Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis

Background: Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Naikeng Mai [verfasserIn] Yujie Wu [verfasserIn] Xiaomei Zhong [verfasserIn] Ben Chen [verfasserIn] Min Zhang [verfasserIn] Qi Peng [verfasserIn] Yuping Ning [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	late life depression Granger causality brain network modularity normalized mutual information

Übergeordnetes Werk:	In: Frontiers in Aging Neuroscience - Frontiers Media S.A., 2010, 13(2021)
Übergeordnetes Werk:	volume:13 ; year:2021

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fnagi.2021.625175

Katalog-ID:	DOAJ078544661

Internformat


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520			\|a Background: Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis.Method: The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants.Result: The Granger function network analysis suggested that the functional modularity was different among the three groups (Pauc = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD (Pauc = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient (P = 0.0002, Pfdr = 0.0744 & P = 0.0004, Pfdr = 0.0744).Conclusion: This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD.
650		4	\|a late life depression
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allfields	10.3389/fnagi.2021.625175 doi (DE-627)DOAJ078544661 (DE-599)DOAJ63b8182e765a459791f84e83579c6481 DE-627 ger DE-627 rakwb eng RC321-571 Naikeng Mai verfasserin aut Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis.Method: The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants.Result: The Granger function network analysis suggested that the functional modularity was different among the three groups (Pauc = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD (Pauc = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient (P = 0.0002, Pfdr = 0.0744 & P = 0.0004, Pfdr = 0.0744).Conclusion: This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD. late life depression Granger causality brain network modularity normalized mutual information Neurosciences. Biological psychiatry. Neuropsychiatry Yujie Wu verfasserin aut Xiaomei Zhong verfasserin aut Ben Chen verfasserin aut Min Zhang verfasserin aut Qi Peng verfasserin aut Yuping Ning verfasserin aut Yuping Ning verfasserin aut Yuping Ning verfasserin aut In Frontiers in Aging Neuroscience Frontiers Media S.A., 2010 13(2021) (DE-627)629834350 (DE-600)2558898-9 16634365 nnns volume:13 year:2021 https://doi.org/10.3389/fnagi.2021.625175 kostenfrei https://doaj.org/article/63b8182e765a459791f84e83579c6481 kostenfrei https://www.frontiersin.org/articles/10.3389/fnagi.2021.625175/full kostenfrei https://doaj.org/toc/1663-4365 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2021
spelling	10.3389/fnagi.2021.625175 doi (DE-627)DOAJ078544661 (DE-599)DOAJ63b8182e765a459791f84e83579c6481 DE-627 ger DE-627 rakwb eng RC321-571 Naikeng Mai verfasserin aut Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis.Method: The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants.Result: The Granger function network analysis suggested that the functional modularity was different among the three groups (Pauc = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD (Pauc = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient (P = 0.0002, Pfdr = 0.0744 & P = 0.0004, Pfdr = 0.0744).Conclusion: This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD. late life depression Granger causality brain network modularity normalized mutual information Neurosciences. Biological psychiatry. Neuropsychiatry Yujie Wu verfasserin aut Xiaomei Zhong verfasserin aut Ben Chen verfasserin aut Min Zhang verfasserin aut Qi Peng verfasserin aut Yuping Ning verfasserin aut Yuping Ning verfasserin aut Yuping Ning verfasserin aut In Frontiers in Aging Neuroscience Frontiers Media S.A., 2010 13(2021) (DE-627)629834350 (DE-600)2558898-9 16634365 nnns volume:13 year:2021 https://doi.org/10.3389/fnagi.2021.625175 kostenfrei https://doaj.org/article/63b8182e765a459791f84e83579c6481 kostenfrei https://www.frontiersin.org/articles/10.3389/fnagi.2021.625175/full kostenfrei https://doaj.org/toc/1663-4365 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2021
