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Chen RB, Li XT, Huang X. Topological Organization of the Brain Network in Patients with Primary Angle-closure Glaucoma Through Graph Theory Analysis. Brain Topogr 2024:10.1007/s10548-024-01060-4. [PMID: 38822211 DOI: 10.1007/s10548-024-01060-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Accepted: 05/29/2024] [Indexed: 06/02/2024]
Abstract
Primary angle-closure glaucoma (PACG) is a sight-threatening eye condition that leads to irreversible blindness. While past neuroimaging research has identified abnormal brain function in PACG patients, the relationship between PACG and alterations in brain functional networks has yet to be explored. This study seeks to examine the influence of PACG on brain networks, aiming to advance knowledge of its neurobiological processes for better diagnostic and therapeutic approaches utilizing graph theory analysis. A cohort of 44 primary angle-closure glaucoma (PACG) patients and 44 healthy controls participated in this study. Functional brain networks were constructed using fMRI data and the Automated Anatomical Labeling 90 template. Subsequently, graph theory analysis was employed to evaluate global metrics, nodal metrics, modular organization, and network-based statistics (NBS), enabling a comparative analysis between PACG patients and the control group. The analysis of global metrics, including small-worldness and network efficiency, did not exhibit significant differences between the two groups. However, PACG patients displayed elevated nodal metrics, such as centrality and efficiency, in the left frontal superior medial, right frontal superior medial, and right posterior central brain regions, along with reduced values in the right temporal superior gyrus region compared to healthy controls. Furthermore, Module 5 showed notable disparities in intra-module connectivity, while Module 1 demonstrated substantial differences in inter-module connectivity with both Module 7 and Module 8. Noteworthy, the NBS analysis unveiled a significantly altered network when comparing the PACG and healthy control groups. The study proposes that PACG patients demonstrate variations in nodal metrics and modularity within functional brain networks, particularly affecting the prefrontal, occipital, and temporal lobes, along with cerebellar regions. However, an analysis of global metrics suggests that the overall connectivity patterns of the entire brain network remain unaltered in PACG patients. These results have the potential to serve as early diagnostic and differential markers for PACG, and interventions focusing on brain regions with high degree centrality and nodal efficiency could aid in optimizing therapeutic approaches.
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Affiliation(s)
- Ri-Bo Chen
- Department of Radiology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, Jiangxi, China
| | - Xiao-Tong Li
- Queen Mary School, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Xin Huang
- Department of Ophthalmology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, No 152, Ai Guo Road, Dong Hu District, Nanchang, 330006, Jiangxi, China.
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2
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Koivu M, Sihvonen AJ, Eerola-Rautio J, Pauls KAM, Resendiz-Nieves J, Vartiainen N, Kivisaari R, Scheperjans F, Pekkonen E. Clinical and Brain Morphometry Predictors of Deep Brain Stimulation Outcome in Parkinson's Disease. Brain Topogr 2024:10.1007/s10548-024-01054-2. [PMID: 38662300 DOI: 10.1007/s10548-024-01054-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 04/18/2024] [Indexed: 04/26/2024]
Abstract
Subthalamic deep brain stimulation (STN-DBS) is known to improve motor function in advanced Parkinson's disease (PD) and to enable a reduction of anti-parkinsonian medication. While the levodopa challenge test and disease duration are considered good predictors of STN-DBS outcome, other clinical and neuroanatomical predictors are less established. This study aimed to evaluate, in addition to clinical predictors, the effect of patients' individual brain topography on DBS outcome. The medical records of 35 PD patients were used to analyze DBS outcomes measured with the following scales: Part III of the Unified Parkinson's Disease Rating Scale (UPDRS-III) off medication at baseline, and at 6-months during medication off and stimulation on, use of anti-parkinsonian medication (LED), Abnormal Involuntary Movement Scale (AIMS) and Non-Motor Symptoms Questionnaire (NMS-Quest). Furthermore, preoperative brain MRI images were utilized to analyze the brain morphology in relation to STN-DBS outcome. With STN-DBS, a 44% reduction in the UPDRS-III score and a 43% decrease in the LED were observed (p<0.001). Dyskinesia and non-motor symptoms decreased significantly [median reductions of 78,6% (IQR 45,5%) and 18,4% (IQR 32,2%) respectively, p=0.001 - 0.047]. Along with the levodopa challenge test, patients' age correlated with the observed DBS outcome measured as UPDRS-III improvement (ρ= -0.466 - -0.521, p<0.005). Patients with greater LED decline had lower grey matter volumes in left superior medial frontal gyrus, in supplementary motor area and cingulum bilaterally. Additionally, patients with greater UPDRS-III score improvement had lower grey matter volume in similar grey matter areas. These findings remained significant when adjusted for sex, age, baseline LED and UPDRS scores respectively and for total intracranial volume (p=0.0041- 0.001). However, only the LED decrease finding remained significant when the analyses were further controlled for stimulation amplitude. It appears that along with the clinical predictors of STN-DBS outcome, individual patient topographic differences may influence DBS outcome. Clinical Trial Registration Number: NCT06095245, registration date October 23, 2023, retrospectively registered.
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Affiliation(s)
- Maija Koivu
- Department of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences (Neurology), University of Helsinki, Finland, Helsinki, Finland.
| | - Aleksi J Sihvonen
- Department of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences (Neurology), University of Helsinki, Finland, Helsinki, Finland
- Cognitive Brain Research Unit, Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Johanna Eerola-Rautio
- Department of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences (Neurology), University of Helsinki, Finland, Helsinki, Finland
| | - K Amande M Pauls
- Department of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences (Neurology), University of Helsinki, Finland, Helsinki, Finland
| | | | - Nuutti Vartiainen
- Department of Neurosurgery, Helsinki University Hospital, Helsinki, Finland
| | - Riku Kivisaari
- Department of Neurosurgery, Helsinki University Hospital, Helsinki, Finland
| | - Filip Scheperjans
- Department of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences (Neurology), University of Helsinki, Finland, Helsinki, Finland
| | - Eero Pekkonen
- Department of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences (Neurology), University of Helsinki, Finland, Helsinki, Finland
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Andrews L, Keller SS, Osman-Farah J, Macerollo A. A structural magnetic resonance imaging review of clinical motor outcomes from deep brain stimulation in movement disorders. Brain Commun 2023; 5:fcad171. [PMID: 37304793 PMCID: PMC10257440 DOI: 10.1093/braincomms/fcad171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 04/05/2023] [Accepted: 05/30/2023] [Indexed: 06/13/2023] Open
Abstract
Patients with movement disorders treated by deep brain stimulation do not always achieve successful therapeutic alleviation of motor symptoms, even in cases where surgery is without complications. Magnetic resonance imaging (MRI) offers methods to investigate structural brain-related factors that may be predictive of clinical motor outcomes. This review aimed to identify features which have been associated with variability in clinical post-operative motor outcomes in patients with Parkinson's disease, dystonia, and essential tremor from structural MRI modalities. We performed a literature search for articles published between 1 January 2000 and 1 April 2022 and identified 5197 articles. Following screening through our inclusion criteria, we identified 60 total studies (39 = Parkinson's disease, 11 = dystonia syndromes and 10 = essential tremor). The review captured a range of structural MRI methods and analysis techniques used to identify factors related to clinical post-operative motor outcomes from deep brain stimulation. Morphometric markers, including volume and cortical thickness were commonly identified in studies focused on patients with Parkinson's disease and dystonia syndromes. Reduced metrics in basal ganglia, sensorimotor and frontal regions showed frequent associations with reduced motor outcomes. Increased structural connectivity to subcortical nuclei, sensorimotor and frontal regions was also associated with greater motor outcomes. In patients with tremor, increased structural connectivity to the cerebellum and cortical motor regions showed high prevalence across studies for greater clinical motor outcomes. In addition, we highlight conceptual issues for studies assessing clinical response with structural MRI and discuss future approaches towards optimizing individualized therapeutic benefits. Although quantitative MRI markers are in their infancy for clinical purposes in movement disorder treatments, structural features obtained from MRI offer the powerful potential to identify candidates who are more likely to benefit from deep brain stimulation and provide insight into the complexity of disorder pathophysiology.
