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Please use this identifier to cite or link to this item: http://hdl.handle.net/2005/1012

Title: Neuronal Correlations And Real-Time Implementation Of Spatio-Temporal Patterns Of Cultured Hippocampal Neural Networks in vitro
Authors: Kamal, Hassan
Advisors: Rajan, K
Keywords: Neural Networks - Instrumentation
Neuronal Network
Real-time Neuronal System
Neuronal Signals
Hippocampal Neurons
Neuronal Correlations
Multi-electrode Array (MEA)
Epileptic Neural Network
Hippocampal Neural Networks
Submitted Date: Sep-2009
Series/Report no.: G23600
Abstract: The study of cultured neuronal networks has opened up avenues for understanding the ion channels, receptor molecules, and synaptic plasticity that may form the basis of learning and memory. The hippocampal neurons prepared from Wistar rats and put in culture, show, after a few days, spontaneous activity with typical electrophysiological pattern ranging from stochastic spiking to synchronized bursting. Using a multi-electrode array (MEA) having 64 electrodes, the electrophysiological signals are acquired, and connectivity maps are constructed using correlation matrix to understand how the neurons in a network communicate during the burst. The response of the neuronal system to epilepsy caused by induced glutamate injury and subsequent exposure of the system to phenobarbital to form different connectivity networks is analyzed in this study. The correlation matrix of the neuronal network before and after administering glutamate as well as after administering phenobarbital is used to understand the neuronal and network level changes that take place in the system. In order to interface a neuronal network to a physical world, the major computations to be performed are noise removal, pattern recovery, pattern matching and clustering. These computations are to be performed in real time. The system should be able to identify a pattern and relate a physical task to the pattern in about 200-400 ms. Algorithms have been developed for the implementation of a real-time neuronal system on a multi-node digital processor system.
URI: http://hdl.handle.net/2005/1012
Appears in Collections:Instrumentation (isu)

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