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Sergiu Groppa

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7 papers

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YNIMG Journal 2021 Journal Article

EEG and MEG primers for tracking DBS network effects

Vladimir Litvak
Esther Florin
Gertrúd Tamás
Sergiu Groppa
Muthuraman Muthuraman

Deep brain stimulation (DBS) is an effective treatment method for a range of neurological and psychiatric disorders. It involves implantation of stimulating electrodes in a precisely guided fashion into subcortical structures and, at a later stage, chronic stimulation of these structures with an implantable pulse generator. While the DBS surgery makes it possible to both record brain activity and stimulate parts of the brain that are difficult to reach with non-invasive techniques, electroencephalography (EEG) and magnetoencephalography (MEG) provide complementary information from other brain areas, which can be used to characterize brain networks targeted through DBS. This requires, however, the careful consideration of different types of artifacts in the data acquisition and the subsequent analyses. Here, we review both the technical issues associated with EEG/MEG recordings in DBS patients and the experimental findings to date. One major line of research is simultaneous recording of local field potentials (LFPs) from DBS targets and EEG/MEG. These studies revealed a set of cortico-subcortical coherent networks functioning at distinguishable physiological frequencies. Specific network responses were linked to clinical state, task or stimulation parameters. Another experimental approach is mapping of DBS-targeted networks in chronically implanted patients by recording EEG/MEG responses during stimulation. One can track responses evoked by single stimulation pulses or bursts as well as brain state shifts caused by DBS. These studies have the potential to provide biomarkers for network responses that can be adapted to guide stereotactic implantation or optimization of stimulation parameters. This is especially important for diseases where the clinical effect of DBS is delayed or develops slowly over time. The same biomarkers could also potentially be utilized for the online control of DBS network effects in the new generation of closed-loop stimulators that are currently entering clinical use. Through future studies, the use of network biomarkers may facilitate the integration of circuit physiology into clinical decision making.

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YNIMG Journal 2021 Journal Article

Normative vs. patient-specific brain connectivity in deep brain stimulation

Qiang Wang
Harith Akram
Muthuraman Muthuraman
Gabriel Gonzalez-Escamilla
Sameer A. Sheth
Simón Oxenford
Fang-Cheng Yeh
Sergiu Groppa

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, a number of 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 their ability to predict clinical improvement. Data from 33 patients suffering from Parkinson's 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 patient-specific diffusion-MRI data, age- and disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were calculated and used to estimate 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 this present novel multi-center cohort. In a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample predictions of clinical improvements were calculated. Using either patient-specific connectivity (R = 0.43 at p = 0.001), an age- and disease-matched group connectome (R = 0.25, p = 0.048) and a normative connectome based on healthy/young subjects (R = 0.31 at p = 0.028), significant predictions could be made. Our results of patient-specific connectivity and normative connectomes lead to similar 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 explaining slightly more variance than group connectomes. Furthermore, use of normative connectomes involves datasets with high signal-to-noise acquired on specialized MRI hardware, while clinical datasets as the ones used here may not exactly match their quality. Our findings support the role of DBS electrode connectivity profiles as a promising method to investigate DBS effects and to potentially guide DBS programming.

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YNIMG Journal 2020 Journal Article

Neuroimaging and electrophysiology meet invasive neurostimulation for causal interrogations and modulations of brain states

Gabriel Gonzalez-Escamilla
Muthuraman Muthuraman
Dumitru Ciolac
Volker A. Coenen
Alfons Schnitzler
Sergiu Groppa

Deep brain stimulation (DBS) has developed over the last twenty years into a highly effective evidenced-based treatment option for neuropsychiatric disorders. Moreover, it has become a fascinating tool to provide illustrative insights into the functioning of brain networks. New anatomical and pathophysiological models of DBS action have accelerated our understanding of neurological and psychiatric disorders and brain functioning. The description of the brain networks arose through the unique ability to illustrate long-range interactions between interconnected brain regions as derived from state-of-the-art neuroimaging (structural, diffusion, and functional MRI) and the opportunity to record local and large-scale brain activity at millisecond temporal resolution (microelectrode recordings, local field potential, electroencephalography, and magnetoencephalography). In the first part of this review, we describe how neuroimaging techniques have led to current understanding of DBS effects, by identifying and refining the DBS targets and illustrate the actual view on the relationships between electrode locations and clinical effects. One step further, we discuss how neuroimaging has shifted the view of localized DBS effects to a modulation of specific brain circuits, which has been possible from the combination of electrode location reconstructions with recently introduced network imaging methods. We highlight how these findings relate to clinical effects, thus postulating neuroimaging as a key factor to understand the mechanisms of DBS action on behavior and clinical effects. In the second part, we show how invasive electrophysiology techniques have been efficiently integrated into the DBS set-up to precisely localize the neuroanatomical targets of DBS based on distinct region-specific patterns of neural activity. Next, we show how multi-site electrophysiological recordings have granted a real-time window into the aberrant brain circuits within and beyond DBS targets to quantify and map the dynamic properties of rhythmic oscillations. We also discuss how DBS alters the transient synchrony states of oscillatory networks in temporal and spatial domains during resting, task-based and motion conditions, and how this modulation of brain states ultimately shapes the functional response. Finally, we show how a successful decoding and management of electrophysiological proxies (beta bursts, phase-amplitude coupling) of aberrant brain circuits was translated into adaptive DBS stimulation paradigms for a targeted and state-dependent invasive electrical neuromodulation.

