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  Neural circuits of hierarchical visuo-spatial sequence processing

Bahlmann, J., Schubotz, R., Mueller, J. L., Koester, D., & Friederici, A. D. (2009). Neural circuits of hierarchical visuo-spatial sequence processing. Brain Research, 1298, 161-170. doi:10.1016/j.brainres.2009.08.017.

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 Creators:
Bahlmann, Jörg1, Author           
Schubotz, Ricarda2, Author
Mueller, Jutta L.1, Author           
Koester, Dirk3, Author
Friederici, Angela D.1, Author           
Affiliations:
1Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              
2Max Planck Institute for Neurological Research, Cologne, Germany, ou_persistent22              
3Center of Excellence “Cognitive Interaction Technology" (CITEC), University of Bielefeld, Germany, ou_persistent22              

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Free keywords: Visual sequence processing; Hierarchy; Broca's area; Pre-SMA; fMRI
 Abstract: Sequence processing has been investigated in a number of studies using serial reaction time tasks or simple artificial grammar tasks. Little, however, is known about higher-order sequence processing entailing the hierarchical organization of events. Here, we manipulated the regularities within sequentially occurring, non-linguistic visual symbols by applying two types of prediction rules. In one rule (the adjacent dependency rule), the sequences consisted of alternating items from two different categories. In the second rule (the hierarchical dependency rule), a hierarchical structure was generated using the same set of item types. Thus, predictions about non-adjacent elements were required for the latter rule. Functional Magnetic Resonance Imaging (fMRI) was used to investigate the neural correlates of the application of the two prediction rules. We found that the hierarchical dependency rule correlated with activity in the pre-supplementary motor area, and the head of the caudate nucleus. In addition, in a hypothesis-driven ROI analysis in Broca's area (BA 44), we found a significantly higher hemodynamic response to the hierarchical dependency rule than to the adjacent dependency rule. These results suggest that this neural network supports hierarchical sequencing, possibly contributing to the integration of sequential elements into higher-order structural events. Importantly, the findings suggest that Broca's area is also engaged in hierarchical sequencing in domains other than language.

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Language(s): eng - English
 Dates: 2009-10-28
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 458538
DOI: 10.1016/j.brainres.2009.08.017
 Degree: -

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Title: Brain Research
  Other : Brain Res.
Source Genre: Journal
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Publ. Info: Amsterdam : Elsevier
Pages: - Volume / Issue: 1298 Sequence Number: - Start / End Page: 161 - 170 Identifier: ISSN: 0006-8993
CoNE: https://pure.mpg.de/cone/journals/resource/954926250616