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DOI 10.1016/j.neuroimage.2019.116485

Медицинская библиотека · NeuroImage · 2019

Hippocampal diaschisis contributes to anosognosia for hemiplegia: Evidence from lesion network-symptom-mapping.

Klingbeil Julian, Wawrzyniak Max, Stockert Anika, Karnath Hans-Otto, Saur Dorothee

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Anosognosia for hemiplegia (AHP) is known to be associated with lesions to the motor system combined with varying lesions to the right insula, premotor cortex, parietal lobe or hippocampus. Due to this widespread cortical lesion distribution, AHP can be understood best as a network disorder. We used lesion maps and behavioral data (n ​= ​49) from two previous studies on AHP and performed a lesion network-symptom-mapping (LNSM) analysis. This new approach permits the identification of relationships between behavior and regions connected to the lesion site based on normative functional connectome data. In a first step, using ordinary voxel-based lesion-symptom mapping, we found an association of AHP with lesions in the right posterior insula. This is in accordance with previous studies. Applying LNSM, we were able to additionally identify a region in the right posterior hippocampus where AHP was associated with significantly higher normative lesion connectivity. Notably, this region was spared by infarction in all patients. We therefore argue that remote neuronal dysfunction caused by disrupted functional connections between the lesion site and the hippocampus (i.e. diaschisis) contributed to the phenotype of AHP. An indirect affection of the hippocampus may lead to memory deficits which, in turn, impair the stable encoding of updated beliefs on the bodily state thus contributing to the multifactorial phenomenon of AHP.

Для цитирования: Klingbeil Julian, Wawrzyniak Max, Stockert Anika, Karnath Hans-Otto, Saur Dorothee. Hippocampal diaschisis contributes to anosognosia for hemiplegia: Evidence from lesion network-symptom-mapping.. NeuroImage. 2019. DOI: 10.1016/j.neuroimage.2019.116485.

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