An Anatomically Constrained Model for Path Integration in the Bee Brain
- Submitting institution
-
University of Edinburgh
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 58618682
- Type
- D - Journal article
- DOI
-
10.1016/j.cub.2017.08.052
- Title of journal
- Current Biology
- Article number
- -
- First page
- 3069
- Volume
- 27
- Issue
- 10
- ISSN
- 0960-9822
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- 4 - Psychology, Psychiatry and Neuroscience
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
9
- Research group(s)
-
D - Language, Interaction and Robotics
- Citation count
- 89
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Explains the precise computational function of a biological neural circuit for navigation. An algorithm for self localisation is mapped one-to-one to identified neurons in the brain of an insect through novel use of a force graph on anatomical connectivity data and derivation of mathematical equivalence of the neural calculation. Subject of a 'highlight' commentary when published; already a standard citation as the solution to the long-standing problem (>50 years) of how path integration is performed by insects. Taken up by other researchers (in Germany and Sweden) for novel neuromorphic and optical computing implementations for efficient navigation devices.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -