Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging
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Abstract
Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural/functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient's preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the preprocessing method of choice. 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.
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Historically, most targets discussed were identified pre-surgically in standard stereotactic anatomical space based on atlases.
“Historically, most targets discussed here have been identified pre-surgically in standard stereotactic anatomical space based on atlases [11,87].”
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Co-registration of stereotactic MRI and isofieldlines during deep brain stimulation
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Thalamic deep brain stimulation decelerates automatic lexical activation
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Self-citationGeneration and evaluation of an ultra-high-field atlas with applications in DBS planning
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Self-citationPost-operative deep brain stimulation assessment: Automatic data integration and report generation
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Self-citationPersistence of Mania After Cessation of Stimulation Following Subthalamic Deep Brain Stimulation
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A structural group-connectome in standard stereotactic (MNI) space
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A 3D multimodal approach to precisely locate DBS electrodes in the basal ganglia brain region
da Silva, N. M., Rozanski, V. E., & Cunha, J. P. S. (2015) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2015.7146617 · Cited by 11 · see citing works
Reply: Oscillatory coupling of the subthalamic nucleus in obsessive compulsive disorder
Accolla, E. A., Horn, A., Ruiz, M. H., Neumann, W., & Kühn, A. A. (2017) · Brain · doi:10.1093/brain/awx165 · Cited by 10 · see citing works
Self-citationPrAGMATiC: a Probabilistic and Generative Model of Areas Tiling the CortexPreprint
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Hohlefeld, F. U., Ewald, A., Ehlen, F., Tiedt, H. O., Horn, A., Kühn, A. A., Curio, G., Klostermann, F., & Nikulin, V. V. (2017) · Clinical Neurophysiology · doi:10.1016/j.clinph.2016.12.026 · Cited by 7 · see citing works
Self-citationA Virtual Patient Simulator Based on Human Connectome and 7 T MRI for Deep Brain Stimulation.
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MNI T1 6thGen NLIN to MNI 2009b NLIN ANTs transform
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Self-citationRobert, K. S., Rafay, A. Q., Natalie, R. H., Dara, B., Tuo, P. L., Samir, J. M., & Tang, C. (2014) · Cited by 6 · see citing works
A High-Resolution Probabilistic In Vivo Atlas of Human Subcortical Brain NucleiPreprint
Pauli, W. M., Nili, A. N., & Tyszka, J. M. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/211201 · Cited by 6 · see citing works
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Self-citationThe next step for imaging the subthalamic nucleus
Forstmann, B. U., Keuken, M. C., & Alkemade, A. (2016) · Brain · doi:10.1093/brain/aww245 · Cited by 3 · see citing works
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Technology of deep brain stimulation: current status and future directions
Krauss, J. K., Lipsman, N., Aziz, T. Z., Boutet, A., Brown, P., Chang, J. W., Davidson, B., Grill, W. M., Hariz, M. I., Horn, A., et al. (2020) · Nature Reviews Neurology · doi:10.1038/s41582-020-00426-z · Cited by 930 · see citing works
Self-citationA unified connectomic target for deep brain stimulation in obsessive-compulsive disorder
