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

被引:28
|
作者
Wawrzyniak, Max [1 ]
Klingbeil, Julian [1 ]
Zeller, Daniel [2 ]
Saur, Dorothee [1 ]
Classen, Joseph [1 ]
机构
[1] Univ Leipzig, Dept Neurol, Liebigstr 20, Leipzig, Germany
[2] Univ Wurzburg, Dept Neurol, Josef Schneider Str 11, Wurzburg, Germany
关键词
Body-ownership; Rubber hand illusion; Stroke; Lesion network mapping; Lesion network-symptom-mapping; Temporoparietal junction; Resting-state functional connectivity; Functional magnetic resonance imaging; Diaschisis; GLOBAL SIGNAL; RUBBER HAND; FUNCTIONAL CONNECTIVITY; PREMOTOR CORTEX; BODY OWNERSHIP; LIMB OWNERSHIP; HUMAN BRAIN; LOCALIZATION; MECHANISMS; HEMICHOREA;
D O I
10.1016/j.neuroimage.2017.11.011
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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.
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页码:317 / 324
页数:8
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