Dasgupta, S., Stevens, C. F., Navlakha, S. (November 2017) A neural algorithm for a fundamental computing problem. Science, 358 (6364). pp. 793-796. ISSN 0036-8075 (Public Dataset)
Abstract
Similarity search-for example, identifying similar images in a database or similar documents on the web-is a fundamental computing problem faced by large-scale information retrieval systems. We discovered that the fruit fly olfactory circuit solves this problem with a variant of a computer science algorithm (called locality-sensitive hashing). The fly circuit assigns similar neural activity patterns to similar odors, so that behaviors learned from one odor can be applied when a similar odor is experienced. The fly algorithm, however, uses three computational strategies that depart from traditional approaches. These strategies can be translated to improve the performance of computational similarity searches. This perspective helps illuminate the logic supporting an important sensory function and provides a conceptually new algorithm for solving a fundamental computational problem.
| Item Type: | Paper |
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| Subjects: | organism description > animal > insect > Drosophila bioinformatics > computational biology > algorithms organs, tissues, organelles, cell types and functions > tissues types and functions > neural networks organism description > animal behavior > olfactory |
| CSHL Authors: | |
| Communities: | CSHL labs > Navlakha lab |
| Depositing User: | Matthew Dunn |
| Date: | 10 November 2017 |
| Date Deposited: | 06 Nov 2019 15:40 |
| Last Modified: | 06 Nov 2019 15:40 |
| Related URLs: | |
| Dataset ID: |
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| URI: | https://repository.cshl.edu/id/eprint/38630 |
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