Published December 23, 2025 | Version First version
Dataset Embargoed

ASEEG: Atieh Schizophrenia EEG, a novel high-quality dataset designed to advance biomarker research

Authors/Creators

  • 1. ROR icon Islamic Azad University, Science and Research Branch
  • 2. Department of Biotechnology, College of Science, University of Tehran
  • 3. School of Electrical Engineering, Iran University of Science and Technology
  • 4. Department of Biological Sciences, Tarbiat Modares University
  • 5. ROR icon Tarbiat Modares University
  • 6. Department of Entrepreneurship, University of Tehran
  • 7. Department of Psychology, University of Tehran
  • 8. ROR icon Shahid Beheshti University of Medical Sciences

Contributors

Data curator:

Supervisor:

  • 1. ROR icon Islamic Azad University, Science and Research Branch
  • 2. College of Science, University of Tehran
  • 3. ROR icon Tarbiat Modares University
  • 4. ROR icon Iran University of Science and Technology
  • 5. Department of Entrepreneurship, University of Tehran
  • 6. Department of Psychology, University of Tehran
  • 7. ROR icon Shahid Beheshti University of Medical Sciences

Description

Objective, quantifiable EEG biomarkers for schizophrenia (SZ) research are limited by the scarcity of large, diverse, and high-quality public datasets. To address this gap, we present ASEEG (Atieh Schizophrenia EEG), a resting-state EEG dataset designed to support methodological development and benchmarking in SZ studies. ASEEG comprises 198 recordings from 101 subjects, including 51 individuals diagnosed with SZ according to DSM-5 criteria and 50 demographically matched healthy controls. Data were collected at a clinical setting using a standardized 19-channel EEG montage (international 10–20 system) with a sampling rate of 500 Hz. For each subject, both eyes-open and eyes-closed resting-state conditions were recorded for five minutes each, enabling analysis of complementary neural dynamics. The dataset spans a wide age range (15–65 years) and provides balanced diagnostic groups and extended recording durations. ASEEG is intended for use in feature extraction, machine and deep learning model development, validation, and comparative evaluation of EEG-based approaches for SZ research.

Files

Embargoed

The files will be made publicly available on March 15, 2027.

Reason: This dataset contains unpublished EEG recordings from schizophrenia patients and matched healthy control subjects. An embargo is applied to allow the research team sufficient time to complete ongoing analyses, finalize the project, and publish the associated scientific papers. Public release after the embargo period will ensure data integrity, proper interpretation, and appropriate citation of the original work.

Additional details

Identifiers

DOI
10.5281/zenodo.18029536

Dates

Submitted
2025-12-23