allfields_unstemmed	10.3389/fnagi.2021.625175 doi (DE-627)DOAJ078544661 (DE-599)DOAJ63b8182e765a459791f84e83579c6481 DE-627 ger DE-627 rakwb eng RC321-571 Naikeng Mai verfasserin aut Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis.Method: The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants.Result: The Granger function network analysis suggested that the functional modularity was different among the three groups (Pauc = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD (Pauc = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient (P = 0.0002, Pfdr = 0.0744 & P = 0.0004, Pfdr = 0.0744).Conclusion: This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD. late life depression Granger causality brain network modularity normalized mutual information Neurosciences. Biological psychiatry. Neuropsychiatry Yujie Wu verfasserin aut Xiaomei Zhong verfasserin aut Ben Chen verfasserin aut Min Zhang verfasserin aut Qi Peng verfasserin aut Yuping Ning verfasserin aut Yuping Ning verfasserin aut Yuping Ning verfasserin aut In Frontiers in Aging Neuroscience Frontiers Media S.A., 2010 13(2021) (DE-627)629834350 (DE-600)2558898-9 16634365 nnns volume:13 year:2021 https://doi.org/10.3389/fnagi.2021.625175 kostenfrei https://doaj.org/article/63b8182e765a459791f84e83579c6481 kostenfrei https://www.frontiersin.org/articles/10.3389/fnagi.2021.625175/full kostenfrei https://doaj.org/toc/1663-4365 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2021
allfieldsGer	10.3389/fnagi.2021.625175 doi (DE-627)DOAJ078544661 (DE-599)DOAJ63b8182e765a459791f84e83579c6481 DE-627 ger DE-627 rakwb eng RC321-571 Naikeng Mai verfasserin aut Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis.Method: The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants.Result: The Granger function network analysis suggested that the functional modularity was different among the three groups (Pauc = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD (Pauc = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient (P = 0.0002, Pfdr = 0.0744 & P = 0.0004, Pfdr = 0.0744).Conclusion: This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD. late life depression Granger causality brain network modularity normalized mutual information Neurosciences. Biological psychiatry. Neuropsychiatry Yujie Wu verfasserin aut Xiaomei Zhong verfasserin aut Ben Chen verfasserin aut Min Zhang verfasserin aut Qi Peng verfasserin aut Yuping Ning verfasserin aut Yuping Ning verfasserin aut Yuping Ning verfasserin aut In Frontiers in Aging Neuroscience Frontiers Media S.A., 2010 13(2021) (DE-627)629834350 (DE-600)2558898-9 16634365 nnns volume:13 year:2021 https://doi.org/10.3389/fnagi.2021.625175 kostenfrei https://doaj.org/article/63b8182e765a459791f84e83579c6481 kostenfrei https://www.frontiersin.org/articles/10.3389/fnagi.2021.625175/full kostenfrei https://doaj.org/toc/1663-4365 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2021
allfieldsSound	10.3389/fnagi.2021.625175 doi (DE-627)DOAJ078544661 (DE-599)DOAJ63b8182e765a459791f84e83579c6481 DE-627 ger DE-627 rakwb eng RC321-571 Naikeng Mai verfasserin aut Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis.Method: The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants.Result: The Granger function network analysis suggested that the functional modularity was different among the three groups (Pauc = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD (Pauc = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient (P = 0.0002, Pfdr = 0.0744 & P = 0.0004, Pfdr = 0.0744).Conclusion: This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD. late life depression Granger causality brain network modularity normalized mutual information Neurosciences. Biological psychiatry. Neuropsychiatry Yujie Wu verfasserin aut Xiaomei Zhong verfasserin aut Ben Chen verfasserin aut Min Zhang verfasserin aut Qi Peng verfasserin aut Yuping Ning verfasserin aut Yuping Ning verfasserin aut Yuping Ning verfasserin aut In Frontiers in Aging Neuroscience Frontiers Media S.A., 2010 13(2021) (DE-627)629834350 (DE-600)2558898-9 16634365 nnns volume:13 year:2021 https://doi.org/10.3389/fnagi.2021.625175 kostenfrei https://doaj.org/article/63b8182e765a459791f84e83579c6481 kostenfrei https://www.frontiersin.org/articles/10.3389/fnagi.2021.625175/full kostenfrei https://doaj.org/toc/1663-4365 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2021
language	English
source	In Frontiers in Aging Neuroscience 13(2021) volume:13 year:2021
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topic_facet	late life depression Granger causality brain network modularity normalized mutual information Neurosciences. Biological psychiatry. Neuropsychiatry
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container_title	Frontiers in Aging Neuroscience
authorswithroles_txt_mv	Naikeng Mai @@aut@@ Yujie Wu @@aut@@ Xiaomei Zhong @@aut@@ Ben Chen @@aut@@ Min Zhang @@aut@@ Qi Peng @@aut@@ Yuping Ning @@aut@@
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callnumber-first	R - Medicine
