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Khan OA, Rahman S, Baduni K, Modlesky CM. Assessment of cortical activity, functional connectivity, and neuroplasticity in cerebral palsy using functional near-infrared spectroscopy: A scoping review. Dev Med Child Neurol 2025; 67:875-891. [PMID: 39963963 PMCID: PMC12134447 DOI: 10.1111/dmcn.16238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2024] [Revised: 12/04/2024] [Accepted: 12/07/2024] [Indexed: 06/11/2025]
Abstract
AIM To map and critically appraise the literature on the feasibility and current use of functional near-infrared spectroscopy (fNIRS) to assess cortical activity, functional connectivity, and neuroplasticity in individuals with cerebral palsy (CP). METHOD A scoping review methodology was prospectively registered and reported following Preferred Reporting Items for Systematic review and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) guidelines. A systematic search was conducted in four databases. Empirical studies using fNIRS to assess neural activity, functional connectivity, or neuroplasticity in individuals with CP aged 3 years or older were included. RESULTS Sixteen studies met the inclusion criteria. Individuals with CP (age range = 3-43 years; 70% unilateral CP) underwent fNIRS-based assessment for task-evoked activity (studies [n] = 15) and/or resting-state functional connectivity (n = 3). Preliminary observations suggest greater magnitude, extent, and ipsilateral hemispheric lateralization of sensorimotor cortex activity in CP, while magnitude and patterns of prefrontal cortex activity in CP appear dependent on task demands. Normalization of fNIRS-based activity metrics observed postintervention (n = 3) paralleled improvements in functional outcomes, highlighting their potential as promising biomarkers for functional gains in CP. INTERPRETATION This review details the use of fNIRS in CP, highlights research gaps and technical limitations, and offers recommendations to support fNIRS implementation for ecologically valid functional neuroimaging in individuals with CP.
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Affiliation(s)
- Owais A. Khan
- Department of KinesiologyUniversity of GeorgiaAthensGAUSA
| | - Simin Rahman
- Department of KinesiologyUniversity of GeorgiaAthensGAUSA
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Chai C, Yang X, Zheng Y, Bin Heyat MB, Li Y, Yang D, Chen YH, Sawan M. Multimodal fusion of magnetoencephalography and photoacoustic imaging based on optical pump: Trends for wearable and noninvasive Brain-Computer interface. Biosens Bioelectron 2025; 278:117321. [PMID: 40049046 DOI: 10.1016/j.bios.2025.117321] [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: 10/24/2024] [Revised: 02/19/2025] [Accepted: 02/26/2025] [Indexed: 03/30/2025]
Abstract
Wearable noninvasive brain-computer interface (BCI) technologies, such as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), have experienced significant progress since their inception. However, these technologies have not achieved revolutionary advancements, largely because of their inherently low signal-to-noise ratio and limited penetration depth. In recent years, the application of quantum-theory-based optically pumped (OP) technologies, particularly optical pumped magnetometers (OPMs) for magnetoencephalography (MEG) and photoacoustic imaging (PAI) utilizing OP pulsed laser sources, has opened new avenues for development in noninvasive BCIs. These advanced technologies have garnered considerable attention owing to their high sensitivity in tracking neural activity and detecting blood oxygen saturation. This paper represents the first attempt to discuss and compare technologies grounded in OP theory by examining the technical advantages of OPM-MEG and PAI over traditional EEG and fNIRS. Furthermore, the paper investigates the theoretical and structural feasibility of hardware reuse in OPM-MEG and PAI applications.
