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An Open-source Computational Neuroscience Virtual Laboratory Tool for Simulating Spiking neurons and Circuits

Publication Type : Conference Paper

Thematic Areas : Biotech, Learning-Technologies, Medical Sciences

Publisher : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

Source : 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, Udupi, India (2017)

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Keywords : Adaptation models, adaptive exponential model, animal nervous systems, Biological system modeling, Brain models, circuit dynamics modeling, circuits simulation, computational modeling, data visualisation, digital simulation, educational tools, Graphical user interfaces, GUI, Hodgkin-Huxley model, HTML5, hypothesis testing, Integrate and Fire Model, Integrated circuit modeling, Izhikevich model, Java, Javascript, large-scale neural networks, mathematical model, neural nets, neurological disorders prediction, neuronal dynamics, neuronal models, Neurons, Neurophysiology, open-source computational neuroscience virtual laboratory tool, physiological data, public domain software, Python, real-time simulations, single neuron responses, small-scale network dynamics, spatiotemporal computations, spatiotemporal phenomena, spiking neurons simulation, Visualization, Web technology, zoology .

Campus : Amritapuri

School : School of Biotechnology

Center : Amrita Mind Brain Center, Biotechnology, Computational Neuroscience and Neurophysiology

Department : biotechnology, Computational Neuroscience Laboratory

Year : 2017

Abstract : Neuronal models and real-time simulations of large-scale neural networks allow hypothesis testing of physiological data and for predicting neurological disorders. Simulators using web technologies serve as educational tools in addition to allowing experimentalists make predictions on experimental hypotheses. In this paper, we have developed a web-based neuron and network simulator to model spatio-temporal computations in animal nervous systems. Neuronal models including Hodgkin-Huxley (HH), Adaptive Exponential (AdEx) integrate and fire model and Izhikevich model were incorporated. All models were implemented using JavaScript and python with visualization using HTML5. Single neuron responses and a small-scale network dynamics corresponding to experimentally-known stimuli patterns were simulated. The simulator allows configuring neuronal dynamics through the GUI and can also allow modeling complex dynamics by interfacing with BRIAN for more large-scale and complex simulations. This web technology-based simulation environment may be used by neurophysiologists to simulate experimental protocols and modeling simple circuit dynamics with or without backend programming.

Cite this Research Publication : J. Alphonse, Chaitanya Medini, Dr. Bipin G. Nair, and Dr. Shyam Diwakar, “An open-source computational neuroscience virtual laboratory tool for simulating spiking neurons and circuits”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Udupi, India, 2017

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