author	Naikeng Mai
spellingShingle	Naikeng Mai misc RC321-571 misc late life depression misc Granger causality misc brain network misc modularity misc normalized mutual information misc Neurosciences. Biological psychiatry. Neuropsychiatry Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis
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topic_title	RC321-571 Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis late life depression Granger causality brain network modularity normalized mutual information
topic	misc RC321-571 misc late life depression misc Granger causality misc brain network misc modularity misc normalized mutual information misc Neurosciences. Biological psychiatry. Neuropsychiatry
topic_unstemmed	misc RC321-571 misc late life depression misc Granger causality misc brain network misc modularity misc normalized mutual information misc Neurosciences. Biological psychiatry. Neuropsychiatry
topic_browse	misc RC321-571 misc late life depression misc Granger causality misc brain network misc modularity misc normalized mutual information misc Neurosciences. Biological psychiatry. Neuropsychiatry
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title	Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis
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title_full	Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis
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author_browse	Naikeng Mai Yujie Wu Xiaomei Zhong Ben Chen Min Zhang Qi Peng Yuping Ning
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title_sort	different modular organization between early onset and late onset depression: a study base on granger causality analysis
callnumber	RC321-571
title_auth	Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis
abstract	Background: Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis.Method: The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants.Result: The Granger function network analysis suggested that the functional modularity was different among the three groups (Pauc = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD (Pauc = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient (P = 0.0002, Pfdr = 0.0744 & P = 0.0004, Pfdr = 0.0744).Conclusion: This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD.
abstractGer	Background: Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis.Method: The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants.Result: The Granger function network analysis suggested that the functional modularity was different among the three groups (Pauc = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD (Pauc = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient (P = 0.0002, Pfdr = 0.0744 & P = 0.0004, Pfdr = 0.0744).Conclusion: This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD.
abstract_unstemmed	Background: Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis.Method: The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants.Result: The Granger function network analysis suggested that the functional modularity was different among the three groups (Pauc = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD (Pauc = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient (P = 0.0002, Pfdr = 0.0744 & P = 0.0004, Pfdr = 0.0744).Conclusion: This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD.
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title_short	Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis
url	https://doi.org/10.3389/fnagi.2021.625175 https://doaj.org/article/63b8182e765a459791f84e83579c6481 https://www.frontiersin.org/articles/10.3389/fnagi.2021.625175/full https://doaj.org/toc/1663-4365
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author2	Yujie Wu Xiaomei Zhong Ben Chen Min Zhang Qi Peng Yuping Ning
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doi_str	10.3389/fnagi.2021.625175
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up_date	2024-07-03T18:37:30.107Z
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We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants.Result: The Granger function network analysis suggested that the functional modularity was different among the three groups (Pauc = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD (Pauc = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient (P = 0.0002, Pfdr = 0.0744 & P = 0.0004, Pfdr = 0.0744).Conclusion: This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. 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Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis

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