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Affiliation(s)
- Chengpeng Chai
- CenBRAIN Neurotech, School of Engineering, Westlake University, 600 Dunyu Road, Xihu District, Hangzhou, Zhejiang, 310030, China; Institute of Advanced Technology, Westlake Institute for Advanced Study, 18 Shilongshan Street, Xihu District, Hangzhou, Zhejiang, 310024, China
| | - Xi Yang
- CenBRAIN Neurotech, School of Engineering, Westlake University, 600 Dunyu Road, Xihu District, Hangzhou, Zhejiang, 310030, China; Institute of Advanced Technology, Westlake Institute for Advanced Study, 18 Shilongshan Street, Xihu District, Hangzhou, Zhejiang, 310024, China
| | - Yuqiao Zheng
- CenBRAIN Neurotech, School of Engineering, Westlake University, 600 Dunyu Road, Xihu District, Hangzhou, Zhejiang, 310030, China; Institute of Advanced Technology, Westlake Institute for Advanced Study, 18 Shilongshan Street, Xihu District, Hangzhou, Zhejiang, 310024, China
| | - Md Belal Bin Heyat
- CenBRAIN Neurotech, School of Engineering, Westlake University, 600 Dunyu Road, Xihu District, Hangzhou, Zhejiang, 310030, China; Institute of Advanced Technology, Westlake Institute for Advanced Study, 18 Shilongshan Street, Xihu District, Hangzhou, Zhejiang, 310024, China
| | - Yifan Li
- Faculty of Engineering, University of Bristol, Bristol, BS8 1QU, United Kingdom
| | - Dingbo Yang
- Department of Neurosurgery, Affiliated Hangzhou First People's Hospital, Westlake University School of Medicine, Hangzhou, 310000, China; Department of Neurosurgery, Nanjing Medical University Affiliated Hangzhou Hospital, Hangzhou First People's Hospital, Hangzhou, 310000, China
| | - Yun-Hsuan Chen
- CenBRAIN Neurotech, School of Engineering, Westlake University, 600 Dunyu Road, Xihu District, Hangzhou, Zhejiang, 310030, China; Institute of Advanced Technology, Westlake Institute for Advanced Study, 18 Shilongshan Street, Xihu District, Hangzhou, Zhejiang, 310024, China.
| | - Mohamad Sawan
- CenBRAIN Neurotech, School of Engineering, Westlake University, 600 Dunyu Road, Xihu District, Hangzhou, Zhejiang, 310030, China; Institute of Advanced Technology, Westlake Institute for Advanced Study, 18 Shilongshan Street, Xihu District, Hangzhou, Zhejiang, 310024, China.
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Segal N, Kalyuzhner Z, Agdarov S, Beiderman Y, Beiderman Y, Zalevsky Z. AI-powered remote monitoring of brain responses to clear and incomprehensible speech via speckle pattern analysis. JOURNAL OF BIOMEDICAL OPTICS 2025; 30:067001. [PMID: 40492267 PMCID: PMC12148044 DOI: 10.1117/1.jbo.30.6.067001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2025] [Revised: 04/10/2025] [Accepted: 04/24/2025] [Indexed: 06/11/2025]
Abstract
Significance Functional magnetic resonance imaging provides high spatial resolution but is limited by cost, infrastructure, and the constraints of an enclosed scanner. Portable methods such as functional near-infrared spectroscopy and electroencephalography improve accessibility but require physical contact with the scalp. Our speckle pattern imaging technique offers a remote, contactless, and low-cost alternative for monitoring cortical activity, enabling neuroimaging in environments where contact-based methods are impractical or MRI access is unfeasible. Aim We aim to develop a remote photonic technique for detecting human brain cortex activity by applying deep learning to the speckle pattern videos captured from specific brain cortex areas illuminated by a laser beam. Approach We enhance laser speckle pattern tracking with artificial intelligence (AI) to enable remote brain monitoring. In this study, a laser beam was projected onto Wernicke's area to detect brain responses to a clear and incomprehensible speech. The speckle pattern videos were analyzed using a convolutional long short-term memory-based deep neural network classifier. Results The classifier distinguished brain responses to a clear and incomprehensible speech in unseen subjects, achieving a mean area under the receiver operating characteristic curve (area under the curve) of 0.94 for classifications based on at least 1 s of input. Conclusions This remote method for distinguishing brain responses has practical applications in brain function research, medical monitoring, sports, and real-life scenarios, particularly for individuals sensitive to scalp contact or headgear.
