MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1016/j.jad.2017.03.073

Медицинская библиотека · Journal of affective disorders · 2017

Functional network-based statistics in depression: Theory of mind subnetwork and importance of parietal region.

Lai Chien-Han, Wu Yu-Te, Hou Yuh-Ming

Сравнительное исследованиеСтатьяПеревод пока не подготовлен

Аннотация

OBJECTIVE

The functional network analysis of whole brain is an emerging field for research in depression. We initiated this study to investigate which subnetwork is significantly altered within the functional connectome in major depressive disorder (MDD).

METHODS

The study enrolled 52 first-episode medication-naïve patients with MDD and 40 controls for functional network analysis. All participants received the resting-state functional imaging using a 3-Tesla magnetic resonance scanner. After preprocessing, we calculated the connectivity matrix of functional connectivity in whole brain for each subject. The network-based statistics of connectome was used to perform group comparisons between patients and controls. The correlations between functional connectivity and clinical parameters were also performed.

RESULTS

MDD patients had significant alterations in the network involving "theory of mind" regions, such as the left precentral gyrus, left angular gyrus, bilateral rolandic operculums and left inferior frontal gyrus. The center node of significant network was the left angular gyrus. No significant correlations of functional connectivity within the subnetwork and clinical parameters were noted.

CONCLUSION

Functional connectivity of "theory of mind" subnetwork may be the core issue for pathophysiology in MDD. In addition, the center role of parietal region should be emphasized in future study.

Для цитирования: Lai Chien-Han, Wu Yu-Te, Hou Yuh-Ming. Functional network-based statistics in depression: Theory of mind subnetwork and importance of parietal region.. Journal of affective disorders. 2017. DOI: 10.1016/j.jad.2017.03.073.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.