Brain Data Science Platform

Featured Resources

Database Credentialed Access

The Brain Imaging and Neurophysiology Database (BIND)

Charlotte Maschke, Peter 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 Kim, Shibani Mukerji, Adrian Dalca, Sahar Zafar, Alice Lam, Emmanuel Mignot, M Brandon Westover

BIND Database 1: Neuroimaging Data (MRI, CT, PET, SPECT) that can be paired with EEG and PSG (found in the Harvard EEG Database https://bdsp.io/content/harvard-eeg-db/4.1/). LLMs helped categorize pathology.

ct mri brain imaging

Published: Sept. 9, 2025. Version: 1.0

Database Credentialed Access

The Human Sleep Project

Haoqi Sun, Wolfgang Ganglberger, Samaneh Nasiri, Aditya Gupta, Manohar Ghanta, Valdery Moura Junior, Sydney Cash, Katie Stone, Zhiyong Zhang, Gauri Ganjoo, Thijs E Nassi, Ruoqi Wei, Erik-Jan Meulenbrugge, Rhoda Au, Gari Clifford, Lynn Marie Trotti, Dennis Hwang, Emmanuel Mignot, Umakanth Katwa, M Brandon Westover

The Human Sleep Project (HSP) is a large collection of clinical sleep physiology recordings created to enable brain health research.

brain health artificial intelligence sleep

Published: Nov. 1, 2023. Version: 2.0

Database Credentialed Access

Harvard Electroencephalography Database

Sahar Zafar, Tobias Loddenkemper, Jong Woo Lee, Andrew Cole, Daniel Goldenholz, Jurriaan Peters, Alice Lam, Edilberto Amorim, Catherine Chu, Sydney Cash, Valdery Moura Junior, Aditya Gupta, Manohar Ghanta, Marta Fernandes, Haoqi Sun, Jin Jing, M Brandon Westover

Harvard Electroencephalography Database

routine eeg epilepsy monitoring unit electroencephalography icu eeg epilepsy eeg

Published: Feb. 10, 2025. Version: 4.1

Database Credentialed Access

The Boston Childrens Hospital Sleep Corpus

Ayush Tripathi, Wolfgang Ganglberger, Haoqi Sun, Callison Alcott, Niels Turley, Rebecca Fitzgerald, Ayan Mitra, Samuel Waters, Arnav Gupta, Aditya Gupta, Manohar Ghanta, Valdery Moura Junior, Samaneh Nasiri, Bruce Nearing, Katie Stone, Emmanuel Mignot, Dennis Hwang, Matthew Reyna, Zuzana Koscova, Chad Robichaux, Zhiyong Zhang, Qiao Li, Gauri Ganjoo, Lynn Marie Trotti, Gari Clifford, Christine Tsien Silvers, Bharath Gunapati, Robert Thomas, M Brandon Westover, Kiran Maski, Umakanth Katwa

The Boston Children’s Hospital (BCH) Sleep Corpus comprises 15,695 fully annotated pediatric polysomnography (PSG) recordings collected between 2010 and 2024.

Published: Aug. 6, 2025. Version: 1.0.1

Database Restricted Access

I-CARE: International Cardiac Arrest REsearch consortium Electroencephalography Database

Edilberto Amorim, Wei-Long Zheng, Mohammad Ghassemi, Mahsa Aghaeeaval, Pravinkumar Kandhare, Vishnu Karukonda, Jong Woo Lee, Susan Herman, adithya sivaraju, Nicolas Gaspard, Jeannette Hofmeijer, Michel JAM van Putten, Reza Sameni, Matthew Reyna, Gari Clifford, M Brandon Westover

Multicenter clinical and EEG Database including patients who were comatose after cardiac arrest. This database includes 1,020 patients and more than 50,000 hours of continuous EEG from 7 hospitals in the U.S. and Europe.

Published: Oct. 11, 2023. Version: 1.0

Database Restricted Access

Targeted Metabolomics in the REGARDS Stroke Case-Cohort Study

Zsuzsanna Ament, Naruchorn Kijpaisalratana, Varun Bhave, Catharine Couch, Ana-Lucia Garcia Guarniz, Amit Patki, Mary Cushman, Suzanne Judd, Ryan Irvin, William Kimberly

This dataset contains metabolomics data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) Study, a large, biracial cohort investigating metabolic biomarkers linked to stroke risk and health disparities across the United State

Published: Feb. 26, 2025. Version: 1.0.0

Latest Resources

Software Credentialed Access

Effects of epileptiform activity on discharge outcome in critically ill patients

Harsh Parikh, Kentaro Hoffman, Haoqi Sun, Sahar F. Zafar, Wendong Ge, Jin Jing, Lin Liu, Jimeng Sun, Aaron F Struck, Alexander Volfovsky, Cynthia Rudin, M. Brandon Westover

De-identified data and a PK-PD + MALTS causal-inference pipeline reproducing the effect of untreated epileptiform-activity burden on poor discharge outcome in critically ill patients (Parikh et al., Lancet Digital Health 2023).

