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Quantifying stimulus information in spike trains during plasticity

Publication Type : Poster

Thematic Areas : Biotech, Learning-Technologies, Medical Sciences

Publisher : INCF workshop, India .

Source : INCF workshop, India (2012)

Keywords : Spiking time-dependent plasticity, Neural code, Predictions, Neural adaptation, Synchronization.

Campus : Amritapuri

School : School of Biotechnology, Department of Computer Science and Engineering, School of Engineering

Center : Amrita Mind Brain Center, Biotechnology, Computational Neuroscience and Neurophysiology

Department : Computer Science, biotechnology, Computational Neuroscience Laboratory

Year : 2012

Abstract : Latency reduction in postsynaptic spikes is a well-known effect of spiking time-dependent plasticity. We expand this notion for long postsynaptic spike trains on single neurons, showing that, for a fixed input spike train, STDP reduces the number of postsynaptic spikes and concentrates the remaining ones. Then, we study the consequences of this phenomena in terms of coding, finding that this mechanism improves the neural code by increasing the signal-to-noise ratio and lowering the metabolic costs of frequent stimuli. Finally, we illustrate that the reduction in postsynaptic latencies can lead to the emergence of predictions.

Cite this Research Publication : Parasuram H. and Dr. Shyam Diwakar, “Constraining extracellular matrix by modeling local field potential”, in INCF workshop, India, 2012.

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