Comparing Kurtosis Score to Traditional Statistical Metrics for Characterizing the Structure in Neural Ensemble Activity

Stratton, Peter and Wiles, Janet H. (2008). Comparing Kurtosis Score to Traditional Statistical Metrics for Characterizing the Structure in Neural Ensemble Activity. In Maria Marinaro, Silvia Scarpetta and Yoko Yamaguchi (Ed.), Dynamic Brain - from Neural Spikes to Behaviors. Proceedings of: 12th International Summer School on Neural Networks (pp. 115-122) Berlin / Heidelberg: Springer. doi:10.1007/978-3-540-88853-6-9


Author Stratton, Peter
Wiles, Janet H.
Title of chapter Comparing Kurtosis Score to Traditional Statistical Metrics for Characterizing the Structure in Neural Ensemble Activity
Title of book Dynamic Brain - from Neural Spikes to Behaviors. Proceedings of: 12th International Summer School on Neural Networks
Place of Publication Berlin / Heidelberg
Publisher Springer
Publication Year 2008
Sub-type Research book chapter (original research)
DOI 10.1007/978-3-540-88853-6-9
Open Access Status
Series Lecture Notes in Computer Science
ISBN 978-3-540-88852-9
Editor Maria Marinaro
Silvia Scarpetta
Yoko Yamaguchi
Volume number 5286
Start page 115
End page 122
Total pages 8
Language eng
Subjects 920111 Nervous System and Disorders
1109 Neurosciences
B1
Abstract/Summary This study investigates the range of behaviors possible in ensembles of spiking neurons and the effect of their connectivity on ensemble dynamics utilizing a novel application of statistical measures and visualization techniques. One thousand spiking neurons were simulated, systematically varying the strength of excitation and inhibition, and the traditional measures of spike distributions – spike count, ISI-CV, and Fano factor – were compared. We also measured the kurtosis of the spike count distributions. Visualizations of these measures across the parameter spaces show a range of dynamic regimes, from simple uncorrelated spike trains (low connectivity) through intermediate levels of structure through to seizure-like activity. Like absolute spike counts, both ISI-CV and Fano factor were maximized for different types of seizure states. By contrast, kurtosis was maximized for intermediate regions, which from inspection of the spike raster plots exhibit nested oscillations and fine temporal dynamics. Brain regions exhibit nested oscillations during tasks that involve active attending, sensory processing and memory retrieval. We therefore propose that kurtosis is a useful addition to the statistical toolbox for identifying interesting structure in neuron ensemble activity.
Q-Index Code B1
Q-Index Status Confirmed Code

 
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Created: Fri, 27 Mar 2009, 00:46:08 EST by Debra McMurtrie on behalf of Queensland Brain Institute