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Affiliation(s)
- Luke Andrews
- Correspondence to: Luke Andrews The BRAIN Lab, University of Liverpool Cancer Research Centre 200 London Rd, Liverpool L3 9TA, United Kingdom E-mail:
| | - Simon S Keller
- The Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L3 9TA, UK
| | - Jibril Osman-Farah
- Department of Neurology and Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool L97LJ, UK
| | - Antonella Macerollo
- Correspondence may also be sent to: Antonella Macerollo. The Walton Centre NHS Trust, Lower Lane Liverpool L9 7LJ, United Kingdom E-mail:
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Wang F, Lai Y, Pan Y, Li H, Liu Q, Sun B. A systematic review of brain morphometry related to deep brain stimulation outcome in Parkinson's disease. NPJ Parkinsons Dis 2022; 8:130. [PMID: 36224189 PMCID: PMC9556527 DOI: 10.1038/s41531-022-00403-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 09/29/2022] [Indexed: 11/05/2022] Open
Abstract
While the efficacy of deep brain stimulation (DBS) is well-established in Parkinson’s Disease (PD), the benefit of DBS varies across patients. Using imaging features for outcome prediction offers potential in improving effectiveness, whereas the value of presurgical brain morphometry, derived from the routinely used imaging modality in surgical planning, remains under-explored. This review provides a comprehensive investigation of links between DBS outcomes and brain morphometry features in PD. We systematically searched PubMed and Embase databases and retrieved 793 articles, of which 25 met inclusion criteria and were reviewed in detail. A majority of studies (24/25), including 1253 of 1316 patients, focused on the outcome of DBS targeting the subthalamic nucleus (STN), while five studies included 57 patients receiving globus pallidus internus (GPi) DBS. Accumulated evidence showed that the atrophy of motor cortex and thalamus were associated with poor motor improvement, other structures such as the lateral-occipital cortex and anterior cingulate were also reported to correlated with motor outcome. Regarding non-motor outcomes, decreased volume of the hippocampus was reported to correlate with poor cognitive outcomes. Structures such as the thalamus, nucleus accumbens, and nucleus of basalis of Meynert were also reported to correlate with cognitive functions. Caudal middle frontal cortex was reported to have an impact on postsurgical psychiatric changes. Collectively, the findings of this review emphasize the utility of brain morphometry in outcome prediction of DBS for PD. Future efforts are needed to validate the findings and demonstrate the feasibility of brain morphometry in larger cohorts.
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Affiliation(s)
- Fengting Wang
- grid.16821.3c0000 0004 0368 8293Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yijie Lai
- grid.16821.3c0000 0004 0368 8293Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yixin Pan
- grid.16821.3c0000 0004 0368 8293Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongyang Li
- grid.16821.3c0000 0004 0368 8293Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qimin Liu
- grid.152326.10000 0001 2264 7217Department of Psychology and Human Development, Vanderbilt University, Nashville, USA
| | - Bomin Sun
- grid.16821.3c0000 0004 0368 8293Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Leisman G, Melillo R. Front and center: Maturational dysregulation of frontal lobe functional neuroanatomic connections in attention deficit hyperactivity disorder. Front Neuroanat 2022; 16:936025. [PMID: 36081853 PMCID: PMC9446472 DOI: 10.3389/fnana.2022.936025] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 07/29/2022] [Indexed: 12/21/2022] Open
Abstract
Frontal lobe function may not universally explain all forms of attention deficit hyperactivity disorder (ADHD) but the frontal lobe hypothesis described supports an internally consistent model for integrating the numerous behaviors associated with ADHD. The paper examines the developmental trajectories of frontal and prefrontal lobe development, framing ADHD as maturational dysregulation concluding that the cognitive, motor, and behavioral abilities of the presumptive majority of ADHD children may not primarily be disordered or dysfunctional but reflect maturational dysregulation that is inconsistent with the psychomotor and cognitive expectations for the child’s chronological and mental age. ADHD children demonstrate decreased activation of the right and middle prefrontal cortex. Prefrontal and frontal lobe regions have an exuberant network of shared pathways with the diencephalic region, also having a regulatory function in arousal as well as with the ascending reticular formation which has a capacity for response suppression to task-irrelevant stimuli. Prefrontal lesions oftentimes are associated with the regulatory breakdown of goal-directed activity and impulsivity. In conclusion, a presumptive majority of childhood ADHD may result from maturational dysregulation of the frontal lobes with effects on the direct, indirect and/or, hyperdirect pathways.
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Affiliation(s)
- Gerry Leisman
- Movement and Cognition Laboratory, Department of Physical Therapy, University of Haifa, Haifa, Israel
- Department of Neurology, University of Medical Sciences of Havana, Havana, Cuba
- *Correspondence: Gerry Leisman,
| | - Robert Melillo
- Movement and Cognition Laboratory, Department of Physical Therapy, University of Haifa, Haifa, Israel
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Papo D. Attaining the recesses of the cognitive space. Cogn Neurodyn 2022; 16:767-778. [PMID: 35847536 PMCID: PMC9279523 DOI: 10.1007/s11571-021-09755-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 10/31/2021] [Accepted: 11/08/2021] [Indexed: 11/26/2022] Open
Abstract
Existing neuropsychological tests of executive function often manifest a difficulty pinpointing cognitive deficits when these are intermittent and come in the form of omissions. We discuss the hypothesis that two partially interrelated reasons for this failure stem from relative inability of neuropsychological tests to explore the cognitive space and to explicitly take into account strategic and opportunistic resource allocation decisions, and to address the temporal aspects of both behaviour and task-related brain function in data analysis. Criteria for tasks suitable for neuropsychological assessment of executive function, as well as appropriate ways to analyse and interpret observed behavioural data are suggested. It is proposed that experimental tasks should be devised which emphasize typical rather than optimal performance, and that analyses should quantify path-dependent fluctuations in performance levels rather than averaged behaviour. Some implications for experimental neuropsychology are illustrated for the case of planning and problem-solving abilities and with particular reference to cognitive impairment in closed-head injury.
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Affiliation(s)
- David Papo
- Department of Neuroscience and Rehabilitation, Section of Physiology, University of Ferrara, Ferrara, Italy
- Fondazione Istituto Italiano di Tecnologia, Ferrara, Italy
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Gracco VL, Sares AG, Koirala N. Structural brain network topological alterations in stuttering adults. Brain Commun 2022; 4:fcac058. [PMID: 35368614 PMCID: PMC8971894 DOI: 10.1093/braincomms/fcac058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 01/06/2022] [Accepted: 03/08/2022] [Indexed: 11/13/2022] Open
Abstract
Abstract
Persistent developmental stuttering is a speech disorder that primarily affects normal speech fluency but encompasses a complex set of symptoms ranging from reduced sensorimotor integration to socioemotional challenges. Here, we investigated the whole brain structural connectome and its topological alterations in adults who stutter. Diffusion weighted imaging data of 33 subjects (13 adults who stutter and 20 fluent speakers) was obtained along with a stuttering severity evaluation. The structural brain network properties were analyzed using Network-based statistics and graph theoretical measures particularly focusing on community structure, network hubs and controllability. Bayesian power estimation was used to assess the reliability of the structural connectivity differences by examining the effect size. The analysis revealed reliable and wide-spread decreases in connectivity for adults who stutter in regions associated with sensorimotor, cognitive, emotional, and memory-related functions. The community detection algorithms revealed different subnetworks for fluent speakers and adults who stutter, indicating considerable network adaptation in adults who stutter. Average and modal controllability differed between groups in a subnetwork encompassing frontal brain regions and parts of the basal ganglia.
The results revealed extensive structural network alterations and substantial adaptation in neural architecture in adults who stutter well beyond the sensorimotor network. These findings highlight the impact of the neurodevelopmental effects of persistent stuttering on neural organization and the importance of examining the full structural connectome and the network alterations that underscore the behavioral phenotype.
