Flexible neural connectivity under constraints on total connection strength.
Neural computation is determined by neurons' dynamics and circuit connectivity. Uncertain and dynamic environments may require neural hardware to adapt to different computational tasks, each requiring different connectivity configurations. At the same time, connectivity is subject to a variety...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2020-08-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1008080 |
| _version_ | 1819021848076091392 |
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| author | Gabriel Koch Ocker Michael A Buice |
| author_facet | Gabriel Koch Ocker Michael A Buice |
| author_sort | Gabriel Koch Ocker |
| collection | DOAJ |
| description | Neural computation is determined by neurons' dynamics and circuit connectivity. Uncertain and dynamic environments may require neural hardware to adapt to different computational tasks, each requiring different connectivity configurations. At the same time, connectivity is subject to a variety of constraints, placing limits on the possible computations a given neural circuit can perform. Here we examine the hypothesis that the organization of neural circuitry favors computational flexibility: that it makes many computational solutions available, given physiological constraints. From this hypothesis, we develop models of connectivity degree distributions based on constraints on a neuron's total synaptic weight. To test these models, we examine reconstructions of the mushroom bodies from the first instar larva and adult Drosophila melanogaster. We perform a Bayesian model comparison for two constraint models and a random wiring null model. Overall, we find that flexibility under a homeostatically fixed total synaptic weight describes Kenyon cell connectivity better than other models, suggesting a principle shaping the apparently random structure of Kenyon cell wiring. Furthermore, we find evidence that larval Kenyon cells are more flexible earlier in development, suggesting a mechanism whereby neural circuits begin as flexible systems that develop into specialized computational circuits. |
| first_indexed | 2024-12-21T04:13:37Z |
| format | Article |
| id | doaj.art-a7951897f1244e279b535dede5683ddf |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-21T04:13:37Z |
| publishDate | 2020-08-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-a7951897f1244e279b535dede5683ddf2022-12-21T19:16:23ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582020-08-01168e100808010.1371/journal.pcbi.1008080Flexible neural connectivity under constraints on total connection strength.Gabriel Koch OckerMichael A BuiceNeural computation is determined by neurons' dynamics and circuit connectivity. Uncertain and dynamic environments may require neural hardware to adapt to different computational tasks, each requiring different connectivity configurations. At the same time, connectivity is subject to a variety of constraints, placing limits on the possible computations a given neural circuit can perform. Here we examine the hypothesis that the organization of neural circuitry favors computational flexibility: that it makes many computational solutions available, given physiological constraints. From this hypothesis, we develop models of connectivity degree distributions based on constraints on a neuron's total synaptic weight. To test these models, we examine reconstructions of the mushroom bodies from the first instar larva and adult Drosophila melanogaster. We perform a Bayesian model comparison for two constraint models and a random wiring null model. Overall, we find that flexibility under a homeostatically fixed total synaptic weight describes Kenyon cell connectivity better than other models, suggesting a principle shaping the apparently random structure of Kenyon cell wiring. Furthermore, we find evidence that larval Kenyon cells are more flexible earlier in development, suggesting a mechanism whereby neural circuits begin as flexible systems that develop into specialized computational circuits.https://doi.org/10.1371/journal.pcbi.1008080 |
| spellingShingle | Gabriel Koch Ocker Michael A Buice Flexible neural connectivity under constraints on total connection strength. PLoS Computational Biology |
| title | Flexible neural connectivity under constraints on total connection strength. |
| title_full | Flexible neural connectivity under constraints on total connection strength. |
| title_fullStr | Flexible neural connectivity under constraints on total connection strength. |
| title_full_unstemmed | Flexible neural connectivity under constraints on total connection strength. |
| title_short | Flexible neural connectivity under constraints on total connection strength. |
| title_sort | flexible neural connectivity under constraints on total connection strength |
| url | https://doi.org/10.1371/journal.pcbi.1008080 |
| work_keys_str_mv | AT gabrielkochocker flexibleneuralconnectivityunderconstraintsontotalconnectionstrength AT michaelabuice flexibleneuralconnectivityunderconstraintsontotalconnectionstrength |