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Morphology and Synaptic Characteristics Based Prediction of Visual Cortex Spike Properties for Different Functions


Venkateswaran Nagarajan (WAran Research FoundaTion), Vignesh Saptarishi Ramesh (Charaka Group - Computational Neuroscience, WAran Research FoundaTion), Ramprakash Srinivasan (Charaka Group - Computational Neuroscience, WAran Research FoundaTion), Dinesh Kannan Kabaleeswaran (Charaka Group - Computational Neuroscience, WAran Research FoundaTion), Vishal Raghu (Charaka Group - Computational Neuroscience, WAran Research FoundaTion), Sharan Srinivas Jagathrakshakan (Charaka Group - Computational Neuroscience, WAran Research FoundaTion), Sharath Navalpakkam Krishnan (Charaka Group - Computational Neuroscience, WAran Research FoundaTion), Thiagarajan Thirupatchur Sanjayasarathy (Charaka Group - Computational Neuroscience, WAran Research FoundaTion)

The need to improve understanding of cortical organization dependent functioning of visualcortex actuated this initiative where we are trying to establish a relationship across functions defined by visualcortex(edge detection,segment analysis,orientation specificity,motion processing)& morphological properties including dendritic arborization,soma geometry & synapse characteristics of regions involved in discharging these functions.Computer architectures like VonNeumann or Harvard model have separate memory for instructions & data & standalone functional units unlike the brain where the synapse with plasticity in addition to laying a foundation for long term & short term memory also plays a major role in functional aspects.Existing synapse models have accounted for synapse characteristics like plasticity only for single synapse whereas plasticity study for network of synapses & neurons has been minimal.We define RegionalSynapticPlasticity(RSP) for network of neurons which is essential to link synapse characteristics to functions performed by specific network through spatiotemporal spike distribution.Linking morphology & spike activity for single neuron is brought about by modeling postsynaptic current as stochastic function of concentration of neurotransmitter,state of receptors,membrane reversal potential,among structural parameters including dendritic spanning & synaptic geometry.Further improvements can be done by capturing spike activity of network as function of intracellular parameters1.This single neuron model is extended to network of neurons using ChapmanKolmogorov equation to relate independent probability densities which under appropriate assumptions is reduced to PDE thereby establishing link between RSP,morphology & spike activity of the network.The relationship is established independently for each region of the visualcortex by varying parameters for the network from empirical data.With this relationship an ongoing investigation is undertaken to link morphology & spike activity of separate regions of visualcortex to the functions they are responsible for, which can help in the fundamental understanding of visualcortex.We believe that this understanding of synapse & morphology can also contribute in replacing current VonNeumann & Harvard computer models with more efficient brain-inspired ones.
1:Venkateswaran,et al Energetics based spike generation of a single neuron:simulation results & analysis Front.Neuroenerg4:2doi10.3389/fnene.2012.00002
Preferred presentation format: Poster
Topic: Computational neuroscience