Mathematical Modelling of Cerebellar Granular Layer Neurons and Network Activity: Information Estimation, Population Behaviour and Robotic Abstractions

  • Shyam DiwakarEmail author
  • Chaitanya Nutakki
  • Sandeep Bodda
  • Arathi Rajendran
  • Asha Vijayan
  • Bipin Nair
Part of the Springer INdAM Series book series (SINDAMS, volume 24)


Recent studies show cerebellum having a crucial role in motor coordination and cognition, and it has been observed that in patients with movement disorders and other neurological conditions cerebellar circuits are known to be affected. Simulations allow insight on how cerebellar granular layer processes spike information and to understand afferent information divergence in the cerebellar cortex. With excitation-inhibition ratios adapted from in vitro experimental data in the cerebellum granular layer, the model allows reconstructing spatial recoding of sensory and tactile patterns in cerebellum. Granular layer population activity reconstruction was performed with biophysical modeling of fMRI BOLD signals and evoked local field potentials from single neuron and network models implemented in NEURON environment. In this chapter, evoked local field potentials have been reconstructed using biophysical and neuronal mass models interpreting averaged activity and constraining population behavior as observed in experiments. Using neuronal activity and correlating blood flow using the balloon and modified Windkessel model, generated cerebellar granular layer BOLD response. With the focus of relating neural activity to clinical correlations such models help constraining network models and predicting activity-dependent emergent behavior and manifestations. To reverse engineering brain function, cerebellar circuit functions were abstracted into a spiking network based trajectory control model for robotic articulation.


Cerebellum Granular layer Mutual information Plasticity Local field potential fMRI BOLD Pattern 



This work derives direction and ideas from the Chancellor of Amrita University, Sri Mata Amritanandamayi Devi. Authors would like to acknowledge Egidio D’Angelo of University of Pavia, Giovanni Naldi and Thierry Nieus of University of Milan, for their support towards work in this manuscript. This work was supported by Grants SR/CSI/49/2010, SR/CSI/60/2011, SR/CSRI/60/2013, SR/CSRI/61/2014 and Indo-Italy POC 2012-2014 from DST, BT/PR5142/MED/30/764/2012 from DBT, and Sir Visveswaraya Faculty fellowship to SD from MeitY, Government of India and partially by Embracing the World.


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© Springer International Publishing AG, part of Springer Nature 2017

Authors and Affiliations

  • Shyam Diwakar
    • 1
    Email author
  • Chaitanya Nutakki
    • 1
  • Sandeep Bodda
    • 1
  • Arathi Rajendran
    • 1
  • Asha Vijayan
    • 1
  • Bipin Nair
    • 1
  1. 1.Amrita School of BiotechnologyAmrita Vishwa VidyapeethamKollamIndia

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