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ファイル | 記述 | サイズ | フォーマット | |
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j.nicl.2023.103342.pdf | 3.85 MB | Adobe PDF | 見る/開く |
タイトル: | Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait |
著者: | Togo, Hiroki ![]() ![]() Nakamura, Tatsuhiro Wakasugi, Noritaka Takahashi, Yuji Hanakawa, Takashi ![]() ![]() ![]() |
著者名の別形: | 東口, 大樹 中村, 達弘 花川, 隆 |
キーワード: | Freezing of gait Parkinson’s disease Resting state fMRI Functional connectivity |
発行日: | 2023 |
出版者: | Elsevier BV |
誌名: | NeuroImage: Clinical |
巻: | 37 |
論文番号: | 103342 |
抄録: | Freezing of gait (FOG) is a gait disorder affecting patients with Parkinson's disease (PD) and related disorders. The pathophysiology of FOG is unclear because of its phenomenological complexity involving motor, cognitive, and emotional aspects of behavior. Here we used resting-state functional MRI to retrieve functional connectivity (FC) correlated with the New FOG questionnaire (NFOGQ) reflecting severity of FOG in 67 patients with PD. NFOGQ scores were correlated with FCs in the extended basal ganglia network (BGN) involving the striatum and amygdala, and in the extra-cerebellum network (CBLN) involving the frontoparietal network (FPN). These FCs represented interactions across the emotional (amygdala), subcortical motor (BGN and CBLN), and cognitive networks (FPN). Using these FCs as features, we constructed statistical models that explained 40% of the inter-individual variances of FOG severity and that discriminated between PD patients with and without FOG. The amygdala, which connects to the subcortical motor (BGN and CBLN) and cognitive (FPN) networks, may have a pivotal role in interactions across the emotional, cognitive, and subcortical motor networks. Future refinement of the machine learning-based classifier using FCs may clarify the complex pathophysiology of FOG further and help diagnose and evaluate FOG in clinical settings. |
著作権等: | © 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license. |
URI: | http://hdl.handle.net/2433/282045 |
DOI(出版社版): | 10.1016/j.nicl.2023.103342 |
PubMed ID: | 36739790 |
出現コレクション: | 学術雑誌掲載論文等 |

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