The FieldTrip-SimBio pipeline for EEG forward solutions

Vorwerk, Johannes; Oostenveld, Robert; Piastra, Maria Carla; Magyari, Lilla; Wolters, Carsten H.

doi:10.1186/s12938-018-0463-y

Cited by 135 publications

(115 citation statements)

References 41 publications

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“…Grey matter was defined by the DISTAL atlas (Ewert et al, 2018) for relevant structures (STN, internal and external pallidum, red nucleus). The electric field (E-field) distribution was then simulated using an adaptation of the FieldTrip-SimBio pipeline (Vorwerk et al, 2018) that was integrated into Lead-DBS All rights reserved. No reuse allowed without permission.…”

Section: Localization Of Dbs Electrodes and Vta Estimationmentioning

confidence: 99%

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

Wang

Akram

González‐Escamilla

et al. 2020

Preprint

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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: Localization Of Dbs Electrodes and Vta Estimationmentioning

confidence: 99%

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

Wang

Akram

González‐Escamilla

et al. 2020

Preprint

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“…SimBio: https://www.mrt.uni-jena.de/simbio/index.php/Main_Page and its integration into FieldTrip (see Vorwerk, Oostenveld, Piastra, Magyari, & Wolters, )…”

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confidence: 99%

The effect of stimulation type, head modeling, and combined EEG and MEG on the source reconstruction of the somatosensory P20/N20 component

Antonakakis

Schrader

Wollbrink

et al. 2019

Human Brain Mapping

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Modeling and experimental parameters influence the Electro‐ (EEG) and Magnetoencephalography (MEG) source analysis of the somatosensory P20/N20 component. In a sensitivity group study, we compare P20/N20 source analysis due to different stimulation type (Electric‐Wrist [EW], Braille‐Tactile [BT], or Pneumato‐Tactile [PT]), measurement modality (combined EEG/MEG – EMEG, EEG, or MEG) and head model (standard or individually skull‐conductivity calibrated including brain anisotropic conductivity). Considerable differences between pairs of stimulation types occurred (EW‐BT: 8.7 ± 3.3 mm/27.1° ± 16.4°, BT‐PT: 9 ± 5 mm/29.9° ± 17.3°, and EW‐PT: 9.8 ± 7.4 mm/15.9° ± 16.5° and 75% strength reduction of BT or PT when compared to EW) regardless of the head model used. EMEG has nearly no localization differences to MEG, but large ones to EEG (16.1 ± 4.9 mm), while source orientation differences are non‐negligible to both EEG (14° ± 3.7°) and MEG (12.5° ± 10.9°). Our calibration results show a considerable inter‐subject variability (3.1–14 mS/m) for skull conductivity. The comparison due to different head model show localization differences smaller for EMEG (EW: 3.4 ± 2.4 mm, BT: 3.7 ± 3.4 mm, and PT: 5.9 ± 6.8 mm) than for EEG (EW: 8.6 ± 8.3 mm, BT: 11.8 ± 6.2 mm, and PT: 10.5 ± 5.3 mm), while source orientation differences for EMEG (EW: 15.4° ± 6.3°, BT: 25.7° ± 15.2° and PT: 14° ± 11.5°) and EEG (EW: 14.6° ± 9.5°, BT: 16.3° ± 11.1° and PT: 12.9° ± 8.9°) are in the same range. Our results show that stimulation type, modality and head modeling all have a non‐negligible influence on the source reconstruction of the P20/N20 component. The complementary information of both modalities in EMEG can be exploited on the basis of detailed and individualized head models.

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“…These atlases were specifically adapted or created for use within the Lead-DBS pipeline. The electric field (E-field) distribution was then simulated using an adaptation of the FieldTrip-SimBio pipeline90 that was integrated into Lead-DBS (https://www.mrt.uni-jena.de/simbio/; http://fieldtriptoolbox.org/) and thresholded at a level of 0.2 V/m 83 .…”

mentioning

confidence: 99%

Toward a unified connectomic target for deep brain stimulation in obsessive-compulsive disorder

Baldermann

Kibleur

et al. 2019

Preprint

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Multiple surgical targets have been proposed for treating obsessive-compulsive disorder (OCD) with deep brain stimulation (DBS). However, different targets may modulate the same neural network responsible for clinical improvement. Here we analyzed data from four cohorts of OCD patients (N = 50) that underwent DBS to the anterior limb of the internal capsule (ALIC), the nucleus accumbens (NAcc) or the subthalamic nucleus (STN). Fiber tracts that were predominantly connected to electrodes in good or poor DBS responders were isolated from a normative structural connectome and assigned a predictive value. Strikingly, the same fiber bundle was related to treatment response when independently analyzing two large training cohorts that targeted either ALIC or STN. This discriminative tract is a subsection of the ALIC and connects frontal regions (such as the dorsal anterior cingulate, dACC, and ventral prefrontal, vlPFC, cortices to the STN). When informing the tract solely based on one cohort (e.g. ALIC), clinical improvements in the other (e.g. STN)could be significantly predicted, and vice versa. Finally, clinical improvements of eight patients from a third center with electrodes in the NAcc and six patients from a fourth center in which electrodes had been implanted in both STN and ALIC were significantly predicted based on this novel tract-based DBS target. Results suggest a functional role of a limbic hyperdirect pathway that projects from dACC and vlPFC to anteriomedial STN. Obsessivecompulsive symptoms seem to be tractable by modulating the specific bundle isolated here.Our results show that connectivity-derived improvement models can inform clinical improvement across DBS targets, surgeons and centers. The identified tract is now threedimensionally defined in stereotactic standard space and will be made openly available.

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The FieldTrip-SimBio pipeline for EEG forward solutions

Cited by 135 publications

References 41 publications

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

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

The effect of stimulation type, head modeling, and combined EEG and MEG on the source reconstruction of the somatosensory P20/N20 component

Toward a unified connectomic target for deep brain stimulation in obsessive-compulsive disorder

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