Integrating Space, Time, and Orientation in Spiking Neural Networks: A Case Study on Multimodal Brain Data Modelling
- Submitting institution
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University of Ulster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 85782425
- Type
- D - Journal article
- DOI
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10.1109/TNNLS.2018.2796023
- Title of journal
- IEEE Transactions on Neural Networks and Learning Systems
- Article number
- -
- First page
- 5249
- Volume
- 29
- Issue
- 11
- ISSN
- 2162-237X
- Open access status
- Deposit exception
- Month of publication
- February
- 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
-
3
- Research group(s)
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A - Intelligent Systems Research Centre
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- <12> The method was tested on 30 schizophrenic patients to predict response to treatment using fMRI+DTI data (Clozapine Response Study, University of Auckland, PI B.Russel; SRIF/AUT/Intellecte project, NZD450,000, PI N.Kasabov). The paper was nominated by Prof. Z. Hou of the China Academy of Science Institute Automation for 2018 best paper of IEEE Transactions on Neural Networks and Learning Systems. Sengupta and McNabb completed PhD study and joined NZ Spark and University of Reading.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -