NIMH MEG Core Facility

National Institute Of Mental Health

Investigators

Linked publications & trials

Abstract

Hardware Development: The MEG Core Facility has continued its development of a novel optically pumped magnetometer (OPM) system. With a combination of IRP and Brain Initiative funding (ZIA MH-0002975) we acquired 64 sensors, with which we have built a 56-channel array with three reference sensors (and additional spare sensors for redundancy). The array was designed in collaboration with George Dold and the Section on Instrumentation. In addition, the SI also worked with us to design a calibration jig to precisely characterize the position, orientation, and gain of every sensor in the array. During FY2025, we continued to refine our methods for calibration of the array, and have a manuscript which we expect to submit by the end of the fiscal year describing our calibration results. In FY2025, we installed a new magnetically shielded room which will accelerate our progress as it provides a dedicated space for our experiments. This has necessitated the construction of a new chair and gantry for patient and equipment support. With this new space, we are also looking forward to collaborating with other IRP investigators to find new applications for our OPM array. We received additional funding through a brain initiative grant to purchase next-generation OPM sensors, and details appear in report ZIA MH002990-01. Software Development: A variety of software for data analysis is maintained and supported by the Core. These include proprietary CTF code, beamformer source reconstruction software (the SAM suite) written in-house, and MNE-python. We also provide support for non-MEG specific software packages that these programs interface with, such as FreeSurfer and AFNI. In addition, the MEG Core Facility frequently writes custom scripts to integrate stimulus and response data with the MEG dataset. In FY2025, we completed a GUI driven tool for investigators that enables efficient review for data quality and provides seamless conversion of datasets into the BIDS format, the gold standard for sharing data. Education and Training: One-on-one training and support are provided upon request, and accounts for a significant portion of the scientific staff's time. We have continued to hold a once-weekly seminar that includes traditional journal club presentations, presentations of recent results by NIH investigators or extramural scientists, and tutorials. We have continued to hold office hours on Wednesdays where we invite users to come to the MEG Core offices and work on data analysis and ask questions on any MEG related topics. We additionally hold a yearly MEG course, teaching both the basic principles and basic data analysis techniques. This year, in addition to our basic MEG “boot camp,” we also held an “advanced topics” training course aimed at advanced users of our system to explore state-of-the-art analysis techniques. Support of the Larger MEG Community: As part of the NIMH protocol Recruitment and Characterization of Healthy Research Volunteers for NIMH Intramural studies (NCT03304665) we have now shared 123 MEG datasets on the OpenNeuro data repository, in collaboration with the Data Science and Sharing Team. In addition, MEG data collection has restarted with a new task battery, designed to probe cognitive domains not covered in the original protocol. The new task protocol includes a resting state scan and naturalistic (movie) viewing task, as the original protocol. The new tasks include a language processing task, designed to probe how syntactic structures are processed in the brain; a flanker task, designed to probe response inhibition and attention; and a monetary incentive delay task, designed to investigate reward processing. We plan to share data from these new tasks at least yearly. Our largest initiative in this domain has been the formation of the ENIGMA MEG working group. ENIGMA is a worldwide consortium of scientists in the domains of imaging and genomics. ENIGMA groups use meta-analysis or mega-analysis to understand how genotypes and neuroimaging phenotypes vary in health and a variety of neuropsychiatric disorders. We have recruited approximately 35 international MEG scientists to our working group. We have processed over 6082 datasets. Our full analysis pipeline for the ENIGMA software is now complete, and also available on GitHub (https://github.com/jstout211/enigma_MEG). A manuscript describing the pipeline is currently under revision. Additional work on the ENIGMA project includes the first ever application of data harmonization techniques such as ComBat to MEG data, a manuscript on this work has been submitted. We are also nearing completion of our first major analysis of the ENIGMA dataset. This first analysis includes 3,598 datasets from 3,119 healthy volunteers, the largest MEG analysis ever undertaken. In this analysis, we have been able to map the maturational trajectory of the brain’s biomagnetic activity in unprecedented detail. A manuscript on this project is in progress.