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      Cerebellar resting-state functional connectivity in Parkinson's disease and multiple system atrophy: Characterization of abnormalities and potential for differential diagnosis at the single-patient level

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          Abstract

          Background

          Recent studies using resting-state functional connectivity and machine-learning to distinguish patients with neurodegenerative diseases from other groups of subjects show promising results. This approach has not been tested to discriminate between Parkinson's disease (PD) and multiple system atrophy (MSA) patients.

          Objectives

          Our first aim is to characterize possible abnormalities in resting-state functional connectivity between the cerebellum and a set of intrinsic-connectivity brain networks and between the cerebellum and different regions of the striatum in PD and MSA. The second objective of this study is to assess the potential of cerebellar connectivity measures to distinguish between PD and MSA patients at the single-patient level.

          Methods

          Fifty-nine healthy controls, 62 PD patients, and 30 MSA patients underwent resting-state functional MRI with a 3T scanner. Independent component analysis and dual regression were used to define seven resting-state networks of interest. To assess striatal connectivity, a seed-to-voxel approach was used after dividing the striatum into six regions bilaterally. Measures of cerebellar-brain network and cerebellar-striatal connectivity were then used as features in a support vector machine to discriminate between PD and MSA patients.

          Results

          MSA patients displayed reduced cerebellar connectivity with different brain networks and with the striatum compared with PD patients and with controls. The classification procedure achieved an overall accuracy of 77.17% with 83.33% of the MSA subjects and 74.19% of the PD patients correctly classified.

          Conclusion

          Our findings suggest that measures of cerebellar functional connectivity have the potential to distinguish between PD and MSA patients.

          Highlights

          • •

            Reduced cerebellar functional connectivity in MSA compared with healthy controls.

          • •

            Reduced cerebellar-striatal functional connectivity in MSA compared with PD.

          • •

            Reduced connectivity between cerebellum and brain networks in MSA compared with PD.

          • •

            Cerebellar connectivity might help discriminate between MSA and PD patients.

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          Most cited references44

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          The accuracy of diagnosis of parkinsonian syndromes in a specialist movement disorder service.

          Andrew Hughes, Susan Daniel, Yoav Ben-Shlomo … (2002)
          We have reviewed the clinical and pathological diagnoses of 143 cases of parkinsonism seen by neurologists associated with the movement disorders service at The National Hospital for Neurology and Neurosurgery in London who came to neuropathological examination at the United Kingdom Parkinson's Disease Society Brain Research Centre, over a 10-year period between 1990 and the end of 1999. Seventy-three (47 male, 26 female) cases were diagnosed as having idiopathic Parkinson's disease (IPD) and 70 (42 male, 28 female) as having another parkinsonian syndrome. The positive predictive value of the clinical diagnosis for the whole group was 85.3%, with 122 cases correctly clinically diagnosed. The positive predictive value of the clinical diagnosis of IPD was extremely high, at 98.6% (72 out of 73), while for the other parkinsonian syndromes it was 71.4% (50 out of 70). The positive predictive values of a clinical diagnosis of multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) were 85.7 (30 out of 35) and 80% (16 out of 20), respectively. The sensitivity for IPD was 91.1%, due to seven false-negative cases, with 72 of the 79 pathologically established cases being diagnosed in life. For MSA, the sensitivity was 88.2% (30 out of 34), and for PSP it was 84.2% (16 out of 19). The diagnostic accuracy for IPD, MSA and PSP was higher than most previous prospective clinicopathological series and studies using the retrospective application of clinical diagnostic criteria. The seven false-negative cases of IPD suggest a broader clinical picture of disease than previously thought acceptable. This study implies that neurologists with particular expertise in the field of movement disorders may be using a method of pattern recognition for diagnosis which goes beyond that inherent in any formal set of diagnostic criteria.
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            The cerebellum and cognition

