Literature DB >> 27238074

Distinction in EEG slow oscillations between chronic mild traumatic brain injury and PTSD.

Laura M Franke1, William C Walker2, Kathy W Hoke3, Joanna R Wares4.   

Abstract

Spectral information from resting state EEG is altered in acute mild traumatic brain injury (mTBI) and in disorders of consciousness, but there is disagreement about whether mTBI can elicit long term changes in the spectral profile. Even when identified, any long-term changes attributed to TBI can be confounded by psychiatric comorbidities such as PTSD, particularly for combat-related mTBI where postdeployment distress is commonplace. To address this question, we measured spectral power during the resting state in a large sample of service members and Veterans varying in mTBI history and active PTSD diagnosis but matched for having had combat blast exposure. We found that PTSD was associated with decreases in low frequency power, especially in the right temporoparietal region, while conversely, blast-related mTBI was associated with increases in low frequency power, especially in prefrontal and right temporal areas. Results support the idea that long-term neurophysiological effects of mTBI share some features with states of reduced arousal and cognitive dysfunction, suggesting a role for EEG in tracking the trajectory of recovery and persisting vulnerabilities to injury. Additionally, results suggest that EEG power reflects distinct pathophysiologies for current PTSD and chronic mTBI.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Electroencephalography; Mild traumatic brain injury; PTSD; Resting state

Mesh:

Year:  2016        PMID: 27238074     DOI: 10.1016/j.ijpsycho.2016.05.010

Source DB:  PubMed          Journal:  Int J Psychophysiol        ISSN: 0167-8760            Impact factor:   2.997


  8 in total

Review 1.  Supplements, nutrition, and alternative therapies for the treatment of traumatic brain injury.

Authors:  Brandon P Lucke-Wold; Aric F Logsdon; Linda Nguyen; Ahmed Eltanahay; Ryan C Turner; Patrick Bonasso; Chelsea Knotts; Adam Moeck; Joseph C Maroon; Julian E Bailes; Charles L Rosen
Journal:  Nutr Neurosci       Date:  2016-10-05       Impact factor: 4.994

2.  Enhanced Performance by Interpretable Low-Frequency Electroencephalogram Oscillations in the Machine Learning-Based Diagnosis of Post-traumatic Stress Disorder.

Authors:  Miseon Shim; Chang-Hwan Im; Seung-Hwan Lee; Han-Jeong Hwang
Journal:  Front Neuroinform       Date:  2022-04-26       Impact factor: 3.739

3.  Evaluating the Contribution of EEG Power Profiles to Characterize and Discriminate Posttraumatic Stress Symptom Factors in a Combat-Exposed Population.

Authors:  Christina M Sheerin; Laura M Franke; Steven H Aggen; Ananda B Amstadter; William C Walker
Journal:  Clin EEG Neurosci       Date:  2018-04-03       Impact factor: 1.843

4.  Impaired functional cortical networks in the theta frequency band of patients with post-traumatic stress disorder during auditory-cognitive processing.

Authors:  Miseon Shim; Han-Jeong Hwang; Seung-Hwan Lee
Journal:  Front Psychiatry       Date:  2022-08-11       Impact factor: 5.435

Review 5.  Mind the gap: State-of-the-art technologies and applications for EEG-based brain-computer interfaces.

Authors:  Roberto Portillo-Lara; Bogachan Tahirbegi; Christopher A R Chapman; Josef A Goding; Rylie A Green
Journal:  APL Bioeng       Date:  2021-07-20

Review 6.  Neuroimaging of deployment-associated traumatic brain injury (TBI) with a focus on mild TBI (mTBI) since 2009.

Authors:  David H Salat; Meghan E Robinson; Danielle R Miller; Dustin C Clark; Regina E McGlinchey
Journal:  Brain Inj       Date:  2017       Impact factor: 2.167

7.  Longitudinal Functional Assessment of Brain Injury Induced by High-Intensity Ultrasound Pulse Sequences.

Authors:  Meijun Ye; Krystyna Solarana; Harmain Rafi; Shyama Patel; Marjan Nabili; Yunbo Liu; Stanley Huang; Jonathan A N Fisher; Victor Krauthamer; Matthew Myers; Cristin Welle
Journal:  Sci Rep       Date:  2019-10-29       Impact factor: 4.379

8.  Evaluating Performance of EEG Data-Driven Machine Learning for Traumatic Brain Injury Classification.

Authors:  Nicolas Vivaldi; Michael Caiola; Krystyna Solarana; Meijun Ye
Journal:  IEEE Trans Biomed Eng       Date:  2021-10-19       Impact factor: 4.756

  8 in total

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