TY - JOUR
T1 - Differential effect of first versus second concussive episodes on wavelet information quality of EEG
AU - Slobounov, Semyon
AU - Cao, Cheng
AU - Sebastianelli, Wayne
N1 - Funding Information:
This study was supported by NIH, NINDS Grant R01NS056227-01A2.
PY - 2009/5
Y1 - 2009/5
N2 - Objective: Recent reports have suggested that long-term residual brain dysfunctions from mild traumatic brain injury (MTBI) that are often overlooked by clinical criteria may be detected using advanced research methods. The aim of the present study was to examine the feasibility of EEG wavelet information quality measures (EEG-IQ) in monitoring alterations of brain functions as well as to determine the differential rate of recovery between the first and second concussive episodes. Methods: Student-athletes at high risk for MTBI (n = 265) were tested prior to concussive episodes as a baseline. From this subject pool, twenty one athletes who suffered from two concussive episodes within one athletic season and were tested on days 7, 14 and 21 post-first and second injuries using a within-subjects design. Specifically, EEG was recorded and processed using wavelet entropy (EEG-IQ) algorithm along with a battery of neuropsychological (NS) tests. Spatial distribution of EEG-IQ and its dynamics in conjunction with NS data were analyzed prior to and after MTBI. Results: No neuropsychological deficits were present in concussed subjects beyond 7 days post-injury after first and second concussions. However, EEG-IQ measures were significantly reduced primarily at temporal, parietal and the occipital regions (ROIs) after first and especially after second MTBI (p < 0.01) beyond 7 days post-injury. Rate of recovery of EEG-IQ measures was significantly slower after second MTBI compared to those after the first concussion (p < 0.01). Conclusions: EEG-IQ measures may reveal alterations in the brain of concussed individuals that are most often overlooked by current assessment tools. In this regard, EEG-IQ may potentially be a valuable tool for assessing and monitoring residual brain dysfunction in "asymptomatic" MTBI subjects. Significance: The results demonstrate the potential utility of EEG-IQ measures to classify concussed individuals at various stages of recovery.
AB - Objective: Recent reports have suggested that long-term residual brain dysfunctions from mild traumatic brain injury (MTBI) that are often overlooked by clinical criteria may be detected using advanced research methods. The aim of the present study was to examine the feasibility of EEG wavelet information quality measures (EEG-IQ) in monitoring alterations of brain functions as well as to determine the differential rate of recovery between the first and second concussive episodes. Methods: Student-athletes at high risk for MTBI (n = 265) were tested prior to concussive episodes as a baseline. From this subject pool, twenty one athletes who suffered from two concussive episodes within one athletic season and were tested on days 7, 14 and 21 post-first and second injuries using a within-subjects design. Specifically, EEG was recorded and processed using wavelet entropy (EEG-IQ) algorithm along with a battery of neuropsychological (NS) tests. Spatial distribution of EEG-IQ and its dynamics in conjunction with NS data were analyzed prior to and after MTBI. Results: No neuropsychological deficits were present in concussed subjects beyond 7 days post-injury after first and second concussions. However, EEG-IQ measures were significantly reduced primarily at temporal, parietal and the occipital regions (ROIs) after first and especially after second MTBI (p < 0.01) beyond 7 days post-injury. Rate of recovery of EEG-IQ measures was significantly slower after second MTBI compared to those after the first concussion (p < 0.01). Conclusions: EEG-IQ measures may reveal alterations in the brain of concussed individuals that are most often overlooked by current assessment tools. In this regard, EEG-IQ may potentially be a valuable tool for assessing and monitoring residual brain dysfunction in "asymptomatic" MTBI subjects. Significance: The results demonstrate the potential utility of EEG-IQ measures to classify concussed individuals at various stages of recovery.
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U2 - 10.1016/j.clinph.2009.03.009
DO - 10.1016/j.clinph.2009.03.009
M3 - Article
C2 - 19375981
AN - SCOPUS:67349244384
SN - 1388-2457
VL - 120
SP - 862
EP - 867
JO - Clinical Neurophysiology
JF - Clinical Neurophysiology
IS - 5
ER -