This dataset was utilized for the publication of the manuscript by Zhang et al. [1]. A subset of the data has been employed in [2], [3], [4], and [5].

Summary:
This data set comprises the de-identified subjects with interictal iEEG recordings with sleep from University of California Los Angels Mattel Children’s Hospital, and Children’s Hospital of Michigan, Detroit. 
Subject-wise information is contained in each folder, including iEEGs collected from 185 subjects during sleep. The channel name and valuables, such as the anatomical label and the resection status, are attached to each folder. The outcome and background information of all the subjects are summarized in ‘paticipant.tsv’ located in the parental directory.

Derivatives
The processed data for HFO detection and classification are shown in the derivatives/folder. The HFO analysis contains detection from two methods: RMS and MNI detectors. The bipolar iEEG data used for [5] is also uploaded, and the credit for creating such dataset is given to the authors of the manuscript. 

References: 

[1] Zhang Y, Daida A, Liu L, Kuroda N, Ding Y, Oana S, Kanai S, Monsoor T, Duan C, Hussain SA, Qiao JX, Salamon N, Fallah A, Sim MS, Sankar R, Staba RJ, Engel J Jr, Asano E, Roychowdhury V, Nariai H. Self-supervised data-driven approach defines pathological high-frequency oscillations in epilepsy. Epilepsia. 2025 Nov;66(11):4434-4450. doi: 10.1111/epi.18545.

[2] Monsoor T, Kanai S, Daida A, Kuroda N, Sinha P, Oana S, Zhang Y, Liu L, Singh G, Duan C, Sim MS, Fallah A, Speier W, Asano E, Roychowdhury V, Nariai H. Mini-Seizures: Novel Interictal iEEG Biomarker Capturing Synchronization Network Dynamics at the Epileptogenic Zone. medRxiv. 2025 Feb 2:2025.01.31.25321482. doi: 10.1101/2025.01.31.25321482.

[3] Zhang Y, Lu Q, Monsoor T, Hussain SA, Qiao JX, Salamon N, Fallah A, Sim MS, Asano E, Sankar R, Staba RJ, Engel J Jr, Speier W, Roychowdhury V, Nariai H. Refining epileptogenic high-frequency oscillations using deep learning: a reverse engineering approach. Brain Commun. 2021 Nov 3;4(1):fcab267. doi: 10.1093/braincomms/fcab267. 

[4] Kuroda N, Sonoda M, Miyakoshi M, Nariai H, Jeong JW, Motoi H, Luat AF, Sood S, Asano E. Objective interictal electrophysiology biomarkers optimize prediction of epilepsy surgery outcome. Brain Commun. 2021 Mar 14;3(2):fcab042. doi: 10.1093/braincomms/fcab042.

[5]  Blanca Romero Milà, Nathan Phi Hoang, Marco Pinto-Orellana, Atsuro Daida, Sotaro Kanai, Naoto Kuroda, Shaun A. Hussain, Daniel W. Shrey, Eishi Asano, Hiroki Nariai, Beth A. Lopour. Discovering Novel intracranial EEG Biomarkers of Seizure Generating Tissue through Time-Frequency Analysis. medRxiv. doi: https://doi.org/10.64898/2026.06.12.26355482. Posted June 22, 2026.