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Affiliation(s)
- Vincent L. Gracco
- Haskins Laboratories, New Haven, CT, USA
- School of Communication Sciences & Disorders, McGill University, Montreal, Canada
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Gonzalez-Escamilla G, Koirala N, Bange M, Glaser M, Pintea B, Dresel C, Deuschl G, Muthuraman M, Groppa S. Deciphering the Network Effects of Deep Brain Stimulation in Parkinson's Disease. Neurol Ther 2022; 11:265-282. [PMID: 35000133 PMCID: PMC8857357 DOI: 10.1007/s40120-021-00318-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 12/21/2021] [Indexed: 10/31/2022] Open
Abstract
INTRODUCTION Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an established therapy for Parkinson's disease (PD). However, a more detailed characterization of the targeted network and its grey matter (GM) terminals that drive the clinical outcome is needed. In this direction, the use of MRI after DBS surgery is now possible due to recent advances in hardware, opening a window for the clarification of the association between the affected tissue, including white matter fiber pathways and modulated GM regions, and the DBS-related clinical outcome. Therefore, we present a computational framework for reconstruction of targeted networks on postoperative MRI. METHODS We used a combination of preoperative whole-brain T1-weighted (T1w) and diffusion-weighted MRI data for morphometric integrity assessment and postoperative T1w MRI for electrode reconstruction and network reconstruction in 15 idiopathic PD patients. Within this framework, we made use of DBS lead artifact intensity profiles on postoperative MRI to determine DBS locations used as seeds for probabilistic tractography to cortical and subcortical targets within the motor circuitry. Lastly, we evaluated the relationship between brain microstructural characteristics of DBS-targeted brain network terminals and postoperative clinical outcomes. RESULTS The proposed framework showed robust performance for identifying the DBS electrode positions. Connectivity profiles between the primary motor cortex (M1), supplementary motor area (SMA), and DBS locations were strongly associated with the stimulation intensity needed for the optimal clinical outcome. Local diffusion properties of the modulated pathways were related to DBS outcomes. STN-DBS motor symptom improvement was highly associated with cortical thickness in the middle frontal and superior frontal cortices, but not with subcortical volumetry. CONCLUSION These data suggest that STN-DBS outcomes largely rely on the modulatory interference from cortical areas, particularly M1 and SMA, to DBS locations.
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Affiliation(s)
- Gabriel Gonzalez-Escamilla
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany.
| | - Nabin Koirala
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Manuel Bange
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Martin Glaser
- Department of Neurosurgery, University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Bogdan Pintea
- Department of Neurosurgery, University Hospital Bergmannsheil, Bürkle de la Camp-Platz 1, 44789, Bochum, Germany
| | - Christian Dresel
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Günther Deuschl
- Department of Neurology, Schleswig-Holstein University Hospital UKSH, Arnold-Heller-Straße 3, 24105, Kiel, Germany
| | - Muthuraman Muthuraman
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstrasse 1, 55131, Mainz, Germany.
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Shih YC, Tseng WYI, Montaser-Kouhsari L. Recent advances in using diffusion tensor imaging to study white matter alterations in Parkinson's disease: A mini review. Front Aging Neurosci 2022; 14:1018017. [PMID: 36910861 PMCID: PMC9992993 DOI: 10.3389/fnagi.2022.1018017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 12/26/2022] [Indexed: 02/24/2023] Open
Abstract
Parkinson's disease (PD) is the second most common age-related neurodegenerative disease with cardinal motor symptoms. In addition to motor symptoms, PD is a heterogeneous disease accompanied by many non-motor symptoms that dominate the clinical manifestations in different stages or subtypes of PD, such as cognitive impairments. The heterogeneity of PD suggests widespread brain structural changes, and axonal involvement appears to be critical to the pathophysiology of PD. As α-synuclein pathology has been suggested to cause axonal changes followed by neuronal degeneration, diffusion tensor imaging (DTI) as an in vivo imaging technique emerges to characterize early detectable white matter changes due to PD. Here, we reviewed the past 5-year literature to show how DTI has helped identify axonal abnormalities at different PD stages or in different PD subtypes and atypical parkinsonism. We also showed the recent clinical utilities of DTI tractography in interventional treatments such as deep brain stimulation (DBS). Mounting evidence supported by multisite DTI data suggests that DTI along with the advanced analytic methods, can delineate dynamic pathophysiological processes from the early to late PD stages and differentiate distinct structural networks affected in PD and other parkinsonism syndromes. It indicates that DTI, along with recent advanced analytic methods, can assist future interventional studies in optimizing treatments for PD patients with different clinical conditions and risk profiles.
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Affiliation(s)
- Yao-Chia Shih
- Graduate Institute of Medicine, Yuan Ze University, Taoyuan, Taiwan
| | - Wen-Yih Isaac Tseng
- AcroViz Inc., Taipei, Taiwan.,Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan
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Wu C, Ferreira F, Fox M, Harel N, Hattangadi-Gluth J, Horn A, Jbabdi S, Kahan J, Oswal A, Sheth SA, Tie Y, Vakharia V, Zrinzo L, Akram H. Clinical applications of magnetic resonance imaging based functional and structural connectivity. Neuroimage 2021; 244:118649. [PMID: 34648960 DOI: 10.1016/j.neuroimage.2021.118649] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 09/24/2021] [Accepted: 10/10/2021] [Indexed: 12/23/2022] Open
Abstract
Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.
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Affiliation(s)
- Chengyuan Wu
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, 909 Walnut Street, Third Floor, Philadelphia, PA 19107, USA; Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut Street, First Floor, Philadelphia, PA 19107, USA.
| | - Francisca Ferreira
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
| | - Michael Fox
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, Radiology, and Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA.
| | - Noam Harel
- Center for Magnetic Resonance Research, University of Minnesota, 2021 Sixth Street S.E., Minneapolis, MN 55455, USA.
| | - Jona Hattangadi-Gluth
- Department of Radiation Medicine and Applied Sciences, Center for Precision Radiation Medicine, University of California, San Diego, 3855 Health Sciences Drive, La Jolla, CA 92037, USA.
| | - Andreas Horn
- Neurology Department, Movement Disorders and Neuromodulation Section, Charité - University Medicine Berlin, Charitéplatz 1, D-10117, Berlin, Germany.
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK.
| | - Joshua Kahan
- Department of Neurology, Weill Cornell Medicine, 525 East 68th Street, New York, NY, 10065, USA.
| | - Ashwini Oswal
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Mansfield Rd, Oxford OX1 3TH, UK.
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, 7200 Cambridge, Ninth Floor, Houston, TX 77030, USA.
| | - Yanmei Tie
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, Radiology, and Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA; Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA.
| | - Vejay Vakharia
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK.
| | - Ludvic Zrinzo
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
| | - Harith Akram
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
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Koirala N, Kleinman D, Perdue MV, Su X, Villa M, Grigorenko EL, Landi N. Widespread effects of dMRI data quality on diffusion measures in children. Hum Brain Mapp 2021; 43:1326-1341. [PMID: 34799957 PMCID: PMC8837592 DOI: 10.1002/hbm.25724] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 11/02/2021] [Accepted: 11/11/2021] [Indexed: 12/12/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) datasets are susceptible to several confounding factors related to data quality, which is especially true in studies involving young children. With the recent trend of large‐scale multicenter studies, it is more critical to be aware of the varied impacts of data quality on measures of interest. Here, we investigated data quality and its effect on different diffusion measures using a multicenter dataset. dMRI data were obtained from 691 participants (5–17 years of age) from six different centers. Six data quality metrics—contrast to noise ratio, outlier slices, and motion (absolute, relative, translation, and rotational)—and four diffusion measures—fractional anisotropy, mean diffusivity, tract density, and length—were computed for each of 36 major fiber tracts for all participants. The results indicated that four out of six data quality metrics (all except absolute and translation motion) differed significantly between centers. Associations between these data quality metrics and the diffusion measures differed significantly across the tracts and centers. Moreover, these effects remained significant after applying recently proposed harmonization algorithms that purport to remove unwanted between‐site variation in diffusion data. These results demonstrate the widespread impact of dMRI data quality on diffusion measures. These tracts and measures have been routinely associated with individual differences as well as group‐wide differences between neurotypical populations and individuals with neurological or developmental disorders. Accordingly, for analyses of individual differences or group effects (particularly in multisite dataset), we encourage the inclusion of data quality metrics in dMRI analysis.
