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Chen H, Mirg S, Gaddale P, Agrawal S, Li M, Nguyen V, Xu T, Li Q, Liu J, Tu W, Liu X, Drew PJ, Zhang N, Gluckman BJ, Kothapalli S. Multiparametric Brain Hemodynamics Imaging Using a Combined Ultrafast Ultrasound and Photoacoustic System. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2401467. [PMID: 38884161 PMCID: PMC11336909 DOI: 10.1002/advs.202401467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 04/25/2024] [Indexed: 06/18/2024]
Abstract
Studying brain-wide hemodynamic responses to different stimuli at high spatiotemporal resolutions can help gain new insights into the mechanisms of neuro- diseases and -disorders. Nonetheless, this task is challenging, primarily due to the complexity of neurovascular coupling, which encompasses interdependent hemodynamic parameters including cerebral blood volume (CBV), cerebral blood flow (CBF), and cerebral oxygen saturation (SO2). The current brain imaging technologies exhibit inherent limitations in resolution, sensitivity, and imaging depth, restricting their capacity to comprehensively capture the intricacies of cerebral functions. To address this, a multimodal functional ultrasound and photoacoustic (fUSPA) imaging platform is reported, which integrates ultrafast ultrasound and multispectral photoacoustic imaging methods in a compact head-mountable device, to quantitatively map individual dynamics of CBV, CBF, and SO2 as well as contrast agent enhanced brain imaging at high spatiotemporal resolutions. Following systematic characterization, the fUSPA system is applied to study brain-wide cerebrovascular reactivity (CVR) at single-vessel resolution via relative changes in CBV, CBF, and SO2 in response to hypercapnia stimulation. These results show that cortical veins and arteries exhibit differences in CVR in the stimulated state and consistent anti-correlation in CBV oscillations during the resting state, demonstrating the multiparametric fUSPA system's unique capabilities in investigating complex mechanisms of brain functions.
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Affiliation(s)
- Haoyang Chen
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Shubham Mirg
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Prameth Gaddale
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Sumit Agrawal
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Menghan Li
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Van Nguyen
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Tianbao Xu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Qiong Li
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Jinyun Liu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Wenyu Tu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Xiao Liu
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Institute for Computational and Data SciencesThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Patrick J. Drew
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of Engineering Science and MechanicsThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of BiologyThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of NeurosurgeryThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Nanyin Zhang
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Bruce J. Gluckman
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of Engineering Science and MechanicsThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Department of NeurosurgeryThe Pennsylvania State UniversityUniversity ParkPA16802USA
| | - Sri‐Rajasekhar Kothapalli
- Department of Biomedical EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Center for Neural EngineeringThe Pennsylvania State UniversityUniversity ParkPA16802USA
- Penn State Cancer InstituteThe Pennsylvania State UniversityHersheyPA17033USA
- Graduate Program in AcousticsThe Pennsylvania State UniversityUniversity ParkPA16802USA
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2
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Sanchez-Rodriguez LM, Bezgin G, Carbonell F, Therriault J, Fernandez-Arias J, Servaes S, Rahmouni N, Tissot C, Stevenson J, Karikari TK, Ashton NJ, Benedet AL, Zetterberg H, Blennow K, Triana-Baltzer G, Kolb HC, Rosa-Neto P, Iturria-Medina Y. Personalized whole-brain neural mass models reveal combined Aβ and tau hyperexcitable influences in Alzheimer's disease. Commun Biol 2024; 7:528. [PMID: 38704445 PMCID: PMC11069569 DOI: 10.1038/s42003-024-06217-2] [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: 08/24/2023] [Accepted: 04/19/2024] [Indexed: 05/06/2024] Open
Abstract
Neuronal dysfunction and cognitive deterioration in Alzheimer's disease (AD) are likely caused by multiple pathophysiological factors. However, mechanistic evidence in humans remains scarce, requiring improved non-invasive techniques and integrative models. We introduce personalized AD computational models built on whole-brain Wilson-Cowan oscillators and incorporating resting-state functional MRI, amyloid-β (Aβ) and tau-PET from 132 individuals in the AD spectrum to evaluate the direct impact of toxic protein deposition on neuronal activity. This subject-specific approach uncovers key patho-mechanistic interactions, including synergistic Aβ and tau effects on cognitive impairment and neuronal excitability increases with disease progression. The data-derived neuronal excitability values strongly predict clinically relevant AD plasma biomarker concentrations (p-tau217, p-tau231, p-tau181, GFAP) and grey matter atrophy obtained through voxel-based morphometry. Furthermore, reconstructed EEG proxy quantities show the hallmark AD electrophysiological alterations (theta band activity enhancement and alpha reductions) which occur with Aβ-positivity and after limbic tau involvement. Microglial activation influences on neuronal activity are less definitive, potentially due to neuroimaging limitations in mapping neuroprotective vs detrimental activation phenotypes. Mechanistic brain activity models can further clarify intricate neurodegenerative processes and accelerate preventive/treatment interventions.
