scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Connectivity Predicts deep brain stimulation outcome in Parkinson disease.

TL;DR: The structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) is identified and its ability to predict outcome in an independent cohort is tested.
Abstract: Objective: The benefit of deep brain stimulation (DBS) for Parkinson's disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remains unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort. Methods: A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of Unified Parkinson's Disease Rating Scale). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center. Results: In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p < 0.001). This same connectivity profile predicted response in an independent patient cohort (p < 0.01). Structural and functional connectivity were independent predictors of clinical improvement (p < 0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease-matched to our DBS patients. Interpretation: Effective STN-DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves. This article is protected by copyright. All rights reserved.

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI
TL;DR: This work represents a multi‐institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.

473 citations


Cites background or methods from "Connectivity Predicts deep brain st..."

  • ...…group connectome 1000 healthy subjects GSP Harvard Genomic Superstruct Project (GSP) 1000 Controls Yeo et al., 2011 Lead Connectome fMRI pipeline Horn, 2017 Functional group connectome 74 PPMI PD-patients, 15 controls Parkinson‘s Disease Progression Marker Initiative (PPMI) 74/15 PD…...

    [...]

  • ...Name Repository N Population Publication – Dataset Processing Methods Publication – Processing rs-fMRI based “functional connectivity” Functional group connectome 1000 healthy subjects GSP Harvard Genomic Superstruct Project (GSP) 1000 Controls Yeo et al., 2011 Lead Connectome fMRI pipeline Horn, 2017 Functional group connectome 74 PPMI PD-patients, 15 controls Parkinson‘s Disease Progression Marker Initiative (PPMI) 74/15 PD patients, controls Marek et al., 2011 Lead Connectome fMRI pipeline Horn, 2017 dMRI based “structural connectivity” Structural group connectome 20 subjects Gibbs-tracker Horn et al., 2014 study 20 Controls Horn et al., 2014 Lead Connectome, Gibbs’ tracker Horn et al., 2014 Structural group connectome 169 NKI subjects Gibbstracker Enhanced NKI Rockland Sample 169 Controls Nooner et al., 2012 Lead Connectome, Gibbs' tracker Horn, 2016 Structural group connectome 32 Adult Diffusion HCP subjects GQI HCP MGH Adult Diffusion dataset 30 Controls Setsompop et al., 2013 Lead Connectome, DSI Studio (GQI) Horn, 2017 Structural group connectome 90 PPMI PD-patients GQI Parkinson‘s Disease Progression Marker Initiative (PPMI) 90 PD patients Marek et al., 2011 Lead Connectome, DSI Studio (GQI) Ewert et al. 2018a,b SyN approach without the subcortical refinement step was applied....

    [...]

  • ...…15 controls Parkinson‘s Disease Progression Marker Initiative (PPMI) 74/15 PD patients, controls Marek et al., 2011 Lead Connectome fMRI pipeline Horn, 2017 dMRI based “structural connectivity” Structural group connectome 20 subjects Gibbs-tracker Horn et al., 2014 study 20 Controls Horn…...

    [...]

  • ...…group connectome 32 Adult Diffusion HCP subjects GQI HCP MGH Adult Diffusion dataset 30 Controls Setsompop et al., 2013 Lead Connectome, DSI Studio (GQI) Horn, 2017 Structural group connectome 90 PPMI PD-patients GQI Parkinson‘s Disease Progression Marker Initiative (PPMI) 90 PD patients…...

    [...]

  • ...Since no FGATIR-template exists in 2009b space, Lead-DBS automatically paired this scan with an aggregated PCA template (Horn, 2017)....

    [...]

Journal ArticleDOI
TL;DR: The Brain Connectome and New Methods of Lesion Analysis Complex neurologic and psychiatric syndromes cannot be understood on the basis of focal brain lesions.
Abstract: The Brain Connectome and New Methods of Lesion Analysis Complex neurologic and psychiatric syndromes cannot be understood on the basis of focal brain lesions. Functional neuroimaging, maps of inter...

363 citations

Journal ArticleDOI
TL;DR: This Review examines the field of network neuroscience, focusing on organizing principles that can help overcome challenges in the diversity of meanings of the term network model, and draws on biology, philosophy and other disciplines to establish validation principles for these models.
Abstract: Network theory provides an intuitively appealing framework for studying relationships among interconnected brain mechanisms and their relevance to behaviour. As the space of its applications grows, so does the diversity of meanings of the term network model. This diversity can cause confusion, complicate efforts to assess model validity and efficacy, and hamper interdisciplinary collaboration. In this Review, we examine the field of network neuroscience, focusing on organizing principles that can help overcome these challenges. First, we describe the fundamental goals in constructing network models. Second, we review the most common forms of network models, which can be described parsimoniously along the following three primary dimensions: from data representations to first-principles theory; from biophysical realism to functional phenomenology; and from elementary descriptions to coarse-grained approximations. Third, we draw on biology, philosophy and other disciplines to establish validation principles for these models. We close with a discussion of opportunities to bridge model types and point to exciting frontiers for future pursuits.

299 citations

Journal ArticleDOI
TL;DR: This study provides prospective validation that functional connectivity between an individual's rTMS cortical target and the subgenual cingulate predicts antidepressant response.

