Date: July 6, 2007
Creator: Tam, Nicoladie D.
Description: This article accompanies a poster presentation on a self-adaptive burst-detection algorithm. A self-adaptive, time-scale invariant single-unit spike train analysis technique is introduced to detect burst firings in neurons. This burst-detection method is an adaptive algorithm that uses the characteristic firing patterns statistics within and between bursts to identify the inter-burst period, intra-burst period and burst duration.
Contributing Partner: UNT College of Arts and Sciences