We present a new statistical method to analyze multichannel steady-state local field potentials (LFP) recorded within different sensory cortices of different rodent species. Our spatiotemporal multi-dimensional cluster statistics (MCS) method enables statistical analyzing and comparing clusters of data points in n-dimensional space. We demonstrate that using this approach stimulus-specific attractor-like spatiotemporal activity patterns can be detected and be significantly different from each other during stimulation with long-lasting stimuli. Our method may be applied to other types of multichannel neuronal data, like EEG, MEG or spiking responses and used for the development of new read-out algorithms of brain activity and by that opens new perspectives for the development of brain-computer interfaces.
@article{arxiv.1611.07677,
title = {A statistical method for analyzing and comparing spatiotemporal cortical activation patterns},
author = {Patrick Krauss and Claus Metzner and Achim Schilling and Konstantin Tziridis and Maximilian Traxdorf and Holger Schulze},
journal= {arXiv preprint arXiv:1611.07677},
year = {2016}
}