Hardware: The 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 November of 2017, the electronics controlling the MEG system was completely replaced by new equipment, reducing noise in the MEG signals, increasing reliability, and decreasing power and cooling requirements. Backup stimulus delivery hardware was acquired to ensure uninterrupted operation of the facility. We upgraded existing equipment to allow NIH IRP laboratories to use more complex response devices (such as joysticks). We have also acquired and installed a state of the art Propixx projection system, which will enable vision research with exquisite precision of stimulus delivery. Additionally, in FY18 a contract was awarded to install a 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. 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 (SSCC, DIRP, NIMH) 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). Automated MEG-MRI co-registration based on cortical surface normals was developed and will be presented at the 2018 BioMag meeting in Philadelphia, PA. A novel method for calculating connectivity based upon measurements of entropy has also been developed and will be presented at the same meeting. Additional software development includes the implementation of a patch beamformer which may offer greater signal to noise than a distributed source model approach. 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 FY 2018, the MEG Core facility held the first ever MEG Course on the NIH campus. There were 24 attendees, from 3 different NIH institutes. The course handouts are available freely on our website (https://megcore.nih.gov). This course is expected to continue on an annual basis. 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 first hosted the MEG-North America Workshop in 2016 over two days on the NIH campus. Building upon the success of the first meeting, a second meeting was held in November 2017, also over two days. The first day of the meeting was a series of working groups, examining issues of interest to the greater community, including reproducibility and reliability, data sharing, facilitation of best practices, and academic/industry partnerships. A collaborative white paper based upon these working groups is in progress. At the end of FY 2018, a half-day MEG-North America symposium will be held as a satellite meeting to the 2018 BioMag conference in Philadelphia, PA. We plan to continue these meetings to further facilitate collaboration and synergy across laboratories. During FY 2018, 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. The intention of this is to compile a normative database of healthy subjects, with MEG, MRI, behavioral phenotyping, and genetic information. It is anticipated that this will serve as a valuable resource to the MEG community as a whole. As part of this project, a paradigm was designed by the MEG Core, with input from PIs involved in MEG research at the NIH, designed to assess multiple cognitive domains which are important in the pathophysiology of psychiatric and neurological disorders. Scientific Contribution: 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.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Scientific Cores Intramural Research (ZIC)
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U.S. National Institute of Mental Health
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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:
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
Chander, Bankim S; Witkowski, Matthias; Braun, Christoph et al. (2016) tACS Phase Locking of Frontal Midline Theta Oscillations Disrupts Working Memory Performance. Front Cell Neurosci 10:120

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