This title appears in the Scientific Report :
2022
Please use the identifier:
http://dx.doi.org/10.1103/PhysRevLett.128.168301 in citations.
Please use the identifier: http://hdl.handle.net/2128/32544 in citations.
Gell-Mann–Low Criticality in Neural Networks
Gell-Mann–Low Criticality in Neural Networks
Criticality is deeply related to optimal computational capacity. The lack of a renormalized theory of critical brain dynamics, however, so far limits insights into this form of biological information processing to mean-field results. These methods neglect a key feature of critical systems: the inter...
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Personal Name(s): | Tiberi, Lorenzo (Corresponding author) |
---|---|
Stapmanns, Jonas / Kühn, Tobias / Luu, Thomas / Dahmen, David / Helias, Moritz | |
Contributing Institute: |
Computational and Systems Neuroscience; INM-6 Theorie der starken Wechselwirkung; IKP-3 Theorie der Starken Wechselwirkung; IAS-4 Theoretical Neuroscience; IAS-6 Jara-Institut Brain structure-function relationships; INM-10 |
Published in: | Physical review letters, 128 (2022) 16, S. 168301 |
Imprint: |
College Park, Md.
APS
2022
|
DOI: |
10.1103/PhysRevLett.128.168301 |
Document Type: |
Journal Article |
Research Program: |
Transparent Deep Learning with Renormalized Flows Human Brain Project Specific Grant Agreement 3 Neuroscientific Foundations |
Link: |
OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://hdl.handle.net/2128/32544 in citations.
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