Literature DB >> 29122723

The neuronal network involved in self-attribution of an artificial hand: A lesion network-symptom-mapping study.

Max Wawrzyniak1, Julian Klingbeil2, Daniel Zeller3, Dorothee Saur2, Joseph Classen2.   

Abstract

The feeling of body-ownership can be experimentally manipulated using the rubber hand illusion (RHI) paradigm. Participants experience a sense of ownership over an artificial hand when their hidden real hand and the visible artificial hand are synchronously stroked. Using lesion masks and behavioral data from a previous study on RHI failure in acute stroke patients, we here employed lesion network-symptom-mapping (LNSM) based on normative functional connectome data to identify lesion-dependent network connectivity related to the experience of self-attribution of an artificial hand in the RHI paradigm. We found that failure to experience the RHI was associated with higher normative lesion-dependent network connectivity to the right temporoparietal junction (rTPJ), right anterior Insula (raI) and right inferior frontal gyrus (rIFG). Since these areas were spared by the infarction in most patients with RHI failure (89% for rTPJ and 94% for raI/rIFG), the analysis suggests that remote dysfunction in rTPJ, raI, and rIFG accounted for RHI failure. These results highlight the potential role of rTPJ, raI, and rIFG in bodily self-consciousness. LNSM is a powerful tool capable of delineating the architecture of functional networks underlying complex cognitive function.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Body-ownership; Diaschisis; Functional magnetic resonance imaging; Lesion network mapping; Lesion network-symptom-mapping; Resting-state functional connectivity; Rubber hand illusion; Stroke; Temporoparietal junction

Mesh:

Year:  2017        PMID: 29122723     DOI: 10.1016/j.neuroimage.2017.11.011

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  9 in total

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Authors:  Marilia Lira; Fernanda Naomi Pantaleão; Carolina Gudin de Souza Ramos; Paulo S Boggio
Journal:  Exp Brain Res       Date:  2018-08-06       Impact factor: 1.972

3.  Lesion network mapping predicts post-stroke behavioural deficits and improves localization.

Authors:  Alexander L Cohen; Michael A Ferguson; Michael D Fox
Journal:  Brain       Date:  2021-05-07       Impact factor: 15.255

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8.  Accuracy and practical aspects of semi- and fully automatic segmentation methods for resected brain areas.

Authors:  Karin Gau; Charlotte S M Schmidt; Horst Urbach; Josef Zentner; Andreas Schulze-Bonhage; Christoph P Kaller; Niels Alexander Foit
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Authors:  Gustavo S P Pamplona; Julio A D Salgado; Philipp Staempfli; Erich Seifritz; Roger Gassert; Silvio Ionta
Journal:  Cereb Cortex       Date:  2022-01-10       Impact factor: 5.357

  9 in total

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