Slow Gamma Suppression Correlates with Therapeutic Response to Anterior Thalamic Deep Brain Stimulation in Intractable Epilepsy

preprint OA: closed
📄 Open PDF Full text JSON View at publisher
AI-generated summary by claude@2026-07, 2026-07-15

Slow gamma oscillation suppression in the anterior thalamus correlates with therapeutic response in patients undergoing deep brain stimulation for intractable epilepsy.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

AI-generated deep summary by claude@2026-07, 2026-07-15 · read from full text

The study investigated drug-resistant epilepsy patients undergoing anterior thalamic deep brain stimulation (ANT-DBS) and aimed to identify real-time electrophysiological biomarkers to guide stimulation parameter selection in a prospective optimization trial (N=11). Researchers analyzed acute and chronic suppression of slow gamma oscillations (SGOs, 20–50 Hz) recorded in the ANT and found that 6/7 participants with SGOs were responders, with progressive “gamma fade” during chronic stimulation correlating with long-term seizure reduction in 5/6 responders, and acute in-clinic multi-setting testing suppressing SGOs in 4/5 responders. A major caveat was the small sample size, which limits confidence in broader generalization, and the finding that only one responder used the clinical gold standard parameters at last follow-up challenges fixed-program paradigms. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

In drug-resistant epilepsy patients who undergo anterior thalamic deep brain stimulation (ANT-DBS), efficacy is assessed months after therapy initiation and clinicians have no guidance when choosing stimulation parameters due to the lack of real-time biomarkers. Here, we identified acute and chronic suppression of slow gamma oscillations (SGOs) (20–50Hz) in the ANT as a novel electrophysiological biomarker correlated with therapeutic response. Through analysis of an ongoing prospective ANT-DBS parameter optimization trial (N=11), 6/7 participants exhibiting SGOs were responders. Progressive suppression (“gamma fade”) of SGOs under chronic stimulation correlated with long-term seizure reduction in 5/6 responders. Acute stimulation in-clinic with multiple settings suppressed SGOs in 4/5 responders, challenging fixed-programming paradigms, with only one responder using the clinical gold standard parameters at the last follow-up visit. These findings establish SGO suppression as a potential multiscale biomarker for responder identification, parameter titration, and therapeutic tracking for precise, biomarker-guided intervention.
Full text 3,210 characters · extracted from oa-doi-fallback · click to expand
Abstract In drug-resistant epilepsy patients who undergo anterior thalamic deep brain stimulation (ANT-DBS), efficacy is assessed months after therapy initiation and clinicians have no guidance when choosing stimulation parameters due to the lack of real-time biomarkers. Here, we identified acute and chronic suppression of slow gamma oscillations (SGOs) (20–50Hz) in the ANT as a novel electrophysiological biomarker correlated with therapeutic response. Through analysis of an ongoing prospective ANT-DBS parameter optimization trial (N=11), 6/7 participants exhibiting SGOs were responders. Progressive suppression (“gamma fade”) of SGOs under chronic stimulation correlated with long-term seizure reduction in 5/6 responders. Acute stimulation in-clinic with multiple settings suppressed SGOs in 4/5 responders, challenging fixed-programming paradigms, with only one responder using the clinical gold standard parameters at the last follow-up visit. These findings establish SGO suppression as a potential multiscale biomarker for responder identification, parameter titration, and therapeutic tracking for precise, biomarker-guided intervention. Competing Interest Statement Zachary Sanger was a part time graduate student intern at Medtronic during a portion of time while conducting this work. The internship work was not related to any research shown here and his time conducting this work was supported through the project's funding. Clinical Trial NCT05493722 Funding Statement This work has been supported by the National Institute of Neurological Disorders and Stroke (U01NS124616). Zachary Sanger is a 2024–2025 MnDrive Brain Conditions Fellow and his time conducting research reported in this publication was supported by the University of Minnesota′s MnDRIVE (Minnesota′s Discovery, Research and Innovation Economy) initiative. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee/IRB of the University of Minnesota gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00