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Affiliation(s)
- Lazaro M Sanchez-Rodriguez
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, QC, Canada
| | - Gleb Bezgin
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | | | - Joseph Therriault
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Jaime Fernandez-Arias
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Stijn Servaes
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Nesrine Rahmouni
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Cécile Tissot
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
- Lawrence Berkeley National Laboratory, Berkeley, USA
| | - Jenna Stevenson
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Andréa L Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | | | - Hartmuth C Kolb
- Neuroscience Biomarkers, Janssen Research & Development, La Jolla, CA, USA
| | - Pedro Rosa-Neto
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, QC, Canada
| | - Yasser Iturria-Medina
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada.
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada.
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, QC, Canada.
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Gomez DEP, Polimeni JR, Lewis LD. The temporal specificity of BOLD fMRI is systematically related to anatomical and vascular features of the human brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.01.578428. [PMID: 38352610 PMCID: PMC10862860 DOI: 10.1101/2024.02.01.578428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
The ability to detect fast responses with functional MRI depends on the speed of hemodynamic responses to neural activity, because hemodynamic responses act as a temporal low-pass filter smoothing out rapid changes. However, hemodynamic responses (their shape and timing) are highly variable across the brain and across stimuli. This heterogeneity of responses implies that the temporal specificity of fMRI signals, or the ability of fMRI to preserve fast information, should also vary substantially across the cortex. In this work we investigated how local differences in hemodynamic response timing impact the temporal specificity of fMRI. We conducted our research using ultra-high field (7T) fMRI at high spatiotemporal resolution, using the primary visual cortex (V1) as a model area for investigation. We used visual stimuli oscillating at slow and fast frequencies to probe the temporal specificity of individual voxels. As expected, we identified substantial variability in temporal specificity, with some voxels preserving their responses to fast neural activity more effectively than others. We investigated which voxels had the highest temporal specificity and related those to anatomical and vascular features of V1. We found that low temporal specificity is only weakly explained by the presence of large veins or cerebral cortical depth. Notably, however, temporal specificity depended strongly on a voxel's position along the anterior-posterior anatomical axis of V1, with voxels within the calcarine sulcus being capable of preserving close to 25% of their amplitude as the frequency of stimulation increased from 0.05-Hz to 0.20-Hz, and voxels nearest to the occipital pole preserving less than 18%. These results indicate that detection biases in high-resolution fMRI will depend on the anatomical and vascular features of the area being imaged, and that these biases will differ depending on the timing of the underlying neuronal activity. Importantly, this spatial heterogeneity of temporal specificity suggests that it could be exploited to achieve higher specificity in some locations, and that tailored data analysis strategies may help improve the detection and interpretation of fast fMRI responses.
