Poster Title

Assessing the Mean Neuronal Firing Rate Information Hypothesis via Mutual Information

Presenter Information

Greg Zdor, Andrews University

Abstract

While it is currently well accepted that the mean neuronal firing rate (MNFR) is a key parameter encoding information about sensory and motor events, in some cases the measured information due to MNFR is not adequate to explain the total neuron signal information content. In this study, several auditory neuron responses and corresponding MNFR—generated surrogates are analyzed using mutual information (MI) as a metric of information content. Results showed that for particular inter-spike gaps (ISG), data MI exceeded two standard deviations of the MNFR mutual MI, indicating spike spacing and order also encode information.

Acknowledgments

Faculty Mentor: Jay Johnson, Engineering

Location

Buller Hall Lobby

Start Date

11-15-2018 4:00 PM

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COinS
 
Nov 15th, 4:00 PM

Assessing the Mean Neuronal Firing Rate Information Hypothesis via Mutual Information

Buller Hall Lobby

While it is currently well accepted that the mean neuronal firing rate (MNFR) is a key parameter encoding information about sensory and motor events, in some cases the measured information due to MNFR is not adequate to explain the total neuron signal information content. In this study, several auditory neuron responses and corresponding MNFR—generated surrogates are analyzed using mutual information (MI) as a metric of information content. Results showed that for particular inter-spike gaps (ISG), data MI exceeded two standard deviations of the MNFR mutual MI, indicating spike spacing and order also encode information.