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2007•Acta Biophysica SinicaRequires access

A METHOD FOR RECOGNIZING PATTERNS OF NEURAL SPIKE TRAINS AND ITS APPLICATION

Shimin Wang

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Abstract

A spike train is treated as a time-dependent stair-like function called response function.Three characteristic variables defined at sequential moments,including two formal derivatives and the integration of the response function,are introduced to reflect the temporal patterns of a spike train.These variables have obvious geometric meaning in expressing the response and coding of neural spike trains reasonably.The reconstruction of a spike train with these variables demonstrates that the information carried by spike trains can be well preserved.A mathematical model of cold receptor is considered as an example to study the temporal patterns based on the characteristic variables of its response functions under different temperature conditions.

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What this paper is about

A spike train is treated as a time-dependent stair-like function called response function.Three characteristic variables defined at sequential moments,including two formal derivatives and the integration of the response function,are introduced to reflect the temporal patterns of a spike train.These variables have obvious geometric meaning in expressing the response and coding of neural spike trains reasonably.The reconstruction of a spike train with these variables demonstrates that the information carried by spike trains can be well preserved.A mathematical model of cold receptor is considered as an example to study the temporal patterns based on the characteristic variables of its response functions under different temperature conditions.

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Available abstract

A spike train is treated as a time-dependent stair-like function called response function.Three characteristic variables defined at sequential moments,including two formal derivatives and the integration of the response function,are introduced to reflect the temporal patterns of a spike train.These variables have obvious geometric meaning in expressing the response and coding of neural spike trains reasonably.The reconstruction of a spike train with these variables demonstrates that the information carried by spike trains can be well preserved.A mathematical model of cold receptor is considered as an example to study the temporal patterns based on the characteristic variables of its response functions under different temperature conditions.

Key concepts: Spike (software development), Spike train, Train, Computer science, Neural coding, Function (biology), Artificial neural network, Coding (social sciences)

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