Cargando…
Free Energy and Dendritic Self-Organization
In this paper, we pursue recent observations that, through selective dendritic filtering, single neurons respond to specific sequences of presynaptic inputs. We try to provide a principled and mechanistic account of this selectivity by applying a recent free-energy principle to a dendrite that is im...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Research Foundation
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3190184/ https://www.ncbi.nlm.nih.gov/pubmed/22013413 http://dx.doi.org/10.3389/fnsys.2011.00080 |
_version_ | 1782213547186454528 |
---|---|
author | Kiebel, Stefan J. Friston, Karl J. |
author_facet | Kiebel, Stefan J. Friston, Karl J. |
author_sort | Kiebel, Stefan J. |
collection | PubMed |
description | In this paper, we pursue recent observations that, through selective dendritic filtering, single neurons respond to specific sequences of presynaptic inputs. We try to provide a principled and mechanistic account of this selectivity by applying a recent free-energy principle to a dendrite that is immersed in its neuropil or environment. We assume that neurons self-organize to minimize a variational free-energy bound on the self-information or surprise of presynaptic inputs that are sampled. We model this as a selective pruning of dendritic spines that are expressed on a dendritic branch. This pruning occurs when postsynaptic gain falls below a threshold. Crucially, postsynaptic gain is itself optimized with respect to free energy. Pruning suppresses free energy as the dendrite selects presynaptic signals that conform to its expectations, specified by a generative model implicit in its intracellular kinetics. Not only does this provide a principled account of how neurons organize and selectively sample the myriad of potential presynaptic inputs they are exposed to, but it also connects the optimization of elemental neuronal (dendritic) processing to generic (surprise or evidence-based) schemes in statistics and machine learning, such as Bayesian model selection and automatic relevance determination. |
format | Online Article Text |
id | pubmed-3190184 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Frontiers Research Foundation |
record_format | MEDLINE/PubMed |
spelling | pubmed-31901842011-10-19 Free Energy and Dendritic Self-Organization Kiebel, Stefan J. Friston, Karl J. Front Syst Neurosci Neuroscience In this paper, we pursue recent observations that, through selective dendritic filtering, single neurons respond to specific sequences of presynaptic inputs. We try to provide a principled and mechanistic account of this selectivity by applying a recent free-energy principle to a dendrite that is immersed in its neuropil or environment. We assume that neurons self-organize to minimize a variational free-energy bound on the self-information or surprise of presynaptic inputs that are sampled. We model this as a selective pruning of dendritic spines that are expressed on a dendritic branch. This pruning occurs when postsynaptic gain falls below a threshold. Crucially, postsynaptic gain is itself optimized with respect to free energy. Pruning suppresses free energy as the dendrite selects presynaptic signals that conform to its expectations, specified by a generative model implicit in its intracellular kinetics. Not only does this provide a principled account of how neurons organize and selectively sample the myriad of potential presynaptic inputs they are exposed to, but it also connects the optimization of elemental neuronal (dendritic) processing to generic (surprise or evidence-based) schemes in statistics and machine learning, such as Bayesian model selection and automatic relevance determination. Frontiers Research Foundation 2011-10-11 /pmc/articles/PMC3190184/ /pubmed/22013413 http://dx.doi.org/10.3389/fnsys.2011.00080 Text en Copyright © 2011 Kiebel and Friston. http://www.frontiersin.org/licenseagreement This is an open-access article subject to a non-exclusive license between the authors and Frontiers Media SA, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and other Frontiers conditions are complied with. |
spellingShingle | Neuroscience Kiebel, Stefan J. Friston, Karl J. Free Energy and Dendritic Self-Organization |
title | Free Energy and Dendritic Self-Organization |
title_full | Free Energy and Dendritic Self-Organization |
title_fullStr | Free Energy and Dendritic Self-Organization |
title_full_unstemmed | Free Energy and Dendritic Self-Organization |
title_short | Free Energy and Dendritic Self-Organization |
title_sort | free energy and dendritic self-organization |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3190184/ https://www.ncbi.nlm.nih.gov/pubmed/22013413 http://dx.doi.org/10.3389/fnsys.2011.00080 |
work_keys_str_mv | AT kiebelstefanj freeenergyanddendriticselforganization AT fristonkarlj freeenergyanddendriticselforganization |