Disrupted Nodal and Hub Organization Account for Brain Network Abnormalities in Parkinson’s Disease

Koshimori, Yuko; Cho, Sang Soo; Criaud, Marion; Christopher, Leigh; Jacobs, Mark F.; Ghadery, Christine; Coakeley, Sarah; Harris, Madeleine; Mizrahi, Romina; Hamani, Clement; Lang, Anthony E.; Houle, Sylvain; Strafella, Antonio P.

doi:10.3389/fnagi.2016.00259

Cited by 49 publications

(44 citation statements)

References 64 publications

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“…For example, dysfunction of somatomotor networks is not surprising, given the characteristic motor manifestations of PD (Jankovic 2008) and previous reports of their disruptions (Hacker et al 2012;Gottlich et al 2013;Olde Dubbelink et al 2014;Campbell et al 2015;Canu et al 2015;Gorges et al 2015;Tan et al 2015;Guimaraes et al 2016;Koshimori et al 2016;Peraza et al 2017). However, we show disruptions of internetwork somatomotor interactions.…”

Section: Pd Impacts Specific Cortical and Subcortical Network And Esupporting

confidence: 66%

Emergent Functional Network Effects in Parkinson Disease

et al. 2018

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The hallmark pathology underlying Parkinson disease (PD) is progressive synucleinopathy, beginning in caudal brainstem that later spreads rostrally. However, the primarily subcortical pathology fails to account for the wide spectrum of clinical manifestations in PD. To reconcile these observations, resting-state functional dysfunction across connectivity (FC) can be used to examine dysfunction across distributed brain networks. We measured FC in a large, single-site study of nondemented PD (N = 107; OFF medications) and healthy controls (N = 46) incorporating rigorous quality control measures and comprehensive sampling of cortical, subcortical and cerebellar regions. We employed novel statistical approaches to determine group differences across the entire connectome, at the network-level, and for select brain regions. Group differences respected well-characterized network delineations producing a striking "block-wise" pattern of network-to-network effects. Surprisingly, these results demonstrate that the greatest FC differences involve sensorimotor, thalamic, and cerebellar networks, with notably smaller striatal effects. Split-half replication demonstrates the robustness of these results. Finally, block-wise FC correlations with behavior suggest that FC disruptions may contribute to clinical manifestations in PD. Overall, these results indicate a concerted breakdown of functional network interactions, remote from primary pathophysiology, and suggest that FC deficits in PD are related to emergent network-level phenomena rather than focal pathology.

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Section: Pd Impacts Specific Cortical and Subcortical Network And Esupporting

confidence: 66%

Emergent Functional Network Effects in Parkinson Disease

et al. 2018

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“…Further investigations have aimed to explore functional changes in sensorimotor and cognitive networks in PD, focusing on inter‐ and intraconnectivity organization in the disease‐associated nodal and hub regions, using graph theoretical analyses. To date, findings have highlighted diffuse alterations in nodal organization and regional hub disruption that result in a number of distributed abnormalities across brain networks that may be related to the specific clinical manifestations of PD …”

Section: Mri In Pdmentioning

confidence: 99%

“…To date, findings have highlighted diffuse alterations in nodal organization and regional hub disruption that result in a number of distributed abnormalities across brain networks that may be related to the specific clinical manifestations of PD. 126 The Role of Ultra-High Field Imaging Despite several limitations, MRI has certainly enhanced the diagnostic accuracy in the differential diagnosis of neurodegenerative parkinsonism over the last years.…”

Section: Reviewmentioning

confidence: 99%

Imaging Markers of Progression in Parkinson's Disease

Strafella

Bohnen

Pavese

et al. 2018

Movement Disord Clin Pract

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Background Parkinson's disease (PD) is the second‐most common neurodegenerative disorder after Alzheimer's disease; however, to date, there is no approved treatment that stops or slows down disease progression. Over the past decades, neuroimaging studies, including molecular imaging and MRI are trying to provide insights into the mechanisms underlying PD. Methods This work utilized a literature review. Results It is now becoming clear that these imaging modalities can provide biomarkers that can objectively detect brain changes related to PD and monitor these changes as the disease progresses, and these biomarkers are required to establish a breakthrough in neuroprotective or disease‐modifying therapeutics. Conclusions Here, we provide a review of recent observations deriving from PET, single‐positron emission tomography, and MRI studies exploring PD and other parkinsonian disorders.

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“…Furthermore, the characteristics of the brain networks can be investigated with graph-theory, which divides the networks in nodes (the brain regions) and in edges , representing the connections between the nodes ( Bullmore and Sporns, 2009 , Van Den Heuvel et al, 2010 ). Most graph-theoretical studies in PD showed significant reductions in both global and local parameters compared with HC ( Göttlich et al, 2013 , Koshimori et al, 2016 , Luo et al, 2015 , Skidmore et al, 2011 , Tinaz et al, 2016 ) but increased graph parameters have also been found in PD compared with HC ( Göttlich et al, 2013 , Zhang et al, 2015 ). A graph theory approach may contribute to understanding of cognitive impairment in PD.…”

Section: Introductionmentioning

confidence: 99%

Dynamic functional connectivity in Parkinson's disease patients with mild cognitive impairment and normal cognition

Díez‐Cirarda

Strafella

Kim

et al. 2018

NeuroImage: Clinical

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The objective was to assess dynamic functional connectivity (FC) and local/global connectivity in Parkinson's disease (PD) patients with mild cognitive impairment (PD-MCI) and with normal cognition (PD-NC).The sample included 35 PD patients and 26 healthy controls (HC). Cognitive assessment followed an extensive neuropsychological battery. For resting-state functional MRI (rs-fMRI) analysis, independent component analysis (ICA) was performed and components were located in 7 networks: Subcortical (SC), Auditory (AUD), Somatomotor (SM), visual (VI), cognitive-control (CC), default-mode (DMN), and cerebellar (CB). Dynamic FC analysis was performed using the GIFT toolbox. FC differences between groups in each FC state were analysed with the network-based statistic (NBS) approach. Finally, a graph-theoretical analysis for local/global parameters was performed.The whole sample showed 2 dynamic FC states during the rs-fMRI. PD-MCI patients showed decreased mean dwell time in the hypo-connectivity state (p = 0.030) and showed increased number of state transitions (p = 0.007) compared with the HC. In addition, in the hypo-connectivity state, PD-MCI patients showed reduced inter-network FC between the SM-CC, SM-VI, SM-AUD, CC-VI and SC-DMN compared with the HC (p < 0.05-FDR). These FC alterations in PD-MCI were accompanied by graph-topological alterations in nodes located in the SM network (p < 0.001). In contrast, no differences were found between the PD-NC and HC.Findings suggest the presence of dynamic functional brain deteriorations in PD-MCI that are not present in PD-NC, showing the PD-MCI group dynamic FC dysfunctions, reduced FC mostly between SM-CC networks and graph-topological deteriorations in the SM network. A dynamic FC approach could be helpful to understand cognitive deterioration in PD.

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Disrupted Nodal and Hub Organization Account for Brain Network Abnormalities in Parkinson’s Disease

Cited by 49 publications

References 64 publications

Emergent Functional Network Effects in Parkinson Disease

Emergent Functional Network Effects in Parkinson Disease

Imaging Markers of Progression in Parkinson's Disease

Dynamic functional connectivity in Parkinson's disease patients with mild cognitive impairment and normal cognition

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