Published: July 11, 2026. Version: 1.0.1

Software Credentialed Access

Automated annotation of epileptiform burden and its association with outcomes

Sahar F. Zafar, Eric Rosenthal, Jin Jing, Wendong Ge, Mohammad Tabaeizadeh, Hassan Aboul Nour, Maryum Shoukat, Haoqi Sun, Farrukh Javed, Solomon Kassa, Muhammad Edhi, Elahe Bordbar, John Gallagher, Valdery Moura, Manohar Ghanta, Yu-Ping Shao, Sungtae An, Jimeng Sun, Andrew J. Cole, M. Brandon Westover

MATLAB code and de-identified data (1,991 patients) relating automatically-quantified ictal-interictal-continuum/seizure burden on continuous EEG to discharge outcome (Zafar et al., Ann Neurol 2021).

Published: July 11, 2026. Version: 1.0.0

Software Credentialed Access

How many patients do you need? A trial-design simulation for anti-seizure treatment in acute brain injury

Harsh Parikh, Haoqi Sun, Rajesh Amerineni, Eric Rosenthal, Alexander Volfovsky, Cynthia Rudin, M. Brandon Westover, Sahar F. Zafar

MATLAB/Python code and de-identified data for a simulation framework that estimates required sample sizes and effect sizes for randomized trials of anti-seizure treatment in critically ill patients (Parikh et al., Ann Clin Transl Neurol 2024).

Published: July 11, 2026. Version: 1.0.0

Software Credentialed Access

Optimal spindle detection parameters for predicting cognitive performance

Noor Adra, Haoqi Sun, Wolfgang Ganglberger, Elissa Ye, Lena L. Dümmer, Ryan A. Tesh, Mike Westmeijer, Madalena D. S. Cardoso, Erin Kitchener, An Ouyang, Joel Salinas, Jonathan Rosand, Sydney Cash, Robert Thomas, M. Brandon Westover

De-identified sleep-spindle feature data (BDSP-linked) + cognition data + Python code to find the spindle-detection parameters that best predict cognitive performance (Adra et al., Sleep 2022).

Published: July 10, 2026. Version: 1.0.0

Software Credentialed Access

Prognostic significance of EEG patterns in post-cardiac arrest coma: a 1,000-patient multicenter cohort

Rajib Kanti Dey, Aysenur Yaramis, Niels Turley, Hillary Mullan, Sakshi Chougule, Kaileigh Gallagher, Grace Bayas, Nirav Barot, Frank W. Drislane, Mouhsin Shafi, Trudy Pang, Daniel Goldenholz, Aaron F Struck, Jennifer Kim, Sahar F. Zafar, Jong Woo Lee, Edilberto Amorim, M. Brandon Westover

De-identified 1,000-patient multicenter dataset (BDSP-linked) and Python code for the prognostic significance of continuous-EEG patterns after cardiac arrest, with exact Clopper-Pearson CIs and temporal-trend analysis.

Published: July 10, 2026. Version: 1.0.0

Software Credentialed Access

A Primer on EEG Spectrograms: a de-identified EEG/qEEG teaching atlas

Marcus Ng, Jin Jing, M. Brandon Westover

A de-identified teaching atlas of 224 labeled EEG segments, each pairing raw EEG with its qEEG spectrogram, plus MATLAB code to regenerate the paired figures. Accompanies "A Primer on EEG Spectrograms" (Ng et al., 2022).

Published: July 10, 2026. Version: 1.0.0

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News

BDSP Recognized as NIH-Approved Data Repository

Nov. 21, 2024

As of Nov 21, 2024, the National Institutes of Health (NIH) has officially recognized BDSP as an approved repository for researchers to meet NIH Data Management and Sharing (DMS) requirements. This designation enables NIH-funded researchers to utilize BDSP for depositing and sharing their research data in compliance with NIH data sharing policies. As a vetted repository on the NIH's list of domain-specific repositories, BDSP is commited to advancing open science and facilitating collaborative research in brain data science.

For more information about depositing data in BDSP, please contact our support team.

Learn how to interact with the project data

Oct. 16, 2023

Take a look at the Tutorial explaining how to interact and download with the data published together with BDSP Projects. You can find more details here.

New I-CARE train dataset released !

News from: I-CARE: International Cardiac Arrest REsearch consortium Electroencephalography Database v1.0.

Oct. 16, 2023

The International Cardiac Arrest REsearch consortium (I-CARE) Database includes baseline clinical information and continuous electroencephalography (EEG) recordings from 1,020 comatose patients with a diagnosis of cardiac arrest who were admitted to an intensive care unit from seven academic hospitals in the U.S. and Europe. Patients were monitored with 18 bipolar EEG channels over hours to days for the diagnosis of seizures and for neurological prognostication. Long-term neurological function was determined using the Cerebral Performance Category scale.

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