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Affiliation(s)
| | | | - Meaghan V Perdue
- Haskins Laboratories, New Haven, Connecticut, USA.,Department of Psychological Sciences, University of Connecticut, Connecticut, USA
| | - Xing Su
- Haskins Laboratories, New Haven, Connecticut, USA
| | - Martina Villa
- Haskins Laboratories, New Haven, Connecticut, USA.,Department of Psychological Sciences, University of Connecticut, Connecticut, USA
| | - Elena L Grigorenko
- Haskins Laboratories, New Haven, Connecticut, USA.,Department of Psychology, University of Houston, Houston, Texas, USA
| | - Nicole Landi
- Haskins Laboratories, New Haven, Connecticut, USA.,Department of Psychological Sciences, University of Connecticut, Connecticut, USA
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12
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Koirala N, Perdue MV, Su X, Grigorenko EL, Landi N. Neurite density and arborization is associated with reading skill and phonological processing in children. Neuroimage 2021; 241:118426. [PMID: 34303796 PMCID: PMC8539928 DOI: 10.1016/j.neuroimage.2021.118426] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 06/25/2021] [Accepted: 07/21/2021] [Indexed: 12/03/2022] Open
Abstract
Background: Studies exploring neuroanatomic correlates of reading have associated white matter tissue properties with reading disability and related componential skills (e.g., phonological and single-word reading skills). Mean diffusivity (MD) and fractional anisotropy (FA) are widely used surrogate measures of tissue microstructure with high sensitivity; however, they lack specificity for individual microstructural features. Here we investigated neurite features with higher specificity in order to explore the underlying microstructural architecture. Methods: Diffusion weighted images (DWI) and a battery of behavioral and neuropsychological assessments were obtained from 412 children (6 – 16 years of age). Neurite indices influenced by orientation and density were attained from 23 major white matter tracts. Partial correlations were calculated between neurite indices and indicators of phonological processing and single-word reading skills using age, sex, and image quality metrics as covariates. In addition, mediation analysis was performed using structural equation modeling (SEM) to evaluate the indirect effect of phonological processing on reading skills. Results: We observed that orientation dispersion index (ODI) and neurite density index (NDI) were negatively correlated with single-word reading and phonological processing skills in several tracts previously shown to have structural correlates with reading efficiency. We also observed a significant and substantial effect in which phonological processing mediated the relationship between neurite indices and reading skills in most tracts. Conclusions: In sum, we established that better reading and phonological processing skills are associated with greater tract coherence (lower ODI) and lower neurite density (lower NDI). We interpret these findings as evidence that reading is associated with neural architecture and its efficiency.
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Affiliation(s)
- Nabin Koirala
- Haskins Laboratories, New Haven, Connecticut, United States.
| | - Meaghan V Perdue
- Haskins Laboratories, New Haven, Connecticut, United States; Department of Psychological Sciences, University of Connecticut, Connecticut, United States
| | - Xing Su
- Haskins Laboratories, New Haven, Connecticut, United States
| | - Elena L Grigorenko
- Haskins Laboratories, New Haven, Connecticut, United States; Department of Psychology, University of Houston, Texas, United States
| | - Nicole Landi
- Haskins Laboratories, New Haven, Connecticut, United States; Department of Psychological Sciences, University of Connecticut, Connecticut, United States
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13
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Vedam-Mai V, Deisseroth K, Giordano J, Lazaro-Munoz G, Chiong W, Suthana N, Langevin JP, Gill J, Goodman W, Provenza NR, Halpern CH, Shivacharan RS, Cunningham TN, Sheth SA, Pouratian N, Scangos KW, Mayberg HS, Horn A, Johnson KA, Butson CR, Gilron R, de Hemptinne C, Wilt R, Yaroshinsky M, Little S, Starr P, Worrell G, Shirvalkar P, Chang E, Volkmann J, Muthuraman M, Groppa S, Kühn AA, Li L, Johnson M, Otto KJ, Raike R, Goetz S, Wu C, Silburn P, Cheeran B, Pathak YJ, Malekmohammadi M, Gunduz A, Wong JK, Cernera S, Wagle Shukla A, Ramirez-Zamora A, Deeb W, Patterson A, Foote KD, Okun MS. Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies. Front Hum Neurosci 2021; 15:644593. [PMID: 33953663 PMCID: PMC8092047 DOI: 10.3389/fnhum.2021.644593] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 03/10/2021] [Indexed: 12/20/2022] Open
Abstract
We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field. The emphasis is on cutting edge research and collaboration aimed to advance the DBS field. The Eighth Annual DBS Think Tank was held virtually on September 1 and 2, 2020 (Zoom Video Communications) due to restrictions related to the COVID-19 pandemic. The meeting focused on advances in: (1) optogenetics as a tool for comprehending neurobiology of diseases and on optogenetically-inspired DBS, (2) cutting edge of emerging DBS technologies, (3) ethical issues affecting DBS research and access to care, (4) neuromodulatory approaches for depression, (5) advancing novel hardware, software and imaging methodologies, (6) use of neurophysiological signals in adaptive neurostimulation, and (7) use of more advanced technologies to improve DBS clinical outcomes. There were 178 attendees who participated in a DBS Think Tank survey, which revealed the expansion of DBS into several indications such as obesity, post-traumatic stress disorder, addiction and Alzheimer’s disease. This proceedings summarizes the advances discussed at the Eighth Annual DBS Think Tank.
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Affiliation(s)
- Vinata Vedam-Mai
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, United States.,Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States
| | - James Giordano
- Department of Neurology and Neuroethics Studies Program, Georgetown University Medical Center, Washington, DC, United States
| | - Gabriel Lazaro-Munoz
- Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX, United States
| | - Winston Chiong
- Weill Institute for Neurosciences, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Nanthia Suthana
- Department of Neurosurgery, David Geffen School of Medicine and Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States
| | - Jean-Philippe Langevin
- Department of Neurosurgery, David Geffen School of Medicine and Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States.,Neurosurgery Service, Department of Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, United States
| | - Jay Gill
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - Wayne Goodman
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
| | - Nicole R Provenza
- School of Engineering, Brown University, Providence, RI, United States
| | - Casey H Halpern
- Department of Neurosurgery, Stanford University Medical Center, Stanford, CA, United States
| | - Rajat S Shivacharan
- Department of Neurosurgery, Stanford University Medical Center, Stanford, CA, United States
| | - Tricia N Cunningham
- Department of Neurosurgery, Stanford University Medical Center, Stanford, CA, United States
| | - Sameer A Sheth
- Department of Neurological Surgery, Baylor College of Medicine, Houston, TX, United States
| | - Nader Pouratian
- Department of Neurosurgery, David Geffen School of Medicine and Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, United States
| | - Katherine W Scangos
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States
| | - Helen S Mayberg
- Department of Neurology and Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Andreas Horn
- Movement Disorders & Neuromodulation Unit, Department for Neurology, Charité - University Medicine Berlin, Berlin, Germany
| | - Kara A Johnson
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States.,Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States
| | - Christopher R Butson
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States.,Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, United States
| | - Ro'ee Gilron
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Coralie de Hemptinne
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States.,Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Robert Wilt
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Maria Yaroshinsky
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Simon Little
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Philip Starr
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Greg Worrell
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Prasad Shirvalkar
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States.,Department of Anesthesiology (Pain Management) and Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Edward Chang
- Department of Neurological Surgery, Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, San Francisco, CA, United States
| | - Jens Volkmann
- Neurologischen Klinik Universitätsklinikum Würzburg, Würzburg, Germany
| | - Muthuraman Muthuraman
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Andrea A Kühn
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Luming Li
- National Engineering Laboratory for Neuromodulation, School of Aerospace Engineering, Tsinghua University, Beijing, China
| | - Matthew Johnson
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Kevin J Otto
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States
| | - Robert Raike
- Restorative Therapies Group Implantables, Research and Core Technology, Medtronic, Minneapolis, MN, United States
| | - Steve Goetz
- Restorative Therapies Group Implantables, Research and Core Technology, Medtronic, Minneapolis, MN, United States
| | - Chengyuan Wu
- Department of Neurological Surgery, Thomas Jefferson University Hospitals, Philadelphia, PA, United States
| | - Peter Silburn
- Asia Pacific Centre for Neuromodulation, Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Binith Cheeran
- Neuromodulation Division, Abbott, Plano, TX, United States
| | - Yagna J Pathak
- Neuromodulation Division, Abbott, Plano, TX, United States
| | | | - Aysegul Gunduz
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States.,J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States
| | - Joshua K Wong
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Stephanie Cernera
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States.,J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States
| | - Aparna Wagle Shukla
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Adolfo Ramirez-Zamora
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Wissam Deeb
- Department of Neurology, University of Massachusetts, Worchester, MA, United States
| | - Addie Patterson
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Kelly D Foote
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Michael S Okun
- Norman Fixel Institute for Neurological Diseases and the Program for Movement Disorders and Neurorestoration, Department of Neurology, University of Florida, Gainesville, FL, United States
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14
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Michels L, Koirala N, Groppa S, Luechinger R, Gantenbein AR, Sandor PS, Kollias S, Riederer F, Muthuraman M. Structural brain network characteristics in patients with episodic and chronic migraine. J Headache Pain 2021; 22:8. [PMID: 33657996 PMCID: PMC7927231 DOI: 10.1186/s10194-021-01216-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 01/28/2021] [Indexed: 12/28/2022] Open
Abstract
Background Migraine is a primary headache disorder that can be classified into an episodic (EM) and a chronic form (CM). Network analysis within the graph-theoretical framework based on connectivity patterns provides an approach to observe large-scale structural integrity. We test the hypothesis that migraineurs are characterized by a segregated network. Methods 19 healthy controls (HC), 17 EM patients and 12 CM patients were included. Cortical thickness and subcortical volumes were computed, and topology was analyzed using a graph theory analytical framework and network-based statistics. We further used support vector machines regression (SVR) to identify whether these network measures were able to predict clinical parameters. Results Network based statistics revealed significantly lower interregional connectivity strength between anatomical compartments including the fronto-temporal, parietal and visual areas in EM and CM when compared to HC. Higher assortativity was seen in both patients’ group, with higher modularity for CM and higher transitivity for EM compared to HC. For subcortical networks, higher assortativity and transitivity were observed for both patients’ group with higher modularity for CM. SVR revealed that network measures could robustly predict clinical parameters for migraineurs. Conclusion We found global network disruption for EM and CM indicated by highly segregated network in migraine patients compared to HC. Higher modularity but lower clustering coefficient in CM is suggestive of more segregation in this group compared to EM. The presence of a segregated network could be a sign of maladaptive reorganization of headache related brain circuits, leading to migraine attacks or secondary alterations to pain. Supplementary Information The online version contains supplementary material available at 10.1186/s10194-021-01216-8.
