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Many top-down frameworks for understanding neural computation boil down to assuming that the brain simply optimizes a single, given cost function for a single computational architecture.
“Interestingly, many of the “top down” frameworks boil down to assuming that the brain simply optimizes a single, given cost function for a single computational architecture.”
From Toward an integration of deep learning and neuroscience (2016) · cites this paper as Pinker, 1999
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- Authors
- PINKER, S.
- Affiliations
- Massachusetts Institute of Technology (US)
- Corresponding author
- PINKER, STEVEN
- ORCID
- PINKER, STEVEN
- Venue
- Annals of the New York Academy of Sciences
- Publisher
- Wiley
- Published
- 1999-06
- Volume
- 882
- Issue
- 1
- Pages
- 119-127
- ISSN
- 0077-8923 (ISSN-L)
- 1749-6632
- OpenAlex
- W2133735566
- Cited by
- 3,738
- References
- 0
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 10 · 2023: 8 · 2022: 8 · 2021: 52 · 2020: 84 · 2019: 92 · 2018: 115 · 2017: 128 · 2016: 122 · 2015: 161 · 2014: 198 · 2013: 191 · 2012: 220
- FWCI
- 305.11
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Annals of the New York Academy of Sciences (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Philosophy and Theoretical Science
- Life Sciences › Neuroscience › Cognitive Neuroscience › Cognitive Science and Education Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- mind, cognition, cognitive processes, neuroscience of cognition
- MeSH terms
- Brain, Cognition, Humans, Mental Processes, Thinking, Vision, Ocular
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