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Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932566/ https://www.ncbi.nlm.nih.gov/pubmed/36739790 http://dx.doi.org/10.1016/j.nicl.2023.103342 |
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author | Togo, Hiroki Nakamura, Tatsuhiro Wakasugi, Noritaka Takahashi, Yuji Hanakawa, Takashi |
author_facet | Togo, Hiroki Nakamura, Tatsuhiro Wakasugi, Noritaka Takahashi, Yuji Hanakawa, Takashi |
author_sort | Togo, Hiroki |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9932566 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99325662023-02-17 Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait Togo, Hiroki Nakamura, Tatsuhiro Wakasugi, Noritaka Takahashi, Yuji Hanakawa, Takashi Neuroimage Clin Regular Article 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. Elsevier 2023-02-02 /pmc/articles/PMC9932566/ /pubmed/36739790 http://dx.doi.org/10.1016/j.nicl.2023.103342 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Regular Article Togo, Hiroki Nakamura, Tatsuhiro Wakasugi, Noritaka Takahashi, Yuji Hanakawa, Takashi Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait |
title | Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait |
title_full | Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait |
title_fullStr | Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait |
title_full_unstemmed | Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait |
title_short | Interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait |
title_sort | interactions across emotional, cognitive and subcortical motor networks underlying freezing of gait |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932566/ https://www.ncbi.nlm.nih.gov/pubmed/36739790 http://dx.doi.org/10.1016/j.nicl.2023.103342 |
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