Mapping dysfunctional circuits in the frontal cortex using deep brain stimulation.
Journal
Nature neuroscience
ISSN: 1546-1726
Titre abrégé: Nat Neurosci
Pays: United States
ID NLM: 9809671
Informations de publication
Date de publication:
22 Feb 2024
22 Feb 2024
Historique:
received:
02
03
2023
accepted:
05
01
2024
medline:
23
2
2024
pubmed:
23
2
2024
entrez:
22
2
2024
Statut:
aheadofprint
Résumé
Frontal circuits play a critical role in motor, cognitive and affective processing, and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)functions remains largely elusive. We studied 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregated the frontal cortex into circuits that had become dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to frontal, ranging from interconnections with sensorimotor cortices in dystonia, the primary motor cortex in Tourette's syndrome, the supplementary motor area in Parkinson's disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairments in the human brain.
Identifiants
pubmed: 38388734
doi: 10.1038/s41593-024-01570-1
pii: 10.1038/s41593-024-01570-1
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Project-ID 424778381 - TRR 295
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Project-ID 424778381 - TRR 295
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Project-ID 424778381 - TRR 295
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Project-ID FI 2309/1-1
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Project-ID FI 2309/2-1
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Project-ID 424778381 - TRR 295
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Project-ID 347325977
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Project-ID 424778381 - TRR 2955
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Project-ID 424778381 - TRR 295
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : Project-ID 431549029-C07 amp;#x2013; SFB 1451
Organisme : Deutsches Zentrum für Luft- und Raumfahrt (German Centre for Air and Space Travel)
ID : DynaSti grant within the EU Joint Programme Neurodegenerative Disease Research, JPND
Organisme : U.S. Department of Health & Human Services | National Institutes of Health (NIH)
ID : R01 13478451
Organisme : U.S. Department of Health & Human Services | National Institutes of Health (NIH)
ID : 2R01 MH113929
Organisme : U.S. Department of Health & Human Services | National Institutes of Health (NIH)
ID : the BRAIN Initiative CONNECTS comprehensive center award UM1-NS132358
Organisme : Einstein Stiftung Berlin (Einstein Foundation Berlin)
ID : PhD Scholarship (Einstein Center for Neurosciences)
Organisme : Einstein Stiftung Berlin (Einstein Foundation Berlin)
ID : PhD Scholarship (Einstein Center for Neurosciences)
Organisme : Einstein Stiftung Berlin (Einstein Foundation Berlin)
ID : PhD Scholarship (Einstein Center for Neurosciences Berlin)
Organisme : Agence Nationale de la Recherche (French National Research Agency)
ID : grant "Infrastructure d'Avenir en Biologie Santé - ANR-11-INBS-0006"
Organisme : Agence Nationale de la Recherche (French National Research Agency)
ID : grant ANR-CE17 "NeurOCD"
Organisme : RCUK | Medical Research Council (MRC)
ID : Grant No. MR/J012009/1
Organisme : RCUK | Medical Research Council (MRC)
ID : Grant No. MR/J012009/1
Informations de copyright
© 2024. The Author(s).
Références
Horn, A. & Fox, M. D. Opportunities of connectomic neuromodulation. Neuroimage 221, 117180 (2020).
pubmed: 32702488
doi: 10.1016/j.neuroimage.2020.117180
Siddiqi, S. H., Kording, K. P., Parvizi, J. & Fox, M. D. Causal mapping of human brain function. Nat. Rev. Neurosci. 23, 361–375 (2022).
Hollunder, B. et al. Toward personalized medicine in connectomic deep brain stimulation. Prog. Neurobiol. 210, 102211 (2022).
pubmed: 34958874
doi: 10.1016/j.pneurobio.2021.102211
Grill, W. M., Snyder, A. N. & Miocinovic, S. Deep brain stimulation creates an informational lesion of the stimulated nucleus. Neuroreport 15, 1137–1140 (2004).
pubmed: 15129161
doi: 10.1097/00001756-200405190-00011
Haber, S. N., Liu, H., Seidlitz, J. & Bullmore, E. Prefrontal connectomics: from anatomy to human imaging. Neuropsychopharmacology 47, 20–40 (2021).
pubmed: 34584210
pmcid: 8617085
doi: 10.1038/s41386-021-01156-6
Haynes, W. I. A. & Haber, S. N. The organization of prefrontal-subthalamic inputs in primates provides an anatomical substrate for both functional specificity and integration: implications for basal ganglia models and deep brain stimulation. J. Neurosci. 33, 4804–4814 (2013).
