White-matter pathways for statistical learning of temporal structures
- Submitting institution
-
Nottingham Trent University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 39 - 698137
- Type
- D - Journal article
- DOI
-
10.1523/eneuro.0382-17.2018
- Title of journal
- eNeuro
- Article number
- e0382
- First page
- -
- Volume
- 5
- Issue
- 3
- ISSN
- 2373-2822
- Open access status
- Compliant
- Month of publication
- June
- 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)
-
A - Computing and Informatics Research Centre
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- To investigate how training can help to improve learning performance (e.g., in life-long learning), a new study on alternation of white-matter connectivity is presented by researchers from NTU, University of Cambridge, UoB and Chinese Academy of Sciences. This paper is significant because it led to new research with a publication in Nature Human Behaviour (https://doi.org/10.1038/s41562-018-0503-4) where brain connectivity data were interrogated to predict learning behaviour. Additionally, this paper underpins a new large collaborative grant project with https://www.cares.cam.ac.uk/research/clic/ and Nanyang Technological University. This paper also forms the basis for an on-line game app for personalised learning study (Prof Kourtzi and https://www.abg.psychol.cam.ac.uk/participation/iabc).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
