Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
7028
pubmed:dateCreated
2005-2-24
pubmed:abstractText
To navigate our complex world, our brains have evolved a sophisticated ability to quickly learn arbitrary rules such as 'stop at red'. Studies in monkeys using a laboratory test of this capacity--conditional association learning--have revealed that frontal lobe structures (including the prefrontal cortex) as well as subcortical nuclei of the basal ganglia are involved in such learning. Neural correlates of associative learning have been observed in both brain regions, but whether or not these regions have unique functions is unclear, as they have typically been studied separately using different tasks. Here we show that during associative learning in monkeys, neural activity in these areas changes at different rates: the striatum (an input structure of the basal ganglia) showed rapid, almost bistable, changes compared with a slower trend in the prefrontal cortex that was more in accordance with slow improvements in behavioural performance. Also, pre-saccadic activity began progressively earlier in the striatum but not in the prefrontal cortex as learning took place. These results support the hypothesis that rewarded associations are first identified by the basal ganglia, the output of which 'trains' slower learning mechanisms in the frontal cortex.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1476-4687
pubmed:author
pubmed:issnType
Electronic
pubmed:day
24
pubmed:volume
433
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
873-6
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Different time courses of learning-related activity in the prefrontal cortex and striatum.
pubmed:affiliation
The Picower Center for Learning and Memory, RIKEN-MIT Neuroscience Research Center and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 USA. anitha@mit.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't