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Affiliation(s)
- Daniel E. P. Gomez
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Laura D. Lewis
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States
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4
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Sanchez-Rodriguez LM, Bezgin G, Carbonell F, Therriault J, Fernandez-Arias J, Servaes S, Rahmouni N, Tissot C, Stevenson J, Karikari TK, Ashton NJ, Benedet AL, Zetterberg H, Blennow K, Triana-Baltzer G, Kolb HC, Rosa-Neto P, Iturria-Medina Y. Revealing the combined roles of Aβ and tau in Alzheimer's disease via a pathophysiological activity decoder. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.21.529377. [PMID: 37502947 PMCID: PMC10370127 DOI: 10.1101/2023.02.21.529377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Neuronal dysfunction and cognitive deterioration in Alzheimer's disease (AD) are likely caused by multiple pathophysiological factors. However, evidence in humans remains scarce, necessitating improved non-invasive techniques and integrative mechanistic models. Here, we introduce personalized brain activity models incorporating functional MRI, amyloid-β (Aβ) and tau-PET from AD-related participants ( N = 132 ) . Within the model assumptions, electrophysiological activity is mediated by toxic protein deposition. Our integrative subject-specific approach uncovers key patho-mechanistic interactions, including synergistic Aβ and tau effects on cognitive impairment and neuronal excitability increases with disease progression. The data-derived neuronal excitability values strongly predict clinically relevant AD plasma biomarker concentrations (p-tau217, p-tau231, p-tau181, GFAP). Furthermore, our results reproduce hallmark AD electrophysiological alterations (theta band activity enhancement and alpha reductions) which occur with Aβ-positivity and after limbic tau involvement. Microglial activation influences on neuronal activity are less definitive, potentially due to neuroimaging limitations in mapping neuroprotective vs detrimental phenotypes. Mechanistic brain activity models can further clarify intricate neurodegenerative processes and accelerate preventive/treatment interventions.
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Affiliation(s)
- Lazaro M. Sanchez-Rodriguez
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada
| | - Gleb Bezgin
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, Canada
| | | | - Joseph Therriault
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, Canada
| | - Jaime Fernandez-Arias
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, Canada
| | - Stijn Servaes
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, Canada
| | - Nesrine Rahmouni
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, Canada
| | - Cecile Tissot
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, Canada
| | - Jenna Stevenson
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, Canada
| | - Thomas K. Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl Institute Clinical Neuroscience Institute London UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation London UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Andréa L. Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal
| | | | - Hartmuth C. Kolb
- Neuroscience Biomarkers, Janssen Research & Development, La Jolla, California, USA
| | - Pedro Rosa-Neto
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- McGill University Research Centre for Studies in Aging, Douglas Research Centre, Montreal, Canada
| | - Yasser Iturria-Medina
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada
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Abstract
Pain is an unpleasant sensory and emotional experience. Understanding the neural mechanisms of acute and chronic pain and the brain changes affecting pain factors is important for finding pain treatment methods. The emergence and progress of non-invasive neuroimaging technology can help us better understand pain at the neural level. Recent developments in identifying brain-based biomarkers of pain through advances in advanced imaging can provide some foundations for predicting and detecting pain. For example, a neurologic pain signature (involving brain regions that receive nociceptive afferents) and a stimulus intensity-independent pain signature (involving brain regions that do not show increased activity in proportion to noxious stimulus intensity) were developed based on multivariate modeling to identify processes related to the pain experience. However, an accurate and comprehensive review of common neuroimaging techniques for evaluating pain is lacking. This paper reviews the mechanism, clinical application, reliability, strengths, and limitations of common neuroimaging techniques for assessing pain to promote our further understanding of pain.
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Affiliation(s)
- Jing Luo
- Department of Sport Rehabilitation, Xian Physical Education University, Xian, China
- Department of Sport Rehabilitation, Shanghai University of Sport, Shanghai, China
| | - Hui-Qi Zhu
- Department of Sport Rehabilitation, Shanghai University of Sport, Shanghai, China
- Department of Sport Rehabilitation, Shenyang Sport University, Shenyang, China
| | - Bo Gou
- Department of Sport Rehabilitation, Xian Physical Education University, Xian, China.
| | - Xue-Qiang Wang
- Department of Sport Rehabilitation, Shanghai University of Sport, Shanghai, China.
