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  Compositionality of rule representations in human prefrontal cortex

Reverberi, C., Görgen, K., & Haynes, J.-D. (2012). Compositionality of rule representations in human prefrontal cortex. Cerebral Cortex, 22(6), 1237-1246. doi:10.1093/cercor/bhr200.

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Reverberi_2012_Compositionality.pdf (Publisher version), 556KB
 
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 Creators:
Reverberi, Carlo1, 2, Author
Görgen, Kai1, Author
Haynes, John-Dylan1, 3, Author           
Affiliations:
1Bernstein Center for Computational Neuroscience, Berlin, Germany, ou_persistent22              
2Department of Psychology, University of Milano–Bicocca, Milan, Italy, ou_persistent22              
3Max Planck Fellow Research Group Attention and Awareness, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634553              

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Free keywords: Control functions; Decoding; fMRI; Frontal lobe; Neural code
 Abstract: Rules are widely used in everyday life to organize actions and thoughts in accordance with our internal goals. At the simplest level, single rules can be used to link individual sensory stimuli to their appropriate responses. However, most tasks are more complex and require the concurrent application of multiple rules. Experiments on humans and monkeys have shown the involvement of a frontoparietal network in rule representation. Yet, a fundamental issue still needs to be clarified: Is the neural representation of multiple rules compositional, that is, built on the neural representation of their simple constituent rules? Subjects were asked to remember and apply either simple or compound rules. Multivariate decoding analyses were applied to functional magnetic resonance imaging data. Both ventrolateral frontal and lateral parietal cortex were involved in compound representation. Most importantly, we were able to decode the compound rules by training classifiers only on the simple rules they were composed of. This shows that the code used to store rule information in prefrontal cortex is compositional. Compositional coding in rule representation suggests that it might be possible to decode other complex action plans by learning the neural patterns of the known composing elements.

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Language(s): eng - English
 Dates: 2011-08-042012-06
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1093/cercor/bhr200
PMID: 21817092
Other: Epub 2011
 Degree: -

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Title: Cerebral Cortex
Source Genre: Journal
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Publ. Info: New York, NY : Oxford University Press
Pages: - Volume / Issue: 22 (6) Sequence Number: - Start / End Page: 1237 - 1246 Identifier: ISSN: 1047-3211
CoNE: https://pure.mpg.de/cone/journals/resource/954925592440