The statistical characterization of stimulus evoked human brain electrical activity

Abstract

Human behaviour is constituted from a broadly defined triad of perception, cognition and action.  In turn these functions depend upon a seemingly vast array of complex and involved interactions and cooperation’s between various regions and areas of the brain.  At present the dominant paradigm attempting to identify these interactions, and defining their functional role, involves the systematic determination of the temporal coincidences between spatially distinct neurophysiological events.  

Such temporal coincidences, collectively referred to as functional connectivity, are typically estimated from the statistical correlations between time series quantifying spontaneous (or resting) fluctuations in spatially localised cerebral blood flow that are thought to fairly represent spatially localized neurophysiological activity.  While this imaging approach, referred to as resting state functional magnetic resonance imaging, has been useful in exploring the brain’s functional organization it is nevertheless restricted in that it is unable to image the rapid changes in functional connectivity that are expected to attend cognitive activity.

Recently an alternative approach has been developed that addresses such a deficiency.  This approach depends upon measuring the variability of the scalp recorded electrical activity of the brain (the electroencephalogram or EEG) in response to a repeated sensory stimulus (typically a short duration image or sound).  By quantifying such variability at multiple scalp, and thus brain, locations and at a series of times with respect to stimulus presentation, we can, in principle, build up a detailed picture of the functional connectivity architecture of human cognition.