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Affiliation(s)
- Lars Michels
- Department of Neuroradiology, University Hospital Zurich, Sternwartstr. 6, CH-8091, Zurich, Switzerland.
| | - Nabin Koirala
- Haskins Laboratories, New Haven, Connecticut, USA.,Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Roger Luechinger
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Andreas R Gantenbein
- Department of Neurology and Neurorehabilitation, RehaClinic, Bad Zurzach, CH-5330, Switzerland.,Department of Neurology, University Hospital Zurich, CH-8091, Zurich, Switzerland
| | - Peter S Sandor
- Department of Neurology and Neurorehabilitation, RehaClinic, Bad Zurzach, CH-5330, Switzerland.,Department of Neurology, University Hospital Zurich, CH-8091, Zurich, Switzerland
| | - Spyros Kollias
- Department of Neuroradiology, University Hospital Zurich, Sternwartstr. 6, CH-8091, Zurich, Switzerland
| | - Franz Riederer
- Department of Neurology, Clinic Hietzing and Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, Wolkerssbergenstrasse 1, AT-1130, Vienna, Austria.,University of Zurich, Faculty of Medicine, Rämistrasse 100, CH-8091, Zurich, Switzerland
| | - Muthuraman Muthuraman
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
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15
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Pretreatment brain volumes can affect the effectiveness of deep brain stimulation in Parkinson's disease patients. Sci Rep 2020; 10:22065. [PMID: 33328550 PMCID: PMC7744532 DOI: 10.1038/s41598-020-79138-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 11/30/2020] [Indexed: 11/11/2022] Open
Abstract
We aimed to assess whether brain volumes may affect the results of deep brain stimulation (DBS) in patients with Parkinson’s disease (PD). Eighty-one consecutive patients with PD (male:female 40:41), treated with DBS between June 2012 and December 2017, were enrolled. Total and regional brain volumes were measured using automated brain volumetry (NeuroQuant). The Unified Parkinson Disease Rating Scale motor score quotient was used to assess changes in clinical outcome and compare the preoperative regional brain volume in patients categorized into the higher motor improvement and lower motor improvement groups based on changes in the postoperative scores. The study groups showed significant volume differences in multiple brain areas. In the higher motor improvement group, the anterior cingulate and right thalamus showed high volumes after false discovery rate (FDR) correction. In the lower motor improvement group, the left caudate, paracentral, right primary sensory and left primary motor cortex showed high volume, but no area showed high volumes after FDR correction. Our data suggest that the effectiveness of DBS in patients with PD may be affected by decreased brain volume in different areas, including the cingulate gyrus and thalamus. Preoperative volumetry could help predict outcomes in patients with PD undergoing DBS.
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16
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Muthuraman M, Bange M, Koirala N, Ciolac D, Pintea B, Glaser M, Tinkhauser G, Brown P, Deuschl G, Groppa S. Cross-frequency coupling between gamma oscillations and deep brain stimulation frequency in Parkinson's disease. Brain 2020; 143:3393-3407. [PMID: 33150359 PMCID: PMC7116448 DOI: 10.1093/brain/awaa297] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 07/16/2020] [Accepted: 07/20/2020] [Indexed: 12/30/2022] Open
Abstract
The disruption of pathologically enhanced beta oscillations is considered one of the key mechanisms mediating the clinical effects of deep brain stimulation on motor symptoms in Parkinson's disease. However, a specific modulation of other distinct physiological or pathological oscillatory activities could also play an important role in symptom control and motor function recovery during deep brain stimulation. Finely tuned gamma oscillations have been suggested to be prokinetic in nature, facilitating the preferential processing of physiological neural activity. In this study, we postulate that clinically effective high-frequency stimulation of the subthalamic nucleus imposes cross-frequency interactions with gamma oscillations in a cortico-subcortical network of interconnected regions and normalizes the balance between beta and gamma oscillations. To this end we acquired resting state high-density (256 channels) EEG from 31 patients with Parkinson's disease who underwent deep brain stimulation to compare spectral power and power-to-power cross-frequency coupling using a beamformer algorithm for coherent sources. To show that modulations exclusively relate to stimulation frequencies that alleviate motor symptoms, two clinically ineffective frequencies were tested as control conditions. We observed a robust reduction of beta and increase of gamma power, attested in the regions of a cortical (motor cortex, supplementary motor area, premotor cortex) and subcortical network (subthalamic nucleus and cerebellum). Additionally, we found a clear cross-frequency coupling of narrowband gamma frequencies to the stimulation frequency in all of these nodes, which negatively correlated with motor impairment. No such dynamics were revealed within the control posterior parietal cortex region. Furthermore, deep brain stimulation at clinically ineffective frequencies did not alter the source power spectra or cross-frequency coupling in any region. These findings demonstrate that clinically effective deep brain stimulation of the subthalamic nucleus differentially modifies different oscillatory activities in a widespread network of cortical and subcortical regions. Particularly the cross-frequency interactions between finely tuned gamma oscillations and the stimulation frequency may suggest an entrainment mechanism that could promote dynamic neural processing underlying motor symptom alleviation.
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Affiliation(s)
- Muthuraman Muthuraman
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Manuel Bange
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Nabin Koirala
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Dumitru Ciolac
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Bogdan Pintea
- Department of Neurosurgery, Bergmannsheil Clinic, Ruhr University Bochum, Bochum, Germany
| | - Martin Glaser
- Department of Neurosurgery, University Medical Center of the Johannes Gutenberg University, Mainz, Mainz, Germany
| | - Gerd Tinkhauser
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
- Department of Neurology, Bern University Hospital and University of Bern, Switzerland
| | - Peter Brown
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Günther Deuschl
- Department of Neurology, Christian Albrecht’s University, Kiel, Germany
| | - Sergiu Groppa
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
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17
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Mapping of subthalamic nucleus using microelectrode recordings during deep brain stimulation. Sci Rep 2020; 10:19241. [PMID: 33159098 PMCID: PMC7648837 DOI: 10.1038/s41598-020-74196-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2020] [Accepted: 09/23/2020] [Indexed: 11/17/2022] Open
Abstract
Alongside stereotactic magnetic resonance imaging, microelectrode recording (MER) is frequently used during the deep brain stimulation (DBS) surgery for optimal target localization. The aim of this study is to optimize subthalamic nucleus (STN) mapping using MER analytical patterns. 16 patients underwent bilateral STN-DBS. MER was performed simultaneously for 5 microelectrodes in a setting of Ben’s-gun pattern in awake patients. Using spikes and background activity several different parameters and their spectral estimates in various frequency bands including low frequency (2–7 Hz), Alpha (8–12 Hz), Beta (sub-divided as Low_Beta (13–20 Hz) and High_Beta (21–30 Hz)) and Gamma (31 to 49 Hz) were computed. The optimal STN lead placement with the most optimal clinical effect/side-effect ratio accorded to the maximum spike rate in 85% of the implantation. Mean amplitude of background activity in the low beta frequency range was corresponding to right depth in 85% and right location in 94% of the implantation respectively. MER can be used for STN mapping and intraoperative decisions for the implantation of DBS electrode leads with a high accuracy. Spiking and background activity in the beta range are the most promising independent parameters for the delimitation of the proper anatomical site.
