Information-Geometric Measure for Neural Spikes

The present study introduces information-geometricmeasures to analyze neural ring patterns by taking not only the secondorder but also higher-order interactions among neurons into account. Information geometry provides useful tools and concepts for this purpose, including the orthogonality of coordinate parameters and the Pythagoras relation in the Kullback-Leibler divergence. Based on this orthogonality, we show a novel method to analyze spike ring patterns by decomposing the interactions of neurons of various orders. As a result, purely pairwise, triplewise, and higher-order interactions are singled out. We also demonstrate the bene ts of our proposal by using real neural data, recorded in the prefrontal and parietal cortices of monkeys. 

• Type: Journal
• Year: 2002
• Where: NECO
• Authors: Hiroyuki Nakahara, Shun-ichi Amari
• Keywords: NECO 2002, Neural Ring Patterns, Present Study, Pythagoras Relation