pubmed: 23486951
pmcid: 3755746
doi: 10.1523/JNEUROSCI.4674-12.2013
Haber, S. N. The primate basal ganglia: parallel and integrative networks. J. Chem. Neuroanat. 26, 317–330 (2003).
pubmed: 14729134
doi: 10.1016/j.jchemneu.2003.10.003
Alexander, G., DeLong, M. R. & Strick, P. L. Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annu. Rev. Neurosci. 9, 357–381 (1986).
pubmed: 3085570
doi: 10.1146/annurev.ne.09.030186.002041
Deffains, M. et al. Subthalamic, not striatal, activity correlates with basal ganglia downstream activity in normal and parkinsonian monkeys. eLife 5, e16443 (2016).
pubmed: 27552049
pmcid: 5030093
doi: 10.7554/eLife.16443
Hardman, C. D. et al. Comparison of the basal ganglia in rats, marmosets, macaques, baboons, and humans: volume and neuronal number for the output, internal relay, and striatal modulating nuclei. J. Comp. Neurol. 445, 238–255 (2002).
pubmed: 11920704
doi: 10.1002/cne.10165
Deuschl, G. et al. A randomized trial of deep-brain stimulation for Parkinson’s disease. N. Engl. J. Med. 355, 896–908 (2006).
pubmed: 16943402
doi: 10.1056/NEJMoa060281
Ostrem, J. L. et al. Subthalamic nucleus deep brain stimulation in primary cervical dystonia. Neurology 76, 870–878 (2011).
pubmed: 21383323
doi: 10.1212/WNL.0b013e31820f2e4f
Lin, S. et al. Deep brain stimulation of the globus pallidus internus versus the subthalamic nucleus in isolated dystonia. J. Neurosurg. 132, 721–732 (2019).
pubmed: 30849756
doi: 10.3171/2018.12.JNS181927
Mallet, L. et al. Subthalamic nucleus stimulation in severe obsessive-compulsive disorder. N. Engl. J. Med. 359, 2121–2134 (2008).
pubmed: 19005196
doi: 10.1056/NEJMoa0708514
Chabardes, S. et al. Deep brain stimulation of the subthalamic nucleus in obsessive-compulsives disorders: long-term follow-up of an open, prospective, observational cohort. J. Neurol. Neurosurg. Psychiatry 91, 1349–1356 (2020).
pubmed: 33033168
doi: 10.1136/jnnp-2020-323421
Dai, L. et al. Subthalamic deep brain stimulation for refractory Gilles de la Tourette’s syndrome: clinical outcome and functional connectivity. J. Neurol. 269, 6116–6126 (2022).
pubmed: 35861855
pmcid: 9553760
doi: 10.1007/s00415-022-11266-w
Vissani, M. et al. Spatio-temporal structure of single neuron subthalamic activity identifies DBS target for anesthetized Tourette syndrome patients. J. Neural Eng. 16, 066011 (2019).
pubmed: 31370042
doi: 10.1088/1741-2552/ab37b4
Horn, A. et al. Optimal deep brain stimulation sites and networks for cervical vs. generalized dystonia. Proc. Natl Acad. Sci. USA 119, e2114985119 (2022).
pubmed: 35357970
pmcid: 9168456
doi: 10.1073/pnas.2114985119
Irmen, F. et al. Left prefrontal connectivity links subthalamic stimulation with depressive symptoms. Ann. Neurol. 87, 962–975 (2020).
pubmed: 32239535
doi: 10.1002/ana.25734
Baldermann, J. C. et al. Connectomic deep brain stimulation for obsessive-compulsive disorder. Biol. Psychiatry 90, 678–688 (2021).
pubmed: 34482949
doi: 10.1016/j.biopsych.2021.07.010
Li, N. et al. A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder. Nat. Commun. 11, 3364 (2020).
pubmed: 32620886
pmcid: 7335093
doi: 10.1038/s41467-020-16734-3
Van Essen, D. C. et al. The WU-Minn Human Connectome Project: an overview. Neuroimage 80, 62–79 (2013).
pubmed: 23684880
doi: 10.1016/j.neuroimage.2013.05.041
Wang, F. et al. In vivo human whole-brain Connectom diffusion MRI dataset at 760 µm isotropic resolution. Sci. Data 8, 122 (2021).
pubmed: 33927203
pmcid: 8084962
doi: 10.1038/s41597-021-00904-z
Maier-Hein, K. H. et al. The challenge of mapping the human connectome based on diffusion tractography. Nat. Commun. 8, 1349 (2017).
