Gamma-Tetha Local Field Potentials as Biomarkers in Treatment Resistant Depression on Bilateral Subgenual Corpus Callosum Deep Brain Stimulation. Integrated Behavioral, Neurophysiological and Clinical Effects
Notice bibliographique
Résumé
Introduction: Treatment-resistant depression (TRD) remains a significant therapeutic challenge globally. Although (DBS) has been an option for treatment, some suggests that a personalized approach base on main symptomatology and individual biomarkers, may yield more efficacious outcomes. Since 2013, our center at Rionegro San Vicente Fundacion Hospital Colombia, South America, has implemented a multidisciplinary neurofunctional program and performed bilateral subcallosal cingulate DBS (SCC-DBS) in 7 patients. Recently, 3 of these patients underwent device replacement with the PerceptTM RC neurostimulator Brain SenseTM technology, enabling advanced local field potential (LFP) recordings and behavioral and neurophysiological assessments. This study focuses on these 3 patients, each representing a distinct depressive phenotype: hypersensitive, stable, and anhedonic. We conducted comprehensive evaluations integrating emotional perception tasks, local field potential recordings, and longitudinal clinical profiling to elucidate the mechanisms and effects of SCC-DBS.Method: EMOTIONAL PERCEPTION TASK Patients viewed 10 standardized images 5 happy 5 sad in randomized order during two conditions stimON Chronic therapeutic stimulation and stim-OFF: 1 hour washout period. For each image, patients provided: Happiness rating 1 very sad to 10 very happy semantic association single-word descriptor and response latency measurement.Results: Behaviorally, SCC-DBS significantly enhanced positive image perception +9.5% and reduced negative bias −28% with a 34% improvement in emotional discrimination capacity. Neurophysiologically, stimulation led to increased gamma oscillations up to +175% suppressed theta activity up to −41.9% strongly correlated with affective improvements r = 0.76 and r = 0.71 respectively). Clinically 49.3% overall improvement in QofL with phenotype specific responses beta/gamma ratio was most effective in the hypersensitive patient theta-alpha phase-amplitude coupling relevant in the stable phenotype and high gamma power was a key biomarker in the anhedonic patient.Discussion: Our observations suggest that deep brain stimulation (DBS) of the (SCC) achieves therapeutic effects through frequency-specific, dissociable mechanisms. Gamma oscillations may facilitate long-term synchronization between the SCC and the nucleus accumbens, enabling positive valence encoding. Pathological theta hyperactivity during StimOFF states may reflect limbic-cortical dysrhythmia, consistent with the Broadway model of depressive hyperarousal. Theta suppression correlated with reduced connectivity between the amygdala and SCC may suggest normalized threat processing. All of this could have clinical application when programming real life patients, but more cases and scenarios are required for applicability across all individuals.Conclusions: We can suggest that SCC DBS may modulates affective circuits through frequency specific mechanisms gamma enhancement may facilitates positive affect and reward processing, while theta suppression may mitigates negative cognitive bias. The therapeutic response varies by depression phenotype, supporting a personalized neuromodulation approach guided by electrophysiological biomarkers. The use of Percept RC technology may enable real-time monitoring and biomarker identification. This optimized programming framework may have the potential to improve clinical outcomes in TRD and maybe establish SCC DBS as a targeted, phenotype-driven therapy.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».