Computing Information in Neuronal Spikes

Authors:
Dorian Aur;Christopher I. Connolly;Mandar S. Jog
Affiliations:
Department of Clinical Neurological Sciences, Movement Disorders Program, London, Canada;SRI International, California, USA;Department of Clinical Neurological Sciences, Movement Disorders Program, London, Canada
Venue:
Neural Processing Letters
Year:
2006

Citing 7
Cited 1

Entropy and information theory

Entropy and information theory
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Spikes: exploring the neural code

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Enhancement of information transmission efficiency by synaptic failures

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Detection of weak signals using adaptive stochastic resonance

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Estimation of the information by an adaptive partitioning of the observation space

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Neuronal spatial learning

Neural Processing Letters

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Abstract

This paper provides new insights regarding the transfer of information between input signal and the output of neurons. Simulations of the Hodgkin-Huxley (HH) model combined with computational techniques are used to estimate this transfer of information. Our analysis shows that comparatively, mutual information (MI) between input signal and sodium flux is about two times that between input signal and output spikes during each spike within a millisecond-level time domain. This higher transfer of information provided by ionic fluxes extends the working frequency domain of neural cells beyond those accessible to information transfer within spikes alone.