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Title of Journal: Ann Biomed Eng

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Abbravation: Annals of Biomedical Engineering

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Springer US

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DOI

10.1007/bf02886343

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1573-9686

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Boolean Modeling of Neural Systems with PointProc

Authors: Theodoros P Zanos Robert E Hampson Samuel E Deadwyler Theodore W Berger Vasilis Z Marmarelis
Publish Date: 2009/06/05
Volume: 37, Issue: 8, Pages: 1668-1682
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Abstract

This paper presents a pilot application of the Boolean–Volterra modeling methodology presented in the companion paper Part I that is suitable for the analysis of systems with pointprocess inputs and outputs eg recordings of the activity of neuronal ensembles This application seeks to discover the causal links between two neuronal ensembles in the hippocampus of a behaving rat The experimental data come from multiunit recordings in the CA3 and CA1 regions of the hippocampus in the form of sequences of action potentials—treated mathematically as pointprocesses and computationally as spiketrains—that are collected in vivo during two behavioral tasks The modeling objective is to identify and quantify the causal links among the neurons generating the recorded activity using Boolean–Volterra models estimated directly from the data according to the methodological framework presented in the companion paper The obtained models demonstrate the feasibility of the proposed approach using short datarecords and provide some insights into the functional properties of the system eg regarding the presence of rhythmic characteristics in the neuronal dynamics of these ensembles making the proposed methodology an attractive tool for the analysis and modeling of multiunit recordings from neuronal systems in a practical context

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