Computationally efficient bio-realistic reconstructions of cerebellar neuron spiking patterns

Chaitanya Medini, Asha Vijayan, Egidio D'Angelo, Bipin Nair, Shyam Diwakar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Simple spiking models have been known to replicate detailed mathematical models firing properties with reliable accuracy in spike timing. We modified the adaptive exponential integrate and fire mathematical model to reconstruct different cerebellar neuronal firing patterns. We were able to reconstruct the firing dynamics of various types of cerebellar neurons and validated with previously published experimental studies. To model the neurons, we exploited particle swarm optimization to fit the parameters. The study showcases the match of electro-responsiveness of the neuronal models to data from biological neurons. Results suggest that models are close reconstructions of the biological data since frequency and spike-timing closely matched known values and were similar to those in previously published detailed computationally intensive biophysical models. Such spiking models have a number of applications including design of large-scale circuit models in order to understand physiological dysfunction and for various computational advantages.

Original languageEnglish
Title of host publicationProceedings of International Conference on Interdisciplinary Advances in Applied Computing, ICONIAAC 2014
PublisherAssociation for Computing Machinery
Volume10-11-October-2014
ISBN (Electronic)9781450329088
DOIs
Publication statusPublished - Oct 10 2014
Event2014 International Conference on Interdisciplinary Advances in Applied Computing, ICONIAAC 2014 - Coimbatore, India
Duration: Oct 10 2014Oct 11 2014

Other

Other2014 International Conference on Interdisciplinary Advances in Applied Computing, ICONIAAC 2014
Country/TerritoryIndia
CityCoimbatore
Period10/10/1410/11/14

Keywords

  • Cerebellum
  • Computational neuroscience
  • Integrate and fire model
  • Neurons

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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