Work

Linking non-binned spike train kernels to several existing spike train metrics.

Year: 2006

Type: conference-paper

Abstract: This work presents two kernels which can be applied to sets of spike times.This allows the use of state-of-the-art classification techniques to spike trains.The presented kernels are closely related to several recent and often used spike train metrics.One of the main advantages is that it does not require the spike trains to be binned.A high temporal resolution is thus preserved which is needed when temporal coding is used.As a test of the classification possibilities a jittered spike train template classification problem is solved.

Source: Ghent University Academic Bibliography (Ghent University)

Authors: Benjamin Schrauwen, Jan M. Van Campenhout

Institution: Ghent University

Language: English

Topic: Neural dynamics and brain function

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

Funders: Fonds Wetenschappelijk Onderzoek, Vlaamse regering

OpenAlex ID: W2173049006

FWCI:

Cites: 8

Cited by: 1

Related to: 10