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Burst on Hurst algorithm for detecting activity patterns in networks of cortical neurons

By G. Stillo, L. Bonzano, A. Vato, F. Davide and S. Martinoia

Abstract

Abstract — Electrophysiological signals were recorded from primary cultures of dissociated rat cortical neurons coupled to Micro-Electrode Arrays (MEAs). The neuronal discharge patterns may change under varying physiological and pathological conditions. For this reason, we developed a new burst detection method able to identify bursts with peculiar features in different experimental conditions (i.e. spontaneous activity and under the effect of specific drugs). The main feature of our algorithm (i.e. Burst On Hurst), based on the auto-similarity or fractal property of the recorded signal, is the independence from the chosen spike detection method since it works directly on the raw data. Keywords — Burst detection, cortical neuronal networks, Micro-Electrode Array (MEA), wavelets. I

Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.193.1099
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