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18
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Gonzalez-Escamilla G, Muthuraman M, Ciolac D, Coenen VA, Schnitzler A, Groppa S. Neuroimaging and electrophysiology meet invasive neurostimulation for causal interrogations and modulations of brain states. Neuroimage 2020; 220:117144. [DOI: 10.1016/j.neuroimage.2020.117144] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/22/2020] [Accepted: 07/02/2020] [Indexed: 12/13/2022] Open
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19
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Alzaid H, Ethofer T, Hobert MA, Kardatzki B, Erb M, Maetzler W, Berg D. Distinct Relationship Between Cognitive Flexibility and White Matter Integrity in Individuals at Risk of Parkinson’s Disease. Front Aging Neurosci 2020; 12:250. [PMID: 32903902 PMCID: PMC7439016 DOI: 10.3389/fnagi.2020.00250] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2020] [Accepted: 07/20/2020] [Indexed: 11/13/2022] Open
Affiliation(s)
- Haidar Alzaid
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
- *Correspondence: Haidar Alzaid,
| | - Thomas Ethofer
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Markus A. Hobert
- Department of Neurology, Christian-Albrecht University of Kiel, Kiel, Germany
| | - Bernd Kardatzki
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Michael Erb
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Walter Maetzler
- Department of Neurology, Christian-Albrecht University of Kiel, Kiel, Germany
| | - Daniela Berg
- Department of Neurology, Christian-Albrecht University of Kiel, Kiel, Germany
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20
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Porta M, Servello D, Zekaj E, Gonzalez-Escamilla G, Groppa S. Pre-dopa Deep Brain Stimulation: Is Early Deep Brain Stimulation Able to Modify the Natural Course of Parkinson's Disease? Front Neurosci 2020; 14:492. [PMID: 32581675 PMCID: PMC7292013 DOI: 10.3389/fnins.2020.00492] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Accepted: 04/20/2020] [Indexed: 12/23/2022] Open
Abstract
Deep brain stimulation (DBS) is an established therapy for the management of Parkinson’s disease (PD). However, DBS is indicated as the disease progresses and motor complications derived from pharmacological therapy arise. Here, we evaluate the potential of DBS prior to levodopa (L-Dopa) in improving quality of life (QoL), challenging the state of the art for DBS therapy. We present data on clinical manifestation, decision finding during early indication to DBS, and trajectories after DBS. We further discuss current paradigms for DBS and hypothesize on possible mechanisms. Six patients, between 50 and 67 years old, presenting at least 5 years of PD symptoms, and without L-Dopa therapy initiation, received subthalamic nucleus (STN) DBS implantation. In the six PD cases, indication for DBS was not driven by motor complications, as supported by current guidelines, but by relevant QoL impairment and patient’s reluctance to initiate L-Dopa treatment. All patients treated with STN-DBS prior to L-Dopa presented improvement in motor and non-motor symptoms and significant QoL improvement. All patients reduced the intake of dopamine agonists, and five are currently free from L-Dopa medication, with no reported adverse events. We introduce a multicenter observational study to investigate whether early DBS treatment may affect the natural course of PD. Early application of DBS instead of L-Dopa administration could have a pathophysiological basis and be prompted by a significant incline on QoL through disease progression; however, the clinical value of this proposed paradigm shift should be addressed in clinical trials aimed at modulating the natural course of PD.
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Affiliation(s)
- Mauro Porta
- Center for Movement Disorders and Tourette Syndrome, Galeazzi Hospital, Milan, Italy
| | | | - Edvin Zekaj
- Functional Neurosurgery Unit, Galeazzi Hospital, Milan, Italy
| | - Gabriel Gonzalez-Escamilla
- Movement Disorders and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
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21
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Douw L, Quaak M, Fitzsimmons SM, de Wit SJ, van der Werf YD, van den Heuvel OA, Vriend C. Static and dynamic network properties of the repetitive transcranial magnetic stimulation target predict changes in emotion regulation in obsessive-compulsive disorder. Brain Stimul 2020; 13:318-326. [DOI: 10.1016/j.brs.2019.10.017] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 10/18/2019] [Accepted: 10/21/2019] [Indexed: 01/23/2023] Open
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22
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Xu W, Zhang C, Deeb W, Patel B, Wu Y, Voon V, Okun MS, Sun B. Deep brain stimulation for Tourette's syndrome. Transl Neurodegener 2020; 9:4. [PMID: 31956406 PMCID: PMC6956485 DOI: 10.1186/s40035-020-0183-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2019] [Accepted: 01/05/2020] [Indexed: 01/11/2023] Open
Abstract
Tourette syndrome (TS) is a childhood-onset neuropsychiatric disorder characterized by the presence of multiple motor and vocal tics. TS usually co-occurs with one or multiple psychiatric disorders. Although behavioral and pharmacological treatments for TS are available, some patients do not respond to the available treatments. For these patients, TS is a severe, chronic, and disabling disorder. In recent years, deep brain stimulation (DBS) of basal ganglia-thalamocortical networks has emerged as a promising intervention for refractory TS with or without psychiatric comorbidities. Three major challenges need to be addressed to move the field of DBS treatment for TS forward: (1) patient and DBS target selection, (2) ethical concerns with treating pediatric patients, and (3) DBS treatment optimization and improvement of individual patient outcomes (motor and phonic tics, as well as functioning and quality of life). The Tourette Association of America and the American Academy of Neurology have recently released their recommendations regarding surgical treatment for refractory TS. Here, we describe the challenges, advancements, and promises of the use of DBS in the treatment of TS. We summarize the results of clinical studies and discuss the ethical issues involved in treating pediatric patients. Our aim is to provide a better understanding of the feasibility, safety, selection process, and clinical effectiveness of DBS treatment for select cases of severe and medically intractable TS.
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Affiliation(s)
- Wenying Xu
- 1Department of Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Ruijin Hospital, 197 Ruijin Er Road, Shanghai, 200025 China
| | - Chencheng Zhang
- 1Department of Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Ruijin Hospital, 197 Ruijin Er Road, Shanghai, 200025 China
| | - Wissam Deeb
- 2Norman Fixel Institute for Neurological Diseases, Department of Neurology, College of Medicine, University of Florida, Gainesville, FL 32608 USA
| | - Bhavana Patel
- 2Norman Fixel Institute for Neurological Diseases, Department of Neurology, College of Medicine, University of Florida, Gainesville, FL 32608 USA
| | - Yiwen Wu
- 3Department of Neurology & Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Valerie Voon
- 1Department of Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Ruijin Hospital, 197 Ruijin Er Road, Shanghai, 200025 China.,4Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Michael S Okun
- 2Norman Fixel Institute for Neurological Diseases, Department of Neurology, College of Medicine, University of Florida, Gainesville, FL 32608 USA
| | - Bomin Sun
- 1Department of Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Ruijin Hospital, 197 Ruijin Er Road, Shanghai, 200025 China
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23
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Xiao R, Malekmohammadi M, Pouratian N, Hu X. Characterization of pallidocortical motor network in Parkinson's disease through complex network analysis. J Neural Eng 2019; 16:066034. [PMID: 31505469 DOI: 10.1088/1741-2552/ab4341] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Deep brain stimulation (DBS) has been demonstrated by numerous clinical trials to be an advanced therapy for selected patients with Parkinson's disease (PD), while its maximal therapeutic effect is capped by the inadequate understanding of the precise neuronal mechanisms underlying PD. Recordings from multichannel electrodes placed in subcortical and cortical regions of the basal ganglia-thalamocortical (BGTC) motor network during DBS surgical procedures can provide rich physiologic information from accessible network nodes. However, most investigations focus on presumed spatio-spectral points of interest, neither fully utilizing the richness of spatial, spectral and temporal aspects of the multivariate signals nor making discoveries in the context of all possible candidates. In addition, aggregated network-level information has been missed out. APPROACH We use complex network analysis to characterize functional network characteristics of the pallidocortical subcircuit of the BGTC motor network in PD at rest and with movement. The network matrix was constructed using distinct frequency bands at each anatomic recording site as virtual nodes and spectral connectivity (through phase-amplitude coupling and coherence) as network edges. MAIN RESULTS We confirm the critical roles of beta bands and provide additional evidence on their differential functional roles in the pallidocortical motor network. Moreover, significant changes (p < 0.05) in network functional segregation and integration between rest and movement conditions are revealed for the first time. More importantly, movement-dependent modulation of these network metrics are significantly correlated with hemibody unified PD rating scales (UPDRS), providing network-level perspectives of the pallidocortical motor network pertaining to PD symptoms (p < 0.05). SIGNIFICANCE Findings in the present study provide network-level understanding of neuronal mechanisms in the pallidocortical motor network underlying PD. It is also highly plausible that the demonstrated approach can be applied in other important subcircuits towards a comprehensive understanding of the BGTC motor network.