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Chen JJ, Uthayakumar B, Hyder F. Mapping oxidative metabolism in the human brain with calibrated fMRI in health and disease. J Cereb Blood Flow Metab 2022; 42:1139-1162. [PMID: 35296177 PMCID: PMC9207484 DOI: 10.1177/0271678x221077338] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Conventional functional MRI (fMRI) with blood-oxygenation level dependent (BOLD) contrast is an important tool for mapping human brain activity non-invasively. Recent interest in quantitative fMRI has renewed the importance of oxidative neuroenergetics as reflected by cerebral metabolic rate of oxygen consumption (CMRO2) to support brain function. Dynamic CMRO2 mapping by calibrated fMRI require multi-modal measurements of BOLD signal along with cerebral blood flow (CBF) and/or volume (CBV). In human subjects this "calibration" is typically performed using a gas mixture containing small amounts of carbon dioxide and/or oxygen-enriched medical air, which are thought to produce changes in CBF (and CBV) and BOLD signal with minimal or no CMRO2 changes. However non-human studies have demonstrated that the "calibration" can also be achieved without gases, revealing good agreement between CMRO2 changes and underlying neuronal activity (e.g., multi-unit activity and local field potential). Given the simpler set-up of gas-free calibrated fMRI, there is evidence of recent clinical applications for this less intrusive direction. This up-to-date review emphasizes technological advances for such translational gas-free calibrated fMRI experiments, also covering historical progression of the calibrated fMRI field that is impacting neurological and neurodegenerative investigations of the human brain.
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Affiliation(s)
- J Jean Chen
- Medical Biophysics, University of Toronto, Toronto, Canada.,Rotman Research Institute, Baycrest, Toronto, Canada
| | - Biranavan Uthayakumar
- Medical Biophysics, University of Toronto, Toronto, Canada.,Sunnybrook Research Institute, Toronto, Canada
| | - Fahmeed Hyder
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, Connecticut, USA.,Department of Radiology, Yale University, New Haven, Connecticut, USA.,Quantitative Neuroscience with Magnetic Resonance (QNMR) Research Program, Yale University, New Haven, Connecticut, USA.,Department of Biomedical Engineering, Yale University, New Haven, Connecticut, USA
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7
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Schneider SC, Archila-Meléndez ME, Göttler J, Kaczmarz S, Zott B, Priller J, Kallmayer M, Zimmer C, Sorg C, Preibisch C. Resting-state BOLD functional connectivity depends on the heterogeneity of capillary transit times in the human brain A combined lesion and simulation study about the influence of blood flow response timing. Neuroimage 2022; 255:119208. [PMID: 35427773 DOI: 10.1016/j.neuroimage.2022.119208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 02/23/2022] [Accepted: 04/11/2022] [Indexed: 11/25/2022] Open
Abstract
Functional connectivity (FC) derived from blood oxygenation level dependent (BOLD) functional magnetic resonance imaging at rest (rs-fMRI), is commonly interpreted as indicator of neuronal connectivity. In a number of brain disorders, however, metabolic, vascular, and hemodynamic impairments can be expected to alter BOLD-FC independently from neuronal activity. By means of a neurovascular coupling (NVC) model of BOLD-FC, we recently demonstrated that aberrant timing of cerebral blood flow (CBF) responses may influence BOLD-FC. In the current work, we support and extend this finding by empirically linking BOLD-FC with capillary transit time heterogeneity (CTH), which we consider as an indicator of delayed and broadened CBF responses. We assessed 28 asymptomatic patients with unilateral high-grade internal carotid artery stenosis (ICAS) as a hemodynamic lesion model with largely preserved neurocognitive functioning and 27 age-matched healthy controls. For each participant, we obtained rs-fMRI, arterial spin labeling, and dynamic susceptibility contrast MRI to study the dependence of left-right homotopic BOLD-FC on local perfusion parameters. Additionally, we investigated the dependency of BOLD-FC on CBF response timing by detailed simulations. Homotopic BOLD-FC was negatively associated with increasing CTH differences between homotopic brain areas. This relation was more pronounced in asymptomatic ICAS patients even after controlling for baseline CBF and relative cerebral blood volume influences. These findings match simulation results that predict an influence of delayed and broadened CBF responses on BOLD-FC. Results demonstrate that increasing CTH differences between homotopic brain areas lead to BOLD-FC reductions. Simulations suggest that CTH increases correspond to broadened and delayed CBF responses to fluctuations in ongoing neuronal activity.
