Identification of Neuronal Networks from Calcium Oscillation Data

Varanasi, Santhosh Kumar and Swain, Sarpras and Giri, Lopamudra and Jampana, Phanindra Varma (2019) Identification of Neuronal Networks from Calcium Oscillation Data. IFAC-PapersOnLine, 52 (1). pp. 544-549. ISSN 24058963

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Neuronal network reconstruction is an important problem in neuroscience as it helps understanding neuronal circuit and function. With the advancements of the calcium imaging technique, the dynamic activity of hundreds of neurons can be observed, which also provides a foundation for modelling and inferring network connectivity directly from data. In this paper, the dynamic behavior of each neuron is described using a non-linear autoregressive exogenous input (NARX) model. Since the neurons are inter-connected, the NARX models contain inputs which depend on outputs of the surrounding neurons. The complete model is expressed in a linear-in-parameter form and the network dynamics are identified by obtaining a block-sparse solution given the calcium oscillation data. The solution to the identification problem also provides the network topology simultaneously, i.e., the physical connections between the neurons. To demonstrate the accuracy of the proposed method, two experimental case studies are considered and the results are compared with other network identification methods.

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IITH Creators:
IITH CreatorsORCiD
Giri, Lopamudra
Jampana, Phanindra Varma
Item Type: Article
Uncontrolled Keywords: Block orthogonal matching pursuit, Calcium oscillations, NARX models, Neuronal networks, Sparse optimization
Subjects: Chemical Engineering
Divisions: Department of Chemical Engineering
Depositing User: Team Library
Date Deposited: 26 Aug 2019 05:39
Last Modified: 26 Aug 2019 05:39
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