A framework for plasticity implementation on the SpiNNaker neural architecture
- Submitting institution
-
The University of Manchester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 40100854
- Type
- D - Journal article
- DOI
-
10.3389/fnins.2014.00429
- Title of journal
- Frontiers in Neuroscience
- Article number
- 429
- First page
- -
- Volume
- 8
- Issue
- 429
- ISSN
- 1662-4548
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2015
- 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 - Computer Science
- Citation count
- 34
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "Outcome of a long international collaboration between the SpiNNaker team in Manchester, the Paris Vision Institute and the Institute of Neuro-informatics at University of Zurich and ETH Zurich.
The work is key to the flexibility in the software-based approach to neuromorphic computing employed on SpiNNaker - this enables the machine to operate well outside its original programming model.
This is achieved via a novel scheme that divides responsibility for neural and synaptic processing between two processor cores, allowing one core to focus on real-time neural processing while the other core implements synaptic plasticity, which has an intrinsically longer time scale."
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
