1. A system for analyzing and classifying neurophysiologic activity of a subject, the system comprising: a data input that receives a set of subject data representing a time series of neurophysiologic activity acquired by a multiplicity of spatially distributed sensors arranged to detect neural signaling in the subject during an eyes-open idle state; a data store that stores a plurality of templates classified according to various brain conditions, wherein each of the templates represents selected subsets of statistically-independent temporal measures among neural populations measured from at least one other subject known to present a given brain condition; a processor communicatively coupled to the data input and to the data store, and programmed to: process the set of subject data to obtain a dynamic model that represents temporal measures among neural populations in the subject; and compare at least a portion of the dynamic model with the plurality of templates to produce a classification of neurophysiologic activity of the subject when the dynamic model corresponds with at least one of the plurality of templates.