NDLI: A Biophysical Model of Synaptic Delay Learning and Temporal Pattern Recognition in a Cerebellar Purkinje Cell

Content Provider	Springer Nature Link
Author	Steuber, Volker Willshaw, David
Copyright Year	2004
Abstract	It has been suggested that information in the brain is encoded in temporal spike patterns which are decoded by a combination of time delays and coincidence detection. Here, we show how a multi-compartmental model of a cerebellar Purkinje cell can learn to recognise temporal parallel fibre activity patterns by adapting latencies of calcium responses after activation of metabotropic glutamate receptors (mGluRs). In each compartment of our model, the mGluR signalling cascade is represented by a set of differential equations that reflect the underlying biochemistry. Phosphorylation of the mGluRs changes the concentration of receptors which are available for activation by glutamate and thereby adjusts the time delay between mGluR stimulation and voltage response. The adaptation of a synaptic delay as opposed to a weight represents a novel non-Hebbian learning mechanism that can also implement the adaptive timing of the classically conditioned eye-blink response.
Starting Page	149
Ending Page	164
Page Count	16
File Format	PDF
ISSN	09295313
Journal	Journal of Computational Neuroscience
Volume Number	17
Issue Number	2
e-ISSN	15736873
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2004-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Human Genetics Neurosciences Neurology Theory of Computation
Content Type	Text
Resource Type	Article
Subject	Cognitive Neuroscience Sensory Systems Cellular and Molecular Neuroscience

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