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Affiliation(s)
- Natalya Segal
- Bar-Ilan University, Faculty of Engineering and the Nanotechnology Center, Ramat-Gan, Israel
| | - Zeev Kalyuzhner
- Bar-Ilan University, Faculty of Engineering and the Nanotechnology Center, Ramat-Gan, Israel
| | - Sergey Agdarov
- Bar-Ilan University, Faculty of Engineering and the Nanotechnology Center, Ramat-Gan, Israel
| | - Yafim Beiderman
- Bar-Ilan University, Faculty of Engineering and the Nanotechnology Center, Ramat-Gan, Israel
| | - Yevgeny Beiderman
- Holon Institute of Technology, Faculty of Electrical and Electronics Engineering, Holon, Israel
| | - Zeev Zalevsky
- Bar-Ilan University, Faculty of Engineering and the Nanotechnology Center, Ramat-Gan, Israel
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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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5
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Baghdadi G, Hadaeghi F, Kamarajan C. Editorial: Multimodal approaches to investigating neural dynamics in cognition and related clinical conditions: integrating EEG, MEG, and fMRI data. Front Syst Neurosci 2025; 19:1495018. [PMID: 40012906 PMCID: PMC11850518 DOI: 10.3389/fnsys.2025.1495018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2024] [Accepted: 01/28/2025] [Indexed: 02/28/2025] Open
Affiliation(s)
- Golnaz Baghdadi
- Biomedical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
| | - Fatemeh Hadaeghi
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, United States
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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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Curzel F, Tillmann B, Ferreri L. Lights on music cognition: A systematic and critical review of fNIRS applications and future perspectives. Brain Cogn 2024; 180:106200. [PMID: 38908228 DOI: 10.1016/j.bandc.2024.106200] [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: 04/06/2024] [Revised: 06/10/2024] [Accepted: 06/16/2024] [Indexed: 06/24/2024]
Abstract
Research investigating the neural processes related to music perception and production constitutes a well-established field within the cognitive neurosciences. While most neuroimaging tools have limitations in studying the complexity of musical experiences, functional Near-Infrared Spectroscopy (fNIRS) represents a promising, relatively new tool for studying music processes in both laboratory and ecological settings, which is also suitable for both typical and pathological populations across development. Here we systematically review fNIRS studies on music cognition, highlighting prospects and potentialities. We also include an overview of fNIRS basic theory, together with a brief comparison to characteristics of other neuroimaging tools. Fifty-nine studies meeting inclusion criteria (i.e., using fNIRS with music as the primary stimulus) are presented across five thematic sections. Critical discussion of methodology leads us to propose guidelines of good practices aiming for robust signal analyses and reproducibility. A continuously updated world map is proposed, including basic information from studies meeting the inclusion criteria. It provides an organized, accessible, and updatable reference database, which could serve as a catalyst for future collaborations within the community. In conclusion, fNIRS shows potential for investigating cognitive processes in music, particularly in ecological contexts and with special populations, aligning with current research priorities in music cognition.
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Affiliation(s)
- Federico Curzel
- Laboratoire d'Étude des Mécanismes Cognitifs (EMC), Université Lumière Lyon 2, Bron, Auvergne-Rhône-Alpes, 69500, France; Lyon Neuroscience Research Center (CRNL), INSERM, U1028, CNRS, UMR 5292, Université Claude Bernard Lyon1, Université de Lyon, Bron, Auvergne-Rhône-Alpes, 69500, France.
| | - Barbara Tillmann
- Lyon Neuroscience Research Center (CRNL), INSERM, U1028, CNRS, UMR 5292, Université Claude Bernard Lyon1, Université de Lyon, Bron, Auvergne-Rhône-Alpes, 69500, France; LEAD CNRS UMR5022, Université de Bourgogne-Franche Comté, Dijon, Bourgogne-Franche Comté 21000, France.
| | - Laura Ferreri
- Laboratoire d'Étude des Mécanismes Cognitifs (EMC), Université Lumière Lyon 2, Bron, Auvergne-Rhône-Alpes, 69500, France; Department of Brain and Behavioural Sciences, Università di Pavia, Pavia, Lombardia 27100, Italy.
