Single Neuron Development - A Neurogenesis Inspired Structure Generation Model

Venkateswaran Nagarajan (Director, WAran Research FoundaTion), Dinesh Kannan Kabaleeswaran (Computational Neuroscience, WARFT), Vignesh SR (Computational Neuroscience, WARFT), Subbu Ramanathan (Computational Neuroscience, WARFT), Sharan Srinivas Jagathrakshakan (Computational Neuroscience, WARFT), Narendran Narayanasamy (Computational Neuroscience, WARFT), Sudarshan Sekhar (Computational Neuroscience, WARFT), Sharath Navalpakkam Krishnan (Computational Neuroscience, WARFT), T.S. Thiagarajan (Computational Neuroscience, WARFT)

Increasing concerns have sparked off advanced, significant research being directed towards the diagnosis and treatment of developmental brain disorders like dyslexia, autism and microcephaly. Our current research at WARFT cardinally focuses on building a simulation model which encompasses an ensemble of molecular signaling pathways and mechanisms responsible for the development of the cell body, cytokinesis, neurite out-growth, dendritic and axon guidance, formation of spines and synapses for a single neuron and extending it to a network of neurons during the natal stages. In this poster, we propose a novel biologically realistic single neuron Neurogenesis Inspired Structure Generation model that incorporates the above mentioned. Primordially, an integrated structure-generation model for a single neuron is developed from a model-set that separately models the soma, dendrites, axon and synapses' geometrical properties like dimension, position, distribution, arborization and kinematic properties through their biochemical pathways and biophysical mechanisms. The mathematical equations governing the transitions between the molecules are modeled using the Michaelis-Menten kinetics, Fokker-Planck diffusion equation and first order differential equations depending upon the dynamics of the reaction. The transitions between the biophysical-biochemical and the geometrical parameters are governed by powerful activity-dependent heuristics which have been framed after an extensive and comprehensive study of experimental data. Due emphasis is given to actin and microtubule cytoskeletal stability and molecules involved in migratory guidance as these are the two main categories which cause developmental brain disorders (Pilz et. al. 2002). The polymerization and de-polymerization reactions of the actin and microtubule filaments are coupled with the force-velocity equation of growing neurites to identify the axon from the set of growing neurites.Our newfangled work in energetics based simulations established a robust link between the spike-activity characteristics of a single neuron to the intra-cellular energetics parameters leading to fine changes in the dynamics of mitochondria being reflected in the concomitant voltage-spike response (Venkateswaran et. al. 2010).The ensuing phase of the model integrates the anatomical aspects powered by neurogenesis and intra-cellular dynamics of the neuron by linking it through the physiological activity of voltage-gated ion channels. This nexus would ultimately pave way to a discursive and powerful model which captures the anatomical, physiological and intra-cellular energetic parameters of a single neuron during its various stages of natal development. It is also critical to extend the model to a network of neurons to help us identify axon and dendritic curvature and distribution of synapses which are crucial parameters to analyze developmental disorders at a large scale inter-processing level.This Neurogenesis Inspired Structure Generation model integrated with the voltage spike-intra cellular energetics has not been proposed before and adds a powerful dimension to model brain developmental disorders, which, with massive collaboration between computational and clinical neuroscientists can lead to drug testing and discovery in a non-invasive environment. Parallel research  at WARFT to combat challenges of brain developmental disorders is to develop a model characterized by changes in the genetic sequence being mapped to the myriad signaling pathways that affect the physiological and geometrical properties of the neuron during natal development.


Pilz, D., N. Stoodley and J.A. Golden. 2002. Neuronal migration, cerebral cortical development, and cerebral cortical anomalies. J. Neuropathol. Exp. Neurol. 61:1-11.

Venkateswaran Nagarajan, et. al. 2010. Energetics based simulation of large-scale 3D neuronal network: Energetics-Based models. 3rd INCF Congress of Neuroinformatics 2010, Kobe, Japan.

Preferred presentation format: Poster
Topic: Computational neuroscience

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