pubmed: 29116093
pmcid: 5677006
doi: 10.1038/s41467-017-01285-x
Noecker, A. M. et al. StimVision v2: examples and applications in subthalamic deep brain stimulation for Parkinson’s disease. Neuromodulation 24, 248–258 (2021).
pubmed: 33389779
pmcid: 8581744
doi: 10.1111/ner.13350
Petersen, M. V. et al. Holographic reconstruction of axonal pathways in the human brain. Neuron 104, 1056–1064 (2019).
pubmed: 31708306
pmcid: 6948195
doi: 10.1016/j.neuron.2019.09.030
Middlebrooks, E. H. et al. Neuroimaging advances in deep brain stimulation: review of indications, anatomy, and brain connectomics. Am. J. Neuroradiol. 41, 1558–1568 (2020).
pubmed: 32816768
pmcid: 7583111
doi: 10.3174/ajnr.A6693
Ewert, S. et al. Toward defining deep brain stimulation targets in MNI space: a subcortical atlas based on multimodal MRI, histology and structural connectivity. Neuroimage 170, 271–282 (2018).
pubmed: 28536045
doi: 10.1016/j.neuroimage.2017.05.015
Rodriguez-Oroz, M. C. et al. Initial clinical manifestations of Parkinson’s disease: features and pathophysiological mechanisms. Lancet Neurol. 8, 1128–1139 (2009).
pubmed: 19909911
doi: 10.1016/S1474-4422(09)70293-5
Horn, A. et al. Teaching NeuroImages: in vivo visualization of Edinger comb and Wilson pencils. Neurology 92, e1663–e1664 (2019).
pubmed: 30936236
pmcid: 6448452
doi: 10.1212/WNL.0000000000007252
Penfield, W. & Perot, P. The brain’s record of auditory and visual experience: a final summary and discussion. Brain 86, 595–696 (1963).
pubmed: 14090522
doi: 10.1093/brain/86.4.595
Albin, R. L., Young, A. B. & Penney, J. B. The functional anatomy of basal ganglia disorders. Trends Neurosci. 12, 366–375 (1989).
pubmed: 2479133
doi: 10.1016/0166-2236(89)90074-X
DeLong, M. R. Primate models of movement disorders of basal ganglia origin. Trends Neurosci. 13, 281–285 (1990).
pubmed: 1695404
doi: 10.1016/0166-2236(90)90110-V
Alexander, G. E. & Crutcher, M. D. Functional architecture of basal ganglia circuits: neural sustrates of parallel processing. Trends Neurosci. 13, 266–271 (1990).
pubmed: 1695401
doi: 10.1016/0166-2236(90)90107-L
Percheron, G. & Filion, M. Parallel processing in the basal ganglia: up to a point. Trends Neurosci. 14, 55–56 (1991).
pubmed: 1708537
doi: 10.1016/0166-2236(91)90020-U
Nambu, A., Tokuno, H. & Takada, M. Functional significance of the cortico-subthalamo-pallidal ‘hyperdirect’ pathway. Neurosci. Res. 43, 111–117 (2002).
pubmed: 12067746
doi: 10.1016/S0168-0102(02)00027-5
Corp, D. T. et al. Network localization of cervical dystonia based on causal brain lesions. Brain 142, 1660–1674 (2019).
pubmed: 31099831
pmcid: 6536848
doi: 10.1093/brain/awz112
Inoue, K. et al. Disinhibition of the somatosensory cortex in cervical dystonia—decreased amplitudes of high-frequency oscillations. Clin. Neurophysiol. 115, 1624–1630 (2004).
pubmed: 15203063
doi: 10.1016/j.clinph.2004.02.006
Prudente, C. N., Hess, E. J. & Jinnah, H. A. Dystonia as a network disorder: what is the role of the cerebellum? Neuroscience 260, 23–35 (2014).
pubmed: 24333801
doi: 10.1016/j.neuroscience.2013.11.062
Neychev, V. K., Fan, X., Mitev, V. I., Hess, E. J. & Jinnah, H. A. The basal ganglia and cerebellum interact in the expression of dystonic movement. Brain 131, 2499–2509 (2008).
pubmed: 18669484
pmcid: 2724906
doi: 10.1093/brain/awn168
Havrankova, P. et al. Repetitive TMS of the somatosensory cortex improves writer’s cramp and enhances cortical activity. Neuroendocrinol. Lett. 31, 73–86 (2010).
pubmed: 20150883
Bradnam, L. V., McDonnell, M. N. & Ridding, M. C. Cerebellar intermittent theta-burst stimulation and motor control training in individuals with cervical dystonia. Brain Sci. 6, 56 (2016).
pubmed: 27886079
pmcid: 5187570
doi: 10.3390/brainsci6040056
Desrochers, P., Brunfeldt, A., Sidiropoulos, C. & Kagerer, F. Sensorimotor control in dystonia. Brain Sci. 9, 79 (2019).
pubmed: 30979073
pmcid: 6523253
doi: 10.3390/brainsci9040079
Hassler, R., Riechert, T., Mundinger, F., Umbach, W. & Ganglberger, J. A. Physiological observations in stereotaxic operations in extrapyramidal motor dysturbances. Brain 83, 337–350 (1960).
pubmed: 13852002
doi: 10.1093/brain/83.2.337
Horn, A. et al. Connectivity predicts deep brain stimulation outcome in Parkinson’s disease. Ann. Neurol. 82, 67–78 (2017).
pubmed: 28586141
pmcid: 5880678
doi: 10.1002/ana.24974
Vanegas-Arroyave, N. et al. Tractography patterns of subthalamic nucleus deep brain stimulation. Brain 139, 1200–1210 (2016).
pubmed: 26921616
pmcid: 5006230
doi: 10.1093/brain/aww020
Shirota, Y. et al. Supplementary motor area stimulation for Parkinson disease: a randomized controlled study. Neurology 80, 1400–1405 (2013).
pubmed: 23516319
doi: 10.1212/WNL.0b013e31828c2f66
Nachev, P., Kennard, C. & Husain, M. Functional role of the supplementary and pre-supplementary motor areas. Nat. Rev. Neurosci. 9, 856–869 (2008).
pubmed: 18843271
doi: 10.1038/nrn2478
Li, N. et al. A unified functional network target for deep brain stimulation in obsessive-compulsive disorder. Biol. Psychiatry 90, 701–713 (2021).
pubmed: 34134839
doi: 10.1016/j.biopsych.2021.04.006
Carmi, L. et al. Efficacy and safety of deep transcranial magnetic stimulation for obsessive-compulsive disorder: A prospective multicenter randomized double-blind placebo-controlled trial. Am. J. Psychiatry 176, 931–938 (2019).
pubmed: 31109199
doi: 10.1176/appi.ajp.2019.18101180
Franzkowiak, S. et al. Motor-cortical interaction in Gilles de la Tourette syndrome. PLoS ONE 7, e27850 (2012).
pubmed: 22238571
pmcid: 3251574
doi: 10.1371/journal.pone.0027850
Worbe, Y. et al. Altered structural connectivity of cortico-striato-pallido-thalamic networks in Gilles de la Tourette syndrome. Brain 138, 472–482 (2015).
pubmed: 25392196
doi: 10.1093/brain/awu311
Andrade, P. et al. Modulation of fibers to motor cortex during thalamic DBS in Tourette patients correlates with tic reduction. Brain Sci. 10, 302 (2020).
pubmed: 32429216
pmcid: 7287978
doi: 10.3390/brainsci10050302
Ganos, C. et al. A neural network for tics: insights from causal brain lesions and deep brain stimulation. Brain 145, 4385–4397 (2022).
Johnson, K. A. et al. Structural connectivity predicts clinical outcomes of deep brain stimulation for Tourette syndrome. Brain 143, 2607–2623 (2020).
pubmed: 32653920
pmcid: 7447520
doi: 10.1093/brain/awaa188
Kleimaker, M. et al. Non-invasive brain stimulation for the treatment of Gilles de la Tourette syndrome. Front. Neurol. 11, 592258 (2020).
pubmed: 33244309
pmcid: 7683779
doi: 10.3389/fneur.2020.592258
Martino, D., Ganos, C. & Worbe, Y. Neuroimaging applications in Tourette’s syndrome. Int. Rev. Neurobiol. 143, 65–108 (2018).
pubmed: 30473198
doi: 10.1016/bs.irn.2018.09.008
Ashkan, K., Rogers, P., Bergman, H. & Ughratdar, I. Insights into the mechanisms of deep brain stimulation. Nat. Rev. Neurol. 13, 548–554 (2017).
pubmed: 28752857
doi: 10.1038/nrneurol.2017.105
Neudorfer, C. et al. Kilohertz-frequency stimulation of the nervous system: a review of underlying mechanisms. Brain Stimul. 14, 513–530 (2021).