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9
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Brickwedde M, Anders P, Kühn AA, Lofredi R, Holtkamp M, Kaindl AM, Grent-'t-Jong T, Krüger P, Sander T, Uhlhaas PJ. Applications of OPM-MEG for translational neuroscience: a perspective. Transl Psychiatry 2024; 14:341. [PMID: 39181883 PMCID: PMC11344782 DOI: 10.1038/s41398-024-03047-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 06/25/2024] [Accepted: 08/01/2024] [Indexed: 08/27/2024] Open
Abstract
Magnetoencephalography (MEG) allows the non-invasive measurement of brain activity at millisecond precision combined with localization of the underlying generators. So far, MEG-systems consisted of superconducting quantum interference devices (SQUIDS), which suffer from several limitations. Recent technological advances, however, have enabled the development of novel MEG-systems based on optically pumped magnetometers (OPMs), offering several advantages over conventional SQUID-MEG systems. Considering potential improvements in the measurement of neuronal signals as well as reduced operating costs, the application of OPM-MEG systems for clinical neuroscience and diagnostic settings is highly promising. Here we provide an overview of the current state-of-the art of OPM-MEG and its unique potential for translational neuroscience. First, we discuss the technological features of OPMs and benchmark OPM-MEG against SQUID-MEG and electroencephalography (EEG), followed by a summary of pioneering studies of OPMs in healthy populations. Key applications of OPM-MEG for the investigation of psychiatric and neurological conditions are then reviewed. Specifically, we suggest novel applications of OPM-MEG for the identification of biomarkers and circuit deficits in schizophrenia, dementias, movement disorders, epilepsy, and neurodevelopmental syndromes (autism spectrum disorder and attention deficit hyperactivity disorder). Finally, we give an outlook of OPM-MEG for translational neuroscience with a focus on remaining methodological and technical challenges.
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Affiliation(s)
- Marion Brickwedde
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Child and Adolescent Psychiatry, 13353, Berlin, Germany.
- Physikalisch-Technische Bundesanstalt, Berlin, Germany.
| | - Paul Anders
- Physikalisch-Technische Bundesanstalt, Berlin, Germany
| | - Andrea A Kühn
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Sektion für Bewegungsstörungen und Neuromodulation, Klinik für Neurologie und Experimentelle Neurologie, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Humboldt-Universität, Berlin, Germany
- NeuroCure, Exzellenzcluster, Charité-Universitätsmedizin Berlin, Berlin, Germany
- DZNE, German center for neurodegenerative diseases, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Roxanne Lofredi
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Sektion für Bewegungsstörungen und Neuromodulation, Klinik für Neurologie und Experimentelle Neurologie, 10117, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Martin Holtkamp
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Neurology, Epilepsy-Center Berlin-Brandenburg, 10117, Berlin, Germany
| | - Angela M Kaindl
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Pediatric Neurology, 13353, Berlin, Germany
- Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Center for Chronically Sick Children, 13353, Berlin, Germany
- Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Institute of Cell Biology and Neurobiology, 10117, Berlin, Germany
| | - Tineke Grent-'t-Jong
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Child and Adolescent Psychiatry, 13353, Berlin, Germany
- Institute for Neuroscience and Psychology, Glasgow University, Scotland, United Kingdom
| | - Peter Krüger
- Physikalisch-Technische Bundesanstalt, Berlin, Germany
| | | | - Peter J Uhlhaas
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Child and Adolescent Psychiatry, 13353, Berlin, Germany
- Institute for Neuroscience and Psychology, Glasgow University, Scotland, United Kingdom
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10
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Bardouille T, Smith V, Vajda E, Leslie CD, Holmes N. Noise Reduction and Localization Accuracy in a Mobile Magnetoencephalography System. SENSORS (BASEL, SWITZERLAND) 2024; 24:3503. [PMID: 38894294 PMCID: PMC11174973 DOI: 10.3390/s24113503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 05/17/2024] [Accepted: 05/21/2024] [Indexed: 06/21/2024]
Abstract
