Two new computational models show that the EEG distinguishes three distinct mental states ranging from alert to fatigue. State 1 indicates heightened alertness and is frequently present during the first few minutes of time on task. State 2 indicates normal alertness, often following and lasting longer than State 1. State 3 indicates fatigue, usually following State 2, but sometimes alternating with State 1 and State 2. Thirty-channel EEGs were re- corded from 16 subjects who performed up to 180 min of nonstop computer- based mental arithmetic. Alert or fatigued states were independently confirmed with measures of subjects’ performance and pre- or post-task mood. We found convergent evidence for a three-state model of fatigue using Bayesian analysis of two different types of EEG features, both computed for single 13-s EEG ep- ochs: 1) kernel partial least squares scores representing composite multichannel power spectra; 2) amplitude and frequency parameters of multiple channel autoregressive models.
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