en.Wedoany.com Reported - On May 27, 2026, the University of California, San Diego (UC San Diego) received $4.85 million from the National Institutes of Health (NIH) to upgrade the NeuroElectroMagnetic data Archive and tools Resource (NEMAR) platform. The platform integrates large-scale neuroscience data with high-performance computing (HPC) resources, aiming to advance brain and body research.
The NEMAR platform is a key infrastructure for sharing and analyzing human neurophysiological data, particularly electroencephalography (EEG) and magnetoencephalography (MEG). It connects curated datasets from sources like OpenNeuro with the computational resources of the San Diego Supercomputer Center (SDSC) at UC San Diego's Halıcıoğlu Data Science Institute, enabling researchers to conduct large-scale analyses without first needing to transfer data to distant locations.
A core feature of the platform is its integration with SDSC's Expanse supercomputer, where NEMAR datasets are directly mounted. Users can analyze data up to petabyte scale in place, eliminating time-consuming transfers and lowering the barrier to entry for computationally intensive neuroscience workflows. Through the Neuroscience Gateway, NEMAR also provides streamlined access to scientific software tools such as EEGLAB, MATLAB, Python, TensorFlow, and PyTorch.
The continued funding will support a significant expansion of NEMAR's artificial intelligence (AI) capabilities. The team plans to develop multimodal foundation models trained on large-scale neuroelectromagnetic datasets, combining brain signals with behavioral and participant-level metadata. These models are expected to support downstream applications such as data quality assessment, cross-modal analysis, cognitive state decoding, and brain-computer interface development.
"NEMAR is at the forefront of open neuroscience infrastructure, and this new phase of funding should allow us to explore exciting new opportunities in statistical and AI modeling to understand how our brains support our experience and behavior," said Scott Makeig, co-Principal Investigator and Director of the Swartz Center for Computational Neuroscience at UC San Diego's Institute for Neural Computation.
"By combining data formatted using accepted standards with easily accessible high-performance computing, we can train large models that generalize across experiments," said Arnaud Delorme, co-Principal Investigator of the project and co-Director of the Swartz Center for Computational Neuroscience at the Institute for Neural Computation.
The platform's emphasis on standardized data remains central to its design. NEMAR supports the Brain Imaging Data Structure (BIDS) and uses the Hierarchical Event Descriptor (HED) system to incorporate detailed event annotations, enabling interoperability across tools and study groups.
The project also plans to expand training and outreach efforts, covering workshops and tutorials on data standards, signal processing, and machine learning methods.
"By co-locating large-scale datasets with HPC resources, we enable researchers to focus on analysis rather than data logistics. This funding allows us to further extend this model and broaden access to a wider community," said Amitava Majumdar, co-Principal Investigator of the NEMAR project and Director of the Data-Enabled Scientific Computing Division at SDSC.
As the volume and complexity of neuroscience data continue to grow, platforms like NEMAR are making HPC infrastructure a critical enabler of data-driven research. The project is funded by the National Institute of Mental Health (NIMH), part of the NIH, under grant number R24-MH120037. The new award supports the project from April 2026 to December 2030 and is part of the NIH's Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative for sharing neuroelectromagnetic data resources. The project is co-led by Scott Makeig, Amitava Majumdar, Taylor Berg-Kirkpatrick, and Arnaud Delorme from UC San Diego, along with Russ Poldrack from Stanford University, with collaborators including Srikantan Nagarajan from the University of California, San Francisco, and Kay Robbins from the University of Texas at San Antonio. SDSC researchers Subha Sivagnanam, Choonhan Youn, and Yahya Shirazi are participating.
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