Learning predictive statistics: strategies and brain mechanisms
- Submitting institution
-
Nottingham Trent University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 21 - 1068788
- Type
- D - Journal article
- DOI
-
10.1523/JNEUROSCI.0144-17.2017
- Title of journal
- Journal of Neuroscience
- Article number
- -
- First page
- 8412
- Volume
- 37
- Issue
- 35
- ISSN
- 1529-2401
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2017
- 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
-
4
- Research group(s)
-
A - Computing and Informatics Research Centre
- Citation count
- 11
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents a novel experimental design for brain imaging study of human sequence learning. The new design is helpful for the discovery of brain mechanisms that mediate our ability to adapt to changes at home and work, which makes the paper significant as it underpins a new large collaborative grant project supporting life-long learning (the CLIC programme, https://www.cares.cam.ac.uk/research/clic/). Additionally, this paper is significant because it led to 3 publications in top Neuroscience journals, including Nature Human Behaviour (https://doi.org/10.1038/s41562-018-0503-4), https://doi.org/10.1523/ENEURO.0382-17.2018, and https://doi.org/10.1016/j.cortex.2017.08.014. The authors include this paper’s NTU author and his collaborators at University of Cambridge and University of Birmingham.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
