From internal models toward metacognitive AI.
- Published in:
- Biological Cybernetics, 2021, v. 115, n. 5, p. 415, doi. 10.1007/s00422-021-00904-7
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- Publication type:
- Article
Works matching IS 03401200 AND DT 2021 AND VI 115 AND IP 5
Results: 8
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Toward understanding the neural code of the brain.
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- Biological Cybernetics, 2021, v. 115, n. 5, p. 439, doi. 10.1007/s00422-021-00903-8
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- Article
3
Mapping input noise to escape noise in integrate-and-fire neurons: a level-crossing approach.
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- Biological Cybernetics, 2021, v. 115, n. 5, p. 539, doi. 10.1007/s00422-021-00899-1
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- Article
4
Global entrainment in the brain–body–environment: retrospective and prospective views.
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- Biological Cybernetics, 2021, v. 115, n. 5, p. 431, doi. 10.1007/s00422-021-00898-2
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- Article
5
Excitable networks for finite state computation with continuous time recurrent neural networks.
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- Biological Cybernetics, 2021, v. 115, n. 5, p. 519, doi. 10.1007/s00422-021-00895-5
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- Publication type:
- Article
6
Comprehensive characterization of oscillatory signatures in a model circuit with PV- and SOM-expressing interneurons.
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- Biological Cybernetics, 2021, v. 115, n. 5, p. 487, doi. 10.1007/s00422-021-00894-6
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- Article
7
A dynamic neural field model of continuous input integration.
- Published in:
- Biological Cybernetics, 2021, v. 115, n. 5, p. 451, doi. 10.1007/s00422-021-00893-7
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- Publication type:
- Article
8
Flexible prediction of opponent motion with internal representation in interception behavior.
- Published in:
- Biological Cybernetics, 2021, v. 115, n. 5, p. 473, doi. 10.1007/s00422-021-00891-9
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- Publication type:
- Article