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

Ekaterina D. Gribkova, Baher A. Ibrahim, Daniel A. Llano

Research output: Contribution to journalArticlepeer-review


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 (con-ceptualized 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.

Original languageEnglish (US)
Pages (from-to)2730-2744
Number of pages15
JournalJournal of neurophysiology
Issue number6
StatePublished - Dec 2018


  • Adaptive partition
  • Bursting
  • Mutual information
  • Thalamic reticular nucleus
  • Thalamus

ASJC Scopus subject areas

  • Neuroscience(all)
  • Physiology

Fingerprint Dive into the research topics of 'A novel mutual information estimator to measure spike train correlations in a model thalamocortical network'. Together they form a unique fingerprint.

Cite this