New Insights into Freezing of Gait in Parkinson's Disease from Spectral Dynamic Causal Modeling

Taniguchi, Seira; Kajiyama, Yuta; Kochiyama, Takanori; Revankar, Gajanan; Ogawa, Kotaro; Shirahata, Emi; Asai, Kana; Saeki, Chizu; Ozono, Tatsuhiko; Kimura, Yasuyoshi; Ikenaka, Kensuke; D'Cruz, Nicholas; Gilat, Moran; Nieuwboer, Alice; Mochizuki, Hideki

doi:https://doi.org/10.1002/mds.29988

New Insights into Freezing of Gait in Parkinson's Disease from Spectral Dynamic Causal Modeling

Taniguchi, Seira; Kajiyama, Yuta; Kochiyama, Takanori et al.

Movement Disorders, 2024, 39(11), 1982-1992

アクセス数:205件（2025-05-24 23:04 集計）

固定URL: https://hdl.handle.net/11094/98297

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タイトル	New Insights into Freezing of Gait in Parkinson's Disease from Spectral Dynamic Causal Modeling
著者	NRID 1000000894370 1000000894370 ORCID 0000-0002-5297-7716 0000-0002-5297-7716 researchmap permalink seirataniguchi seirataniguchi Scopus Author ID 57336847600 57336847600 著者名 Taniguchi, Seira
	NRID 1000080792390 1000080792390 ORCID 0000-0001-7170-0758 0000-0001-7170-0758 researchmap permalink ykajiyama ykajiyama 著者名 Kajiyama, Yuta
	NRID 1000090380146 1000090380146 著者名 Kochiyama, Takanori
	NRID 1000070899773 1000070899773 ORCID 0000-0002-3753-4140 0000-0002-3753-4140 researchmap permalink revankar revankar Scopus Author ID 55553476300 55553476300 著者名 Revankar, Gajanan
	NRID 1000080870500 1000080870500 researchmap permalink jihdiegisojosugudc jihdiegisojosugudc Scopus Author ID 57200553653 57200553653 著者名 Ogawa, Kotaro
	著者名 Shirahata, Emi
	著者名 Asai, Kana
	著者名 Saeki, Chizu
	NRID 1000090898264 1000090898264 researchmap permalink TO_90 TO_90 著者名 Ozono, Tatsuhiko
	NRID 1000050727451 1000050727451 ORCID 0000-0001-9147-8058 0000-0001-9147-8058 researchmap permalink y-kimura_neurol y-kimura_neurol Scopus Author ID 56673363900 56673363900 著者名 Kimura, Yasuyoshi
	NRID 1000070774058 1000070774058 researchmap permalink kensukeikenaka kensukeikenaka Scopus Author ID 8588484300 8588484300 著者名 Ikenaka, Kensuke
	著者名 D'Cruz, Nicholas
	著者名 Gilat, Moran
	著者名 Nieuwboer, Alice
	NRID 1000090230044 1000090230044 ORCID 0000-0002-0874-7542 0000-0002-0874-7542 researchmap permalink read0207787 read0207787 Scopus Author ID 7202006099 7202006099 著者名 Mochizuki, Hideki
キーワード等	dynamic causal modeling
	freezing of gait
	neuroimaging
	Parkinson's disease
内容	Taniguchi S., Kajiyama Y., Kochiyama T., et al. New Insights into Freezing of Gait in Parkinson's Disease from Spectral Dynamic Causal Modeling. Movement Disorders, (2024); https://doi.org/10.1002/mds.29988.
抄録	Background: Freezing of gait is one of the most disturbing motor symptoms of Parkinson's disease (PD). However, the effective connectivity between key brain hubs that are associated with the pathophysiological mechanism of freezing of gait remains elusive. Objective: The aim of this study was to identify effective connectivity underlying freezing of gait. Methods: This study applied spectral dynamic causal modeling (DCM) of resting-state functional magnetic resonance imaging in dedicated regions of interest determined using a data-driven approach. Results: Abnormally increased functional connectivity between the bilateral dorsolateral prefrontal cortex (DLPFC) and the bilateral mesencephalic locomotor region (MLR) was identified in freezers compared with nonfreezers. Subsequently, spectral DCM analysis revealed that increased top-down excitatory effective connectivity from the left DLPFC to bilateral MLR and an independent self-inhibitory connectivity within the left DLPFC in freezers versus nonfreezers (>99% posterior probability) were inversely associated with the severity of freezing of gait. The lateralization of these effective connectivity patterns was not attributable to the initial dopaminergic deficit nor to structural changes in these regions. Conclusions: We have identified novel effective connectivity and an independent self-inhibitory connectivity underlying freezing of gait. Our findings imply that modulating the effective connectivity between the left DLPFC and MLR through neurostimulation or other interventions could be a target for reducing freezing of gait in PD.
出版者	John Wiley and Sons Inc
収録物名	Movement Disorders
巻(号)	39(11)
ページ	1982-1992
刊行年月	2024-09-18
言語	英語
ハンドルURL	https://hdl.handle.net/11094/98297
PISSN	08853185
eISSN	15318257
関連情報 (isIdenticalTo)	DOI (出版社版) https://doi.org/10.1002/mds.29988
アクセス権	open access
権利情報	This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
出版タイプ	Version of Record
カテゴリ	学術雑誌論文 Journal Article

