Nanoconnectomic upper bound on the variability of synaptic plasticity
Information in a computer is quantified by the number of bits that can be stored and recovered. An important question about the brain is how much information can be stored at a synapse through synaptic plasticity, which depends on the history of probabilistic synaptic activity. The strong correlatio...
| Main Authors: | , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
eLife Sciences Publications, Ltd.
2016
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| Online Access: | http://hdl.handle.net/1721.1/101021 |
| _version_ | 1826192091472986112 |
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| author | Bromer, Cailey Kinney, Justin Bartol, Thomas M. Chirillo, Michael A. Bourne, Jennifer N. Harris, Kristen M. Sejnowski, Terrence J. |
| author2 | Massachusetts Institute of Technology. Media Laboratory |
| author_facet | Massachusetts Institute of Technology. Media Laboratory Bromer, Cailey Kinney, Justin Bartol, Thomas M. Chirillo, Michael A. Bourne, Jennifer N. Harris, Kristen M. Sejnowski, Terrence J. |
| author_sort | Bromer, Cailey |
| collection | MIT |
| description | Information in a computer is quantified by the number of bits that can be stored and recovered. An important question about the brain is how much information can be stored at a synapse through synaptic plasticity, which depends on the history of probabilistic synaptic activity. The strong correlation between size and efficacy of a synapse allowed us to estimate the variability of synaptic plasticity. In an EM reconstruction of hippocampal neuropil we found single axons making two or more synaptic contacts onto the same dendrites, having shared histories of presynaptic and postsynaptic activity. The spine heads and neck diameters, but not neck lengths, of these pairs were nearly identical in size. We found that there is a minimum of 26 distinguishable synaptic strengths, corresponding to storing 4.7 bits of information at each synapse. Because of stochastic variability of synaptic activation the observed precision requires averaging activity over several minutes. |
| first_indexed | 2024-09-23T09:06:08Z |
| format | Article |
| id | mit-1721.1/101021 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:06:08Z |
| publishDate | 2016 |
| publisher | eLife Sciences Publications, Ltd. |
| record_format | dspace |
| spelling | mit-1721.1/1010212022-09-26T10:29:56Z Nanoconnectomic upper bound on the variability of synaptic plasticity Bromer, Cailey Kinney, Justin Bartol, Thomas M. Chirillo, Michael A. Bourne, Jennifer N. Harris, Kristen M. Sejnowski, Terrence J. Massachusetts Institute of Technology. Media Laboratory McGovern Institute for Brain Research at MIT Kinney, Justin Information in a computer is quantified by the number of bits that can be stored and recovered. An important question about the brain is how much information can be stored at a synapse through synaptic plasticity, which depends on the history of probabilistic synaptic activity. The strong correlation between size and efficacy of a synapse allowed us to estimate the variability of synaptic plasticity. In an EM reconstruction of hippocampal neuropil we found single axons making two or more synaptic contacts onto the same dendrites, having shared histories of presynaptic and postsynaptic activity. The spine heads and neck diameters, but not neck lengths, of these pairs were nearly identical in size. We found that there is a minimum of 26 distinguishable synaptic strengths, corresponding to storing 4.7 bits of information at each synapse. Because of stochastic variability of synaptic activation the observed precision requires averaging activity over several minutes. 2016-01-28T02:34:01Z 2016-01-28T02:34:01Z 2015-11 2015-08 Article http://purl.org/eprint/type/JournalArticle 2050-084X http://hdl.handle.net/1721.1/101021 Bartol, Thomas M, Cailey Bromer, Justin Kinney, Michael A Chirillo, Jennifer N Bourne, Kristen M Harris, and Terrence J Sejnowski. “Nanoconnectomic Upper Bound on the Variability of Synaptic Plasticity.” eLife 4 (November 30, 2015). en_US http://dx.doi.org/10.7554/eLife.10778 eLife Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ application/pdf eLife Sciences Publications, Ltd. eLife Sciences Publications, Ltd. |
| spellingShingle | Bromer, Cailey Kinney, Justin Bartol, Thomas M. Chirillo, Michael A. Bourne, Jennifer N. Harris, Kristen M. Sejnowski, Terrence J. Nanoconnectomic upper bound on the variability of synaptic plasticity |
| title | Nanoconnectomic upper bound on the variability of synaptic plasticity |
| title_full | Nanoconnectomic upper bound on the variability of synaptic plasticity |
| title_fullStr | Nanoconnectomic upper bound on the variability of synaptic plasticity |
| title_full_unstemmed | Nanoconnectomic upper bound on the variability of synaptic plasticity |
| title_short | Nanoconnectomic upper bound on the variability of synaptic plasticity |
| title_sort | nanoconnectomic upper bound on the variability of synaptic plasticity |
| url | http://hdl.handle.net/1721.1/101021 |
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