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Affiliation(s)
- Ran Xiao
- Department of Physiological Nursing, University of California, San Francisco, CA, United States of America
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24
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Radetz A, Koirala N, Krämer J, Johnen A, Fleischer V, Gonzalez-Escamilla G, Cerina M, Muthuraman M, Meuth SG, Groppa S. Gray matter integrity predicts white matter network reorganization in multiple sclerosis. Hum Brain Mapp 2019; 41:917-927. [PMID: 32026599 PMCID: PMC7268008 DOI: 10.1002/hbm.24849] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Revised: 10/16/2019] [Accepted: 10/17/2019] [Indexed: 01/19/2023] Open
Abstract
Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease leading to gray matter atrophy and brain network reconfiguration as a response to increasing tissue damage. We evaluated whether white matter network reconfiguration appears subsequently to gray matter damage, or whether the gray matter degenerates following alterations in white matter networks. MRI data from 83 patients with clinically isolated syndrome and early relapsing-remitting MS were acquired at two time points with a follow-up after 1 year. White matter network integrity was assessed based on probabilistic tractography performed on diffusion-weighted data using graph theoretical analyses. We evaluated gray matter integrity by computing cortical thickness and deep gray matter volume in 94 regions at both time points. The thickness of middle temporal cortex and the volume of deep gray matter regions including thalamus, caudate, putamen, and brain stem showed significant atrophy between baseline and follow-up. White matter network dynamics, as defined by modularity and distance measure changes over time, were predicted by deep gray matter volume of the atrophying anatomical structures. Initial white matter network properties, on the other hand, did not predict atrophy. Furthermore, gray matter integrity at baseline significantly predicted physical disability at 1-year follow-up. In a sub-analysis, deep gray matter volume was significantly related to cognitive performance at baseline. Hence, we postulate that atrophy of deep gray matter structures drives the adaptation of white matter networks. Moreover, deep gray matter volumes are highly predictive for disability progression and cognitive performance.
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Affiliation(s)
- Angela Radetz
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Nabin Koirala
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Julia Krämer
- Department of Neurology, University of Münster, Münster, Germany
| | - Andreas Johnen
- Department of Neurology, University of Münster, Münster, Germany
| | - Vinzenz Fleischer
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Manuela Cerina
- Department of Neurology, University of Münster, Münster, Germany
| | - Muthuraman Muthuraman
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sven G Meuth
- Department of Neurology, University of Münster, Münster, Germany
| | - Sergiu Groppa
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
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25
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Douw L, van Dellen E, Gouw AA, Griffa A, de Haan W, van den Heuvel M, Hillebrand A, Van Mieghem P, Nissen IA, Otte WM, Reijmer YD, Schoonheim MM, Senden M, van Straaten ECW, Tijms BM, Tewarie P, Stam CJ. The road ahead in clinical network neuroscience. Netw Neurosci 2019; 3:969-993. [PMID: 31637334 PMCID: PMC6777944 DOI: 10.1162/netn_a_00103] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 07/23/2019] [Indexed: 12/15/2022] Open
Abstract
Clinical network neuroscience, the study of brain network topology in neurological and psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a multidisciplinary group of clinical network neuroscience experts based in The Netherlands, we often discuss the current state of the art and possible avenues for future investigations. These discussions revolve around questions like "How do dynamic processes alter the underlying structural network?" and "Can we use network neuroscience for disease classification?" This opinion paper is an incomplete overview of these discussions and expands on ten questions that may potentially advance the field. By no means intended as a review of the current state of the field, it is instead meant as a conversation starter and source of inspiration to others.
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Affiliation(s)
- Linda Douw
- Department of Anatomy and Neuroscience, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Edwin van Dellen
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Alida A. Gouw
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Alessandra Griffa
- Connectome Lab, Department of Neuroscience, section Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Willem de Haan
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Martijn van den Heuvel
- Connectome Lab, Department of Neuroscience, section Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Piet Van Mieghem
- Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
| | - Ida A. Nissen
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Willem M. Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
- Department of Pediatric Neurology, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Yael D. Reijmer
- Department of Neurology, Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Menno M. Schoonheim
- Department of Anatomy and Neuroscience, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Mario Senden
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Elisabeth C. W. van Straaten
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Betty M. Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Prejaas Tewarie
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Cornelis J. Stam
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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26
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Gonzalez-Escamilla G, Muthuraman M, Reich MM, Koirala N, Riedel C, Glaser M, Lange F, Deuschl G, Volkmann J, Groppa S. Cortical network fingerprints predict deep brain stimulation outcome in dystonia. Mov Disord 2019; 34:1537-1546. [PMID: 31433874 DOI: 10.1002/mds.27808] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 07/02/2019] [Accepted: 07/08/2019] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Deep brain stimulation (DBS) is an effective evidence-based therapy for dystonia. However, no unequivocal predictors of therapy responses exist. We investigated whether patients optimally responding to DBS present distinct brain network organization and structural patterns. METHODS From a German multicenter cohort of 82 dystonia patients with segmental and generalized dystonia who received DBS implantation in the globus pallidus internus, we classified patients based on the clinical response 3 years after DBS. Patients were assigned to the superior-outcome group or moderate-outcome group, depending on whether they had above or below 70% motor improvement, respectively. Fifty-one patients met MRI-quality and treatment response requirements (mean age, 51.3 ± 13.2 years; 25 female) and were included in further analysis. From preoperative MRI we assessed cortical thickness and structural covariance, which were then fed into network analysis using graph theory. We designed a support vector machine to classify subjects for the clinical response based on individual gray-matter fingerprints. RESULTS The moderate-outcome group showed cortical atrophy mainly in the sensorimotor and visuomotor areas and disturbed network topology in these regions. The structural integrity of the cortical mantle explained about 45% of the DBS stimulation amplitude for optimal response in individual subjects. Classification analyses achieved up to 88% of accuracy using individual gray-matter atrophy patterns to predict DBS outcomes. CONCLUSIONS The analysis of cortical integrity, informed by group-level network properties, could be developed into independent predictors to identify dystonia patients who benefit from DBS. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Gabriel Gonzalez-Escamilla
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Martin M Reich
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Nabin Koirala
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Christian Riedel
- Department of Neuroradiology, UKSH, Christian-Albrechts-University Kiel, Kiel, Germany
| | - Martin Glaser
- Department of Neurosurgery, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Florian Lange
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Günther Deuschl
- Department of Neurology, UKSH, Christian-Albrechts-University Kiel, Kiel, Germany
| | - Jens Volkmann
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Sergiu Groppa
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
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27
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Ciolac D, Luessi F, Gonzalez-Escamilla G, Koirala N, Riedel C, Fleischer V, Bittner S, Krämer J, Meuth SG, Muthuraman M, Groppa S. Selective Brain Network and Cellular Responses Upon Dimethyl Fumarate Immunomodulation in Multiple Sclerosis. Front Immunol 2019; 10:1779. [PMID: 31417557 PMCID: PMC6682686 DOI: 10.3389/fimmu.2019.01779] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Accepted: 07/15/2019] [Indexed: 11/13/2022] Open
Abstract
Background: Efficient personalized therapy paradigms are needed to modify the disease course and halt gray (GM) and white matter (WM) damage in patients with multiple sclerosis (MS). Presently, promising disease-modifying drugs show impressive efficiency, however, tailored markers of therapy responses are required. Here, we aimed to detect in a real-world setting patients with a more favorable brain network response and immune cell dynamics upon dimethyl fumarate (DMF) treatment. Methods: In a cohort of 78 MS patients we identified two thoroughly matched groups, based on age, disease duration, disability status and lesion volume, receiving DMF (n = 42) and NAT (n = 36) and followed them over 16 months. The rate of cortical atrophy and deep GM volumes were quantified. GM and WM network responses were characterized by brain modularization as a marker of regional and global structural alterations. In the DMF group, lymphocyte subsets were analyzed by flow cytometry and related to clinical and MRI parameters. Results: Sixty percent (25 patients) of the DMF and 36% (13 patients) of the NAT group had disease activity during the study period. The rate of cortical atrophy was higher in the DMF group (-2.4%) compared to NAT (-2.1%, p < 0.05) group. GM and WM network dynamics presented increased modularization in both groups. When dividing the DMF-treated cohort into patients free of disease activity (n = 17, DMFR) and patients with disease activity (n = 25, DMFNR) these groups differed significantly in CD8+ cell depletion counts (DMFR: 197.7 ± 97.1/μl; DMFNR: 298.4 ± 190.6/μl, p = 0.03) and also in cortical atrophy (DMFR: -1.7%; DMFNR: -3.2%, p = 0.01). DMFR presented reduced longitudinal GM and WM modularization and less atrophy as markers of preserved structural global network integrity in comparison to DMFNR and even NAT patients. Conclusions: NAT treatment contributes to a reduced rate of cortical atrophy compared to DMF therapy. However, patients under DMF treatment with a stronger CD8+ T cell depletion present a more favorable response in terms of cortical integrity and GM and WM network responses. Our findings may serve as basis for the development of personalized treatment paradigms.
