Race, E.A., Shanker, S. and Wagner, A.D., 2009. Neural Priming in Human Prefrontal Cortex: Multiple Forms of Learning Reduce Demands on the Prefrontal Executive System. Journal of Cognitive Neuroscience, 21 (9), 1766 - 1781.
Full text available as:
|
PDF
RACE_JOCN09.pdf - Published Version 640kB | |
Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. |
Official URL: http://cognet.mit.edu/node/28447
Abstract
Past experience is hypothesized to reduce computational demands in PFC by providing bottom-up predictive information that informs subsequent stimulus-action mapping. The present fMRI study measured cortical activity reductions ("neural priming"/"repetition suppression") during repeated stimulus classification to investigate the mechanisms through which learning from the past decreases demands on the prefrontal executive system. Manipulation of learning at three levels of representation-stimulus, decision, and response-revealed dissociable neural priming effects in distinct frontotemporal regions, supporting a multiprocess model of neural priming. Critically, three distinct patterns of neural priming were identified in lateral frontal cortex, indicating that frontal computational demands are reduced by three forms of learning: (a) cortical tuning of stimulus-specific representations, (b) retrieval of learned stimulus-decision mappings, and (c) retrieval of learned stimulus-response mappings. The topographic distribution of these neural priming effects suggests a rostrocaudal organization of executive function in lateral frontal cortex.
Item Type: | Article |
---|---|
ISSN: | 0898-929X |
Group: | Faculty of Science & Technology |
ID Code: | 29528 |
Deposited By: | Symplectic RT2 |
Deposited On: | 26 Jul 2017 08:59 |
Last Modified: | 14 Mar 2022 14:06 |
Downloads
Downloads per month over past year
Repository Staff Only - |