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Background: High-frequency EEG (HFE) as a potential predictor of alertness/drowsiness was first proposed by Kaplan and Loparo. Sampling EEG at 950 Hz, they established an HFE bandwidth of interest ranging from 100-475 Hz. We extend their work by applying discrete Fourier transform (DFT) of HFE signals sampled at 1000 Hz and partitioned into spectral bands along specific frequency ranges for the assessment of sleep-wake state transition, sleep, and active cognitive engagement., Methods: There were 13 volunteers (6 men, 7 women, 30 +/- 3 yr) who participated in a 40-h sleep-deprivation study, during which time they performed multiple cognitive tasks. EEG, in synchrony with other physiological signals, was collected at a sampling rate of 1000 Hz. EEG and task performance results from two volunteers are discussed in this preliminary analysis of the C3-C4 region data. Spectral components obtained from DFT are delineated into five main frequency bands: low, (LFB, 1-15 Hz); intermediate (IFB, 16-50 Hz); and 3 high frequency bands: HFB1 (51-100 Hz); HFB2 (101-200 Hz); and HFB3 (201-500 Hz) for analysis purposes., Results: LFB in the 1-15 Hz range at 0.40 spectrum proportion indicated declining alertness; LFB above 0.50 signals transition to sleep; and LFB at 0.70 indicates Stage 2/3 sleep. HFB3 in the 201-500 Hz range at 0.25 and above was a marker of cognitive function and/or capacity., Conclusions: HFE may provide a quantitative measure of cognitive function capacity. LFB may provide a measure for awake, asleep, or awake-sleep transition, and HFB3 an estimate of cognitive task engagement. HFE may be applied for electroencephalographic monitoring of cognitive performance.

Primary objective: To examine differences between thebaseline-referencedandnorm-referencedapproaches for determining decrements in Automated Neuropsychological Assessment Metrics Version 4 TBI-MIL (ANAM) performance following mild traumatic brain injury (mTBI). Research design: ANAM data were reviewed for 616 US Service members, with 528 of this sample having experienced an mTBI and 88 were controls. Methods and procedures: Post-injury change scores were calculated for each sub-test: (1) normative change score = in-theater score – normative mean and (2) baseline change score = in-theater score – pre-deployment baseline. Reliable change cut-scores were applied to the change and the resulting frequency distributions were compared using McNemar tests. Receiver operator curves (ROC) using both samples (i.e. mTBI and control) were calculated for the change scores for each approach to determine the discriminate ability of the ANAM. Main outcomes and results: There were no statistical differences,p< 0.05 (Bonferonni-Holm corrected), between the approaches. When the area under the curve for the ROCs were averaged across sub-tests, there were no significant differences between either thenorm-referenced(0.65) or baseline-referenced (0.66) approaches,p> 0.05. Conclusions: Overall, the findings suggest there is no clear advantage of using thebaseline-referencedapproach overnorm-referencedapproach. [ABSTRACT FROM AUTHOR]