pubmed: 33757930
doi: 10.1016/j.brs.2021.03.008
Horn, A. et al. Lead-DBS v2: towards a comprehensive pipeline for deep brain stimulation imaging. Neuroimage 184, 293–316 (2019).
pubmed: 30179717
doi: 10.1016/j.neuroimage.2018.08.068
Husch, A. et al. PaCER—a fully automated method for electrode trajectory and contact reconstruction in deep brain stimulation. Neuroimage Clin. 17, 80–89 (2018).
pubmed: 29062684
doi: 10.1016/j.nicl.2017.10.004
Ewert, S. et al. Optimization and comparative evaluation of nonlinear deformation algorithms for atlas-based segmentation of DBS target nuclei. Neuroimage 184, 586–598 (2019).
pubmed: 30267856
doi: 10.1016/j.neuroimage.2018.09.061
Vogel, D. et al. Anatomical brain structures normalization for deep brain stimulation in movement disorders. Neuroimage Clin. 27, 102271 (2020).
pubmed: 32446242
pmcid: 7240191
doi: 10.1016/j.nicl.2020.102271
Oxenford, S. et al. WarpDrive: improving spatial normalization using manual refinements. Med. Image Anal. 91, 103041 (2024).
pubmed: 38007978
doi: 10.1016/j.media.2023.103041
Baldermann, J. C. et al. Connectivity profile predictive of effective deep brain stimulation in obsessive-compulsive disorder. Biol. Psychiatry 85, 735–743 (2019).
pubmed: 30777287
doi: 10.1016/j.biopsych.2018.12.019
Amunts, K. et al. BigBrain: an ultrahigh-resolution 3D human brain model. Science 340, 1472–1475 (2013).
pubmed: 23788795
doi: 10.1126/science.1235381
Edlow, B. L. et al. 7 Tesla MRI of the ex vivo human brain at 100 micron resolution. Sci. Data 6, 244 (2019).
pubmed: 31666530
pmcid: 6821740
doi: 10.1038/s41597-019-0254-8
Faria, A. V. et al. Atlas-based analysis of resting-state functional connectivity: evaluation for reproducibility and multi-modal anatomy-function correlation studies. Neuroimage 61, 613–621 (2012).
pubmed: 22498656
doi: 10.1016/j.neuroimage.2012.03.078
Pauli, W. M., Nili, A. N. & Tyszka, J. M. A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei. Sci. Data 5, 180063 (2018).
pubmed: 29664465
pmcid: 5903366
doi: 10.1038/sdata.2018.63
Treu, S. et al. Deep brain stimulation: imaging on a group level. Neuroimage 219, 117018 (2020).
pubmed: 32505698
doi: 10.1016/j.neuroimage.2020.117018
Faul, F., Erdfelder, E., Buchner, A. & Lang, A.-G. Statistical power analyses using G*Power 3. 1: tests for correlation and regression analyses. Behav. Genet. 41, 1149–1160 (2009).
Faul, F., Erdfelder, E., Lang, A.-G. & Buchner, A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods 39, 175–191 (2007).
Tyagi, H. et al. A randomized trial directly comparing ventral capsule and anteromedial subthalamic nucleus stimulation in obsessive-compulsive disorder: clinical and imaging evidence for dissociable effects. Biol. Psychiatry 85, 726–734 (2019).
pubmed: 30853111
pmcid: 6467837
doi: 10.1016/j.biopsych.2019.01.017
Neudorfer, C. et al. Lead-DBS v3.0: mapping deep brain stimulation effects to local anatomy and global networks. Neuroimage 268, 119862 (2023).
pubmed: 36610682
doi: 10.1016/j.neuroimage.2023.119862
Avants, B. B., Epstein, C. L., Grossman, M. & Gee, J. C. Symmetric diffeomorphic image registration with cross- correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med. Image Anal. 12, 26–41 (2008).
pubmed: 17659998
doi: 10.1016/j.media.2007.06.004
Fonov, V. et al. Unbiased average age-appropriate atlases for pediatric studies. Neuroimage 54, 313–327 (2011).
pubmed: 20656036
doi: 10.1016/j.neuroimage.2010.07.033
Neudorfer, C. et al. Personalizing deep brain stimulation using advanced imaging sequences. Ann. Neurol. 91, 613–628 (2022).
pubmed: 35165921
doi: 10.1002/ana.26326
Horn, A. & Kühn, A. A. Lead-DBS: a toolbox for deep brain stimulation electrode localizations and visualizations. Neuroimage 107, 127–135 (2015).
