Literature DB >> 12461636

The dynamical stability of reverberatory neural circuits.

Jesper Tegnér1, Albert Compte, Xiao-Jing Wang.   

Abstract

The concept of reverberation proposed by Lorente de Nó and Hebb is key to understanding strongly recurrent cortical networks. In particular, synaptic reverberation is now viewed as a likely mechanism for the active maintenance of working memory in the prefrontal cortex. Theoretically, this has spurred a debate as to how such a potentially explosive mechanism can provide stable working-memory function given the synaptic and cellular mechanisms at play in the cerebral cortex. We present here new evidence for the participation of NMDA receptors in the stabilization of persistent delay activity in a biophysical network model of conductance-based neurons. We show that the stability of working-memory function, and the required NMDA/AMPA ratio at recurrent excitatory synapses, depend on physiological properties of neurons and synaptic interactions, such as the time constants of excitation and inhibition, mutual inhibition between interneurons, differential NMDA receptor participation at excitatory projections to pyramidal neurons and interneurons, or the presence of slow intrinsic ion currents in pyramidal neurons. We review other mechanisms proposed to enhance the dynamical stability of synaptically generated attractor states of a reverberatory circuit. This recent work represents a necessary and significant step towards testing attractor network models by cortical electrophysiology.

Entities:  

Mesh:

Substances:

Year:  2002        PMID: 12461636     DOI: 10.1007/s00422-002-0363-9

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  58 in total

Review 1.  Mechanisms of Persistent Activity in Cortical Circuits: Possible Neural Substrates for Working Memory.

Authors:  Joel Zylberberg; Ben W Strowbridge
Journal:  Annu Rev Neurosci       Date:  2017-07-25       Impact factor: 12.449

2.  A recurrent network model of somatosensory parametric working memory in the prefrontal cortex.

Authors:  Paul Miller; Carlos D Brody; Ranulfo Romo; Xiao-Jing Wang
Journal:  Cereb Cortex       Date:  2003-11       Impact factor: 5.357

3.  Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory.

Authors:  X-J Wang; J Tegnér; C Constantinidis; P S Goldman-Rakic
Journal:  Proc Natl Acad Sci U S A       Date:  2004-01-23       Impact factor: 11.205

Review 4.  Neurophysiological and computational principles of cortical rhythms in cognition.

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

5.  Angular path integration by moving "hill of activity": a spiking neuron model without recurrent excitation of the head-direction system.

Authors:  Pengcheng Song; Xiao-Jing Wang
Journal:  J Neurosci       Date:  2005-01-26       Impact factor: 6.167

6.  Synaptic mechanisms of persistent reverberatory activity in neuronal networks.

Authors:  Pak-Ming Lau; Guo-Qiang Bi
Journal:  Proc Natl Acad Sci U S A       Date:  2005-07-08       Impact factor: 11.205

Review 7.  The appearance of long-latency responses to a conditioned signal in the cortex is explained by strengthening of collateral connections between pyramidal neurons.

Authors:  V I Maiorov
Journal:  Neurosci Behav Physiol       Date:  2005-06

8.  A recurrent network mechanism of time integration in perceptual decisions.

Authors:  Kong-Fatt Wong; Xiao-Jing Wang
Journal:  J Neurosci       Date:  2006-01-25       Impact factor: 6.167

Review 9.  Inside the brain of a neuron.

Authors:  Kyriaki Sidiropoulou; Eleftheria Kyriaki Pissadaki; Panayiota Poirazi
Journal:  EMBO Rep       Date:  2006-09       Impact factor: 8.807

10.  A layered neural architecture for the consolidation, maintenance, and updating of representations in visual working memory.

Authors:  Jeffrey S Johnson; John P Spencer; Gregor Schöner
Journal:  Brain Res       Date:  2009-07-14       Impact factor: 3.252

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.