資源タイプ	学術雑誌論文
ローカル資源タイプ	学術雑誌論文
DCTERMS.bibliographicCitation	Movement Disorders. 2024, 39(11), p. 1982-1992
DC.title	New Insights into Freezing of Gait in Parkinson's Disease from Spectral Dynamic Causal Modeling
DC.creator	Taniguchi, Seira
	Kajiyama, Yuta
	Kochiyama, Takanori
	Revankar, Gajanan
	Ogawa, Kotaro
	Shirahata, Emi
	Asai, Kana
	Saeki, Chizu
	Ozono, Tatsuhiko
	Kimura, Yasuyoshi
	Ikenaka, Kensuke
	D'Cruz, Nicholas
	Gilat, Moran
	Nieuwboer, Alice
	Mochizuki, Hideki
DC.publisher	John Wiley and Sons Inc
DC.language' scheme='DCTERMS.RFC1766	英語
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2024-09-18
DC.identifier	https://doi.org/10.1002/mds.29988
DC.subject	dynamic causal modeling
	freezing of gait
	neuroimaging
	Parkinson's disease
DC.description	Taniguchi S., Kajiyama Y., Kochiyama T., et al. New Insights into Freezing of Gait in Parkinson's Disease from Spectral Dynamic Causal Modeling. Movement Disorders, (2024); https://doi.org/10.1002/mds.29988.
DCTERMS.abstract	Background: Freezing of gait is one of the most disturbing motor symptoms of Parkinson's disease (PD). However, the effective connectivity between key brain hubs that are associated with the pathophysiological mechanism of freezing of gait remains elusive. Objective: The aim of this study was to identify effective connectivity underlying freezing of gait. Methods: This study applied spectral dynamic causal modeling (DCM) of resting-state functional magnetic resonance imaging in dedicated regions of interest determined using a data-driven approach. Results: Abnormally increased functional connectivity between the bilateral dorsolateral prefrontal cortex (DLPFC) and the bilateral mesencephalic locomotor region (MLR) was identified in freezers compared with nonfreezers. Subsequently, spectral DCM analysis revealed that increased top-down excitatory effective connectivity from the left DLPFC to bilateral MLR and an independent self-inhibitory connectivity within the left DLPFC in freezers versus nonfreezers (>99% posterior probability) were inversely associated with the severity of freezing of gait. The lateralization of these effective connectivity patterns was not attributable to the initial dopaminergic deficit nor to structural changes in these regions. Conclusions: We have identified novel effective connectivity and an independent self-inhibitory connectivity underlying freezing of gait. Our findings imply that modulating the effective connectivity between the left DLPFC and MLR through neurostimulation or other interventions could be a target for reducing freezing of gait in PD.
DC.rights	This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
DC.format	98297
citation_title	New Insights into Freezing of Gait in Parkinson's Disease from Spectral Dynamic Causal Modeling
citation_author	Taniguchi, Seira
	Kajiyama, Yuta
	Kochiyama, Takanori
	Revankar, Gajanan
	Ogawa, Kotaro
	Shirahata, Emi
	Asai, Kana
	Saeki, Chizu
	Ozono, Tatsuhiko
	Kimura, Yasuyoshi
	Ikenaka, Kensuke
	D'Cruz, Nicholas
	Gilat, Moran
	Nieuwboer, Alice
	Mochizuki, Hideki
citation_publisher	John Wiley and Sons Inc
citation_language	英語
citation_date	2024-09-18
citation_journal_title	Movement Disorders
citation_volume	39
citation_issue	11
citation_firstpage	1982
citation_lastpage	1992
citation_doi	https://doi.org/10.1002/mds.29988
citation_public_url	https://hdl.handle.net/11094/98297

New Insights into Freezing of Gait in Parkinson's Disease from Spectral Dynamic Causal Modeling

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