Literature DB >> 12066185

Role of experience and oscillations in transforming a rate code into a temporal code.

M R Mehta1, A K Lee, M A Wilson.   

Abstract

In the vast majority of brain areas, the firing rates of neurons, averaged over several hundred milliseconds to several seconds, can be strongly modulated by, and provide accurate information about, properties of their inputs. This is referred to as the rate code. However, the biophysical laws of synaptic plasticity require precise timing of spikes over short timescales (<10 ms). Hence it is critical to understand the physiological mechanisms that can generate precise spike timing in vivo, and the relationship between such a temporal code and a rate code. Here we propose a mechanism by which a temporal code can be generated through an interaction between an asymmetric rate code and oscillatory inhibition. Consistent with the predictions of our model, the rate and temporal codes of hippocampal pyramidal neurons are highly correlated. Furthermore, the temporal code becomes more robust with experience. The resulting spike timing satisfies the temporal order constraints of hebbian learning. Thus, oscillations and receptive field asymmetry may have a critical role in temporal sequence learning.

Mesh:

Year:  2002        PMID: 12066185     DOI: 10.1038/nature00807

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


  213 in total

1.  Learning rules and network repair in spike-timing-based computation networks.

Authors:  J J Hopfield; Carlos D Brody
Journal:  Proc Natl Acad Sci U S A       Date:  2003-12-23       Impact factor: 11.205

2.  Temporal characteristics of the predictive synchronous firing modeled by spike-timing-dependent plasticity.

Authors:  Katsunori Kitano; Tomoki Fukai
Journal:  Learn Mem       Date:  2004 May-Jun       Impact factor: 2.460

3.  Phase precession through acceleration of local theta rhythm: a biophysical model for the interaction between place cells and local inhibitory neurons.

Authors:  Luísa Castro; Paulo Aguiar
Journal:  J Comput Neurosci       Date:  2012-01-04       Impact factor: 1.621

4.  Learning complex temporal patterns with resource-dependent spike timing-dependent plasticity.

Authors:  Jason F Hunzinger; Victor H Chan; Robert C Froemke
Journal:  J Neurophysiol       Date:  2012-04-11       Impact factor: 2.714

5.  Grid cells in rat entorhinal cortex encode physical space with independent firing fields and phase precession at the single-trial level.

Authors:  Eric T Reifenstein; Richard Kempter; Susanne Schreiber; Martin B Stemmler; Andreas V M Herz
Journal:  Proc Natl Acad Sci U S A       Date:  2012-04-02       Impact factor: 11.205

Review 6.  Neurophysiological and computational principles of cortical rhythms in cognition.

Authors:  Xiao-Jing Wang
Journal:  Physiol Rev       Date:  2010-07       Impact factor: 37.312

7.  Temporal delays among place cells determine the frequency of population theta oscillations in the hippocampus.

Authors:  Caroline Geisler; Kamran Diba; Eva Pastalkova; Kenji Mizuseki; Sebastien Royer; György Buzsáki
Journal:  Proc Natl Acad Sci U S A       Date:  2010-04-07       Impact factor: 11.205

8.  Bidirectional changes to hippocampal theta-gamma comodulation predict memory for recent spatial episodes.

Authors:  Prasad R Shirvalkar; Peter R Rapp; Matthew L Shapiro
Journal:  Proc Natl Acad Sci U S A       Date:  2010-03-29       Impact factor: 11.205

9.  Circuit mechanisms of hippocampal reactivation during sleep.

Authors:  Paola Malerba; Maxim Bazhenov
Journal:  Neurobiol Learn Mem       Date:  2018-05-01       Impact factor: 2.877

10.  Hippocampal network dynamics constrain the time lag between pyramidal cells across modified environments.

Authors:  Kamran Diba; György Buzsáki
Journal:  J Neurosci       Date:  2008-12-10       Impact factor: 6.167

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