A common space approach to comparative neuroscience
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 off...
| Главные авторы: | , , |
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| Формат: | Journal article |
| Язык: | English |
| Опубликовано: |
Annual Reviews
2021
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| _version_ | 1826275945570369536 |
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| author | Mars, RB Jbabdi, S Rushworth, MFS |
| author_facet | Mars, RB Jbabdi, S Rushworth, MFS |
| author_sort | Mars, RB |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-06T23:06:32Z |
| format | Journal article |
| id | oxford-uuid:64034605-0865-465d-8a3b-d006b9485fd7 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T23:06:32Z |
| publishDate | 2021 |
| publisher | Annual Reviews |
| record_format | dspace |
| spelling | oxford-uuid:64034605-0865-465d-8a3b-d006b9485fd72022-03-26T18:16:25ZA common space approach to comparative neuroscienceJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:64034605-0865-465d-8a3b-d006b9485fd7EnglishSymplectic ElementsAnnual Reviews2021Mars, RBJbabdi, SRushworth, MFSComparative 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. |
| spellingShingle | Mars, RB Jbabdi, S Rushworth, MFS A common space approach to comparative neuroscience |
| title | A common space approach to comparative neuroscience |
| title_full | A common space approach to comparative neuroscience |
| title_fullStr | A common space approach to comparative neuroscience |
| title_full_unstemmed | A common space approach to comparative neuroscience |
| title_short | A common space approach to comparative neuroscience |
| title_sort | common space approach to comparative neuroscience |
| work_keys_str_mv | AT marsrb acommonspaceapproachtocomparativeneuroscience AT jbabdis acommonspaceapproachtocomparativeneuroscience AT rushworthmfs acommonspaceapproachtocomparativeneuroscience AT marsrb commonspaceapproachtocomparativeneuroscience AT jbabdis commonspaceapproachtocomparativeneuroscience AT rushworthmfs commonspaceapproachtocomparativeneuroscience |