Li, N., Baldermann, J. C., Kibleur, A., Treu, S., Akram, H., Elias, G. J. B., Boutet, A., Lozano, A. M., Al‐Fatly, B., Strange, B. A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16734-3 · Cited by 317 · see citing works
Self-citation7 Tesla MRI of the ex vivo human brain at 100 micron resolution
Edlow, B. L., Mareyam, A., Horn, A., Polimeni, J. R., Witzel, T., Tisdall, M. D., Augustinack, J. C., Stockmann, J., Diamond, B. R., Stevens, A. A., et al. (2019) · Scientific Data · doi:10.1038/s41597-019-0254-8 · Cited by 303 · see citing works
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Dynamic coupling of whole-brain neuronal and neurotransmitter systems
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Towards network-guided neuromodulation for epilepsy
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Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks
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Probabilistic sweet spots predict motor outcome for deep brain stimulation in Parkinson disease
Dembek, T., Roediger, J., Horn, A., Reker, P., Oehrn, C., Dafsari, H., Li, N.-F., Kühn, A., Fink, G., Visser-Vandewalle, V., et al. (2019) · Annals of Neurology · doi:10.1002/ana.25567 · Cited by 199 · see citing works
Self-citationDeep Brain Stimulation in Movement Disorders: From Experimental Surgery to Evidence‐Based Therapy
Krack, P., Volkmann, J., Tinkhauser, G., & Deuschl, G. (2019) · Movement Disorders · doi:10.1002/mds.27860 · Cited by 186 · see citing works
DBS of Thalamic Centromedian Nucleus for Lennox–Gastaut Syndrome ( ESTEL Trial)
Dalic, L. J., Warren, A. E. L., Bulluss, K. J., Thevathasan, W., Roten, A., Churilov, L. P., & Archer, J. S. (2021) · Annals of Neurology · doi:10.1002/ana.26280 · Cited by 214 · see citing works
Neural signatures of hyperdirect pathway activity in Parkinson’s disease
Oswal, A., Cao, C., Yeh, C.-H., Neumann, W., Gratwicke, J., Akram, H., Horn, A., Li, D., Zhan, S., Zhang, C., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25366-0 · Cited by 191 · see citing works
Self-citationOpportunities of connectomic neuromodulation
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Self-citationMapping dysfunctional circuits in the frontal cortex using deep brain stimulation
Hollunder, B., Ostrem, J. L., Sahin, I. A., Rajamani, N., Oxenford, S., Butenko, K., Neudorfer, C., Reinhardt, P., Zvarova, P., Polosan, M., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01570-1 · Cited by 187 · see citing works
Self-citationConnectivity profile of thalamic deep brain stimulation to effectively treat essential tremor
Al‐Fatly, B., Ewert, S., Kübler, D., Kroneberg, D., Horn, A., & Kühn, A. A. (2019) · Brain · doi:10.1093/brain/awz236 · Cited by 177 · see citing works
Self-citationDeep brain stimulation for depression.
Figee, M., Riva-Posse, P., Choi, K. S., Bederson, L., Mayberg, H. S., & Kopell, B. H. (2022) · Neurotherapeutics · doi:10.1007/s13311-022-01270-3 · Cited by 175 · see citing works
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Non-motor outcomes depend on location of neurostimulation in Parkinson’s disease
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Self-citationA high-resolution in vivo magnetic resonance imaging atlas of the human hypothalamic region
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Self-citationNormative vs. patient-specific brain connectivity in deep brain stimulation
Wang, Q., Akram, H., Muthuraman, M., González‐Escamilla, G., Sheth, S. A., Oxenford, S., Yeh, F.-C. F., Groppa, S., Vanegas‐Arroyave, N., Zrinzo, L. U., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117307 · Cited by 134 · see citing works