298 citations

Journal ArticleDOI
TL;DR: The evolution and current status of DBS technology is discussed, future advances are anticipated, and the next major technological advances and hurdles in the field are predicted.
Abstract: Deep brain stimulation (DBS) is a neurosurgical procedure that allows targeted circuit-based neuromodulation. DBS is a standard of care in Parkinson disease, essential tremor and dystonia, and is also under active investigation for other conditions linked to pathological circuitry, including major depressive disorder and Alzheimer disease. Modern DBS systems, borrowed from the cardiac field, consist of an intracranial electrode, an extension wire and a pulse generator, and have evolved slowly over the past two decades. Advances in engineering and imaging along with an improved understanding of brain disorders are poised to reshape how DBS is viewed and delivered to patients. Breakthroughs in electrode and battery designs, stimulation paradigms, closed-loop and on-demand stimulation, and sensing technologies are expected to enhance the efficacy and tolerability of DBS. In this Review, we provide a comprehensive overview of the technical development of DBS, from its origins to its future. Understanding the evolution of DBS technology helps put the currently available systems in perspective and allows us to predict the next major technological advances and hurdles in the field.

259 citations

References
More filters
Journal ArticleDOI
TL;DR: In this paper, the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI data from 1,000 subjects and a clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex.
Abstract: Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.

6,284 citations

Journal ArticleDOI
03 Mar 2005-Neuron
TL;DR: It is suggested that disrupting focal pathological activity in limbic-cortical circuits using electrical stimulation of the subgenual cingulate white matter can effectively reverse symptoms in otherwise treatment-resistant depression.

3,610 citations

Journal ArticleDOI
17 Apr 2009-Science
TL;DR: This work used optogenetics and solid-state optics to systematically drive or inhibit an array of distinct circuit elements in freely moving parkinsonian rodents and found that therapeutic effects within the subthalamic nucleus can be accounted for by direct selective stimulation of afferent axons projecting to this region.
Abstract: Deep brain stimulation (DBS) is a therapeutic option for intractable neurological and psychiatric disorders, including Parkinson's disease and major depression. Because of the heterogeneity of brain tissues where electrodes are placed, it has been challenging to elucidate the relevant target cell types or underlying mechanisms of DBS. We used optogenetics and solid-state optics to systematically drive or inhibit an array of distinct circuit elements in freely moving parkinsonian rodents and found that therapeutic effects within the subthalamic nucleus can be accounted for by direct selective stimulation of afferent axons projecting to this region. In addition to providing insight into DBS mechanisms, these results demonstrate an optical approach for dissection of disease circuitry and define the technological toolbox needed for systematic deconstruction of disease circuits by selectively controlling individual components.

1,481 citations

Journal ArticleDOI
TL;DR: A dynamic 'center-surround model' of basal ganglia function in the control of voluntary limb movements is proposed and the functional significance of the 'hyperdirect' pathway is emphasized.

1,183 citations

Journal ArticleDOI
TL;DR: Subthalamic stimulation was superior to medical therapy in patients with Parkinson's disease and early motor complications and time with good mobility and no dyskinesia.
Abstract: A B S T R AC T BACKGROUND Subthalamic stimulation reduces motor disability and improves quality of life in patients with advanced Parkinson’s disease who have severe levodopa-induced motor complications. We hypothesized that neurostimulation would be beneficial at an earlier stage of Parkinson’s disease. METHODS In this 2-year trial, we randomly assigned 251 patients with Parkinson’s disease and early motor complications (mean age, 52 years; mean duration of disease, 7.5 years) to undergo neurostimulation plus medical therapy or medical therapy alone. The primary end point was quality of life, as assessed with the use of the Parkinson’s Disease Questionnaire (PDQ-39) summary index (with scores ranging from 0 to 100 and higher scores indicating worse function). Major secondary outcomes included parkinsonian motor disability, activities of daily living, levodopa-induced motor com plications (as assessed with the use of the Unified Parkinson’s Disease Rating Scale, parts III, II, and IV, respectively), and time with good mobility and no dyskinesia. RESULTS For the primary outcome of quality of life, the mean score for the neurostimulation group improved by 7.8 points, and that for the medical-therapy group worsened by 0.2 points (between-group difference in mean change from baseline to 2 years, 8.0 points; P = 0.002). Neurostimulation was superior to medical therapy with respect to motor disability (P<0.001), activities of daily living (P<0.001), levodopa-induced motor complications (P<0.001), and time with good mobility and no dyskinesia (P = 0.01). Serious adverse events occurred in 54.8% of the patients in the neuro stimulation group and in 44.1% of those in the medical-therapy group. Serious adverse events related to surgical implantation or the neurostimulation device oc curred in 17.7% of patients. An expert panel confirmed that medical therapy was consistent with practice guidelines for 96.8% of the patients in the neurostimula tion group and for 94.5% of those in the medical-therapy group. CONCLUSIONS Subthalamic stimulation was superior to medical therapy in patients with Parkinson’s disease and early motor complications. (Funded by the German Ministry of Research and others; EARLYSTIM ClinicalTrials.gov number, NCT00354133.)

1,059 citations


"Connectivity Predicts deep brain st..." refers background in this paper

  • ...Deep brain stimulation (DBS) is a well-established treatment for Parkinson disease (PD), yielding improvements in motor symptoms and quality of life.(1) The most common DBS target is the subthalamic nucleus (STN), identified based on stereotactic coordinates and preoperative magnetic resonance imaging (MRI)....

    [...]

Related Papers (5)