Control of criticality and computation in spiking neuromorphic networks with plasticity
Designing efficient artificial networks able to quickly converge to optimal performance for a given task remains a challenge. Here, the authors demonstrate a relation between criticality, task-performance and information theoretic fingerprint in a spiking neuromorphic network with synaptic plasticit...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2020-06-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-020-16548-3 |
| _version_ | 1818851947546935296 |
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| author | Benjamin Cramer David Stöckel Markus Kreft Michael Wibral Johannes Schemmel Karlheinz Meier Viola Priesemann |
| author_facet | Benjamin Cramer David Stöckel Markus Kreft Michael Wibral Johannes Schemmel Karlheinz Meier Viola Priesemann |
| author_sort | Benjamin Cramer |
| collection | DOAJ |
| description | Designing efficient artificial networks able to quickly converge to optimal performance for a given task remains a challenge. Here, the authors demonstrate a relation between criticality, task-performance and information theoretic fingerprint in a spiking neuromorphic network with synaptic plasticity. |
| first_indexed | 2024-12-19T07:13:07Z |
| format | Article |
| id | doaj.art-fb7c0a50753d437fb6161c1380bc2dcd |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-12-19T07:13:07Z |
| publishDate | 2020-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-fb7c0a50753d437fb6161c1380bc2dcd2022-12-21T20:31:09ZengNature PortfolioNature Communications2041-17232020-06-0111111110.1038/s41467-020-16548-3Control of criticality and computation in spiking neuromorphic networks with plasticityBenjamin Cramer0David Stöckel1Markus Kreft2Michael Wibral3Johannes Schemmel4Karlheinz Meier5Viola Priesemann6Kirchhoff-Institute for Physics, Heidelberg UniversityKirchhoff-Institute for Physics, Heidelberg UniversityKirchhoff-Institute for Physics, Heidelberg UniversityCampus Institute for Dynamics of Biological Networks, Georg-August UniversityKirchhoff-Institute for Physics, Heidelberg UniversityKirchhoff-Institute for Physics, Heidelberg UniversityMax-Planck-Institute for Dynamics and Self-OrganizationDesigning efficient artificial networks able to quickly converge to optimal performance for a given task remains a challenge. Here, the authors demonstrate a relation between criticality, task-performance and information theoretic fingerprint in a spiking neuromorphic network with synaptic plasticity.https://doi.org/10.1038/s41467-020-16548-3 |
| spellingShingle | Benjamin Cramer David Stöckel Markus Kreft Michael Wibral Johannes Schemmel Karlheinz Meier Viola Priesemann Control of criticality and computation in spiking neuromorphic networks with plasticity Nature Communications |
| title | Control of criticality and computation in spiking neuromorphic networks with plasticity |
| title_full | Control of criticality and computation in spiking neuromorphic networks with plasticity |
| title_fullStr | Control of criticality and computation in spiking neuromorphic networks with plasticity |
| title_full_unstemmed | Control of criticality and computation in spiking neuromorphic networks with plasticity |
| title_short | Control of criticality and computation in spiking neuromorphic networks with plasticity |
| title_sort | control of criticality and computation in spiking neuromorphic networks with plasticity |
| url | https://doi.org/10.1038/s41467-020-16548-3 |
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