Literature DB >> 9153391

Synaptic plasticity in a cerebellum-like structure depends on temporal order.

C C Bell1, V Z Han, Y Sugawara, K Grant.   

Abstract

Cerebellum-like structures in fish appear to act as adaptive sensory processors, in which learned predictions about sensory input are generated and subtracted from actual sensory input, allowing unpredicted inputs to stand out. Pairing sensory input with centrally originating predictive signals, such as corollary discharge signals linked to motor commands, results in neural responses to the predictive signals alone that are 'negative images' of the previously paired sensory responses. Adding these 'negative images' to actual sensory inputs minimizes the neural response to predictable sensory features. At the cellular level, sensory input is relayed to the basal region of Purkinje-like cells, whereas predictive signals are relayed by parallel fibres to the apical dendrites of the same cells. The generation of negative images could be explained by plasticity at parallel fibre synapses. We show here that such plasticity exists in the electrosensory lobe of mormyrid electric fish and that it has the necessary properties for such a model: it is reversible, anti-hebbian (excitatory postsynaptic potentials (EPSPs) are depressed after pairing with a postsynaptic spike) and tightly dependent on the sequence of pre- and postsynaptic events, with depression occurring only if the postsynaptic spike follows EPSP onset within 60 ms.

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Year:  1997        PMID: 9153391     DOI: 10.1038/387278a0

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  137 in total

1.  Computational consequences of temporally asymmetric learning rules: I. Differential hebbian learning.

Authors:  P D Roberts
Journal:  J Comput Neurosci       Date:  1999 Nov-Dec       Impact factor: 1.621

2.  Formation of temporal-feature maps by axonal propagation of synaptic learning.

Authors:  R Kempter; C Leibold; H Wagner; J L van Hemmen
Journal:  Proc Natl Acad Sci U S A       Date:  2001-03-13       Impact factor: 11.205

3.  Simulations of cerebellar motor learning: computational analysis of plasticity at the mossy fiber to deep nucleus synapse.

Authors:  J F Medina; M D Mauk
Journal:  J Neurosci       Date:  1999-08-15       Impact factor: 6.167

4.  Fast network oscillations in the newborn rat hippocampus in vitro.

Authors:  J M Palva; K Lamsa; S E Lauri; H Rauvala; K Kaila; T Taira
Journal:  J Neurosci       Date:  2000-02-01       Impact factor: 6.167

5.  Stable Hebbian learning from spike timing-dependent plasticity.

Authors:  M C van Rossum; G Q Bi; G G Turrigiano
Journal:  J Neurosci       Date:  2000-12-01       Impact factor: 6.167

6.  Computational consequences of temporally asymmetric learning rules: II. Sensory image cancellation.

Authors:  P D Roberts; C C Bell
Journal:  J Comput Neurosci       Date:  2000 Jul-Aug       Impact factor: 1.621

Review 7.  Paradoxical signal transduction in neurobiological systems.

Authors:  F C Colpaert; Y Frégnac
Journal:  Mol Neurobiol       Date:  2001 Aug-Dec       Impact factor: 5.590

8.  Bidirectional synaptic plasticity in the cerebellum-like mammalian dorsal cochlear nucleus.

Authors:  Kiyohiro Fujino; Donata Oertel
Journal:  Proc Natl Acad Sci U S A       Date:  2002-12-16       Impact factor: 11.205

9.  Tuning neocortical pyramidal neurons between integrators and coincidence detectors.

Authors:  Michael Rudolph; Alain Destexhe
Journal:  J Comput Neurosci       Date:  2003 May-Jun       Impact factor: 1.621

10.  Spike-timing-dependent plasticity in primate corticospinal connections induced during free behavior.

Authors:  Yukio Nishimura; Steve I Perlmutter; Ryan W Eaton; Eberhard E Fetz
Journal:  Neuron       Date:  2013-11-07       Impact factor: 17.173

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