Distinct learning-induced changes in stimulus selectivity and interactions of GABAergic interneuron classes in visual cortex
- Submitting institution
-
University of Edinburgh
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 144097734
- Type
- D - Journal article
- DOI
-
10.1038/s41593-018-0143-z
- Title of journal
- Nature Neuroscience
- Article number
- -
- First page
- 851
- Volume
- 21
- Issue
- 6
- ISSN
- 1546-1726
- Open access status
- Technical exception
- Month of publication
- May
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
6
- Research group(s)
-
B - Data Science and Artificial Intelligence
- Citation count
- 43
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper develops a method to infer neuronal network dynamics from large-scale recordings and applies the method to assess changes in sensory processing over learning. The method reveals for the first time how specific cell types contribute to learning-related improvements in sensory representations, and constitutes a powerful and widely applicable tool for neural data analysis. The project spearheaded the first collaboration between the Gatsby Computational Neuroscience Unit and Sainsbury Wellcome Centre for Neural Circuits and Behaviour, UCL. The paper led a numerous invitations for international talks and was selected for recommendation in a dedicated article by Faculty of 1000.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -