Electroencephalographic prediction of global and domain specific cognitive performance of clinically active Australian nurses

Objective: To investigate the relationship between EEG activity and the global and domain specific cognitive performance of healthy nurses, and determine the predictive capabilities of these relationships. Approach: Sixty-four nurses were recruited for the present study, and data from 61 were utilised in the present analysis. Global and domain specific cognitive performance of each participant was assessed psychometrically using the Mini-mental state exam and the Cognistat, and a 32-lead monopolar EEG was recorded during a resting baseline phase and an active phase in which participants completed the Stroop test. Main results: Global cognitive performance was successfully predicted (81%–85% of variance) by a combination of fast wave activity variables in the alpha, beta and theta frequency bands. Interestingly, predicting domain specific performance had varying degrees of success (42%–99% of the variance predicted) and relied on combinations of both slow and fast wave activity, with delta and gamma activity predicting attention performance; delta, theta, and gamma activity predicting memory performance; and delta and beta variables predicting judgement performance. Significance: Global and domain specific cognitive performance of Australian nurses may be predicted with varying degrees of success by a unique combination of EEG variables. These proposed models image transitory cognitive declines and as such may prove useful in the prediction of early cognitive impairment, and may enable better diagnosis, and management of cognitive impairment.