Antagonistic activation patterns underlie multi-functionality of the right temporo-parietal junction

Danilo Bzdok, Robert Langner, Simon Eickhoff, Angela R. Laird, Peter T. Fox

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The right temporo-parietal junction (RTPJ) is consistently implicated in two cognitive domains - attention and social cognitions. We conducted multi-modal connectivity-based parcellation to investigate potentially separate functional modules within RTPJ implementing this cognitive dualism. Both task-constrained meta-analytic co activation mapping and task-free resting-state connectivity analysis independently identified two distinct clusters within RTPJ, subsequently characterized by network mapping and functional forward/reverse inference. The anterior cluster increased activity concomitantly with a midcingulate-motor-insular network, functionally associated with attention, and decreased activity with a parietal network, functionally associated with social cognition and introspection. The posterior cluster showed the exactly opposite association pattern. Our data thus suggest that RTPJ links two antagonistic brain networks processing external versus internal information.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013
Pages62-65
Number of pages4
DOIs
StatePublished - Oct 15 2013
Event2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013 - Philadelphia, PA, United States
Duration: Jun 22 2013Jun 24 2013

Publication series

NameProceedings - 2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013

Other

Other2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013
CountryUnited States
CityPhiladelphia, PA
Period6/22/136/24/13

Keywords

  • anti-correlation
  • connectivity-based parcellation
  • functional decoding
  • temporo-parietal junction

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

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