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<p>The Brain Imaging and Neurophysiology Dataset (BIND) represents one of the largest multi-institutional, multimodal, clinical neuroimaging repositories, comprising 1.8 million brain scans from 38,942 patients, linked to full-text reports and neurophysiological recordings. This comprehensive dataset addresses critical limitations in neuroimaging research by providing a rich and diverse set of large-scale multimodal data. BIND integrates de-identified data from Massachusetts General Hospital, Brigham and Women’s Hospital, and Stanford University, including 1,723,699 MRI scans (1.5, 3 and 7 Tesla), 54,137 CT scans, 5,093 PET scans, and 526 SPECT scans, converted to standardized NIfTI format following BIDS organization. The dataset spans the full age spectrum and encompasses diverse neurological conditions alongside healthy subjects. We deployed Large Language Models to extract structured clinical metadata from 84,960 reports to extract standardized clinical information. All imaging data are linked to previously published EEG and polysomnography recordings, facilitating future multimodal analyses. BIND is freely accessible for academic research through the Brain Data Science Platform (<a href="https://bdsp.io/">https://bdsp.io/</a>). This resource facilitates large-scale neuroimaging studies, machine learning applications, and multimodal brain research to accelerate discoveries in clinical neuroscience.</p>

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The Brain Imaging and Neurophysiology Dataset of large-scale multimodal neural data

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月21日

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  • Charlotte Maschke,
  • Peter N. Hadar,
  • Yicheng Zhang,
  • Jian Li,
  • Gauri Ganjoo,
  • Andrew Hoopes,
  • Alessandro Guazzo,
  • Aditya Gupta,
  • Manohar Ghanta,
  • Bruce Nearing,
  • Christine Tsien Silvers,
  • Bharath Gunapati,
  • Robert Thomas,
  • Jennifer A. Kim,
  • Shibani S. Mukerji,
  • Adrian Dalca,
  • Sahar Zafar,
  • Alice D. Lam,
  • Emmanuel Mignot,
  • M. Brandon Westover

摘要

The Brain Imaging and Neurophysiology Dataset (BIND) represents one of the largest multi-institutional, multimodal, clinical neuroimaging repositories, comprising 1.8 million brain scans from 38,942 patients, linked to full-text reports and neurophysiological recordings. This comprehensive dataset addresses critical limitations in neuroimaging research by providing a rich and diverse set of large-scale multimodal data. BIND integrates de-identified data from Massachusetts General Hospital, Brigham and Women’s Hospital, and Stanford University, including 1,723,699 MRI scans (1.5, 3 and 7 Tesla), 54,137 CT scans, 5,093 PET scans, and 526 SPECT scans, converted to standardized NIfTI format following BIDS organization. The dataset spans the full age spectrum and encompasses diverse neurological conditions alongside healthy subjects. We deployed Large Language Models to extract structured clinical metadata from 84,960 reports to extract standardized clinical information. All imaging data are linked to previously published EEG and polysomnography recordings, facilitating future multimodal analyses. BIND is freely accessible for academic research through the Brain Data Science Platform (https://bdsp.io/). This resource facilitates large-scale neuroimaging studies, machine learning applications, and multimodal brain research to accelerate discoveries in clinical neuroscience.