Literature DB >> 22159059

Quantitative and qualitative analysis of ambulatory electroencephalography during mild traumatic brain injury.

Jeremy J Moeller1, Bin Tu, Carl W Bazil.   

Abstract

OBJECTIVES: To characterize the neurophysiological changes in a patient with mild traumatic brain injury (mTBI) and to compare these changes with a small cohort of patients with neurocardiogenic syncope, an analogous cause of transient neurological dysfunction.
DESIGN: Case report and quantitative analysis of a small electroencephalography (EEG) cohort.
SETTING: University-affiliated teaching hospital. PATIENTS: A 64-year-old man with mTBI recorded on ambulatory EEG. The comparison group was 4 patients with spontaneous neurocardiogenic syncope during continuous video EEG recording. INTERVENTION: Quantitative and qualitative analysis of EEG. MAIN OUTCOME MEASURES: Changes in quantitative EEG measurements between the patient with mTBI and the comparison group.
RESULTS: In the patient with mTBI, there was an abrupt decrease in high-frequency (beta) power and alpha-delta ratio immediately after the injury and a corresponding increase in lower-frequency (alpha, theta, delta) power. The change in beta power resolved within 5 minutes of the injury, but the increases in low-frequency power persisted up to 20 minutes after the injury before resolving. Similar but smaller changes were seen in the patients with syncope, but these changes resolved within 5 minutes, with no intermediate or long-term changes.
CONCLUSIONS: The quantitative EEG changes in mTBI are initially similar to those in syncope, suggesting acute transient cortical dysfunction. However, there are longer-lasting increases in low-frequency power during mTBI, suggesting ongoing disruption of cortical-thalamic circuits.

Entities:  

Mesh:

Year:  2011        PMID: 22159059     DOI: 10.1001/archneurol.2011.1080

Source DB:  PubMed          Journal:  Arch Neurol        ISSN: 0003-9942


  7 in total

Review 1.  Sport-related concussions: a review of epidemiology, challenges in diagnosis, and potential risk factors.

Authors:  James M Noble; Dale C Hesdorffer
Journal:  Neuropsychol Rev       Date:  2013-11-17       Impact factor: 7.444

Review 2.  Electroencephalography and quantitative electroencephalography in mild traumatic brain injury.

Authors:  Zulfi Haneef; Harvey S Levin; James D Frost; Eli M Mizrahi
Journal:  J Neurotrauma       Date:  2013-04-15       Impact factor: 5.269

3.  Frequency-Dependent Changes in Resting State Electroencephalogram Functional Networks after Traumatic Brain Injury in Piglets.

Authors:  Lorre S Atlan; Susan S Margulies
Journal:  J Neurotrauma       Date:  2019-05-23       Impact factor: 5.269

4.  Callosal dysfunction explains injury sequelae in a computational network model of axonal injury.

Authors:  Jianxia Cui; Laurel J Ng; Vladislav Volman
Journal:  J Neurophysiol       Date:  2016-09-28       Impact factor: 2.714

Review 5.  Traumatic brain injury detection using electrophysiological methods.

Authors:  Paul E Rapp; David O Keyser; Alfonso Albano; Rene Hernandez; Douglas B Gibson; Robert A Zambon; W David Hairston; John D Hughes; Andrew Krystal; Andrew S Nichols
Journal:  Front Hum Neurosci       Date:  2015-02-04       Impact factor: 3.169

6.  Prognostic evaluation of child patients with infectious encephalitis through AEEG and REEG.

Authors:  Yujun Lin; Ge Zhang; Yan Wang; Jianjun Chai; Xiufang Jiang; Cong Li; Hui Xu
Journal:  Exp Ther Med       Date:  2018-10-19       Impact factor: 2.447

7.  HIRREM™: a noninvasive, allostatic methodology for relaxation and auto-calibration of neural oscillations.

Authors:  Lee Gerdes; Peter Gerdes; Sung W Lee; Charles H Tegeler
Journal:  Brain Behav       Date:  2013-01-14       Impact factor: 2.708

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.