Literature DB >> 9527834

Synaptic delay learning in pulse-coupled neurons.

H Hüning, H Glünder, G Palm.   

Abstract

We present rules for the unsupervised learning of coincidence between excitatory postsynaptic potentials (EPSPs) by the adjustment of postsynaptic delays between the transmitter binding and the opening of ion channels. Starting from a gradient descent scheme, we develop a robust and more biological threshold rule by which EPSPs from different synapses can be gradually pulled into coincidence. The synaptic delay changes are determined from the summed potential--at the site where the coincidence is to be established--and from postulated synaptic learning functions that accompany the individual EPSPs. According to our scheme, templates for the detection of spatiotemporal patterns of synaptic activation can be learned, which is demonstrated by computer simulation. Finally, we discuss possible relations to biological mechanisms.

Mesh:

Year:  1998        PMID: 9527834     DOI: 10.1162/089976698300017665

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  3 in total

1.  A biophysical model of synaptic delay learning and temporal pattern recognition in a cerebellar Purkinje cell.

Authors:  Volker Steuber; David Willshaw
Journal:  J Comput Neurosci       Date:  2004 Sep-Oct       Impact factor: 1.621

2.  Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.

Authors:  Takashi Matsubara
Journal:  Front Comput Neurosci       Date:  2017-11-21       Impact factor: 2.380

3.  Robust computation with rhythmic spike patterns.

Authors:  E Paxon Frady; Friedrich T Sommer
Journal:  Proc Natl Acad Sci U S A       Date:  2019-08-20       Impact factor: 11.205

  3 in total

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