Differentiation of alpha coma from awake alpha by nonlinear dynamics of electroencephalography

The electroencephalogram, as a probe of scalp-recorded electrical activity arising from the human cortex, provides useful information because of its temporal and spatial organization. Recent developments in nonlinear dynamics suggest that an object can be constructed in an n-dimensional space out of a temporal sequence of data such as an EEG signal and that its organization is characterized by the dimensionality of the object (in this case, human brain activity). We have carried out an analysis of a set of alpha coma EEG patterns in comparison to the awake alpha EEG patterns of normal volunteers and patients. Alpha coma recorded from a single channel is visually indistinguishable from normal resting alpha due to its similar frequency spectrum (a broad-band spectrum with 1/f characteristics). Our results show that alpha coma dimensionality, however, differs from that of normal alpha in that it has a greater variability over different temporal segments of EEG. Single channel recordings in 7 patients with alpha coma were differentiable from those of 10 subjects with "normal" EEGs. Through dynamic analysis of the EEG, novel methods of signal extraction from EEG may become evident and applicable to clinical practice.