Evidence map›Paper›PMID 41674633›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Distinct Spectral and Directional Thalamocortical Network Dynamics Define Focal Seizure Evolution.

Saarang Panchavati, Atsuro Daida, Sotaro Kanai, Shingo Oana, Hiroya Ono, Masaki Izumi, Kikuko Kaneko, Aria Fallah, Joe X Qiao, Noriko Salamon and 4 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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

14 authors.

Saarang PanchavatiDepartment of Medical Informatics, University of California, Los Angeles, CA, USA.ORCID 0000-0003-1658-0364
Atsuro DaidaDivision of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, USA.ORCID 0000-0003-1350-7700
Sotaro KanaiDivision of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, USA.ORCID 0000-0002-7320-2346
Shingo OanaDivision of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, USA.ORCID 0009-0003-0862-3149
Hiroya OnoDivision of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, USA.ORCID 0000-0002-8439-5657
Masaki IzumiDivision of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, USA.ORCID 0000-0003-2961-6733
Kikuko KanekoDepartment of Radiology, UCLA Medical Center, David Geffen School of Medicine, Los Angeles, CA, USA.
Aria FallahDepartment of Neurosurgery, UCLA Medical Center, David Geffen School of Medicine, Los Angeles, CA, USA.ORCID 0000-0002-9703-0964
Joe X QiaoDepartment of Radiology, UCLA Medical Center, David Geffen School of Medicine, Los Angeles, CA, USA.
Noriko SalamonDepartment of Radiology, UCLA Medical Center, David Geffen School of Medicine, Los Angeles, CA, USA.ORCID 0000-0002-3520-9467
Raman SankarDivision of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, USA.ORCID 0000-0002-5609-0362
Corey ArnoldDepartment of Medical Informatics, University of California, Los Angeles, CA, USA.ORCID 0000-0002-4119-8143
William SpeierDepartment of Medical Informatics, University of California, Los Angeles, CA, USA.ORCID 0000-0002-0890-8684
Hiroki NariaiDivision of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, USA.ORCID 0000-0002-8318-2924

Funding

Refining neurophysiological biomarkers of epilepsy using deep learning to guide pediatric epilepsy surgeryK23NS128318 · NINDS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Hiroki Nariai · 2023 to 2026
$968k
NINDS NIH HHS K23 NS128318
6 · The paper itself

Abstract

Neuromodulation targeting thalamic nuclei is increasingly used to treat drug-resistant focal epilepsy, yet human intracranial EEG studies describing how thalamocortical interactions evolve across seizures remain limited. We aimed to define frequency-specific thalamocortical network dynamics from seizure onset to termination, compare thalamocortical and cortico-cortical network activation, and test whether thalamic EEG features can classify seizure state to inform closed-loop or adaptive thalamic stimulation strategies. We retrospectively analyzed chronic stereo-EEG recordings from 19 patients with pediatric-onset, drug-resistant focal epilepsy (6 females; age at thalamic recording 1.0-28.1 years, median 16.9) with cortical and thalamic sampling. Sixty-six focal seizures were included. Spectral power, imaginary coherence, and spectral Granger causality were computed in non-overlapping two-second windows across slow (1-12 Hz), beta (13-30 Hz), and gamma (30-70 Hz) bands and compared with an interictal baseline. Random forest classifiers were trained using thalamic spectral power and thalamocortical connectivity features to distinguish ictal from non-ictal states using leave-one-patient-out cross-validation, with Shapley additive explanations used for feature attribution. Visual analysis identified thalamic ictal involvement at seizure onset in 82/101 thalamic contacts (81.2%), increasing to near-universal involvement by seizure termination, with onset-to-termination patterns dominated by low-voltage fast activity at onset and rhythmic spike or rhythmic slow-wave patterns at termination. The thalamus and cortical seizure onset zone exhibited broadband power increases at seizure onset that attenuated toward termination, while slow- and beta-band thalamocortical connectivity increased throughout seizures and peaked around the end-of-seizure epoch. Directed connectivity demonstrated bidirectional thalamocortical coupling, with slow-frequency thalamus-to-seizure onset zone outflow exceeding propagation-zone-to-seizure onset zone cortico-cortical outflow during both ictal and end-of-seizure epochs (anterior nucleus: p = 9.06 × 10

Indexed as

corticothalamic networkdirected connectivitymachine learningnetwork biomarkerssystems neuroscience

Identifiers

PMID41674633
PMCPMC12889767

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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 Socratic graph.