Spiking neurons and synaptic stimuli: Neural response comparison using coincidence-factor

Sarangdhar, Mayur; Kambhampati, Chandrasekhar

Abstract

In this chapter, neural responses are generated by changing the Inter-Spike-Interval (ISI) of the stimulus. These responses are subsequently compared and a coincidence factor is obtained. Coincidence-factor, a measure of similarity, is expected to generate a high value for higher similarity and a low value for dissimilarity. It is observed that these coincidence-factors do not have a consistent trend over a simulation time window. Also, the lower-bound limit for faithful behaviour of coincidence factor shifts towards the right with the increase in the reference ISI of the stimulus. In principle, if two responses have a very high similarity, then their respective stimuli should be very similar and could possibly be considered the same. However, as results show, two spike trains generated by highly-varying stimuli have a high coincidence-factor. This is due to limitations imposed by the one-dimensional comparison of coincidence-factor.

Citation

Sarangdhar, M., & Kambhampati, C. (2009). Spiking neurons and synaptic stimuli: Neural response comparison using coincidence-factor. In S.-I. Ao, & L. Gelman (Eds.), Lecture Notes in Electrical Engineering; Advances in Electrical Engineering and Computational Science (681-692). Springer Verlag. https://doi.org/10.1007/978-90-481-2311-7_58

• Publication Date: 2009
• Journal: Lecture Notes in Electrical Engineering
• Print ISSN: 1876-1100
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 39 LNEE
• Pages: 681-692
• Book Title: Lecture Notes in Electrical Engineering; Advances in Electrical Engineering and Computational Science
• ISBN: 9789048123100; 9789048123117
• DOI: https://doi.org/10.1007/978-90-481-2311-7_58
• Public URL: https://hull-repository.worktribe.com/output/409688
• Contract Date: Dec 31, 2009