Paper
8 June 2007 Living ordered neural networks as model systems for signal processing
C. Villard, P. O. Amblard, G. Becq, S. Gory-Faure, J. Brocard, S. Roth
Author Affiliations +
Proceedings Volume 6602, Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems; 660215 (2007) https://doi.org/10.1117/12.724652
Event: SPIE Fourth International Symposium on Fluctuations and Noise, 2007, Florence, Italy
Abstract
Neural circuit architecture is a fundamental characteristic of the brain, and how architecture is bound to biological functions is still an open question. Some neuronal geometries seen in the retina or the cochlea are intriguing: information is processed in parallel by several entities like in "pooling" networks which have recently drawn the attention of signal processing scientists. These systems indeed exhibit the noise-enhanced processing effect, which is also actively discussed in the neuroscience community at the neuron scale. The aim of our project is to use in-vitro ordered neuron networks as living paradigms to test ideas coming from the computational science. The different technological bolts that have to be solved are enumerated and the first results are presented. A neuron is a polarised cell, with an excitatory axon and a receiving dendritic tree. We present how soma confinement and axon differentiation can be induced by surface functionalization techniques. The recording of large neuron networks, ordered or not, is also detailed and biological signals shown. The main difficulty to access neural noise in the case of weakly connected networks grown on micro electrode arrays is explained. This open the door to a new detection technology suitable for sub-cellular analysis and stimulation, whose development will constitute the next step of this project.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
C. Villard, P. O. Amblard, G. Becq, S. Gory-Faure, J. Brocard, and S. Roth "Living ordered neural networks as model systems for signal processing", Proc. SPIE 6602, Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems, 660215 (8 June 2007); https://doi.org/10.1117/12.724652
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KEYWORDS
Neurons

Electrodes

Signal processing

Neural networks

Systems modeling

Axons

Silicon

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