Slow neuronal oscillations in the resting brain vs task execution: A BSS investigation of EEG recordings

Spontaneous very low frequency oscillations (<0.5 Hz) occurring within widely distributed neuroanatomical systems have been increasingly analyzed in brain imaging studies. Whilst being more prominent in the resting brain, these slow waves also persist into task sessions and may potentially interfere with active goal-directed attention, leading to periodic lapses in attention during task execution. This work presents a new experimental framework and a multistage signal processing methodology - comprising blind source separation (BSS) coupled with a neural network feature extraction and classification method - developed for assessing variations in the slow wave characteristics in EEG data recorded during periods of quiet wakefulness (termed as “rest”), and during visual tasks of various difficulty levels. Core results demonstrate that the amplitude and phase of the brain sources in the slow wave band share essential similarities during rest and task conditions, but are distinct enough to be classified separately. These slow wave variations are also significantly correlated with the level of cognitive attention assessed by task performance measures (such as reaction times and error rates). Moreover, the power of the brain sources in the slow wave band is attenuated during task, and the level of attenuation drops as the task difficulty level is increased, whilst the slow wave phase undergoes a change in structure (measured through entropy). The methodology and findings presented here provide a new basis for assessing neural activity during various mental conditions.