Evidence map›Paper›PMID 41726571›Full record

ArticleEpilepsy currents2026

Pathway to Adaptive Neuromodulation: Modeling Epileptogenic Brain States Using SEEG.

Ghassan S Makhoul, Graham W Johnson, Anas Reda, Bruno Hidalgo Monroy Lerma, Joline M Fan, Gregory A Worrell, Dario J Englot

Abstract read
In one paragraph

Article in Epilepsy currents, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Ghassan S MakhoulDepartment of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.ORCID https://orcid.org/0009-0002-9281-541X
Graham W JohnsonDepartment of Neurologic Surgery, Mayo Clinic, Rochester, MN, USA.
Anas RedaDepartment of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.ORCID https://orcid.org/0009-0009-9782-2505
Bruno Hidalgo Monroy LermaDepartment of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.ORCID https://orcid.org/0009-0000-7307-4762
Joline M FanDepartment of Neurology, UCSF Weill Institute for Neurosciences, San Francisco, CA, USA.ORCID https://orcid.org/0000-0003-1099-8479
Gregory A WorrellDepartment of Neurology, Mayo Clinic, Rochester, MN, USA.
Dario J EnglotDepartment of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.ORCID https://orcid.org/0000-0001-8373-690X

Funding

Leveraging the Interictal Suppression Hypothesis to Define Epileptic NetworksF31NS141612 · NINDS · VANDERBILT UNIVERSITY · PI Ghassan Sebastian Peter Makhoul · 2025 to 2026
$110k
NINDS NIH HHS F31 NS141612
6 · The paper itself

Abstract

Neuromodulation is becoming a common treatment strategy for patients with drug-resistant epilepsy who are not candidates for resective surgery. Responsive neurostimulation can effectively reduce seizure burden, however it remains unclear which neural signals are most important for triggered stimulation. Furthermore, the high-dimensional parameter space remains systematically underexamined. As more patients become candidates for neurostimulation, clinical teams will need to decide on the optimal site and stimulation program for therapeutic neuromodulation. In this review, we highlight how recent insight into the biological rhythms of epilepsy may pair with personalization protocols in the emerging field of neuropsychiatric neuromodulation. Finally, we discuss future directions for epilepsy neuromodulation, specifically how machine learning can offer clinical teams actionable feedback on neuromodulation efficacy.

Indexed as

clinical translationelectrophysiologyepilepsymachine learningneuromodulation

Identifiers

PMID41726571
PMCPMC12920160

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.