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Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences

The majority of distinct sensory and motor events occur as temporally ordered sequences with rich probabilistic structure. Sequences can be characterized by the probability of transitioning from the current state to upcoming states (forward probability), as well as the probability of having transiti...

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Autores principales: Bouchard, Kristofer E., Ganguli, Surya, Brainard, Michael S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4508839/
https://www.ncbi.nlm.nih.gov/pubmed/26257637
http://dx.doi.org/10.3389/fncom.2015.00092
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author Bouchard, Kristofer E.
Ganguli, Surya
Brainard, Michael S.
author_facet Bouchard, Kristofer E.
Ganguli, Surya
Brainard, Michael S.
author_sort Bouchard, Kristofer E.
collection PubMed
description The majority of distinct sensory and motor events occur as temporally ordered sequences with rich probabilistic structure. Sequences can be characterized by the probability of transitioning from the current state to upcoming states (forward probability), as well as the probability of having transitioned to the current state from previous states (backward probability). Despite the prevalence of probabilistic sequencing of both sensory and motor events, the Hebbian mechanisms that mold synapses to reflect the statistics of experienced probabilistic sequences are not well understood. Here, we show through analytic calculations and numerical simulations that Hebbian plasticity (correlation, covariance, and STDP) with pre-synaptic competition can develop synaptic weights equal to the conditional forward transition probabilities present in the input sequence. In contrast, post-synaptic competition can develop synaptic weights proportional to the conditional backward probabilities of the same input sequence. We demonstrate that to stably reflect the conditional probability of a neuron's inputs and outputs, local Hebbian plasticity requires balance between competitive learning forces that promote synaptic differentiation and homogenizing learning forces that promote synaptic stabilization. The balance between these forces dictates a prior over the distribution of learned synaptic weights, strongly influencing both the rate at which structure emerges and the entropy of the final distribution of synaptic weights. Together, these results demonstrate a simple correspondence between the biophysical organization of neurons, the site of synaptic competition, and the temporal flow of information encoded in synaptic weights by Hebbian plasticity while highlighting the utility of balancing learning forces to accurately encode probability distributions, and prior expectations over such probability distributions.
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spelling pubmed-45088392015-08-07 Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences Bouchard, Kristofer E. Ganguli, Surya Brainard, Michael S. Front Comput Neurosci Neuroscience The majority of distinct sensory and motor events occur as temporally ordered sequences with rich probabilistic structure. Sequences can be characterized by the probability of transitioning from the current state to upcoming states (forward probability), as well as the probability of having transitioned to the current state from previous states (backward probability). Despite the prevalence of probabilistic sequencing of both sensory and motor events, the Hebbian mechanisms that mold synapses to reflect the statistics of experienced probabilistic sequences are not well understood. Here, we show through analytic calculations and numerical simulations that Hebbian plasticity (correlation, covariance, and STDP) with pre-synaptic competition can develop synaptic weights equal to the conditional forward transition probabilities present in the input sequence. In contrast, post-synaptic competition can develop synaptic weights proportional to the conditional backward probabilities of the same input sequence. We demonstrate that to stably reflect the conditional probability of a neuron's inputs and outputs, local Hebbian plasticity requires balance between competitive learning forces that promote synaptic differentiation and homogenizing learning forces that promote synaptic stabilization. The balance between these forces dictates a prior over the distribution of learned synaptic weights, strongly influencing both the rate at which structure emerges and the entropy of the final distribution of synaptic weights. Together, these results demonstrate a simple correspondence between the biophysical organization of neurons, the site of synaptic competition, and the temporal flow of information encoded in synaptic weights by Hebbian plasticity while highlighting the utility of balancing learning forces to accurately encode probability distributions, and prior expectations over such probability distributions. Frontiers Media S.A. 2015-07-21 /pmc/articles/PMC4508839/ /pubmed/26257637 http://dx.doi.org/10.3389/fncom.2015.00092 Text en Copyright © 2015 Bouchard, Ganguli and Brainard. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Bouchard, Kristofer E.
Ganguli, Surya
Brainard, Michael S.
Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences
title Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences
title_full Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences
title_fullStr Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences
title_full_unstemmed Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences
title_short Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences
title_sort role of the site of synaptic competition and the balance of learning forces for hebbian encoding of probabilistic markov sequences
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4508839/
https://www.ncbi.nlm.nih.gov/pubmed/26257637
http://dx.doi.org/10.3389/fncom.2015.00092
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