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Self-citationEdlow, B. L., Sanz, L. R. D., Polizzotto, L., Pouratian, N., Rolston, J. D., Snider, S. B., Thibaut, A., Stevens, R. D., Gosseries, O., members, T. C. C. C. A. I. C., et al. (2021) · Neurocritical Care · doi:10.1007/s12028-021-01227-y · Cited by 129 · see citing works
Holographic Reconstruction of Axonal Pathways in the Human Brain
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Deep brain stimulation: Imaging on a group level
Treu, S., Strange, B. A., Oxenford, S., Neumann, W., Kühn, A. A., Li, N., & Horn, A. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117018 · Cited by 128 · see citing works
Self-citationProbabilistic Mapping of Deep Brain Stimulation: Insights from 15 Years of Therapy
Elias, G. J. B., Boutet, A., Joel, S. E., Germann, J., Gwun, D., Neudorfer, C., Gramer, R., Algarni, M., Paramanandam, V., Prasad, S., et al. (2020) · Annals of Neurology · doi:10.1002/ana.25975 · Cited by 123 · see citing works
Self-citationTargeting the centromedian thalamic nucleus for deep brain stimulation
Warren, A. E. L., Dalic, L. J., Thevathasan, W., Roten, A., Bulluss, K. J., & Archer, J. S. (2020) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2019-322030 · Cited by 119 · see citing works
Deep brain stimulation of symptom-specific networks in Parkinson’s disease
Rajamani, N., Friedrich, H., Butenko, K., Dembek, T., Lange, F., Navrátil, P., Zvarova, P., Hollunder, B., de Bie, R. M. A., Odekerken, V. J. J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48731-1 · Cited by 118 · see citing works
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Left Prefrontal Connectivity Links Subthalamic Stimulation with Depressive Symptoms
Irmen, F., Horn, A., Mosley, P. E., Perry, A., Petry‐Schmelzer, J. N., Dafsari, H. S., Barbe, M. T., Visser-Vandewalle, V. E. R. M., Schneider, G., Li, N., et al. (2020) · Annals of Neurology · doi:10.1002/ana.25734 · Cited by 115 · see citing works
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Self-citationMetastable oscillatory modes emerge from synchronization in the brain spacetime connectome
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Modulation of beta bursts in subthalamic sensorimotor circuits predicts improvement in bradykinesia
Kehnemouyi, Y. M., Wilkins, K. B., Anidi, C. M., Anderson, R. W., Afzal, M. F., & Bronte-Stewart, H. M. (2020) · Brain · doi:10.1093/brain/awaa394 · Cited by 103 · see citing works
Optimal deep brain stimulation sites and networks for cervical vs. generalized dystonia
Horn, A., Reich, M. M., Ewert, S., Li, N., Al‐Fatly, B., Lange, F., Roothans, J., Oxenford, S., Horn, I., Paschen, S., et al. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2114985119 · Cited by 99 · see citing works
Self-citationClosed‐Loop Deep Brain Stimulation for Essential Tremor Based on Thalamic Local Field Potentials
He, S., Baig, F., Mostofi, A., Pogosyan, A. H., Debarros, J., Green, A. L., Aziz, T. Z., Pereira, E. A. C., Brown, P., & Tan, H. (2021) · Movement Disorders · doi:10.1002/mds.28513 · Cited by 92 · see citing works
Evaluation of methodologies for computing the deep brain stimulation volume of tissue activated
Duffley, G., Anderson, D. N., Vorwerk, J., Dorval, A. D., & Butson, C. R. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab3c95 · Cited by 91 · see citing works
Self-citationPSA and VIM DBS efficiency in essential tremor depends on distance to the dentatorubrothalamic tract
Dembek, T. A., Petry‐Schmelzer, J. N., Reker, P., Wirths, J., Hamacher, S., Steffen, J. K., Dafsari, H. S., Hoevels, M., Fink, G. R., Visser-Vandewalle, V. E. R. M., et al. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102235 · Cited by 90 · see citing works
