.06830.74 ◽

2019 ◽

Vol 93 (14 Supplement 1) ◽

pp. S26.2-S27

Author(s):

Teena Shetty ◽

Joseph Nguyen ◽

Esther Kim ◽

George Skulikidis ◽

Matthew Garvey ◽

...

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

White Matter ◽

Functional Connectivity ◽

Mild Traumatic Brain Injury ◽

Resting State ◽

Symptom Severity ◽

Grey Matter ◽

Clinical Presentation ◽

Severity Scores

ObjectiveTo determine the utility of fractional amplitude of low frequency fluctuations (fALFF) during resting state fMRI (rs-fMRI) as an advanced neuroimaging biomarker for Mild Traumatic Brain Injury (mTBI).BackgroundmTBI is defined by a constellation of functional rather than structural deficits. As a measure of functional connectivity, fALFF has been implicated in long-term outcomes post-mTBI. It is unclear however, how longitudinal changes in fALFF may relate to the clinical presentation of mTBI.Design/Methods111 patients and 32 controls (15–50 years old) were enrolled acutely after mTBI and followed with up to 4 standardized serial assessments. Patients were enrolled at either Encounter 1 (E1), within 72 hours, or Encounter 2 (E2), 5–10 days post-injury, and returned for Encounter 3 (E3) at 15–29 days and Encounter 4 (E4) at 83–97 days. Each encounter included a clinical exam, neuropsychological assessment, as well as rs-fMRI imaging. fALFF was analyzed independently in 14 functional networks and, in grey and white matter as a function of symptom severity. Symptom severity scores (SSS) ranged from 0–132 as defined by the SCAT2 symptom evaluation.ResultsIn mTBI patients, fALFF scores across 5 functional brain networks (language, sensorimotor, visuospatial, higher-order visual, and posterior salience) differed between mTBI patients with low versus high SSS (SSS <5 and >30, respectively). Overall, greater SSS were indexed by reduced connectivity (p < 0.03, Bonferroni corrected). Further analysis also identified corresponding network pairs which were most predictive of increased SSS. White matter fALFF was not correlated with symptom severity, however, decreased grey matter fALFF was significantly correlated with greater SSS (r = −0.25, p = 0.002).ConclusionsGrey matter fALFF was correlated with mTBI symptom burden suggesting that patterns of neural connectivity relate directly to the clinical presentation of mTBI. Furthermore, differences in functional network connectivity as a function of SSS may reflect which networks are implicated in recovery of mTBI.

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Strategy-based reasoning training modulates cortical thickness and resting-state functional connectivity in adults with chronic traumatic brain injury

Brain and Behavior ◽

10.1002/brb3.687 ◽

2017 ◽

Vol 7 (5) ◽

pp. e00687 ◽

Cited By ~ 15

Author(s):

Kihwan Han ◽

Rebecca A. Davis ◽

Sandra B. Chapman ◽

Daniel C. Krawczyk

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Functional Connectivity ◽

Cortical Thickness ◽

Resting State ◽

Resting State Functional Connectivity

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Cortical Function in Acute Severe Traumatic Brain Injury and at Recovery: A Longitudinal fMRI Case Study

Brain Sciences ◽

10.3390/brainsci10090604 ◽

2020 ◽

Vol 10 (9) ◽

pp. 604

Author(s):

Karnig Kazazian ◽

Loretta Norton ◽

Teneille E. Gofton ◽

Derek Debicki ◽

Adrian M. Owen

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Speech Perception ◽

Severe Traumatic Brain Injury ◽

Resting State ◽

Cortical Function ◽

Sound Perception ◽

Command Following ◽

Resting State Connectivity ◽

Recovery Of Consciousness

Differences in the functional integrity of the brain from acute severe brain injury to subsequent recovery of consciousness have not been well documented. Functional magnetic resonance imaging (fMRI) may elucidate this issue as it allows for the objective measurement of brain function both at rest and in response to stimuli. Here, we report the cortical function of a patient with a severe traumatic brain injury (TBI) in a critically ill state and at subsequent functional recovery 9-months post injury. A series of fMRI paradigms were employed to assess sound and speech perception, command following, and resting state connectivity. The patient retained sound perception and speech perception acutely, as indexed by his fMRI responses. Command following was absent acutely, but was present at recovery. Increases in functional connectivity across multiple resting state networks were observed at recovery. We demonstrate the clinical utility of fMRI in assessing cortical function in a patient with severe TBI. We suggest that hallmarks of the recovery of consciousness are associated with neural activity to higher-order cognitive tasks and increased resting state connectivity.

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Cognitive Training Reorganizes Network Modularity in Traumatic Brain Injury

Neurorehabilitation and Neural Repair ◽

10.1177/1545968319868710 ◽

2019 ◽

Vol 34 (1) ◽

pp. 26-38 ◽

Cited By ~ 5

Author(s):

Kihwan Han ◽

Sandra B. Chapman ◽

Daniel C. Krawczyk

Keyword(s):

Traumatic Brain Injury ◽

Brain Injury ◽

Cognitive Training ◽

Resting State ◽

Training Group ◽

Whole Brain ◽

Local Efficiency ◽

Graph Theoretic ◽

Knowledge Based ◽

Global Efficiency

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.

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