Journal article
A common space approach to comparative neuroscience
- Abstract:
- Comparative neuroscience is entering the era of big data. New high-throughput methods and data-sharing initiatives have resulted in the availability of large, digital data sets containing many types of data from ever more species. Here, we present a framework for exploiting the new possibilities offered. The multimodality of the data allows vertical translations, which are comparisons of different aspects of brain organization within a single species and across scales. Horizontal translations compare particular aspects of brain organization across species, often by building abstract feature spaces. Combining vertical and horizontal translations allows for more sophisticated comparisons, including relating principles of brain organization across species by contrasting horizontal translations, and for making formal predictions of unobtainable data based on observed results in a model species.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
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(Preview, Accepted manuscript, 1.0MB, Terms of use)
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- Publisher copy:
- 10.1146/annurev-neuro-100220-025942
Authors
- Publisher:
- Annual Reviews
- Journal:
- Annual Review of Neuroscience More from this journal
- Volume:
- 44
- Publication date:
- 2021-02-03
- Acceptance date:
- 2020-11-23
- DOI:
- EISSN:
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1545-4126
- ISSN:
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0147-006X
- Language:
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English
- Pubs id:
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1162443
- Local pid:
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pubs:1162443
- Deposit date:
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2021-02-25
Terms of use
- Copyright date:
- 2021
- Notes:
- This is the submitted manuscript version of the article. The final published version is available from Annual Reviews at https://doi.org/10.1146/annurev-neuro-100220-025942
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