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A Real-time clustering system for spatio-temporal signals from network of neurons

Hassan, Kamal and Rajan, K and Sikdar, Sujit K (2009) A Real-time clustering system for spatio-temporal signals from network of neurons. In: TENCON 2009-2009 IEEE Region 10 Conference, 23-26 Nov 2009, Singapore.

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Over past few years, the studies of cultured neuronal networks have 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 from rats are dissociated and cultured on a surface containing a grid of 64 electrodes. The signals from these 64 electrodes are acquired using a fast data acquisition system MED64 (Alpha MED Sciences, Japan) at a sampling rate of 20 K samples with a precision of 16-bits per sample. A few minutes of acquired data runs in to a few hundreds of Mega Bytes. The data processing for the neural analysis is highly compute-intensive because the volume of data is huge. The major processing requirements are noise removal, pattern recovery, pattern matching, clustering and so on. In order to interface a neuronal colony to a physical world, these computations need to be performed in real-time. A single processor such as a desk top computer may not be adequate to meet this computational requirements. Parallel computing is a method used to satisfy the real-time computational requirements of a neuronal system that interacts with an external world while increasing the flexibility and scalability of the application. In this work, we developed a parallel neuronal system using a multi-node Digital Signal processing system. With 8 processors, the system is able to compute and map incoming signals segmented over a period of 200 ms in to an action in a trained cluster system in real time.

Item Type: Conference Paper
Additional Information: Copyright 2009 IEEE. Personal use of this material is permitted.However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Physical & Mathematical Sciences > Physics
Depositing User: Ms TV Yashodha
Date Deposited: 16 Dec 2011 09:15
Last Modified: 16 Dec 2011 09:15
URI: http://eprints.iisc.ac.in/id/eprint/41193

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