Statistical Dependence between Neuronal Spike Train Pairs: Quantification based on Empirical Mutual Information Rate

Ande, Sathish and Avasarala, Srinivas and Karunarathne, Ajith and Giri, Lopamudra and Jana, Soumya (2021) Statistical Dependence between Neuronal Spike Train Pairs: Quantification based on Empirical Mutual Information Rate. In: 2021 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2021, 27 July 2021 through 30 July 2021, Virtual, Online.

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Abstract

Statistical dependency between neuronal spike trains forms a basis for information encoding in memory and learning. The said dependency could also be a key to detecting pathologies. For instance, Alzheimer's disease has been associated with hyper-synchronicity, which indicates abnormally high statistical dependency. To study such dependency in depth, one requires its accurate quantification within short intervals in view of inherent time variations. However, existing Lempel-Ziv-based schemes tend to convergence slowly. In response, we propose its quantification based on empirical mutual information rate, which is shown to converge satisfactorily fast. In particular, fast convergence was demonstrated for simulated Markov processes as well as experimentally observed neuronal spike trains. Further, heterogeneity was observed in mutual information rate estimates and in process memory structures even within a few neuron pairs. In a large-scale study, more useful patterns will likely be observed, which can potentially emerge as disease signatures. The proposed statistical dependency estimator will also allow studies relating neuronal organization in physical networks and patterns of information processing. © 2021 IEEE

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IITH Creators:
IITH CreatorsORCiD
Giri, Lopamudrahttp://orcid.org/0000-0002-2352-7919
Jana, Soumyahttps://orcid.org/0000-0002-5880-4023
Item Type: Conference or Workshop Item (Paper)
Additional Information: V. ACKNOWLEDGMENT We thank Drs. Mennerick and Gautam for providing materials and equipment. Sathish Ande thanks the Ministry of Electronics and Information Technology, the Government of India, for fellowship grant under Visvesvaraya PhD Scheme.
Uncontrolled Keywords: Calcium imaging; Empirical probability; Mutual information rate; Spike train
Subjects: Chemical Engineering
Divisions: Department of Chemical Engineering
Department of Electrical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 30 Sep 2022 11:58
Last Modified: 30 Sep 2022 11:58
URI: http://raiithold.iith.ac.in/id/eprint/10749
Publisher URL: http://doi.org/10.1109/BHI50953.2021.9508584
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