Receptive Field Vectors of Genetically-Identified Retinal Ganglion Cells Reveal Cell-Type-Dependent Visual Functions
- Submitting institution
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The University of West London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 12022
- Type
- D - Journal article
- DOI
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10.1371/journal.pone.0147738
- Title of journal
- PLOS ONE
- Article number
- -
- First page
- e0147738
- Volume
- 11
- Issue
- 2
- ISSN
- 1932-6203
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2016
- URL
-
-
- Supplementary information
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-
- 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
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2
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Developed a data-driven ML algorithm for feature extraction by non-parametric quadratic mutual information (QMI) maximisation, which operates in very high dimensional spaces (hundreds of thousands, e.g. images). Used to address the challenge of understanding the mammalian retina information processing and predict the retina response to various visual inputs. The results have been applied to retinal prostheses, sensory substitution systems and advanced silicon retina vision sensors. Recently the algorithm has been successfully applied to the receptive fields of thalamus cells (Prof Schultz, Imperial College London), as well as for diagnostic inference.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -