NIMH MEG Core Facility

National Institute Of Mental Health

Investigators

Linked publications, trials & patents

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 have 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. For much of FY2023, we carried out measurements to better understand the sensors and their limitations. In FY2022, we developed a method to compensate for external field fluctuations, which distort the gain and orientation of the OPM sensors. In addition to that, in FY2023 we worked with our collaborators at the University of Nottingham to implement dynamic control of our external compensation panel coils (MuCoils) which we use to reduce the ambient field in our magnetically shielded room (MSR). This required building an apparatus to hold the sensors controlling the panel coils. In addition, in the summer of 2023 we began acquiring data using our 56 channel array with human participants. One issue we had to address was how to position the array on the participant, and how to support the weight of the array. This required building a suspension gantry for the array. We have now collected somatosensory evoked field data from six participants and are currently in the process of analyzing that data. In addition to this work, we also began to look towards the future. We conducted simulations of sensors that can measure in two or three directions simultaneously, and demonstrated that we could dramatically improve the spatial resolution of our system. 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 an effort to standardize data storage and data analysis procedures, we have been writing software to facilitate the storage of data collected at NIH in the Brain Imaging Data Structure (BIDS) format. We have modified our previously developed modular scripts to operate on data organized in this format, in concert with our development of an ENIGMA MEG working group pipeline, detailed below. We are currently applying these scripts to analyze data acquired under the NIMH Research Volunteer Protocol (NCT03304665). The MEG Core Facility continues to assist investigators in setting up MEG software and ensures that all software is available on shared resources (the NIH High Performance Computing (HPC) center). We are continuing to develop a real-time neurofeedback task using source-localized MEG to modulate activity in the amygdala, in collaboration with Dr. Carlos Zarate's group. While MEG neurofeedback has been performed before, the use of source-localized neurofeedback is unique. It is much more complicated, however, requiring real-time beamforming and integration of the acquisition, reconstruction, and stimulus presentation software systems. Education and Training: One-on-one training and support are provided upon request, and accounts for a significant portion of the scientific staffs 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 inaugurated 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. Support of the Larger MEG Community: Due to the ongoing COVID-19 pandemic, we temporarily suspended the MEG North America meeting; however, we are currently in the planning stages of a MEG North America meeting in November of FY2024. The meeting will include a one day hackathon, industry panel, and full scientific session including two keynote speakers, scientific symposia, and a poster session. As part of the NIMH protocol Recruitment and Characterization of Healthy Research Volunteers for NIMH Intramural studies (NCT03304665) we have now collected 123 MEG recordings from healthy individuals on a comprehensive battery of cognitive tasks. These scans were part of a broader study collecting clinical, cognitive, and MRI data. The first set of 68 recordings was shared online in the BIDS standard format,in collaboration with the NIMH Data Science and Sharing Team, and a data descriptor manuscript was published in Scientific Data. Once the current wave of participants has completed scanning, the plan is to curate and release that data as well. 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 amassed over 1700 raw datasets, and we expect to receive more raw data and subject-level derived data over FY2024. One significant element of the project was retraining a deep neural network model to automatically detect artifacts in the data. This has been completed, and we anticipate that the new model will be integrated into open-source MEG analysis software so it can benefit the larger community. The model is currently available online. Our full analysis pipeline for the ENIGMA software is now complete, and we are currently soliciting beta test users.