Literature DB >> 10946993

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

P D Roberts1, C C Bell.   

Abstract

The electrosensory lateral line lobe (ELL) of mormyrid electric fish is a cerebellum-like structure that receives primary afferent input from electroreceptors in the skin. Purkinje-like cells in ELL store and retrieve a temporally precise negative image of prior sensory input. The stored image is derived from the association of centrally originating predictive signals with peripherally originating sensory input. The predictive signals are probably conveyed by parallel fibers. Recent in vitro experiments have demonstrated that pairing parallel fiber-evoked excitatory postsynaptic potentials (epsps) with postsynaptic spikes in Purkinje-like cells depresses the strength of these synapses. The depression has a tight dependence on the temporal order of pre- and postsynaptic events. The postsynaptic spike must follow the onset of the epsp within a window of about 60 msec for the depression to occur and pairings at other delays yield a nonassociative enhancement of the epsp. Mathematical analyses and computer simulations are used here to test the hypothesis that synaptic plasticity of the type established in vitro could be responsible for the storage of temporal patterns that is observed in vivo. This hypothesis is confirmed. The temporally asymmetric learning rule established in vitro results in the storage of activity patterns as observed in vivo and does so with significantly greater fidelity than other types of learning rules. The results demonstrate the importance of precise timing in pre- and postsynaptic activity for accurate storage of temporal information.

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Year:  2000        PMID: 10946993     DOI: 10.1023/a:1008938428112

Source DB:  PubMed          Journal:  J Comput Neurosci        ISSN: 0929-5313            Impact factor:   1.621


  19 in total

1.  Sensory processing and corollary discharge effects in the mormyromast regions of the mormyrid electrosensory lobe. I. Field potentials, cellular activity in associated structures.

Authors:  C C Bell; K Grant; J Serrier
Journal:  J Neurophysiol       Date:  1992-09       Impact factor: 2.714

2.  Mormyrid electrosensory lobe in vitro: morphology of cells and circuits.

Authors:  V Z Han; C C Bell; K Grant; Y Sugawara
Journal:  J Comp Neurol       Date:  1999-02-15       Impact factor: 3.215

3.  A critical window for cooperation and competition among developing retinotectal synapses.

Authors:  L I Zhang; H W Tao; C E Holt; W A Harris; M Poo
Journal:  Nature       Date:  1998-09-03       Impact factor: 49.962

4.  The mormyrid electrosensory lobe in vitro: physiology and pharmacology of cells and circuits.

Authors:  K Grant; Y Sugawara; L Gómez; V Z Han; C C Bell
Journal:  J Neurosci       Date:  1998-08-01       Impact factor: 6.167

5.  Functional significance of long-term potentiation for sequence learning and prediction.

Authors:  L F Abbott; K I Blum
Journal:  Cereb Cortex       Date:  1996 May-Jun       Impact factor: 5.357

Review 6.  The generation and subtraction of sensory expectations within cerebellum-like structures.

Authors:  C Bell; D Bodznick; J Montgomery; J Bastian
Journal:  Brain Behav Evol       Date:  1997       Impact factor: 1.808

7.  An n-level field theory of biological neural networks.

Authors:  G A Chauvet
Journal:  J Math Biol       Date:  1993       Impact factor: 2.259

8.  Neural simulations of adaptive reafference suppression in the elasmobranch electrosensory system.

Authors:  M E Nelson; M G Paulin
Journal:  J Comp Physiol A       Date:  1995-12       Impact factor: 1.836

9.  Statistical constraints on synaptic plasticity.

Authors:  T J Sejnowski
Journal:  J Theor Biol       Date:  1977-11-21       Impact factor: 2.691

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

Authors:  C C Bell; V Z Han; Y Sugawara; K Grant
Journal:  Nature       Date:  1997-05-15       Impact factor: 49.962

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  28 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.  Decorrelation control by the cerebellum achieves oculomotor plant compensation in simulated vestibulo-ocular reflex.

Authors:  Paul Dean; John Porrill; James V Stone
Journal:  Proc Biol Sci       Date:  2002-09-22       Impact factor: 5.349

3.  Intracortical mechanism of stimulus-timing-dependent plasticity in visual cortical orientation tuning.

Authors:  Haishan Yao; Yaosong Shen; Yang Dan
Journal:  Proc Natl Acad Sci U S A       Date:  2004-03-24       Impact factor: 11.205

4.  Spike-timing-dependent synaptic plasticity and synaptic democracy in dendrites.

Authors:  Albert Gidon; Idan Segev
Journal:  J Neurophysiol       Date:  2009-04-08       Impact factor: 2.714

5.  Synaptic consolidation: an approach to long-term learning.

Authors:  Claudia Clopath
Journal:  Cogn Neurodyn       Date:  2011-10-22       Impact factor: 5.082

6.  Plastic corollary discharge predicts sensory consequences of movements in a cerebellum-like circuit.

Authors:  Tim Requarth; Nathaniel B Sawtell
Journal:  Neuron       Date:  2014-05-21       Impact factor: 17.173

7.  A role for mixed corollary discharge and proprioceptive signals in predicting the sensory consequences of movements.

Authors:  Tim Requarth; Patrick Kaifosh; Nathaniel B Sawtell
Journal:  J Neurosci       Date:  2014-11-26       Impact factor: 6.167

8.  Learning to generalize.

Authors:  André Longtin
Journal:  Elife       Date:  2019-04-10       Impact factor: 8.140

9.  Sensory processing and corollary discharge effects in posterior caudal lobe Purkinje cells in a weakly electric mormyrid fish.

Authors:  Karina Alviña; Nathaniel B Sawtell
Journal:  J Neurophysiol       Date:  2014-04-30       Impact factor: 2.714

Review 10.  A comparative approach to cerebellar function: insights from electrosensory systems.

Authors:  Richard Warren; Nathaniel B Sawtell
Journal:  Curr Opin Neurobiol       Date:  2016-08-08       Impact factor: 6.627

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