Magnetoencephalography (MEG) non-invasively provides important information about human brain electrophysiology. The growing use of optically pumped magnetometers (OPM) for MEG, as opposed to fixed arrays of cryogenic sensors, has opened the door for innovation in system design and use cases. For example, cryogenic MEG systems are housed in large, shielded rooms to provide sufficient space for the system dewar. Here, we investigate the performance of OPM recordings inside of a cylindrical shield with a 1 × 2 m2 footprint. The efficacy of shielding was measured in terms of field attenuation and isotropy, and the value of post hoc noise reduction algorithms was also investigated. Localization accuracy was quantified for 104 OPM sensors mounted on a fixed helmet array based on simulations and recordings from a bespoke current dipole phantom. Passive shielding attenuated the vector field magnitude to 50.0 nT at direct current (DC), to 16.7 pT/√Hz at power line, and to 71 fT/√Hz (median) in the 10-200 Hz range. Post hoc noise reduction provided an additional 5-15 dB attenuation. Substantial field isotropy remained in the volume encompassing the sensor array. The consistency of the isotropy over months suggests that a field nulling solution could be readily applied. A current dipole phantom generating source activity at an appropriate magnitude for the human brain generated field fluctuations on the order of 0.5-1 pT. Phantom signals were localized with 3 mm localization accuracy, and no significant bias in localization was observed, which is in line with performance for cryogenic and OPM MEG systems. This validation of the performance of a small footprint MEG system opens the door for lower-cost MEG installations in terms of raw materials and facility space, as well as mobile imaging systems (e.g., truck-based). Such implementations are relevant for global adoption of MEG outside of highly resourced research and clinical institutions.
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Affiliation(s)
- Timothy Bardouille
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS B3H 4R2, Canada; (V.S.); (E.V.); (C.D.L.)
| | - Vanessa Smith
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS B3H 4R2, Canada; (V.S.); (E.V.); (C.D.L.)
| | - Elias Vajda
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS B3H 4R2, Canada; (V.S.); (E.V.); (C.D.L.)
| | - Carson Drake Leslie
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS B3H 4R2, Canada; (V.S.); (E.V.); (C.D.L.)
| | - Niall Holmes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK;
- Cerca Magnetics Limited, Units 7–8 Castlebridge Office Village, Kirtley Drive, Nottingham NG7 1LD, UK
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11
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Yang Y, Luo S, Wang W, Gao X, Yao X, Wu T. From bench to bedside: Overview of magnetoencephalography in basic principle, signal processing, source localization and clinical applications. Neuroimage Clin 2024; 42:103608. [PMID: 38653131 PMCID: PMC11059345 DOI: 10.1016/j.nicl.2024.103608] [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: 11/22/2023] [Revised: 04/14/2024] [Accepted: 04/16/2024] [Indexed: 04/25/2024]
Abstract
Magnetoencephalography (MEG) is a non-invasive technique that can precisely capture the dynamic spatiotemporal patterns of the brain by measuring the magnetic fields arising from neuronal activity along the order of milliseconds. Observations of brain dynamics have been used in cognitive neuroscience, the diagnosis of neurological diseases, and the brain-computer interface (BCI). In this study, we outline the basic principle, signal processing, and source localization of MEG, and describe its clinical applications for cognitive assessment, the diagnoses of neurological diseases and mental disorders, preoperative evaluation, and the BCI. This review not only provides an overall perspective of MEG, ranging from practical techniques to clinical applications, but also enhances the prevalent understanding of neural mechanisms. The use of MEG is expected to lead to significant breakthroughs in neuroscience.
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Affiliation(s)
- Yanling Yang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China; College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Shichang Luo
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China; College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Wenjie Wang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China; College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
| | - Xiumin Gao
- School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Xufeng Yao
- College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China.
