Aberrant Intra- and Internetwork Functional Connectivity in Depressed Parkinson’s Disease

Wei, Luqing; Hu, Xiao; Zhu, Yajing; Yuan, Yonggui; Liu, Weiguo; Chen, Hong

doi:10.1038/s41598-017-02127-y

Cited by 33 publications

(29 citation statements)

References 75 publications

(120 reference statements)

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“…While there are quite a few PET and SPECT studies on depression in PD, functional connectivity MRI studies are relatively scarce. Previous functional connectivity studies have found in depressed PD patients an increased functional connectivity of the OFC 10 , inferior frontal gyrus 11 anterior cingulate 12 and posterior cingulate 13 , in accordance with our findings, in addition to decreased functional connectivity 12 , 13 , not identified here. We suggest that this may result from the substantial variability across studies in inclusion and exclusion criteria and statistical approaches.…”

Section: Discussionsupporting

confidence: 93%

Separate neural representations of depression, anxiety and apathy in Parkinson’s disease

Dan

Růžička

Bezdíček

et al. 2017

Sci Rep

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Depression, anxiety and apathy are distinct neuropsychiatric symptoms that highly overlap in Parkinson’s disease (PD). It remains unknown whether each symptom is uniquely associated with a functional network dysfunction. Here, we examined whether individual differences in each neuropsychiatric symptom predict functional connectivity patterns in PD patients while controlling for all other symptoms and motor function. Resting-state functional connectivity MRI were acquired from 27 PD patients and 29 healthy controls. Widespread reduced functional connectivity was identified in PD patients and explained by either the neuropsychiatric or motor symptoms. Depression in PD predicted increased functional connectivity between the orbitofrontal, hippocampal complex, cingulate, caudate and thalamus. Apathy in PD predicted decreased caudate-thalamus and orbitofrontal-parahippocampal connectivity. Anxiety in PD predicted three distinct types of functional connectivity not described before: (i) increased limbic-orbitofrontal cortex; (ii) decreased limbic-dorsolateral prefrontal cortex and orbitofrontal-dorsolateral prefrontal cortices and (iii) decreased sensorimotor-orbitofrontal cortices. The first two types of functional connectivity suggest less voluntary and more automatic emotion regulation. The last type is argued to be specific to PD and reflect an impaired ability of the orbitofrontal cortex to guide goal-directed motor actions in anxious PD patients.

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Section: Discussionsupporting

confidence: 93%

Separate neural representations of depression, anxiety and apathy in Parkinson’s disease

Dan

Růžička

Bezdíček

et al. 2017

Sci Rep

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“…For instance, Huang et al (2020) reported that the disrupted connection between the SN and ECN might contribute to depression in PD. Wei et al (2017) reported that the involvement of BGN, DMN, LFPN, and SN in PD facilitates the development of depression. Therefore, the impaired interactions between the triple network are critical for the occurrence and maintenance of depression in PD.…”

Section: Discussionmentioning

confidence: 99%

“…However, the networks do not function independently, and investigation of the connectivity within one specific network may not be enough or may be somewhat unjustified. A study using independent component (IC) analysis (ICA) confirmed the involvement of BGN, DMN, left frontoparietal network (LFPN), and SN in depression in PD patients, facilitating the development of more detailed and integrative neural models of PDD ( Wei et al, 2017 ). Based on the above studies, we hypothesized that PDD may be related to the damage of specific large-scale neural networks, rather than on the disruption of a single, random, discrete brain region; not only the connectivity within these networks but also the coordination between them can be a prominent feature of PDD.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, using ICA, the subnetworks can be independently extracted. A previous study with a small sample size suggested that ICA is effective to identify the abnormal intrinsic FC within and between large-scale neural networks in depressed PD patients ( Wei et al, 2017 ). Therefore, we proposed that determining neural correlations with ICA could lead to the discovery of biomarkers to improve the diagnosis of PDD.…”

