Abstract
In neurobiology the analysis of spike trains is of particular interest. Spike trains can be seen as point processes generated by neurons emitting signals to communicate with other neurons. According to Hebb’s seminal work on neural encoding information is processed in the brain in ensembles of neurons that reveal themselves by synchronized behaviour. One of the many competing hypotheses to explain this synchrony is the spike-time-synchrony hypothesis. The relative timing of spikes emitted by different neurons should explain the processing of information. In this paper we present a novel method to decide for each single neuron whether it is part of (at least) one assembly by analyzing changes in the distribution of spiking patterns.
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Braune, C., Besecke, S., Kruse, R. (2015). Using Changes in Distribution to Identify Synchronized Point Processes. In: Grzegorzewski, P., Gagolewski, M., Hryniewicz, O., Gil, M. (eds) Strengthening Links Between Data Analysis and Soft Computing. Advances in Intelligent Systems and Computing, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-319-10765-3_29
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DOI: https://doi.org/10.1007/978-3-319-10765-3_29
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10764-6
Online ISBN: 978-3-319-10765-3
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