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Xu W, Liao P, Cao M, White DJ, Lyu B, Gao JH. Facilitating cognitive neuroscience research with 80-sensor optically pumped magnetometer magnetoencephalography (OPM-MEG). Neuroimage 2025; 311:121182. [PMID: 40180002 DOI: 10.1016/j.neuroimage.2025.121182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2024] [Revised: 02/28/2025] [Accepted: 03/31/2025] [Indexed: 04/05/2025] Open
Abstract
Recent advancements in optically pumped magnetometer magnetoencephalography (OPM-MEG) make it a promising alternative to conventional SQUID-MEG systems. Nonetheless, as reported in the literature, current OPM-MEG systems are often constrained by a limited number of sampling points, which restricts their capability to match the full-head coverage offered by SQUID-MEG systems. Additionally, whether OPM-MEG can deliver results comparable to SQUID-MEG in practical cognitive neuroscience applications remains largely unexplored. In this study, we introduce a high-density, full-head coverage OPM-MEG system with 80 sensors and systematically compare the performance of OPM-MEG and SQUID-MEG, from sensor- to source-level analysis, across various classic cognitive tasks. Our results demonstrate that visual and auditory evoked fields captured using OPM-MEG align closely with those obtained from SQUID-MEG. Furthermore, steady-state visual evoked field and finger-tapping-induced beta power change recorded with OPM-MEG are accurately localized to corresponding brain regions, with activation centers highly congruent to those observed with SQUID-MEG. For resting-state recordings, the two modalities exhibit similar power distributions, functional connectomes, and microstate clusters. These findings indicate that the 80-sensor OPM-MEG system provides spatial and temporal characteristics comparable to those of traditional SQUID-MEG. Thus, our study offers empirical evidence supporting the efficacy of high-density OPM-MEG and suggests that OPM-MEG, with dense sampling capability, represents a compelling alternative to conventional SQUID-MEG, facilitating further exploration of human cognition.
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Affiliation(s)
- Wei Xu
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China; Changping Laboratory, Beijing, 102206, China
| | - Pan Liao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China; Changping Laboratory, Beijing, 102206, China
| | - Miao Cao
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, VIC, 3122, Australia
| | - David J White
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, VIC, 3122, Australia
| | | | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China; Changping Laboratory, Beijing, 102206, China; Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, 100871, China; McGovern Institute for Brain Research, Peking University, Beijing, 100871, China; National Biomedical Imaging Center, Peking University, Beijing, 100871, China.
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Xu W, Lyu B, Ru X, Li D, Gu W, Ma X, Zheng F, Li T, Liao P, Cheng H, Yang R, Song J, Jin Z, Li C, He K, Gao JH. Decoding the Temporal Structures and Interactions of Multiple Face Dimensions Using Optically Pumped Magnetometer Magnetoencephalography (OPM-MEG). J Neurosci 2024; 44:e2237232024. [PMID: 39358044 PMCID: PMC11580774 DOI: 10.1523/jneurosci.2237-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 09/18/2024] [Accepted: 09/25/2024] [Indexed: 10/04/2024] Open
Abstract
Humans possess a remarkable ability to rapidly access diverse information from others' faces with just a brief glance, which is crucial for intricate social interactions. While previous studies using event-related potentials/fields have explored various face dimensions during this process, the interplay between these dimensions remains unclear. Here, by applying multivariate decoding analysis to neural signals recorded with optically pumped magnetometer magnetoencephalography, we systematically investigated the temporal interactions between invariant and variable aspects of face stimuli, including race, gender, age, and expression. First, our analysis revealed unique temporal structures for each face dimension with high test-retest reliability. Notably, expression and race exhibited a dominant and stably maintained temporal structure according to temporal generalization analysis. Further exploration into the mutual interactions among face dimensions uncovered age effects on gender and race, as well as expression effects on race, during the early stage (∼200-300 ms postface presentation). Additionally, we observed a relatively late effect of race on gender representation, peaking ∼350 ms after the stimulus onset. Taken together, our findings provide novel insights into the neural dynamics underlying the multidimensional aspects of face perception and illuminate the promising future of utilizing OPM-MEG for exploring higher-level human cognition.
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Affiliation(s)
- Wei Xu
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
| | | | - Xingyu Ru
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
| | - Dongxu Li
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
| | - Wenyu Gu
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
| | - Xiao Ma
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
| | - Fufu Zheng
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
| | - Tingyue Li
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
| | - Pan Liao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
| | - Hao Cheng
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
| | - Rui Yang
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
| | - Jingqi Song
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
| | - Zeyu Jin
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
| | | | - Kaiyan He
- Changping Laboratory, Beijing 102206, China
| | - Jia-Hong Gao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Changping Laboratory, Beijing 102206, China
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China
- McGovern Institute for Brain Research, Peking University, Beijing 100871, China
- National Biomedical Imaging Center, Peking University, Beijing 100871, China
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Cheng H, He K, Li C, Ma X, Zheng F, Xu W, Liao P, Yang R, Li D, Qin L, Na S, Lyu B, Gao JH. Wireless optically pumped magnetometer MEG. Neuroimage 2024; 300:120864. [PMID: 39322096 DOI: 10.1016/j.neuroimage.2024.120864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 09/04/2024] [Accepted: 09/23/2024] [Indexed: 09/27/2024] Open
Abstract
The current magnetoencephalography (MEG) systems, which rely on cables for control and signal transmission, do not fully realize the potential of wearable optically pumped magnetometers (OPM). This study presents a significant advancement in wireless OPM-MEG by reducing magnetization in the electronics and developing a tailored wireless communication protocol. Our protocol effectively eliminates electromagnetic interference, particularly in the critical frequency bands of MEG signals, and accurately synchronizes the acquisition and stimulation channels with the host computer's clock. We have successfully achieved single-channel wireless OPM-MEG measurement and demonstrated its reliability by replicating three well-established experiments: The alpha rhythm, auditory evoked field, and steady-state visual evoked field in the human brain. Our prototype wireless OPM-MEG system not only streamlines the measurement process but also represents a major step forward in the development of wearable OPM-MEG applications in both neuroscience and clinical research.
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Affiliation(s)
- Hao Cheng
- Center for MRl Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China; Changping Laboratory, Beijing 102206, PR China
| | - Kaiyan He
- Changping Laboratory, Beijing 102206, PR China
| | - Congcong Li
- Changping Laboratory, Beijing 102206, PR China
| | - Xiao Ma
- Center for MRl Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China; Changping Laboratory, Beijing 102206, PR China; Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy lon Physics, School of Physics, Peking University, Beijing 100871, PR China
| | - Fufu Zheng
- Center for MRl Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China; Changping Laboratory, Beijing 102206, PR China; Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy lon Physics, School of Physics, Peking University, Beijing 100871, PR China
| | - Wei Xu
- Center for MRl Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China; Changping Laboratory, Beijing 102206, PR China
| | - Pan Liao
- Center for MRl Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China; Changping Laboratory, Beijing 102206, PR China
| | - Rui Yang
- Center for MRl Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China; Changping Laboratory, Beijing 102206, PR China; Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy lon Physics, School of Physics, Peking University, Beijing 100871, PR China
| | - Dongxu Li
- Center for MRl Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China; Changping Laboratory, Beijing 102206, PR China; Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy lon Physics, School of Physics, Peking University, Beijing 100871, PR China
| | - Lang Qin
- Center for MRl Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China
| | - Shuai Na
- National Biomedical Imaging Center, Peking University, Beijing 100871, PR China
| | | | - Jia-Hong Gao
- Center for MRl Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China; Changping Laboratory, Beijing 102206, PR China; Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy lon Physics, School of Physics, Peking University, Beijing 100871, PR China; PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China; National Biomedical Imaging Center, Peking University, Beijing 100871, PR China; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, PR China.
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Voineskos AN, Hawco C, Neufeld NH, Turner JA, Ameis SH, Anticevic A, Buchanan RW, Cadenhead K, Dazzan P, Dickie EW, Gallucci J, Lahti AC, Malhotra AK, Öngür D, Lencz T, Sarpal DK, Oliver LD. Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions. World Psychiatry 2024; 23:26-51. [PMID: 38214624 PMCID: PMC10786022 DOI: 10.1002/wps.21159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2024] Open
Abstract
Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.
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Affiliation(s)
- Aristotle N Voineskos
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Nicholas H Neufeld
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, Wexner Medical Center, Ohio State University, Columbus, OH, USA
| | - Stephanie H Ameis
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Cundill Centre for Child and Youth Depression and McCain Centre for Child, Youth and Family Mental Health, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Alan Anticevic
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Robert W Buchanan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kristin Cadenhead
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Erin W Dickie
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Julia Gallucci
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Adrienne C Lahti
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Anil K Malhotra
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
| | - Dost Öngür
- McLean Hospital/Harvard Medical School, Belmont, MA, USA
| | - Todd Lencz
- Institute for Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
| | - Deepak K Sarpal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lindsay D Oliver
- Campbell Family Mental Health Research Institute and Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
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Perera Molligoda Arachchige AS, Garner AK. Seven Tesla MRI in Alzheimer's disease research: State of the art and future directions: A narrative review. AIMS Neurosci 2023; 10:401-422. [PMID: 38188012 PMCID: PMC10767068 DOI: 10.3934/neuroscience.2023030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 11/29/2023] [Accepted: 12/04/2023] [Indexed: 01/09/2024] Open
Abstract
Seven tesla magnetic resonance imaging (7T MRI) is known to offer a superior spatial resolution and a signal-to-noise ratio relative to any other non-invasive imaging technique and provides the possibility for neuroimaging researchers to observe disease-related structural changes, which were previously only apparent on post-mortem tissue analyses. Alzheimer's disease is a natural and widely used subject for this technology since the 7T MRI allows for the anticipation of disease progression, the evaluation of secondary prevention measures thought to modify the disease trajectory, and the identification of surrogate markers for treatment outcome. In this editorial, we discuss the various neuroimaging biomarkers for Alzheimer's disease that have been studied using 7T MRI, which include morphological alterations, molecular characterization of cerebral T2*-weighted hypointensities, the evaluation of cerebral microbleeds and microinfarcts, biochemical changes studied with MR spectroscopy, as well as some other approaches. Finally, we discuss the limitations of the 7T MRI regarding imaging Alzheimer's disease and we provide our outlook for the future.
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