Self-citationMerk, T., Peterson, V., Lipski, W. J., Blankertz, B., Richardson, R. M., Li, N., Horn, A., Kühn, A. A., Richardson, R. M., & Neumann, W. (2021) · eLife · doi:10.7554/elife.75126 · Cited by 90 · see citing works
Self-citationToward personalized medicine in connectomic deep brain stimulation
Hollunder, B., Rajamani, N., Siddiqi, S., Finke, C., Kühn, A. A., Mayberg, H. S., Fox, M., Neudorfer, C., & Horn, A. (2021) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2021.102211 · Cited by 89 · see citing works
Self-citationA neural network for tics: insights from causal brain lesions and deep brain stimulation
Ganos, C., Al‐Fatly, B., Fischer, J.-F., Baldermann, J. C., van der Linden, C., Visser-Vandewalle, V. E. R. M., Neudorfer, C., Martino, D., Li, J., van der Vlis, T. A. M. B., et al. (2022) · Brain · doi:10.1093/brain/awac009 · Cited by 88 · see citing works
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Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation
Merk, T., Peterson, V., Köhler, R. M., Haufe, S., Richardson, R. M., & Neumann, W. (2022) · Experimental Neurology · doi:10.1016/j.expneurol.2022.113993 · Cited by 87 · see citing works
Self-citationComparative connectivity correlates of dystonic and essential tremor deep brain stimulation
Tsuboi, T., Wong, J. K., Eisinger, R. S., Okromelidze, L., Burns, M. R., Ramirez‐Zamora, A., Almeida, L., Shukla, A. W., Foote, K. D., Okun, M. S., et al. (2021) · Brain · doi:10.1093/brain/awab074 · Cited by 86 · see citing works
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A Unified Functional Network Target for Deep Brain Stimulation in Obsessive-Compulsive Disorder
Li, N., Hollunder, B., Baldermann, J. C., Kibleur, A., Treu, S., Akram, H., Al‐Fatly, B., Strange, B. A., Barcia, J. A., Zrinzo, L. U., et al. (2021) · Biological Psychiatry · doi:10.1016/j.biopsych.2021.04.006 · Cited by 81 · see citing works
Self-citationThe Optimal Target and Connectivity for Deep Brain Stimulation in Lennox–Gastaut Syndrome
Warren, A. E. L., Dalic, L. J., Bulluss, K. J., Roten, A., Thevathasan, W., & Archer, J. S. (2022) · Annals of Neurology · doi:10.1002/ana.26368 · Cited by 79 · see citing works
Hell, F., Palleis, C., Mehrkens, J. H., Koeglsperger, T., & Bötzel, K. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.00314 · Cited by 75 · see citing works
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Self-citationSubthalamic and pallidal deep brain stimulation: are we modulating the same network?
Sobesky, L., Goede, L. L., Odekerken, V. J. J., Wang, Q., Li, N., Neudorfer, C., Rajamani, N., Al‐Fatly, B., Reich, M. M., Volkmann, J., et al. (2021) · Brain · doi:10.1093/brain/awab258 · Cited by 72 · see citing works
Self-citationSpectral and spatial distribution of subthalamic beta peak activity in Parkinson's disease patients
Darcy, N., Lofredi, R., Al‐Fatly, B., Neumann, W., Hübl, J., Brücke, C., Krause, P., Schneider, G., & Kühn, A. A. (2022) · Experimental Neurology · doi:10.1016/j.expneurol.2022.114150 · Cited by 71 · see citing works
Self-citationDirectional DBS leads show large deviations from their intended implantation orientation
Dembek, T. A., Hoevels, M., Hellerbach, A., Horn, A., Petry‐Schmelzer, J. N., Borggrefe, J., Wirths, J., Dafsari, H. S., Barbe, M. T., Visser-Vandewalle, V. E. R. M., et al. (2019) · Parkinsonism & Related Disorders · doi:10.1016/j.parkreldis.2019.08.017 · Cited by 70 · see citing works
Self-citationDeep brain stimulation: a review of the open neural engineering challenges
Vissani, M., Isaias, I. U., & Mazzoni, A. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/abb581 · Cited by 70 · see citing works
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“All procedures were approved by the local institutional review board (IRB) at Baylor College of Medicine (BCM; IRB H-48392) and the University of Utah (IRB_00169174).”
Iorio‐Morin, C., Fomenko, A., & Kalia, S. K. (2020) · Brain Sciences · doi:10.3390/brainsci10120925 · Cited by 68 · see citing works
The impact of modern-day neuroimaging on the field of deep brain stimulation
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Self-citationThalamic stereoelectroencephalography in epilepsy surgery: a scoping literature review
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Apathy in Parkinson’s Disease: Clinical Patterns and Neurobiological Basis
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A Comprehensive Review of Brain Connectomics and Imaging to Improve Deep Brain Stimulation Outcomes
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Personalizing Deep Brain Stimulation Using Advanced Imaging Sequences
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Self-citationPrinciples of gait encoding in the subthalamic nucleus of people with Parkinson’s disease
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Roediger, J., Dembek, T. A., Achtzehn, J., Busch, J. L., Krämer, A.-P., Faust, K., Schneider, G., Krause, P., Horn, A., & Kühn, A. A. (2022) · The Lancet Digital Health · doi:10.1016/s2589-7500(22)00214-x · Cited by 62 · see citing works
Self-citationAdvances in Technical Aspects of Deep Brain Stimulation Surgery
Schulder, M., Mishra, A., Mammis, A., Horn, A., Boutet, A., Blomstedt, P. C., Chabardès, S., Flouty, O. E., Lozano, A. M., Neimat, J. S., et al. (2023) · Stereotactic and Functional Neurosurgery · doi:10.1159/000529040 · Cited by 62 · see citing works
Self-citationCombining Multimodal Biomarkers to Guide Deep Brain Stimulation Programming in Parkinson Disease
Shah, A., Nguyen, T. A. K., Petermann, K., Khawaldeh, S., Debove, I., Shah, S. A., Torrecillos, F., Tan, H., Pogosyan, A. H., Lachenmayer, M. L., et al. (2022) · Neuromodulation Technology at the Neural Interface · doi:10.1016/j.neurom.2022.01.017 · Cited by 59 · see citing works
Hypothalamic deep brain stimulation augments walking after spinal cord injury
Cho, N., Squair, J. W., Aureli, V., James, N. D., Bole-Feysot, L., Dewany, I., Hankov, N., Baud, L., Leonhartsberger, A., Sveistyte, K., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-03306-x · Cited by 59 · see citing works
Subthalamic Nucleus and Sensorimotor Cortex Activity During Speech Production
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Self-citationChaitanya, G., Romeo, A. K., Ilyas, A., Irannejad, A. B., Tóth, E., Elsayed, G., Bentley, J. N., Riley, K. O., & Pati, S. B. B. (2020) · Neurosurgical FOCUS · doi:10.3171/2020.1.focus19887 · Cited by 58 · see citing works
Centromedian thalamic deep brain stimulation for drug-resistant epilepsy: single-center experience
Yang, J. C., Bullinger, K. L., Isbaine, F., Alwaki, A., Opri, E., Willie, J. T., & Gross, R. E. (2022) · Journal of neurosurgery · doi:10.3171/2022.2.jns212237 · Cited by 59 · see citing works
Deep Brain Stimulation for Obsessive-Compulsive Disorder: Optimal Stimulation Sites
Meyer, G. M., Hollunder, B., Li, N., Butenko, K., Dembek, T. A., Hart, L., Nombela, C., Mosley, P. E., Akram, H., Acevedo, N., et al. (2023) · Biological Psychiatry · doi:10.1016/j.biopsych.2023.12.010 · Cited by 58 · see citing works
Self-citationMiddlebrooks, E. H., Okromelidze, L., Wong, J. K., Eisinger, R. S., Burns, M. R., Jain, A., Lin, H.-P., Yu, J., Opri, E., Horn, A., et al. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102846 · Cited by 57 · see citing works
Self-citationSubthalamic Nucleus Stimulation Modulates Motor Epileptic Activity in Humans
