The intrarater and interrater reliability (I&IR) of EEG interpretation has significant implications for the value of EEG as a diagnostic tool. We measured both I&IR of EEG interpretation based on interpretation of complete EEGs into standard diagnostic categories and rater confidence in their interpretations, and investigated sources of variance in EEG interpretations. During two distinct time intervals six board-certified clinical neurophysiologists classified 300 EEGs into one or more of seven diagnostic categories, and assigned a subjective confidence to their interpretations. Each EEG was read by three readers. Each reader interpreted 150 unique studies, and 50 studies twice to generate intrarater data. A generalizability study assessed the contribution of subjects, readers, and the interaction between subjects and readers to interpretation variance. Five of the six readers had a median confidence of ≥ 99%, and the upper quartile of confidence values was 100% for all six readers. Intrarater Cohen’s kappa (κc) ranged from 0.33 to 0.73 with an aggregated value of 0.59. κc ranged from 0.29 to 0.62 for the 15 reader pairs, with an aggregated Fleiss kappa of 0.44 for interrater agreement. The κc were not significantly different across rater pairs (Chi-Square = 17.3, df=14, p = 0.24). Variance due to subjects (i.e. EEGs) was 65.3%, to readers was 3.9%, and to the interaction between readers and subjects was 30.8%. Experienced epileptologists have very high confidence in their EEG interpretations and low to moderate I&IR, a common paradox in clinical medicine. A necessary but insufficient condition to improve EEG interpretation accuracy is to increase intrarater and interrater reliability. This goal could be accomplished, for instance, with an automated on-line application integrated into a continuing medical education module that measures and reports EEG I&IR to individual users.

Measuring the diagnostic accuracy (DA) of an EEG device is unconventional and complicated by imperfect interrater reliability. We sought to compare the DA of a miniature, wireless, battery-powered EEG device (“microEEG”) to a reference EEG machine in emergency department (ED) patients with altered mental status (AMS). 225 ED patients with AMS underwent 3 EEGs. EEG1 (Nicolet Monitor, “reference”) and EEG2 (microEEG) were recorded simultaneously with EEG cup electrodes using a signal splitter. EEG3 was recorded with microEEG using an electrode cap, immediately before or after EEG1/EEG2. The official EEG1 interpretation was considered the gold standard (EEG1-GS). EEG1, 2 and 3 were de-identified and blindly interpreted by two independent readers. A generalized mixed linear model was used to estimate the sensitivity & specificity of these interpretations relative to EEG1-GS, and to compute a diagnostic odds ratio (DOR). 79% of EEG1-GS were abnormal. Neither the DOR nor κf representing interrater reliabilities differed significantly between EEG1, EEG2, and EEG3. Mean setup time was 27 minutes for EEG1/EEG2 and 12 minutes for EEG3. Mean electrode impedance of EEG3 recordings was 12.6 kΩ (SD 31.9 kΩ). DA of microEEG was comparable to that of the reference system and was not reduced when the EEG electrodes had high and unbalanced impedances. A common practice with many scientific instruments, measurement of EEG device DA provides an independent and quantitative assessment of device performance.

Traumatic brain injury (TBI) selectively damages white matter. White matter damage does not produce deficits in many behavioral tests used to analyze experimental TBI. Rats were impaired on an active place avoidance task following inactivation of one hippocampal injection of tetrodotoxin. The need for both hippocampi suggests that acquisition of the active place avoidance task may require interhippocampal communication. The controlled cortical impact model of TBI demyelinates midline white matter and impairs rats on the active place avoidance task. One white matter region that is demyelinated is the fimbria that contains hippocampal commissural fibers. We therefore tested whether demyelination of the fimbria produces deficits in active place avoidance. Lysophosphatidylcholine (LPC) was injected stereotaxically to produce a cycle of demyelination-remyelination of the fimbria. At 4 days, myelin loss was observed in the fimbria of LPC-, but not saline-injected rats. Fourteen days after injection, myelin content increased in LPC-, but not saline-injected rats. Three days after injection, both saline- and LPC-injected rats had similar performance on an open field and passive place avoidance task in which the rat avoided a stationary shock zone on a stationary arena. The following day, on the active place avoidance task, LPC-injected rats had a significantly higher number of shock zone entrances suggesting learning was impaired. At 14 days after injection, saline- and LPC-injected rats had similar performance on open field and passive place avoidance. On active place avoidance, however, saline- and LPC-injected rats had a similar number of total entrances suggesting that the impairment seen at 4 days was no longer present at 14 days. These data suggest that active place avoidance is highly sensitive to white matter injury.

Electroencephalography (EEG) has become increasingly valuable outside of its traditional use in neurology. EEG is now used for neuropsychiatric diagnosis, neurological evaluation of traumatic brain injury, neurotherapy, gaming, neurofeedback, mindfulness, and cognitive enhancement training. The trend to increase the number of EEG electrodes, the development of novel analytical methods, and the availability of large data sets has created a data analysis challenge to find the "signal of interest" that conveys the most information about ongoing cognitive effort. Accordingly, we compare three common types of neural synchrony measures that are applied to EEG-power analysis, phase locking, and phase-amplitude coupling to assess which analytical measure provides the best separation between EEG signals that were recorded, while healthy subjects performed eight cognitive tasks-Hopkins Verbal Learning Test and its delayed version, Stroop Test, Symbol Digit Modality Test, Controlled Oral Word Association Test, Trail Marking Test, Digit Span Test, and Benton Visual Retention Test. We find that of the three analytical methods, phase-amplitude coupling, specifically theta (4-7 Hz)-high gamma (70-90 Hz) obtained from frontal and parietal EEG electrodes provides both the largest separation between the EEG during cognitive tasks and also the highest classification accuracy between pairs of tasks. We also find that phase-locking analysis provides the most distinct clustering of tasks based on their utilization of long-term memory. Finally, we show that phase-amplitude coupling is the least sensitive to contamination by intense jaw-clenching muscle artifact.