Weight Change after Striatal/Capsule Deep Brain Stimulation Relates to Connectivity to the Bed Nucleus of the Stria Terminalis and Hypothalamus

Baldermann, Juan Carlos; Hahn, Lisa; Dembek, Till A.; Kohl, Sina; Kuhn, Jens; Visser‐Vandewalle, Veerle; Horn, Andreas; Huys, Daniel

doi:10.3390/brainsci9100264

Cited by 17 publications

(18 citation statements)

References 30 publications

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“…Recently, normative structural connectomes were introduced to account for motor improvement (Horn et al, 2017b) and change of depressive symptoms (Irmen et al, 2019) in Parkinson’s disease patients following STN-DBS. The concept was also applied to DBS in Essential Tremor syndrome (Al-Fatly et al, 2019), Obsessive-Compulsive disorder (J. C. Baldermann et al, 2019; Li et al, 2019) and Epilepsy (Middlebrooks et al, 2018). Furthermore, normative connectomes were used to explain behavioral effects following STN-DBS such as movement speed (Neumann et al, 2018) and motor learning (de Almeida Marcelino et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…Finally, the concept was applied to investigate side-effects such as DBS induced seizures (Boutet et al, 2019), weight-changes (J. Baldermann et al, 2019) or panic attacks (Elias et al, 2019). While this approach was useful to explore the variability in clinical improvement out-of-sample data (i.e.…”

Section: Discussionmentioning

confidence: 99%

“…at the subthalamic nucleus; STN) but also affects distributed basal-ganglia cortical cerebellar networks (Accolla et al, 2016; Helmich et al, 2012; Horn et al, 2017b; Horn, 2019; Kahan et al, 2019; Lozano and Lipsman, 2013; Muthuraman et al, 2018). The impact of DBS on pathological networks has been highlighted in PD (Accolla et al, 2016; Horn, 2019; Kahan et al, 2019) as well as other diseases such as Essential Tremor (Al-Fatly et al, 2019), dystonia (Corp et al, 2019) and obsessive-compulsive disorder (J. C. Baldermann et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…This concept has since then been applied to explore connectivity associated with clinical or behavioral changes in multiple diseases (Al-Fatly et al, 2019; J. C. Baldermann et al, 2019; Johnson et al, 2019; J. Baldermann et al, 2019; de Almeida Marcelino et al, 2019; Irmen et al, 2019; Li et al, 2019; Neumann et al, 2018). With the increasing popularity of this approach, it is timely to compare the results achieved by examining patient-specific connectivity with those obtained when using normative connectivity data from other cohorts.…”

Section: Introductionmentioning

confidence: 99%

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Normative vs. patient-specific brain connectivity in Deep Brain Stimulation

Wang

Akram

González‐Escamilla

et al. 2020

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Brain connectivity profiles seeding from deep brain stimulation (DBS) electrodes have emerged as informative tools to estimate outcome variability across DBS patients. Given the limitations of acquiring and processing patient-specific diffusion-weighted imaging data, most studies have employed normative atlases of the human connectome. To date, it remains unclear whether patient-specific connectivity information would strengthen the accuracy of such analyses. Here, we compared similarities and differences between patient-specific, disease-matched and normative structural connectivity data and retrospective estimation of clinical improvement that they may generate. Data from 33 patients suffering from Parkinson Disease who underwent surgery at three different centers were retrospectively collected. Stimulation-dependent connectivity profiles seeding from active contacts were estimated using three modalities, namely either patient-specific diffusion-MRI data, disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were constructed and used to retrospectively estimate the clinical improvement in out of sample data. All three modalities resulted in highly similar optimal connectivity profiles that could largely reproduce findings from prior research based on a novel multi-center cohort. Connectivity estimates seeding from electrodes when using either patient-specific or normative connectomes correlated significantly to primary motor cortex (R = 0.57, p = 0.001, R=0.73, p=0.001), supplementary motor area (R = 0.40, p = 0.005, R = 0.43, p = 0.003), pre-supplementary motor area (R = 0.33, p = 0.022, R = 0.33, p = 0.031), but not to more frontal regions such as the dorsomedial prefrontal cortex (R = 0.21, p = 0.17, R = 0.18, p = 0.17). However, in a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample estimation of clinical improvements were made and ranged within a similar magnitude when applying either of the three modalities (R = 0.43 at p = 0.001 for patient-specific connectivity; R = 0.25, p = 0.048 for the age- and disease-matched group connectome; R = 0.31 at p = 0.028 for healthy-/young connectome). Conclusions: The use of patient-specific connectivity and normative connectomes lead to identical main conclusions about which brain areas are associated with clinical improvement. Still, although results were not significantly different, they hint at the fact that patient-specific connectivity may bear the potential of estimating slightly more variance when compared to group connectomes. Our findings further support the role of DBS electrode connectivity profiles as a promising method to guide surgical targeting and DBS programming.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Normative vs. patient-specific brain connectivity in Deep Brain Stimulation

Wang

Akram

González‐Escamilla

et al. 2020

Preprint

Self Cite

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“…The finding was highly reproducible and allowed robust cross-predictions across cohorts. In OCD patients, weight change following DBS to the ALIC was associated with functional connectivity to the bed nucleusof the stria terminalis ( Baldermann et al, 2019a ). In a different report, stimulating electrodes that were connected to the periaqueductal grey and amygdala induced panic attacks ( Elias et al, 2019 ).…”

Section: Eight Opportunities Of Connectomic Neuromodulationmentioning

confidence: 99%

Opportunities of connectomic neuromodulation

2020

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The process of altering neural activity – neuromodulation – has long been used to treat patients with brain disorders and answer scientific questions. Deep brain stimulation in particular has provided clinical benefit to over 150,000 patients. However, our understanding of how neuromodulation impacts the brain is evolving. Instead of focusing on the local impact at the stimulation site itself, we are considering the remote impact on brainregions connected to the stimulation site. Brain connectivity information derived from advanced magnetic resonance imaging data can be used to identify these connections and better understand clinical and behavioral effectsof neuromodulation. In this article, we review studies combining neuromodulation and brain connectomics, highlighting opportunities where this approach may prove particularly valuable. We focus on deep brain stimulation, but show that the same principles can be applied to other forms of neuromodulation, such as transcranial magnetic stimulation and MRI-guided focused ultrasound. We outline future perspectives and provide testable hypotheses for future work.

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