Section: Introductionmentioning

confidence: 99%

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Networks Are Associated With Depression in Patients With Parkinson’s Disease: A Resting-State Imaging Study

et al. 2021

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BackgroundDisturbance of networks was recently proposed to be associated with the occurrence of depression in Parkinson’s disease (PD). However, the neurobiological mechanism of depression underlying PD remains unclear.ObjectiveThis study was conducted to investigate whether intra-network and inter-network brain connectivity is differently changed in PD patients with and without depression (PDD and PDND patients, respectively).MethodsForty-one PDD patients, 64 PDND patients, and 55 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (fMRI). The default mode network (DMN), executive control network (ECN), salience network (SN), precuneus network (PCUN), and sensorimotor network (SMN) were extracted using independent component analysis (ICA), and then the functional connectivity (FC) values within and between these networks were measured.ResultsPDD patients exhibited abnormal FC values within the DMN, ECN, SN, PCUN, and SMN. In addition, PDD patients demonstrated decreased connectivity between anterior SN (aSN) and bilateral ECN, between posterior SN (pSN) and dorsal DMN (dDMN), and between PCUN and dDMN/SMN/bilateral ECN. Connectivity within the left hippocampus of dDMN and the right medial superior frontal gyrus of aSN was a significant predictor of depression level in PD patients.ConclusionsAberrant intra- and inter-network FC is involved in several important hubs in the large-scale networks, which can be a biomarker for distinguishing PDD from PDND.

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“…These findings, correlated with a reduced behavioral impairment, suggest compensatory mechanisms in PD patients with tremor (Vervoort et al, 2016). FOG is frequently associated with depression (Giladi and Hausdorff, 2006) and interestingly also depressive PD patients show increased FC in the left fronto-parietal network in addition to increased FC in basal ganglia and decreased FC in salience network and DMN (Wei et al, 2017). The authors also reported hyper-connectivity between the DMN and the left fronto-parietal network in depressed PD.…”

Section: Resting State Network In Functional Magnetic Resonance Imagingmentioning

confidence: 99%

Quantitative Susceptibility Mapping and Resting State Network Analyses in Parkinsonian Phenotypes—A Systematic Review of the Literature

Pelzer

Florin

Schnitzler

2019

Front. Neural Circuits

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An imbalance of iron metabolism with consecutive aggregation of α-synuclein and axonal degeneration of neurons has been postulated as the main pathological feature in the development of Parkinson’s disease (PD). Quantitative susceptibility mapping (QSM) is a new imaging technique, which enables to measure structural changes caused by defective iron deposition in parkinsonian brains. Due to its novelty, its potential as a new imaging technique remains elusive for disease-specific characterization of motor and non-motor symptoms (characterizing the individual parkinsonian phenotype). Functional network changes associated with these symptoms are however frequently described for both magnetoencephalography (MEG) and resting state functional magnetic imaging (rs-fMRI). Here, we performed a systematic review of the current literature about QSM imaging, MEG and rs-fMRI in order to collect existing data about structural and functional changes caused by motor and non-motor symptoms in PD. Whereas all three techniques provide an effect in the motor domain, the understanding of network changes caused by non-motor symptoms is much more lacking for MEG and rs-fMRI, and does not yet really exist for QSM imaging. In order to better understand the influence of pathological iron distribution onto the functional outcome, whole-brain QSM analyses should be integrated in functional analyses (especially for the non-motor domain), to enable a proper pathophysiological interpretation of MEG and rs-fMRI network changes in PD. Herewith, a better understanding of the relationship between neuropathological changes, functional network changes and clinical phenotype might become possible.

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Aberrant Intra- and Internetwork Functional Connectivity in Depressed Parkinson’s Disease

Cited by 33 publications

References 75 publications

Separate neural representations of depression, anxiety and apathy in Parkinson’s disease

Separate neural representations of depression, anxiety and apathy in Parkinson’s disease

Networks Are Associated With Depression in Patients With Parkinson’s Disease: A Resting-State Imaging Study

Quantitative Susceptibility Mapping and Resting State Network Analyses in Parkinsonian Phenotypes—A Systematic Review of the Literature

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