Activity in perceptual classification networks as a basis for human subjective time perception
- Submitting institution
-
University of Sussex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 22981_80727
- Type
- D - Journal article
- DOI
-
10.1038/s41467-018-08194-7
- Title of journal
- Nature Communications
- Article number
- -
- First page
- 1
- Volume
- 10
- Issue
- 267
- ISSN
- 2041-1723
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2019
- URL
-
http://dx.doi.org/10.1038/s41467-018-08194-7
- 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
- Yes
- Number of additional authors
-
5
- Research group(s)
-
-
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "Presents a novel combination of machine learning and human behavioural approaches to support a new theory of human time perception. Published in a leading journal and 96th percentile of articles of similar age in all journals [1]; in top 10% most cited publications worldwide for age (SciVal). Provided the basis for new research directions with three subsequent studies [2-4]. Led to invitations to several public engagement events (e.g. MeetAI London [5], British Science Association SciScreen [6]).
[1] https://www.nature.com/articles/s41467-018-08194-7/metrics
[2] https://doi.org/10.1525/collabra.234
[3] https://doi.org/10.1101/2020.01.09.900423 (also top 5% of articles; Altmetric - https://biorxiv.altmetric.com/details/73809464)
[4] https://doi.org/10.1101/2020.02.17.953133
[5] https://www.meetup.com/NeuroTechLDN/events/246479004/
[6] https://www.eventbrite.co.uk/e/back-to-the-future-sciscreen-tickets-37335870594"
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -