Artificial Neural Networks as Models of Neural Information Processing
| dc.contributor.author | Marcel van Gerven | * |
| dc.contributor.author | Sander Bohte | * |
| dc.date.accessioned | 2021-02-11T08:31:24Z | |
| dc.date.available | 2021-02-11T08:31:24Z | |
| dc.date.issued | 2018 | * |
| dc.date.submitted | 2018-11-16 17:17:57 | * |
| dc.identifier | 29633 | * |
| dc.identifier.issn | 16648714 | * |
| dc.identifier.uri | https://directory.doabooks.org/handle/20.500.12854/41357 | |
| dc.description.abstract | Modern neural networks gave rise to major breakthroughs in several research areas. In neuroscience, we are witnessing a reappraisal of neural network theory and its relevance for understanding information processing in biological systems. The research presented in this book provides various perspectives on the use of artificial neural networks as models of neural information processing. We consider the biological plausibility of neural networks, performance improvements, spiking neural networks and the use of neural networks for understanding brain function. | * |
| dc.language | English | * |
| dc.relation.ispartofseries | Frontiers Research Topics | * |
| dc.subject | RC321-571 | * |
| dc.subject | Q1-390 | * |
| dc.subject.classification | thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciences | en_US |
| dc.subject.other | brain imaging | * |
| dc.subject.other | artificial neural networks | * |
| dc.subject.other | deep learning | * |
| dc.subject.other | neural information processing | * |
| dc.subject.other | backpropagation | * |
| dc.subject.other | spiking neural networks | * |
| dc.title | Artificial Neural Networks as Models of Neural Information Processing | * |
| dc.type | book | |
| oapen.identifier.doi | 10.3389/978-2-88945-401-3 | * |
| oapen.relation.isPublishedBy | bf5ce210-e72e-4860-ba9b-c305640ff3ae | * |
| oapen.relation.isbn | 9782889454013 | * |
| oapen.pages | 220 | * |
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