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Plos One : Synaptic State Matching ; a Dynamical Architecture for Predictive Internal Representation and Feature Detection, Volume 8

By Hamed, Suliann Ben

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Book Id: WPLBN0003967363
Format Type: PDF eBook :
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Reproduction Date: 2015

Title: Plos One : Synaptic State Matching ; a Dynamical Architecture for Predictive Internal Representation and Feature Detection, Volume 8  
Author: Hamed, Suliann Ben
Volume: Volume 8
Language: English
Subject: Journals, Science, Medical Science
Collections: Periodicals: Journal and Magazine Collection (Contemporary)
Historic
Publication Date:
Publisher: Plos

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Hamed, S. B. (n.d.). Plos One : Synaptic State Matching ; a Dynamical Architecture for Predictive Internal Representation and Feature Detection, Volume 8. Retrieved from http://netlibrary.net/


Description
Description : Here we explore the possibility that a core function of sensory cortex is the generation of an internal simulation of sensory environment in real-time. A logical elaboration of this idea leads to a dynamical neural architecture that oscillates between two fundamental network states, one driven by external input, and the other by recurrent synaptic drive in the absence of sensory input. Synaptic strength is modified by a proposed synaptic state matching (SSM) process that ensures equivalence of spike statistics between the two network states. Remarkably, SSM, operating locally at individual synapses, generates accurate and stable network-level predictive internal representations, enabling pattern completion and unsupervised feature detection from noisy sensory input. SSM is a biologically plausible substrate for learning and memory because it brings together sequence learning, feature detection, synaptic homeostasis, and network oscillations under a single unifying computational framework.

 

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