Literature DB >> 30183459

A novel mutual information estimator to measure spike train correlations in a model thalamocortical network.

Ekaterina D Gribkova1,2, Baher A Ibrahim3,2, Daniel A Llano1,3,2.   

Abstract

The impact of thalamic state on information transmission to the cortex remains poorly understood. This limitation exists due to the rich dynamics displayed by thalamocortical networks and because of inadequate tools to characterize those dynamics. Here, we introduce a novel estimator of mutual information and use it to determine the impact of a computational model of thalamic state on information transmission. Using several criteria, this novel estimator, which uses an adaptive partition, is shown to be superior to other mutual information estimators with uniform partitions when used to analyze simulated spike train data with different mean spike rates, as well as electrophysiological data from simultaneously recorded neurons. When applied to a thalamocortical model, the estimator revealed that thalamocortical cell T-type calcium current conductance influences mutual information between the input and output from this network. In particular, a T-type calcium current conductance of ~40 nS appears to produce maximal mutual information between the input to this network (conceptualized as afferent input to the thalamocortical cell) and the output of the network at the level of a layer 4 cortical neuron. Furthermore, at particular combinations of inputs to thalamocortical and thalamic reticular nucleus cells, thalamic cell bursting correlated strongly with recovery of mutual information between thalamic afferents and layer 4 neurons. These studies suggest that the novel mutual information estimator has advantages over previous estimators and that thalamic reticular nucleus activity can enhance mutual information between thalamic afferents and thalamorecipient cells in the cortex. NEW & NOTEWORTHY In this study, a novel mutual information estimator was developed to analyze information flow in a model thalamocortical network. Our findings suggest that this estimator is a suitable tool for signal transmission analysis, particularly in neural circuits with disparate firing rates, and that the thalamic reticular nucleus can potentiate ascending sensory signals, while thalamic recipient cells in the cortex can recover mutual information in ascending sensory signals that is lost due to thalamic bursting.

Entities:  

Keywords:  adaptive partition; bursting; mutual information; thalamic reticular nucleus; thalamus

Mesh:

Substances:

Year:  2018        PMID: 30183459      PMCID: PMC6337027          DOI: 10.1152/jn.00012.2018

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  70 in total

Review 1.  Neuronal circuitry of thalamocortical epilepsy and mechanisms of antiabsence drug action.

Authors:  J R Huguenard
Journal:  Adv Neurol       Date:  1999

2.  The impact of 'bursting' thalamic impulses at a neocortical synapse.

Authors:  H A Swadlow; A G Gusev
Journal:  Nat Neurosci       Date:  2001-04       Impact factor: 24.884

Review 3.  Tonic and burst firing: dual modes of thalamocortical relay.

Authors:  S M Sherman
Journal:  Trends Neurosci       Date:  2001-02       Impact factor: 13.837

4.  Encoding of visual information by LGN bursts.

Authors:  P Reinagel; D Godwin; S M Sherman; C Koch
Journal:  J Neurophysiol       Date:  1999-05       Impact factor: 2.714

5.  Statistical validation of mutual information calculations: comparison of alternative numerical algorithms.

Authors:  C J Cellucci; A M Albano; P E Rapp
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2005-06-22

6.  T-type calcium channels consolidate tonic action potential output of thalamic neurons to neocortex.

Authors:  Charlotte Deleuze; François David; Sébastien Béhuret; Gérard Sadoc; Hee-Sup Shin; Victor N Uebele; John J Renger; Régis C Lambert; Nathalie Leresche; Thierry Bal
Journal:  J Neurosci       Date:  2012-08-29       Impact factor: 6.167

7.  Visual stimuli recruit intrinsically generated cortical ensembles.

Authors:  Jae-eun Kang Miller; Inbal Ayzenshtat; Luis Carrillo-Reid; Rafael Yuste
Journal:  Proc Natl Acad Sci U S A       Date:  2014-09-08       Impact factor: 11.205

Review 8.  Dynamic pattern generation in behavioral and neural systems.

Authors:  G Schöner; J A Kelso
Journal:  Science       Date:  1988-03-25       Impact factor: 47.728

9.  Information Coding through Adaptive Gating of Synchronized Thalamic Bursting.

Authors:  Clarissa J Whitmire; Christian Waiblinger; Cornelius Schwarz; Garrett B Stanley
Journal:  Cell Rep       Date:  2016-01-14       Impact factor: 9.423

Review 10.  Correcting for the sampling bias problem in spike train information measures.

Authors:  Stefano Panzeri; Riccardo Senatore; Marcelo A Montemurro; Rasmus S Petersen
Journal:  J Neurophysiol       Date:  2007-07-05       Impact factor: 2.714

View more
  4 in total

1.  Graph theoretical measures of fast ripples support the epileptic network hypothesis.

Authors:  Shennan A Weiss; Tomas Pastore; Iren Orosz; Daniel Rubinstein; Richard Gorniak; Zachary Waldman; Itzhak Fried; Chengyuan Wu; Ashwini Sharan; Diego Slezak; Gregory Worrell; Jerome Engel; Michael R Sperling; Richard J Staba
Journal:  Brain Commun       Date:  2022-04-20

2.  Projection from the Amygdala to the Thalamic Reticular Nucleus Amplifies Cortical Sound Responses.

Authors:  Mark Aizenberg; Solymar Rolón-Martínez; Tuan Pham; Winnie Rao; Julie S Haas; Maria N Geffen
Journal:  Cell Rep       Date:  2019-07-16       Impact factor: 9.423

3.  Role of NMDAR plasticity in a computational model of synaptic memory.

Authors:  Ekaterina D Gribkova; Rhanor Gillette
Journal:  Sci Rep       Date:  2021-10-27       Impact factor: 4.379

4.  Data-Driven Network Dynamical Model of Rat Brains During Acute Ictogenesis.

Authors:  Victor Hugo Batista Tsukahara; Jordão Natal de Oliveira Júnior; Vitor Bruno de Oliveira Barth; Jasiara Carla de Oliveira; Vinicius Rosa Cota; Carlos Dias Maciel
Journal:  Front Neural Circuits       Date:  2022-08-10       Impact factor: 3.342

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.