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Research article summary:
Interval timing as an emergent learning property.
Abstract Extract: Interval timing in operant conditioning is the learned covariation of a temporal dependent measure such as wait time with a temporal independent variable such as fixed-interval duration. The dominant theories of interval timing all incorporate an ... (Full abstract text below) Published 2003Jan
in Journal: Psychol Rev
(Language : eng)
Full Pubmed Extract
This information was retrieved, real-time, on your behalf from the public area of the Pubmed website:
1. Psychol Rev.
2003 Jan;110(1):126-44
Interval timing as an emergent learning property.
Dragoi V, Staddon JE, Palmer RG, Buhusi CV
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. vdragoi@ai.mit.edu
Interval timing in operant conditioning is the learned covariation of a temporal dependent measure such as wait time with a temporal independent variable such as fixed-interval duration. The dominant theories of interval timing all incorporate an explicit internal clock, or "pacemaker," despite its lack of independent evidence. The authors propose an alternative, pacemaker-free view that demonstrates that temporal discrimination can be explained by using only 2 assumptions: (a) variation and selection of responses through competition between reinforced behavior and all other, elicited, behaviors and (b) modulation of the strength of response competition by the memory for recent reinforcement. The model departs radically from existing timing models: It shows that temporal learning can emerge from a simple dynamic process that lacks a periodic time reference such as a pacemaker.
PMID : 12529059 [PubMed - Indexed for MEDLINE]
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Full Author Information
| First Name | LastName | Initials |
| Valentin | Dragoi | V |
| J E R | Staddon | JE |
| Richard G | Palmer | RG |
| Catalin V | Buhusi | CV |
Affiliation: Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. vdragoi@ai.mit.edu
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