| | - Tao Wu
- College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai University of Medicine and Health Sciences, Shanghai, China
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12
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Wu H, Liang X, Wang R, Ma Y, Gao Y, Ning X. A Multivariate analysis on evoked components of Chinese semantic congruity: an OP-MEG study with EEG. Cereb Cortex 2024; 34:bhae108. [PMID: 38610084 DOI: 10.1093/cercor/bhae108] [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: 01/08/2024] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 04/14/2024] Open
Abstract
The application of wearable magnetoencephalography using optically-pumped magnetometers has drawn extensive attention in the field of neuroscience. Electroencephalogram system can cover the whole head and reflect the overall activity of a large number of neurons. The efficacy of optically-pumped magnetometer in detecting event-related components can be validated through electroencephalogram results. Multivariate pattern analysis is capable of tracking the evolution of neurocognitive processes over time. In this paper, we adopted a classical Chinese semantic congruity paradigm and separately collected electroencephalogram and optically-pumped magnetometer signals. Then, we verified the consistency of optically-pumped magnetometer and electroencephalogram in detecting N400 using mutual information index. Multivariate pattern analysis revealed the difference in decoding performance of these two modalities, which can be further validated by dynamic/stable coding analysis on the temporal generalization matrix. The results from searchlight analysis provided a neural basis for this dissimilarity at the magnetoencephalography source level and the electroencephalogram sensor level. This study opens a new avenue for investigating the brain's coding patterns using wearable magnetoencephalography and reveals the differences in sensitivity between the two modalities in reflecting neuron representation patterns.
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Affiliation(s)
- Huanqi Wu
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Hangzhou Institute of National Extremely-weak Magnetic Field Infrastructure, Hangzhou 310051, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Beijing 100191, China
| | - Xiaoyu Liang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Hangzhou Institute of National Extremely-weak Magnetic Field Infrastructure, Hangzhou 310051, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Beijing 100191, China
| | - Ruonan Wang
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Hangzhou Institute of National Extremely-weak Magnetic Field Infrastructure, Hangzhou 310051, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Beijing 100191, China
| | - Yuyu Ma
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Hangzhou Institute of National Extremely-weak Magnetic Field Infrastructure, Hangzhou 310051, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Beijing 100191, China
| | - Yang Gao
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Hangzhou Institute of National Extremely-weak Magnetic Field Infrastructure, Hangzhou 310051, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Beijing 100191, China
| | - Xiaolin Ning
- Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
- Hangzhou Institute of National Extremely-weak Magnetic Field Infrastructure, Hangzhou 310051, China
- Zhejiang Provincial Key Laboratory of Ultra-Weak Magnetic-Field Space and Applied Technology, Hangzhou Innovation Institute, Beihang University, Beijing 100191, China
- Shandong Key Laboratory for Magnetic Field-free Medicine & Functional Imaging, Institute of Magnetic Field-free Medicine & Functional Imaging, Shandong University, Shandong 264209, China
- Hefei National Laboratory, Anhui 230026, China
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13
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Zhao Q, Ye Z, Deng Y, Chen J, Chen J, Liu D, Ye X, Huan C. An advance in novel intelligent sensory technologies: From an implicit-tracking perspective of food perception. Compr Rev Food Sci Food Saf 2024; 23:e13327. [PMID: 38517017 DOI: 10.1111/1541-4337.13327] [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: 10/28/2023] [Revised: 02/19/2024] [Accepted: 03/01/2024] [Indexed: 03/23/2024]
Abstract
Food sensory evaluation mainly includes explicit and implicit measurement methods. Implicit measures of consumer perception are gaining significant attention in food sensory and consumer science as they provide effective, subconscious, objective analysis. A wide range of advanced technologies are now available for analyzing physiological and psychological responses, including facial analysis technology, neuroimaging technology, autonomic nervous system technology, and behavioral pattern measurement. However, researchers in the food field often lack systematic knowledge of these multidisciplinary technologies and struggle with interpreting their results. In order to bridge this gap, this review systematically describes the principles and highlights the applications in food sensory and consumer science of facial analysis technologies such as eye tracking, facial electromyography, and automatic facial expression analysis, as well as neuroimaging technologies like electroencephalography, magnetoencephalography, functional magnetic resonance imaging, and functional near-infrared spectroscopy. Furthermore, we critically compare and discuss these advanced implicit techniques in the context of food sensory research and then accordingly propose prospects. Ultimately, we conclude that implicit measures should be complemented by traditional explicit measures to capture responses beyond preference. Facial analysis technologies offer a more objective reflection of sensory perception and attitudes toward food, whereas neuroimaging techniques provide valuable insight into the implicit physiological responses during food consumption. To enhance the interpretability and generalizability of implicit measurement results, further sensory studies are needed. Looking ahead, the combination of different methodological techniques in real-life situations holds promise for consumer sensory science in the field of food research.
