Abstract
The prevailing irregular pattern of field potentials is little used due to the uncertain origin and identity of the source populations. After recovering clean source-specific dynamics (field potential-generators) in multiple brain areas of anesthetized rats we explored if they contain temporal identity features and to what extent they remain upon blending in the volume (raw field potentials). Relevant factors and mechanisms were further explored through a feed-forward model of field potentials. Signals were characterized with a multivariate set of statistical, spectral and nonlinear measures and explored with machine-learning classifiers. Despite the strong variability of electrographic patterns, field potential generators exhibit unique temporal signatures that allow their discrimination. Signatures are contained in 1 to 5 s segments in any given brain region and are robust across groups of animals. In contrast, the spatial overlap of sources and the contribution by remote potentials cause indeterminacy of raw field potentials, making them approach a noisy behavior. The so revealed source-specific signatures contain spectral and nonlinear features, thus overcoming the traditional notion of waves and frequency bands. We propose that besides upstream dynamics cytoarchitectural factors of the source population contribute to these unique signatures. These findings pave the way to utilize the vast reserve of information contained in irregular field potentials.