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dc.contributor.advisorRajan, K
dc.contributor.authorKamal, Hassan
dc.date.accessioned2011-01-19T09:23:17Z
dc.date.accessioned2018-07-31T06:03:58Z
dc.date.available2011-01-19T09:23:17Z
dc.date.available2018-07-31T06:03:58Z
dc.date.issued2011-01-19
dc.date.submitted2009
dc.identifier.urihttps://etd.iisc.ac.in/handle/2005/1012
dc.description.abstractThe 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.en_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesG23600en_US
dc.subjectNeural Networks - Instrumentationen_US
dc.subjectNeuronal Networken_US
dc.subjectReal-time Neuronal Systemen_US
dc.subjectNeuronal Signalsen_US
dc.subjectHippocampal Neuronsen_US
dc.subjectNeuronal Correlationsen_US
dc.subjectMulti-electrode Array (MEA)en_US
dc.subjectEpileptic Neural Networken_US
dc.subjectHippocampal Neural Networksen_US
dc.subject.classificationComputer Scienceen_US
dc.titleNeuronal Correlations And Real-Time Implementation Of Spatio-Temporal Patterns Of Cultured Hippocampal Neural Networks in vitroen_US
dc.typeThesisen_US
dc.degree.nameMSc Enggen_US
dc.degree.levelMastersen_US
dc.degree.disciplineFaculty of Engineeringen_US


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