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YNICL Journal 2019 Journal Article

Automated segmentation of changes in FLAIR-hyperintense white matter lesions in multiple sclerosis on serial magnetic resonance imaging

Paul Schmidt
Viola Pongratz
Pascal Küster
Dominik Meier
Jens Wuerfel
Carsten Lukas
Barbara Bellenberg
Frauke Zipp

Longitudinal analysis of white matter lesion changes on serial MRI has become an important parameter to study diseases with white-matter lesions. Here, we build on earlier work on cross-sectional lesion segmentation; we present a fully automatic pipeline for serial analysis of FLAIR-hyperintense white matter lesions. Our algorithm requires three-dimensional gradient echo T1- and FLAIR- weighted images at 3 Tesla as well as available cross-sectional lesion segmentations of both time points. Preprocessing steps include lesion filling and intrasubject registration. For segmentation of lesion changes, initial lesion maps of different time points are fused; herein changes in intensity are analyzed at the voxel level. Significance of lesion change is estimated by comparison with the difference distribution of FLAIR intensities within normal appearing white matter. The method is validated on MRI data of two time points from 40 subjects with multiple sclerosis derived from two different scanners (20 subjects per scanner). Manual segmentation of lesion increases served as gold standard. Across all lesion increases, voxel-wise Dice coefficient (0.7) as well as lesion-wise detection rate (0.8) and false-discovery rate (0.2) indicate good overall performance. Analysis of scans from a repositioning experiment in a single patient with multiple sclerosis did not yield a single false positive lesion. We also introduce the lesion change plot as a descriptive tool for the lesion change of individual patients with regard to both number and volume. An open source implementation of the algorithm is available at http://www.statistical-modeling.de/lst.html.

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YNIMG Journal 2016 Journal Article

Power estimation for non-standardized multisite studies

Anisha Keshavan
Friedemann Paul
Mona K. Beyer
Alyssa H. Zhu
Nico Papinutto
Russell T. Shinohara
William Stern
Michael Amann

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions.

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YNIMG Journal 2012 Journal Article

A novel dual-site transcranial magnetic stimulation paradigm to probe fast facilitatory inputs from ipsilateral dorsal premotor cortex to primary motor cortex

Sergiu Groppa
Nicole Werner-Petroll
Alexander Münchau
Günther Deuschl
Matthew F.S. Ruschworth
Hartwig R. Siebner

The dorsal premotor cortex (PMd) plays an import role in action control, sensorimotor integration and motor recovery. Animal studies and human data have demonstrated direct connections between ipsilateral PMd and primary motor cortex hand area (M1HAND). In this study we adopted a multimodal approach combining highly focal dual-site TMS (dsTMS) and diffusion tensor imaging (DTI) to probe ipsilateral effective and structural connectivity between PMd and M1HAND in humans. A suprathreshold test stimulus (TS) was applied to left M1HAND producing a motor evoked potential (MEP) and a subsequent conditioning stimulus (CS) to ipsilateral rostromedial PMd at short latencies ranging from of 0. 8 to 2. 0ms. At an interstimulus interval of 1. 2ms, dsTMS of the left M1HAND and PMd facilitated MEP amplitudes relative to unconditioned TMS of M1HAND. This PMd to M1HAND facilitation was absent during voluntary contraction of the target muscle. During a two-choice reaction time task, PMd–M1HAND facilitation was only observed when dsTMS was given 125ms after presentation of the cue and subjects responded with their right hand, but not for left hand responses. Our results reveal a short-latency PMd to M1HAND connection which modulates excitability of ipsilateral M1HAND in a task and effector specific manner. DTI revealed that individual increases in PMd to M1HAND facilitation were correlated with fractional anisotropy and axial diffusivity in the juxtacortical white matter underlying the caudal portion of the left superior frontal gyrus. This finding shows that the functional strength of this connection from medial PMd to M1HAND has a microstructural correlate in the underlying subcortical white matter. This novel dsTMS paradigm can be used to non-invasively probe effective PMd to M1HAND connectivity in healthy individuals and patients with impaired hand function.

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YNIMG Journal 2011 Journal Article

Manual activity shapes structure and function in contralateral human motor hand area

Oliver Granert
Martin Peller
Christian Gaser
Sergiu Groppa
Mark Hallett
Arne Knutzen
Günther Deuschl
Kirsten E. Zeuner

From longitudinal voxel-based morphometry (VBM) studies we know that relatively short periods of training can increase regional grey matter volume in trained cortical areas. In 14 right-handed patients with writer's cramp, we employed VBM to test whether suppression (i. e. , immobilization) or enhancement (i. e. , training) of manual activity lead to opposing changes in grey matter in the contralateral primary motor hand area (M1HAND). We additionally used transcranial magnetic stimulation (TMS) to evaluate concurrent changes in regional excitability. Patients were recruited from a clinical trial which was designed to improve handwriting-associated dystonia. Initially the dystonic hand was immobilized for 4weeks with the intention to reverse faulty plasticity. After immobilization, patients accomplished a motor re-training for 8weeks. T1-weighted MRIs of the whole brain and single-pulse TMS measurements of the resting motor threshold (RMT) were performed every 4weeks. Immobilization of the right hand resulted in a relative grey matter decrease in the contralateral left M1HAND along with a decrease in corticomotor excitability as indexed by an increase in RMT. Subsequent training reversed the effects of immobilization, causing an increase in regional grey matter density and excitability of left M1HAND. The relative changes in grey matter correlated with the relative shifts in RMT. This prospective within-subject VBM study in task-specific hand dystonia shows that the grey matter density of M1HAND is dynamically shaped by the level of manual activity. This bi-directional structural plasticity is functionally relevant as local grey matter changes are mirrored by changes in regional excitability.

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