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Affiliation(s)
- Qian Zhao
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, China
| | - Zhiyue Ye
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, China
| | - Yong Deng
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, China
| | - Jin Chen
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
| | - Jianle Chen
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Zhongyuan Institute, Zhejiang University, Zhengzhou, China
- Ningbo Innovation Center, Zhejiang University, Ningbo, China
| | - Donghong Liu
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, China
- Zhongyuan Institute, Zhejiang University, Zhengzhou, China
- Ningbo Innovation Center, Zhejiang University, Ningbo, China
| | - Xingqian Ye
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Zhongyuan Institute, Zhejiang University, Zhengzhou, China
- Ningbo Innovation Center, Zhejiang University, Ningbo, China
| | - Cheng Huan
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, China
- Zhongyuan Institute, Zhejiang University, Zhengzhou, China
- Ningbo Innovation Center, Zhejiang University, Ningbo, China
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14
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Hillebrand A, Holmes N, Sijsma N, O'Neill GC, Tierney TM, Liberton N, Stam AH, van Klink N, Stam CJ, Bowtell R, Brookes MJ, Barnes GR. Non-invasive measurements of ictal and interictal epileptiform activity using optically pumped magnetometers. Sci Rep 2023; 13:4623. [PMID: 36944674 PMCID: PMC10030968 DOI: 10.1038/s41598-023-31111-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 03/06/2023] [Indexed: 03/23/2023] Open
Abstract
Magneto- and electroencephalography (MEG/EEG) are important techniques for the diagnosis and pre-surgical evaluation of epilepsy. Yet, in current cryogen-based MEG systems the sensors are offset from the scalp, which limits the signal-to-noise ratio (SNR) and thereby the sensitivity to activity from deep structures such as the hippocampus. This effect is amplified in children, for whom adult-sized fixed-helmet systems are typically too big. Moreover, ictal recordings with fixed-helmet systems are problematic because of limited movement tolerance and/or logistical considerations. Optically Pumped Magnetometers (OPMs) can be placed directly on the scalp, thereby improving SNR and enabling recordings during seizures. We aimed to demonstrate the performance of OPMs in a clinical population. Seven patients with challenging cases of epilepsy underwent MEG recordings using a 12-channel OPM-system and a 306-channel cryogen-based whole-head system: three adults with known deep or weak (low SNR) sources of interictal epileptiform discharges (IEDs), along with three children with focal epilepsy and one adult with frequent seizures. The consistency of the recorded IEDs across the two systems was assessed. In one patient the OPMs detected IEDs that were not found with the SQUID-system, and in two patients no IEDs were found with either system. For the other patients the OPM data were remarkably consistent with the data from the cryogenic system, noting that these were recorded in different sessions, with comparable SNRs and IED-yields overall. Importantly, the wearability of OPMs enabled the recording of seizure activity in a patient with hyperkinetic movements during the seizure. The observed ictal onset and semiology were in agreement with previous video- and stereo-EEG recordings. The relatively affordable technology, in combination with reduced running and maintenance costs, means that OPM-based MEG could be used more widely than current MEG systems, and may become an affordable alternative to scalp EEG, with the potential benefits of increased spatial accuracy, reduced sensitivity to volume conduction/field spread, and increased sensitivity to deep sources. Wearable MEG thus provides an unprecedented opportunity for epilepsy, and given its patient-friendliness, we envisage that it will not only be used for presurgical evaluation of epilepsy patients, but also for diagnosis after a first seizure.
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Affiliation(s)
- Arjan Hillebrand
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands.
- Brain Imaging, Amsterdam Neuroscience, Amsterdam, The Netherlands.
- Systems and Network Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands.
| | - Niall Holmes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Ndedi Sijsma
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands
| | - George C O'Neill
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Tim M Tierney
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Niels Liberton
- Department of Medical Technology, 3D Innovation Lab, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anine H Stam
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands
| | - Nicole van Klink
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands
- Brain Imaging, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Neurodegeneration, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Gareth R Barnes
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
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