Hardware: The Magnetoencephalography (MEG) Core operates a state-of-the-art 275 channel MEG system (CTF MEG). A complete assortment of stimulus delivery and subject response equipment is interfaced to the MEG system. In FY19, we upgraded our research participant support system to better minimize movement during recordings. We also continued to obtain backup response collection equipment to insure redundancy in case of equipment failure. In addition, we obtained additional data storage hardware to enable ongoing archival storage of MEG scans collected in the MEG Core facility. Finally, a contract was awarded to obtain a BrainSight neuronavigation unit, to enable real-time co-registration of MEG localization fiducial markers and MRI scans. These units are currently in use by some laboratories utilizing the MEG Core Facility, and we are excited about expanding the reach of this technology to all labs utilizing the core, to enable more accurate co-registration. Perhaps our most exciting hardware update is the award of a contract to acquire an initial proof-of-concept optically pumped magnetometer (OPM) system, consisting of 16 primary sensors and 3 reference sensors. A contract was also awarded to obtain a set of active compensation coils to reduce the magnetic fields surrounding the OPM array. We are working closely with the Section on Instrumentation (with George Dold) to design and construct a calibration jig. We expect delivery of the OPM sensors in early FY20, and hope to complete initial calibration measurements over several months. Our plan is to gradually increase the number of sensors in the system to hopefully obtain a system that will approach the spatial resolution of intracranial electroencephelogram (EEG), also known as electrocorticography (EcoG), without the need for neurosurgery. Once the device is fully calibrated, we will begin working with other investigators to develop applications. Finally, in FY19 we moved forward on the installation of our 100% helium recovery and recycling unit. This will eliminate the reliance of the lab on the procurement of liquid helium, a scarce non-renewable natural resource. After an initial break-even point of several years, this system is estimated to save the US federal government approximately $100,000 per year. The planned installation date is early FY20. Software: A variety of software for data analysis is maintained and supported by the Core, including proprietary CTF code, beamformer source reconstruction software (the SAM suite) written in-house, which interfaces with AFNI (NIMH Scientific and Statistical Computing Core) and Freesurfer, Fieldtrip, and MNE-Python. In addition, the MEG Core Facility frequently writes custom scripts to integrate stimulus and response data with the MEG dataset. The Core also actively develops new functionality within the SAM software suite, which is freely available online at our website (https://megcore.nih.gov). A release version of the software, including innovations such as a patch beamformer, automated alignment, and FreeSurfer integration will be in this new release. The MEG Core facility also assists investigators in setting up MEG software and ensures that all software is available on shared resources (The NIH High Performance Computing (HPC) center). Education and Training: As noted earlier, the field of MEG is relatively small compared to the MRI community, and there are fewer well-established methods. The analysis of complex tasks designed to test innovative hypotheses requires unique approaches. The MEG Core Facility staff can leverage its wealth of experience to support and train investigators on these tasks. One-on-one training and support are provided upon request, and accounts for a significant portion of the scientific staffs time. In FY19, to supplement this training, we hosted a three day course teaching all aspects of the MNE-python software package. The course was attended by approximately 25 individuals, at the post-baccalaureate, post-doctoral, and staff scientist levels. Support of the Larger MEG Community: As an effort to foster collaboration and communication across North American research and clinical MEG laboratories, the MEG Core Facility is in the planning stages of the 2019 MEG-North America Workshop to be held on the NIH campus in early FY20. The first day of the meeting will include several working groups, running concurrently with a full day hackathon. Notably, this will be the first ever MEG-focused hackathon. A collaborative white paper based upon prior work of MEG North America will be submitted by September 2019. During FY18, an amendment was crafted to the NIMH protocol Recruitment and Characterization of Healthy Research Volunteers for NIMH Intramural studies (NCT03304665), to add an optional MEG study. We began scanning volunteers in January 2019, and to date, we have completed 36 recordings, an average of 4.5 per month. This represents the first dataset of its type, particularly given that all subjects also have both structural and functional MRI data, as well as NIH toolbox neuropsychiatric measures. We are currently in collaboration with the data science and sharing team to have this data shared broadly with the neuroimaging community. Scientific Contribution and Collaboration: The primary focus of the MEG Core Facility is to facilitate and enable the science of other NIMH investigators. However, based upon scientific interests, MEG Core Facility scientists frequently collaborate with other investigator to analyze data and test novel hypotheses. In FY18, core personnel have collaborated extensively with the labs of Carlos A. Zarate, Jr. (ETPB) and Karen F. Berman (CTNB) to gain insights into the pathophysiology of major depressive disorder (MDD) and schizophrenia. Details regarding these collaborations are available in the attached project bibliography and in forthcoming publications. In order to foster discourse and collaboration between the NIH and extramural researchers, the MEG Core Facility is also hosting a short speaker series. We have scheduled three speakers for late FY19 and early FY20. In addition, the MEG core facility has begun a unique project to demonstrate the ability of MEG to record activity from deep sources in the brain. While many investigators still believe recording from deep/subcortical sources is not feasible, through the use of a system such as the CTF system with axial gradiometers, combined with beamforming techniques, recording signals from these sources is possible. One aspect of the project involves a reward task, and we are currently in active collaboration with Dr. Argyris Stringaris to validate the task using fMRI, and demonstrate the value added from MEG data. The final scientific contribution of the MEG Core Facility is the support of the work of NIH intramural scientists. A list of manuscripts acquired using the Core Facility resources appears below: Bankson BB, Hebart MN, Groen, IIA, Baker CI. (2018). The Temporal Evolution of Conceptual Object Representations Revealed through Models of Behavior, Semantics and Deep Neural Networks. Neuroimage 178, 172-182. Quentin R, King J-R, Sallard E, Fishman N, Thompson R, Buch ER, Cohen LG. (2019). Differential Brain Mechanisms of Selection and Maintenance of Information during Working Memory. J Neurosci 29(19) 3728-3740. Bonstrup M, Iturrate I, Thompson R, Cruciani G, Censor N, Cohen LG. (2019). A Rapid Form of Offline Consolidation in Skill Learning. Curr Bio 29(8), 1346-1351.e4.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Scientific Cores Intramural Research (ZIC)
Project #
1ZICMH002889-13
Application #
10008875
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
13
Fiscal Year
2019
Total Cost
Indirect Cost
Name
U.S. National Institute of Mental Health
Department
Type
DUNS #
City
State
Country
Zip Code
Richter, Craig G; Coppola, Richard; Bressler, Steven L (2018) Top-down beta oscillatory signaling conveys behavioral context in early visual cortex. Sci Rep 8:6991
Maniscalco, Brian; Lee, Jennifer L; Abry, Patrice et al. (2018) Neural Integration of Stimulus History Underlies Prediction for Naturalistically Evolving Sequences. J Neurosci 38:1541-1557
Gilbert, Jessica R; Yarrington, Julia S; Wills, Kathleen E et al. (2018) Glutamatergic Signaling Drives Ketamine-Mediated Response in Depression: Evidence from Dynamic Causal Modeling. Int J Neuropsychopharmacol :
Nugent, Allison C; Luber, Bruce; Carver, Frederick W et al. (2017) Deriving frequency-dependent spatial patterns in MEG-derived resting state sensorimotor network: A novel multiband ICA technique. Hum Brain Mapp 38:779-791
Luo, Qian; Holroyd, Tom; Mitchell, Derek et al. (2017) Heightened amygdala responsiveness in s-carriers of 5-HTTLPR genetic polymorphism reflects enhanced cortical rather than subcortical inputs: An MEG study. Hum Brain Mapp 38:4313-4321
Balderston, Nicholas L; Hale, Elizabeth; Hsiung, Abigail et al. (2017) Threat of shock increases excitability and connectivity of the intraparietal sulcus. Elife 6:
Garcia-Cossio, Eliana; Witkowski, Matthias; Robinson, Stephen E et al. (2016) Simultaneous transcranial direct current stimulation (tDCS) and whole-head magnetoencephalography (MEG): assessing the impact of tDCS on slow cortical magnetic fields. Neuroimage 140:33-40
Scott, Jonathan M; Robinson, Stephen E; Holroyd, Tom et al. (2016) Localization of Interictal Epileptic Spikes With MEG: Optimization of an Automated Beamformer Screening Method (SAMepi) in a Diverse Epilepsy Population. J Clin Neurophysiol 33:414-420
Altamura, Mario; ElvevÄg, Brita; Goldberg, Terry E et al. (2016) The impact of Val108/158Met polymorphism of catechol-O-methyltransferase on brain oscillations during working memory. Neurosci Lett 610:86-91
Nugent, Allison C; Robinson, Stephen E; Coppola, Richard et al. (2016) Preliminary differences in resting state MEG functional connectivity pre- and post-ketamine in major depressive disorder. Psychiatry Res Neuroimaging 254:56-66

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