Differential effect of first versus second concussive episodes on wavelet information quality of EEG.
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.


CONCLUSIONS
The results demonstrate the potential utility of EEG-IQ measures to classify concussed individuals at various stages of recovery.
Slobounov
Semyon
S
The Department of Kinesiology, The Pennsylvania State University, 268 Recreation Building, University Park, PA 16802, USA. sms18@psu.edu
Cao
Cheng
C
Sebastianelli
Wayne
W
D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001265:Athletic Injuries / Q000175:diagnosis* / Q000503:physiopathology*; D001921:Brain / Q000503:physiopathology*; D001924:Brain Concussion / Q000175:diagnosis* / Q000503:physiopathology*; D002540:Cerebral Cortex / Q000293:injuries / Q000503:physiopathology; D003937:Diagnosis, Differential; D004569:Electroencephalography / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology; D005260:Female; D006801:Humans; D008297:Male; D011237:Predictive Value of Tests; D020127:Recovery of Function / Q000502:physiology; D015203:Reproducibility of Results; D012720:Severity of Illness Index; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult