Poster A99, Saturday, March 25, 5:00 – 7:00 pm, Pacific Concourse
A statistical method for analyzing and comparing spatiotemporal cortical activation patterns
Patrick Krauss1, Achim Schilling1, Claus Metzner1, Konstantin Tziridis1, Holger Schulze1; 1University of Erlangen
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 cluster analysis (SCA) method enables statistical analyzing and comparing clusters of data points in n-dimensional space. To evaluate the analytical power of our SCA approach, we first tested the method using artificially generated data sets. Subsequently, we demonstrate that using this approach stimulus-specific spatiotemporal activity patterns can be detected and be significantly distinguished from each other during stimulation with long-lasting stimuli. In addition we extend the method to human electroencephalogram (EEG) data and exemplarily show that therewith different REM and non-REM sleep stages may be differentiated, demonstrating the universal applicability of our approach. Our method thereby may be 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 (BCI).
Topic Area: METHODS: Electrophysiology