Ren, L., Yu, T., Wang, D., Wang, X., Ni, D., Zhang, G., Bartoloméi, F., Wang, Y., & Li, Y. (2020) · Annals of Neurology · doi:10.1002/ana.25776 · Cited by 57 · see citing works
Subthalamic stimulation impairs stopping of ongoing movements
Lofredi, R., Auernig, G. C., Irmen, F., Nieweler, J., Neumann, W., Horn, A., Schneider, G., & Kühn, A. A. (2020) · Brain · doi:10.1093/brain/awaa341 · Cited by 56 · see citing works
Self-citationParkinson’s disease as a somato-cognitive action network disorder
Ren, J., Zhang, W., Dahmani, L., Gordon, E. M., Li, S., Zhou, Y., Long, Y., Huang, J., Zhu, Y., Guo, N., et al. (2026) · Nature · doi:10.1038/s41586-025-10059-1 · Cited by 55 · see citing works
Olaru, M., Cernera, S., Hahn, A., Wozny, T. A., Ansó, J., de Hemptinne, C., Little, S. J., Neumann, W., Abbasi-Asl, R., & Starr, P. A. (2024) · Brain · doi:10.1093/brain/awae004 · Cited by 55 · see citing works
Self-citationOkromelidze, L., Tsuboi, T., Eisinger, R. S., Burns, M. R., Charbel, M., Rana, M., Grewal, S. S., Lu, C., Almeida, L., Foote, K. D., et al. (2020) · American Journal of Neuroradiology · doi:10.3174/ajnr.a6429 · Cited by 55 · see citing works
Beta-triggered adaptive deep brain stimulation during reaching movement in Parkinson’s disease
He, S., Baig, F., Merla, A., Torrecillos, F., Perera, A. P., Wiest, C., Debarros, J., Benjaber, M., Hart, M. G., Ricciardi, L., et al. (2023) · Brain · doi:10.1093/brain/awad233 · Cited by 54 · see citing works
Chen, C.-C., Yeh, C.-H., Chan, H., Chang, Y., Tu, P., Yeh, C., Lu, C., Fischer, P., Tinkhauser, G., Tan, H., et al. (2019) · Neurobiology of Disease · doi:10.1016/j.nbd.2019.104605 · Cited by 54 · see citing works
Subthalamic nucleus activity dynamics and limb movement prediction in Parkinson’s disease
Khawaldeh, S., Tinkhauser, G., Shah, S. A., Petermann, K., Debove, I., Nguyen, T. A. K., Nowacki, A., Lachenmayer, M. L., Schüpbach, M. W. M., Pollo, C., et al. (2019) · Brain · doi:10.1093/brain/awz417 · Cited by 54 · see citing works
Probabilistic Mapping Reveals Optimal Stimulation Site in Essential Tremor
Nowacki, A., Barlatey, S. L., Al‐Fatly, B., Dembek, T. A., Bot, M., Green, A. L., Kübler, D., Lachenmayer, M. L., Debove, I., Amil, A. S., et al. (2022) · Annals of Neurology · doi:10.1002/ana.26324 · Cited by 51 · see citing works
Self-citationSweetspot Mapping in Deep Brain Stimulation: Strengths and Limitations of Current Approaches
Dembek, T. A., Baldermann, J. C., Petry‐Schmelzer, J. N., Jergas, H., Treuer, H., Visser-Vandewalle, V. E. R. M., Dafsari, H. S., & Barbe, M. T. (2021) · Neuromodulation Technology at the Neural Interface · doi:10.1111/ner.13356 · Cited by 51 · see citing works
Self-citationPallidal low‐frequency activity in dystonia after cessation of long‐term deep brain stimulation
Scheller, U., Lofredi, R., van Wijk, B. C. M., Saryyeva, A., Krauss, J. K., Schneider, G., Kroneberg, D., Krause, P., Neumann, W., & Kühn, A. A. (2019) · Movement Disorders · doi:10.1002/mds.27838 · Cited by 50 · see citing works
Self-citationElias, G. J. B., Germann, J., Boutet, A., Pancholi, A., Beyn, M. E., Bhatia, K. D., Neudorfer, C., Loh, A., Rizvi, S. J., Bhat, V., et al. (2021) · Brain · doi:10.1093/brain/awab284 · Cited by 49 · see citing works
Zhang, C., Lai, Y., Li, J., He, N., Liu, Y., Li, Y., Li, H., Wei, H., Yan, F., Horn, A., et al. (2021) · Annals of Neurology · doi:10.1002/ana.26199 · Cited by 49 · see citing works
Self-citation3T MRI of rapid brain activity changes driven by subcallosal cingulate deep brain stimulation
