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Record W4392032200 · doi:10.1038/s41593-024-01570-1

Mapping dysfunctional circuits in the frontal cortex using deep brain stimulation

2024· article· en· W4392032200 on OpenAlexaff
Barbara Hollunder, Jill L. Ostrem, Ilkem Aysu Sahin, Nanditha Rajamani, Simón Oxenford, Konstantin Butenko, Clemens Neudorfer, Pablo Reinhardt, Patricia Zvarova, Mircea Polosan, Harith Akram, Matteo Vissani, Chencheng Zhang, Bomin Sun, P Navrátil, Martin M. Reich, Jens Volkmann, Fang‐Cheng Yeh, Juan Carlos Baldermann, Till A. Dembek, Veerle Visser‐Vandewalle, Eduardo Joaquim Lopes Alho, Paulo Roberto Franceschini, Pranav Nanda, Carsten Finke, Andrea A. Kühn, Darin D. Dougherty, R. Mark Richardson, Hagai Bergman, Mahlon R. DeLong, Alberto Mazzoni, Luigi Romito, Himanshu Tyagi, Ludvic Zrinzo, Eileen M. Joyce, Stéphan Chabardès, Philip A. Starr, Ningfei Li, Andreas Horn

Bibliographic record

VenueNature Neuroscience · 2024
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsCentre for Movement Disorders
FundersMinistero della SaluteNational Institute of Mental HealthMedical Research CouncilNational Institutes of HealthBerlin Institute of HealthUniversity College London Hospitals NHS Foundation TrustNational Institute of Neurological Disorders and StrokeScuola Superiore Sant'AnnaNational Institute for Health and Care ResearchElse Kröner-Fresenius-StiftungAgence Nationale de la RechercheDeutsche Forschungsgemeinschaft
KeywordsNeuroscienceDeep brain stimulationPsychologyConnectomicsDysfunctional familyBrain stimulationPrefrontal cortexAnterior cingulate cortexMotor cortexBiological neural networkCingulate cortexStimulationCognitionFunctional connectivityCentral nervous systemConnectomeParkinson's diseaseMedicineDiseasePsychiatry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score0.216

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.309
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations162
Published2024
Admission routes1
Has abstractyes

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