A Unified Functional Network Target for Deep Brain Stimulation in Obsessive-Compulsive Disorder

Li, Ningfei; Hollunder, Barbara; Baldermann, Juan Carlos; Kibleur, Astrid; Treu, Svenja; Akram, Harith; Al‐Fatly, Bassam; Strange, Bryan A.; Barcia, Juan A.; Zrinzo, Ludvic; Joyce, Eileen M.; Chabardès, Stéphan; Visser-Vandewalle, V.; Polosan, Mircea; Kuhn, Jens; Kühn, Andrea A.; Horn, Andreas

doi:10.1016/j.biopsych.2021.04.006

Cited by 47 publications

(52 citation statements)

References 118 publications

(104 reference statements)

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“…In contrast, computing connectivity between the stimulation site and our cognitive decline network (without the heat map) requires access to our 1000-subject connectome, specialized software, and computational resources that are not routinely accessible to DBS clinicians. This conversion of a connectivity network into a heat map has been used for OCD 37 but to our knowledge this is the first use and validation of this approach for a DBS side effect.…”

Section: Discussionmentioning

confidence: 99%

A brain network for deep brain stimulation induced cognitive decline in Parkinson’s disease

Reich

Hsu

Ferguson

et al. 2022

Brain

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Deep brain stimulation (DBS) is an effective treatment for Parkinson’s disease but can be complicated by side-effects such as cognitive decline. There is often a delay before this side-effect is apparent and the mechanism is unknown, making it difficult to identify patients at risk or select appropriate DBS settings. Here, we test whether connectivity between the stimulation site and other brain regions is associated with cognitive decline following DBS. First, we studied a unique patient cohort with cognitive decline following subthalamic DBS for Parkinson’s disease (n = 10) where re-programming relieved the side-effect without loss of motor benefit. Using resting state functional connectivity data from a large normative cohort (n = 1000), we computed connectivity between each stimulation site and the subiculum, an a priori brain region functionally connected to brain lesions causing memory impairment. Connectivity between DBS sites and this same subiculum region was significantly associated with DBS induced cognitive decline (P < 0.02). We next performed a data-driven analysis to identify connnections most associated with DBS induced cognitive decline. DBS sites causing cognitive decline (versus those that did not) were more connected to the anterior cingulate, caudate nucleus, hippocampus, and cognitive regions of the cerebellum (Pfwe< 0.05). The spatial topography of this DBS-based circuit for cognitive decline aligned with an a priori lesion-based circuit for memory impairment (P = 0.017). To begin translating these results into a clinical tool that might be used for DBS programming, we generated a “heatmap” in which the intensity of each voxel reflects the connectivity to our cognitive decline circuit. We then validated this heatmap using an independent dataset of PD patients in which cognitive performance was measured following subthalamic DBS (n = 33). Intersection of DBS sites with our heatmap was correlated with changes in the Mattis dementia rating scale one year after lead implantation (r = 0.39; p = 0.028). Finally, to illustrate how this heatmap might be used in clinical practice, we present a case that was flagged as “high risk” for cognitive decline based on intersection of the patient’s DBS site with our heatmap. This patient had indeed experienced cognitive decline and our heatmap was used to select alternative DBS parameters. At 14 days follow-up the patient’s cognition improved without loss of motor benefit. These results lend insight into the mechanism of DBS induced cognitive decline and suggest that connectivity-based heatmaps may help identify patients at risk and who might benefit from DBS reprogramming.

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Section: Discussionmentioning

confidence: 99%

A brain network for deep brain stimulation induced cognitive decline in Parkinson’s disease

Reich

Hsu

Ferguson

et al. 2022

Brain

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“…Evidence from non-human primate tract tracing suggests that this spot may best be described by the central portion of the ALIC with projections from dACC and vlPFC (21,48). The hyperdirect pathway projecting from dACC to STN was the most predictive tract from a set of anatomically predefined pathways in the N = common network attributed a central role to the dACC (12). Further support for the dACC as a strong cortical candidate region is provided by the efficacy of anterior cingulotomies in treating OCD (figure 2) (49).…”

Section: Anatomical Considerationsmentioning

confidence: 98%

“…In this critical review, we aim to scrutinize methodologies and findings from connectomic studies and DBS interventions for OCD to identify common and diverse pathways likely to be effective for reducing obsessions and compulsions. We focus on structural connectivity for the sake of conciseness; relevant functional MRI (fMRI) studies in OCD DBS (7,(10)(11)(12) are discussed where appropriate.…”

Section: Introductionmentioning

confidence: 99%

Connectomic Deep Brain Stimulation for Obsessive-Compulsive Disorder

Baldermann

Schüller

Kohl

et al. 2021

Biological Psychiatry

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…The connectome is key for understanding how the brain works. Over the last years, multiple studies have demonstrated that neurological and psychiatric symptoms can be mapped to a common distributed brain network [19][20][21][22][23][24][25][26][27][28][29][30]. The brain connectome can be assessed using different MRI acquisitions: (1) diffusion-weighted MRI (dMRI) to estimate the structural connectivity using the directionality of water diffusion to evaluate tracts and projections [31]; (2) resting state functional MRI (rsfMRI) to estimate functional connectivity making use of the lowfrequency blood oxygen level-dependent (BOLD) fluctuations found in brain regions that are functionally related to each other [32].…”

Section: Connectomicsmentioning

confidence: 99%

Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics

Germann

Zadeh

Mansouri

et al. 2022

Cancers

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Neuro-oncology research is broad and includes several branches, one of which is neuroimaging. Magnetic resonance imaging (MRI) is instrumental for the diagnosis and treatment monitoring of patients with brain tumors. Most commonly, structural and perfusion MRI sequences are acquired to characterize tumors and understand their behaviors. Thanks to technological advances, structural brain MRI can now be transformed into a so-called average brain accounting for individual morphological differences, which enables retrospective group analysis. These normative analyses are uncommonly used in neuro-oncology research. Once the data have been normalized, voxel-wise analyses and spatial mapping can be performed. Additionally, investigations of underlying connectomics can be performed using functional and structural templates. Additionally, a recently available template of spatial transcriptomics has enabled the assessment of associated gene expression. The few published normative analyses have shown relationships between tumor characteristics and spatial localization, as well as insights into the circuitry associated with epileptogenic tumors and depression after cingulate tumor resection. The wide breadth of possibilities with normative analyses remain largely unexplored, specifically in terms of connectomics and imaging transcriptomics. We provide a framework for performing normative analyses in oncology while also highlighting their limitations. Normative analyses are an opportunity to address neuro-oncology questions from a different perspective.

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A Unified Functional Network Target for Deep Brain Stimulation in Obsessive-Compulsive Disorder

Cited by 47 publications

References 118 publications

A brain network for deep brain stimulation induced cognitive decline in Parkinson’s disease

A brain network for deep brain stimulation induced cognitive decline in Parkinson’s disease

Connectomic Deep Brain Stimulation for Obsessive-Compulsive Disorder

Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics

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