Publication Type:

Conference Paper

Source:

Proceedings of the International Conference on Signal, Networks, Computing, and Systems, Springer India, Volume 396, New Delhi, p.57-66 (2016)

ISBN:

9788132235897

URL:

https://link.springer.com/chapter/10.1007%2F978-81-322-3589-7_6

Abstract:

In this paper, we implemented a virtual laboratory of neurons and synapses via dynamical models on a web-based platform to aid neurophysiology and computational neuroscience education. Online labs are one of the best alternatives to many universities confronting socio-economic issues in maintaining infrastructure for good laboratory practice. The neural network virtual laboratory was implemented using HTML5 and JQuery, which allowed users to access the lab as a browser-based app. The simulator allows reconstructions of population code and biophysics of single neuron firing dynamics and hence will allow experimentalists to explore its use for hypothesis-based predictions. Such tools as educational aids allow an interrelationship of cognitive, social, and teaching presence. We found students could easily reproduce the common voltage and current clamp protocols on such models without significant instructor assistance and the platform was developed to allow further extensions like raster plots, network computations using extensions to code modules. With new technologies, we foresee a potential redesign of the use of such virtual labs for large-scale modeling as teaching and learning tools in blended learning environments.

Notes:

cited By 0; Conference of International Conference on Signal, Networks, Computing, and Systems, ICSNCS 2016 ; Conference Date: 25 February 2016 Through 27 February 2016; Conference Code:185629

Cite this Research Publication

A. Sridharan, Sasidharakurup, H., Kumar, D., Nizar, N., Dr. Bipin G. Nair, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Implementing a Web-Based Simulator with Explicit Neuron and Synapse Models to Aid Experimental Neuroscience and Theoretical Biophysics Education”, in Proceedings of the International Conference on Signal, Networks, Computing, and Systems, New Delhi, 2016, vol. 396, pp. 57-66.

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