            Jeremy D Schmahmann (2018)
            What the cerebellum does to sensorimotor and vestibular control, it also does to cognition, emotion, and autonomic function. This hypothesis is based on the theories of dysmetria of thought and the universal cerebellar transform, which hold that the cerebellum maintains behavior around a homeostatic baseline, automatically, without conscious awareness, informed by implicit learning, and performed according to context. Functional topography within the cerebellum facilitates the modulation of distributed networks subserving multiple different functions. The sensorimotor cerebellum is represented in the anterior lobe with a second representation in lobule VIII, and lesions of these areas lead to the cerebellar motor syndrome of ataxia, dysmetria, dysarthria and impaired oculomotor control. The cognitive / limbic cerebellum is in the cerebellar posterior lobe, with current evidence pointing to three separate topographic representations, the nature of which remain to be determined. Posterior lobe lesions result in the cerebellar cognitive affective syndrome (CCAS), the hallmark features of which include deficits in executive function, visual spatial processing, linguistic skills and regulation of affect. The affective dyscontrol manifests in autism spectrum and psychosis spectrum disorders, and disorders of emotional control, attentional control, and social skill set. This report presents an overview of the rapidly growing field of the clinical cognitive neuroscience of the cerebellum. It commences with a brief historical background, then discusses tract tracing experiments in animal models and functional imaging observations in humans that subserve the cerebellar contribution to neurological function. Structure function correlation studies following focal cerebellar lesions in adults and children permit a finer appreciation of the functional topography and nature of the cerebellar motor syndrome, cerebellar vestibular syndrome, and the third cornerstone of clinical ataxiology - the cerebellar cognitive affective syndrome. The ability to detect the CCAS in real time in clinical neurology with a brief and validated scale should make it possible to develop a deeper understanding of the clinical consequences of cerebellar lesions in a wide range of neurological and neuropsychiatric disorders with a link to the cerebellum.
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              Intrinsic architecture underlying the relations among the default, dorsal attention, and frontoparietal control networks of the human brain.

              R. Nathan Spreng, Jorge Sepulcre, Gary Turner … (2013)
              Human cognition is increasingly characterized as an emergent property of interactions among distributed, functionally specialized brain networks. We recently demonstrated that the antagonistic "default" and "dorsal attention" networks--subserving internally and externally directed cognition, respectively--are modulated by a third "frontoparietal control" network that flexibly couples with either network depending on task domain. However, little is known about the intrinsic functional architecture underlying this relationship. We used graph theory to analyze network properties of intrinsic functional connectivity within and between these three large-scale networks. Task-based activation from three independent studies were used to identify reliable brain regions ("nodes") of each network. We then examined pairwise connections ("edges") between nodes, as defined by resting-state functional connectivity MRI. Importantly, we used a novel bootstrap resampling procedure to determine the reliability of graph edges. Furthermore, we examined both full and partial correlations. As predicted, there was a higher degree of integration within each network than between networks. Critically, whereas the default and dorsal attention networks shared little positive connectivity with one another, the frontoparietal control network showed a high degree of between-network interconnectivity with each of these networks. Furthermore, we identified nodes within the frontoparietal control network of three different types--default-aligned, dorsal attention-aligned, and dual-aligned--that we propose play dissociable roles in mediating internetwork communication. The results provide evidence consistent with the idea that the frontoparietal control network plays a pivotal gate-keeping role in goal-directed cognition, mediating the dynamic balance between default and dorsal attention networks.
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                Author and article information

                Contributors
                Hugo C. Baggio
                Alexandra Abos
                Barbara Segura
                Anna Campabadal
                Carme Uribe
                Alexandra Perez-Soriano
                Esteban Muñoz
                Yaroslau Compta
                Carme Junque
                Maria Jose Marti
                Journal
                Journal ID (nlm-ta): Neuroimage Clin
                Journal ID (iso-abbrev): Neuroimage Clin
                Title: NeuroImage : Clinical
                Publisher: Elsevier
                ISSN (Electronic): 2213-1582
                Publication date PMC-release: 13 February 2019
                Publication date Collection: 2019
                Publication date (Electronic): 13 February 2019
                Volume: 22
                Electronic Location Identifier: 101720
                Affiliations
                [a ]Medical Psychology Unit, Department of Medicine, Institute of Neuroscience, University of Barcelona, Barcelona, Catalonia, Spain
                [b ]Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic de Barcelona, Barcelona, Catalonia, Spain
                [c ]Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institute of Neuroscience, University of Barcelona, Barcelona, Catalonia, Spain
                [d ]Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), Barcelona, Catalonia, Spain
                Author notes
                [* ]Corresponding author at: Parkinson's Disease and Movement Disorders Unit of the Neurology Service of Hospital Clinic, Carrer de Villarroel 170, 08036 Barcelona, Catalonia, Spain. mjmarti@ 123456clinic.cat
                [1]

                HCB and AA contributed equally to the manuscript.

                Article
                Publisher ID: S2213-1582(19)30070-1 Publisher ID: 101720
                DOI: 10.1016/j.nicl.2019.101720
                PMC ID: 6383182
                PubMed ID: 30785051
                SO-VID: ec2da107-697f-458a-b25f-4554de5b0f12
                Copyright © © 2019 The Authors
                License:

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                Date received : 15 November 2018
                Date revision received : 3 February 2019
                Date accepted : 12 February 2019
                Categories
                Subject: Regular Article

                Keywords: machine learning,parkinson's disease,multiple system atrophy,functional connectivity,resting state,cerebellum
                Data availability:
                Keywords: machine learning, parkinson's disease, multiple system atrophy, functional connectivity, resting state, cerebellum

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