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Theta‐alpha Oscillations Characterize Emotional Subregion in the Human Ventral Subthalamic Nucleus
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Lesion network localization of depression in multiple sclerosis
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Self-citationStimFit— A Data‐Driven Algorithm for Automated Deep Brain Stimulation Programming
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Self-citationFunctional Activation Patterns of Deep Brain Stimulation of the Anterior Nucleus of the Thalamus
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Deep Brain Stimulation for Chronic Cluster Headache: Meta‐Analysis of Individual Patient Data
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- Authors
- Horn, A., Li, N., Dembek, T. A., Kappel, A., Boulay, C., Ewert, S., Tietze, A., Husch, A., Perera, T., Neumann, W.-J., Reisert, M., Si, H., Oostenveld, R., Rorden, C., Yeh, F.-C., Fang, Q., Herrington, T. M., Vorwerk, J., & Kühn, A. A.
- Affiliations
- Stiftung Charité (DE)
- Charité – Universitätsmedizin Berlin (DE)
- University Hospital Cologne (DE)
- Wayne State University (US)
- Ottawa Hospital Research Institute (CA)
- University of Luxembourg (LU)
- Bionics Institute (AU)
- University of Freiburg (DE)
- Weierstrass Institute for Applied Analysis and Stochastics (DE)
- Radboud University Nijmegen (NL)
- University of Pittsburgh (US)
- Northeastern University (US)
- Harvard University (US)
- University of Utah (US)
- Corresponding author
- Horn, Andreas
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2019-01
- Volume
- 184
- Pages
- 293-316
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC6286150
- OpenAlex
- W2950023299
- Cited by
- 739
- References
- 204
- Citations by year
- 2026: 57 · 2025: 108 · 2024: 101 · 2023: 101 · 2022: 113 · 2021: 115 · 2020: 99 · 2019: 43 · 2018: 2
- FWCI
- 43.89
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- NeuroImage (acceptedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed (publishedVersion)
- Kölner Universitäts PublikationsServer (Universität zu Köln) (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- FreiDok plus (Universitätsbibliothek Freiburg) (submittedVersion)
- Open Repository and Bibliography (University of Luxembourg) (submittedVersion, other-oa)
- Radboud Repository (Radboud University) (submittedVersion)
- Funders
- American Brain Foundation
- National Institute of General Medical Sciences (R01-CA204443)
- American Academy of Neurology
- National Institute of Neurological Disorders and Stroke (K23NS099380)
- National Science Foundation (US IGNITE - 10037840)
- Deutsche Forschungsgemeinschaft (KFO 247, SPP 2041SPP 2041)
- National Institute of Dental and Craniofacial Research
- National Institutes of Health (R01-GM114365)
- State Government of Victoria
- Michael J. Fox Foundation for Parkinson's Research
- Colonial Foundation
- Medtronic
- National Cancer Institute
- National Institute of Mental Health
- Topics
- Health Sciences › Medicine › Neurology › Neurological disorders and treatments
- Social Sciences › Psychology › Clinical Psychology › Obsessive-Compulsive Spectrum Disorders
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- deep brain stimulation, brain shift correction, tractography, structural connectivity, functional connectivity, diffusion MRI, Parkinson's disease, tissue activation volume, connectomics
- MeSH terms
- Aged, Electrodes, Implanted, Female, Humans, Male, Middle Aged, Parkinson Disease, Software, Deep Brain Stimulation, Neuroimaging
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