The shape of dementia: new measures of morphological complexity in event-related potentials (ERP) and its application to the detection of Alzheimer's disease.

In this paper, we address the problem of quantifying the commonly observed disorganization of the stereotyped wave form of the ERP associated with the P300 component in patients with Alzheimer's disease. To that extent, we propose two new measures of complexity which relate the spectral content of the signal with its temporal waveform: the spectral matching coefficient and the spectral matching entropy. We show by means of experiments that those measures effectively measure complexity and are related to the shape in an intuitive way. Those indexes are compared with commonly used measures of complexity when comparing AD patients against age-matched healthy controls. The results indicate that AD ERP signals are, indeed, more complex in the shape than that of controls, and this result is evidenced mainly by means of our new measures which have a better performance compared to similar ones. Finally, we try to explain this increase in complexity in light of the communication through coherence hypothesis framework, relating commonly found changes in the EEG with our own results.