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DOI 10.1371/journal.pone.0249144

Медицинская библиотека · PloS one · 2021

Planning deficits in Huntington's disease: A brain structural correlation by voxel-based morphometry.

Calderon-Villalon Jesus, Ramirez-Garcia Gabriel, Fernandez-Ruiz Juan, Sangri-Gil Fernanda, Campos-Romo Aurelio, Galvez Victor

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

INTRODUCTION

Early Huntington's disease (HD) patients begin to show planning deficits even before motor alterations start to manifest. Generally, planning ability is associated with the functioning of anterior brain areas such as the medial prefrontal cortex. However, early HD neuropathology involves significant atrophy in the occipital and parietal cortex, suggesting that more posterior regions could also be involved in these planning deficits.

OBJECTIVE

To identify brain regions associated with planning deficits in HD patients at an early clinical stage.

MATERIALS AND

METHODS

Twenty-two HD-subjects genetically confirmed with incipient clinical manifestation and twenty healthy subjects were recruited. All participants underwent MRI T1 image acquisition as well as testing in the Stockings of Cambridge (SOC) task to measure planning ability. First, group comparison of SOC measures were performed. Then, correlation voxel-based morphometry analyses were done between gray matter degeneration and SOC performance in the HD group.

RESULTS

Accuracy and efficiency planning scores correlated with gray matter density in right lingual gyrus, middle temporal gyrus, anterior cingulate gyrus, and paracingulate gyrus.

CONCLUSIONS

Our results suggest that planning deficits exhibited by early HD-subjects are related to occipital and temporal cortical degeneration in addition to the frontal areas deterioration.

Для цитирования: Calderon-Villalon Jesus, Ramirez-Garcia Gabriel, Fernandez-Ruiz Juan, Sangri-Gil Fernanda, Campos-Romo Aurelio, Galvez Victor. Planning deficits in Huntington's disease: A brain structural correlation by voxel-based morphometry.. PloS one. 2021. DOI: 10.1371/journal.pone.0249144.

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