pubmed: 25498389
doi: 10.1016/j.neuroimage.2014.12.002
Vorwerk, J., Oostenveld, R., Piastra, M. C., Magyari, L. & Wolters, C. H. The FieldTrip-SimBio pipeline for EEG forward solutions. Biomed. Eng. Online 17, 37 (2018).
pubmed: 29580236
pmcid: 5870695
doi: 10.1186/s12938-018-0463-y
Åström, M., Diczfalusy, E., Martens, H. & Wårdell, K. Relationship between neural activation and electric field distribution during deep brain stimulation. IEEE Trans. Biomed. Eng. 62, 664–672 (2015).
pubmed: 25350910
doi: 10.1109/TBME.2014.2363494
Vasques, X. et al. Stereotactic model of the electrical distribution within the internal globus pallidus during deep brain stimulation. J. Comput. Neurosci. 26, 109–118 (2009).
pubmed: 18553218
doi: 10.1007/s10827-008-0101-y
Horn, A. et al. Deep brain stimulation induced normalization of the human functional connectome in Parkinson’s disease. Brain 142, 3129–3143 (2019).
pubmed: 31412106
doi: 10.1093/brain/awz239
Jakab, A. et al. Feasibility of diffusion tractography for the reconstruction of intra-thalamic and cerebello-thalamic targets for functional neurosurgery: a multi-vendor pilot study in four subjects. Front. Neuroanat. 10, 76 (2016).
pubmed: 27462207
pmcid: 4940380
doi: 10.3389/fnana.2016.00076
Petersen, M. V. et al. Probabilistic versus deterministic tractography for delineation of the cortico-subthalamic hyperdirect pathway in patients with Parkinson disease selected for deep brain stimulation. J. Neurosurg. 126, 1657–1668 (2017).
pubmed: 27392264
doi: 10.3171/2016.4.JNS1624
Yeh, F.-C. et al. Quantifying differences and similarities in whole-brain white matter architecture using local connectome fingerprints. PLoS Comput. Biol. 12, e1005203 (2016).
pubmed: 27846212
pmcid: 5112901
doi: 10.1371/journal.pcbi.1005203
Pijnenburg, R. et al. Myelo- and cytoarchitectonic microstructural and functional human cortical atlases reconstructed in common MRI space. Neuroimage 239, 118274 (2021).
pubmed: 34146709
doi: 10.1016/j.neuroimage.2021.118274
Yeh, F. C. et al. Automatic removal of false connections in diffusion MRI tractography using topology-informed pruning (TIP). Neurotherapeutics 16, 52–58 (2019).
pubmed: 30218214
doi: 10.1007/s13311-018-0663-y
Riva-Posse, P. et al. A connectomic approach for subcallosal cingulate deep brain stimulation surgery: prospective targeting in treatment-resistant depression. Mol. Psychiatry 23, 843–849 (2018).
pubmed: 28397839
doi: 10.1038/mp.2017.59
Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W. & Smith, S. M. FSL. Neuroimage 62, 782–790 (2012).
pubmed: 21979382
doi: 10.1016/j.neuroimage.2011.09.015
Yeh, F. C., Wedeen, V. J. & Tseng, W. Y. I. Generalized q-sampling imaging. IEEE Trans. Med. Imaging 29, 1626–1635 (2010).
pubmed: 20304721
doi: 10.1109/TMI.2010.2045126
Marek, K. et al. The Parkinson Progression Marker Initiative (PPMI). Prog. Neurobiol. 95, 629–635 (2011).
pmcid: 9014725
doi: 10.1016/j.pneurobio.2011.09.005
Ashburner, J. A fast diffeomorphic image registration algorithm. Neuroimage 38, 95–113 (2007).
pubmed: 17761438
doi: 10.1016/j.neuroimage.2007.07.007
Horn, A., Ostwald, D., Reisert, M. & Blankenburg, F. The structural–functional connectome and the default mode network of the human brain. Neuroimage 102, 142–151 (2014).
pubmed: 24099851
doi: 10.1016/j.neuroimage.2013.09.069
Horn, A. & Blankenburg, F. Toward a standardized structural–functional group connectome in MNI space. Neuroimage 124, 310–322 (2016).
pubmed: 26327244
doi: 10.1016/j.neuroimage.2015.08.048
Li, N., Hollunder, B., & Horn, A. DBS dysfunctional circuits Open Science Framework https://doi.org/10.1038/s41593-024-01570-1 (2024).