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Affiliation(s)
- Dumitru Ciolac
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.,Department of Neurology, Institute of Emergency Medicine, Chisinau, Moldova.,Laboratory of Neurobiology and Medical Genetics, Nicolae Testemiţanu State University of Medicine and Pharmacy, Chisinau, Moldova
| | - Felix Luessi
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Nabin Koirala
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | | | - Vinzenz Fleischer
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Stefan Bittner
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Julia Krämer
- Department of Neurology With Institute of Translational Neurology, University of Münster, Münster, Germany
| | - Sven G Meuth
- Department of Neurology With Institute of Translational Neurology, University of Münster, Münster, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
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28
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Koirala N, Anwar AR, Ciolac D, Glaser M, Pintea B, Deuschl G, Muthuraman M, Groppa S. Alterations in White Matter Network and Microstructural Integrity Differentiate Parkinson's Disease Patients and Healthy Subjects. Front Aging Neurosci 2019; 11:191. [PMID: 31404311 PMCID: PMC6676803 DOI: 10.3389/fnagi.2019.00191] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2018] [Accepted: 07/15/2019] [Indexed: 01/15/2023] Open
Abstract
Parkinson’s disease (PD) is a neurodegenerative disease, neuropathologically characterized by progressive loss of neurons in distinct brain areas. We hypothesize that quantifiable network alterations are caused by neurodegeneration. The primary motivation of this study was to assess the specific network alterations in PD patients that are distinct but appear in conjunction with physiological aging. 178 subjects (130 females) stratified into PD patients, young, middle-aged and elderly healthy controls (age- and sex-matched with PD patients), were analyzed using 3D-T1 magnetization-prepared rapid gradient-echo (MPRAGE) and diffusion weighted images acquired in 3T MRI scanner. Diffusion modeling and probabilistic tractography analysis were applied for generating voxel-based connectivity index maps from each seed voxel. The obtained connectivity matrices were analyzed using graph theoretical tools for characterization of involved network. By network-based statistic (NBS) the interregional connectivity differences between the groups were assessed. Measures evaluating local diffusion properties for anisotropy and diffusivity were computed for characterization of white matter microstructural integrity. The graph theoretical analysis showed a significant decrease in distance measures – eccentricity and characteristic path length – in PD patients in comparison to healthy subjects. Both measures as well were lower in PD patients when compared to young and middle-aged healthy controls. NBS analysis demonstrated lowered structural connectivity in PD patients in comparison to young and middle-aged healthy subject groups, mainly in frontal, cingulate, olfactory, insula, thalamus, and parietal regions. These specific network differences were distinct for PD and were not observed between the healthy subject groups. Microstructural analysis revealed diffusivity alterations within the white matter tracts in PD patients, predominantly in the body, splenium and tapetum of corpus callosum, corticospinal tract, and corona radiata, which were absent in normal aging. The identified alterations of network connectivity presumably caused by neurodegeneration indicate the disruption in global network integration in PD patients. The microstructural changes identified within the white matter could endorse network reconfiguration. This study provides a clear distinction between the network changes occurring during aging and PD. This will facilitate a better understanding of PD pathophysiology and the direct link between white matter changes and their role in the restructured network topology.
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Affiliation(s)
- Nabin Koirala
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Abdul Rauf Anwar
- Centre for Biomedical Engineering, University of Engineering and Technology, Lahore, Pakistan
| | - Dumitru Ciolac
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.,Department of Neurology, Institute of Emergency Medicine, Chisinau, Moldova.,Laboratory of Neurobiology and Medical Genetics, State University of Medicine and Pharmacy "Nicolae Testemit̨anu", Chisinau, Moldova
| | - Martin Glaser
- Department of Neurosurgery, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Bogdan Pintea
- Department of Neurosurgery, Bergmannsheil Clinic, Ruhr University Bochum, Bochum, Germany
| | - Günther Deuschl
- Department of Neurology, Christian-Albrechts-University, Kiel, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
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29
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Gonzalez-Escamilla G, Muthuraman M, Chirumamilla VC, Vogt J, Groppa S. Brain Networks Reorganization During Maturation and Healthy Aging-Emphases for Resilience. Front Psychiatry 2018; 9:601. [PMID: 30519196 PMCID: PMC6258799 DOI: 10.3389/fpsyt.2018.00601] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Accepted: 10/29/2018] [Indexed: 12/31/2022] Open
Abstract
Maturation and aging are important life periods that are linked to drastic brain reorganization processes which are essential for mental health. However, the development of generalized theories for delimiting physiological and pathological brain remodeling through life periods linked to healthy states and resilience on one side or mental dysfunction on the other remains a challenge. Furthermore, important processes of preservation and compensation of brain function occur continuously in the cerebral brain networks and drive physiological responses to life events. Here, we review research on brain reorganization processes across the lifespan, demonstrating brain circuits remodeling at the structural and functional level that support mental health and are parallelized by physiological trajectories during maturation and healthy aging. We show evidence that aberrations leading to mental disorders result from the specific alterations of cerebral networks and their pathological dynamics leading to distinct excitability patterns. We discuss how these series of large-scale responses of brain circuits can be viewed as protective or malfunctioning mechanisms for the maintenance of mental health and resilience.
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Affiliation(s)
| | - Muthuraman Muthuraman
- Department of Neurology, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Venkata C. Chirumamilla
- Department of Neurology, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Johannes Vogt
- Institute for Microscopic Anatomy and Neurobiology, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sergiu Groppa
- Department of Neurology, University Medical Center, Johannes Gutenberg University Mainz, Mainz, Germany
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Muthuraman M, Koirala N, Ciolac D, Pintea B, Glaser M, Groppa S, Tamás G, Groppa S. Deep Brain Stimulation and L-DOPA Therapy: Concepts of Action and Clinical Applications in Parkinson's Disease. Front Neurol 2018; 9:711. [PMID: 30210436 PMCID: PMC6119713 DOI: 10.3389/fneur.2018.00711] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 08/06/2018] [Indexed: 12/15/2022] Open
Abstract
L-DOPA is still the most effective pharmacological therapy for the treatment of motor symptoms in Parkinson's disease (PD) almost four decades after it was first used. Deep brain stimulation (DBS) is a safe and highly effective treatment option in patients with PD. Even though a clear understanding of the mechanisms of both treatment methods is yet to be obtained, the combination of both treatments is the most effective standard evidenced-based therapy to date. Recent studies have demonstrated that DBS is a therapy option even in the early course of the disease, when first complications arise despite a rigorous adjustment of the pharmacological treatment. The unique feature of this therapeutic approach is the ability to preferentially modulate specific brain networks through the choice of stimulation site. The clinical effects have been unequivocally confirmed in recent studies; however, the impact of DBS and the supplementary effect of L-DOPA on the neuronal network are not yet fully understood. In this review, we present emerging data on the presumable mechanisms of DBS in patients with PD and discuss the pathophysiological similarities and differences in the effects of DBS in comparison to dopaminergic medication. Targeted, selective modulation of brain networks by DBS and pharmacodynamic effects of L-DOPA therapy on the central nervous system are presented. Moreover, we outline the perioperative algorithms for PD patients before and directly after the implantation of DBS electrodes and strategies for the reduction of side effects and optimization of motor and non-motor symptoms.
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Affiliation(s)
- Muthuraman Muthuraman
- Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Nabin Koirala
- Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Dumitru Ciolac
- Department of Neurology, Institute of Emergency Medicine, Chisinau, Moldova.,Laboratory of Neurobiology and Medical Genetics, Nicolae Testemiţanu State University of Medicine and Pharmacy, Chisinau, Moldova
| | - Bogdan Pintea
- Department of Neurosurgery, University Hospital of Bonn, Bonn, Germany
| | - Martin Glaser
- Department of Neurosurgery, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Stanislav Groppa
- Department of Neurology, Institute of Emergency Medicine, Chisinau, Moldova.,Laboratory of Neurobiology and Medical Genetics, Nicolae Testemiţanu State University of Medicine and Pharmacy, Chisinau, Moldova
| | - Gertrúd Tamás
- Department of Neurology, Semmelweis University, Budapest, Hungary
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
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