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Affiliation(s)
- Sebastian C Schneider
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675, Munich, Germany
| | - Mario E Archila-Meléndez
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675, Munich, Germany
| | - Jens Göttler
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675, Munich, Germany
| | - Stephan Kaczmarz
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675, Munich, Germany; Philips GmbH Market DACH, Hamburg, Germany
| | - Benedikt Zott
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675, Munich, Germany
| | - Josef Priller
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Psychiatry, Ismaningerstr. 22, 81675, Munich, Munich, Germany
| | - Michael Kallmayer
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Vascular and Endovascular Surgery, Ismaningerstr. 22, 81675, Munich, Munich, Germany
| | - Claus Zimmer
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675, Munich, Germany
| | - Christian Sorg
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675, Munich, Germany
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Ismaningerstr. 22, 81675, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Ismaningerstr. 22, 81675, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Neurology, Ismaningerstr. 22, 81675, Munich, Munich, Germany.
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8
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Polimeni JR, Lewis LD. Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response. Prog Neurobiol 2021; 207:102174. [PMID: 34525404 PMCID: PMC8688322 DOI: 10.1016/j.pneurobio.2021.102174] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 07/30/2021] [Accepted: 09/08/2021] [Indexed: 12/20/2022]
Abstract
Fast fMRI enables the detection of neural dynamics over timescales of hundreds of milliseconds, suggesting it may provide a new avenue for studying subsecond neural processes in the human brain. The magnitudes of these fast fMRI dynamics are far greater than predicted by canonical models of the hemodynamic response. Several studies have established nonlinear properties of the hemodynamic response that have significant implications for fast fMRI. We first review nonlinear properties of the hemodynamic response function that may underlie fast fMRI signals. We then illustrate the breakdown of canonical hemodynamic response models in the context of fast neural dynamics. We will then argue that the canonical hemodynamic response function is not likely to reflect the BOLD response to neuronal activity driven by sparse or naturalistic stimuli or perhaps to spontaneous neuronal fluctuations in the resting state. These properties suggest that fast fMRI is capable of tracking surprisingly fast neuronal dynamics, and we discuss the neuroscientific questions that could be addressed using this approach.
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Affiliation(s)
- Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Laura D Lewis
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Biomedical Engineering, Boston University, Boston, MA, USA.
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9
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Cao S, Zhang J, Chen C, Wang X, Ji Y, Nie J, Tian Y, Qiu B, Wei Q, Wang K. Decline in executive function in patients with white matter hyperintensities from the static and dynamic perspectives of amplitude of low-frequency fluctuations. J Neurosci Res 2021; 99:2793-2803. [PMID: 34510531 DOI: 10.1002/jnr.24956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 07/29/2021] [Accepted: 08/18/2021] [Indexed: 11/10/2022]
Abstract
Cognitive impairments are characteristics of patients with white matter hyperintensities (WMHs), and hypoperfusion is currently a relatively recognized mechanism of WMHs. Brain activity is closely coupled to the regulation of local blood flow. This study aimed to investigate the abnormal local brain activity of patients with WMHs from the viewpoint of the static amplitude of low-frequency fluctuations (sALFF) and dynamic amplitude of low-frequency fluctuations (dALFF). Seventy-four patients with WMHs and 35 healthy controls (HCs) were included. Based on the Fazekas scale, patients with WMHs were further divided into a mild WMH group (n = 33, Fazekas score 1-2) and moderate-severe WMH group (n = 41, Fazekas score 3-6). The sALFF and dALFF values were calculated separately and neuropsychological tests including the Montreal Cognitive Assessment (MoCA), Auditory Verbal Learning Test (AVLT), Trail Making Test (TMT), and Boston Naming Test (BNT) were completed by all participants. Patients with WMHs showed increased sALFF and dALFF values in the bilateral thalamus and decreased performance in the MoCA test, AVLT-immediate, AVLT-delay, AVLT-recognition, TMT-A, and BNT. The dALFF values in the bilateral thalamus was correlated with the MoCA in HCs. The sALFF values in the bilateral thalamus correlated with TMT-B in patients with WMHs. Patients with WMHs showed abnormal brain activity and decreased functional stability of the bilateral thalamus, which may be a potential mechanism of decreased executive function.
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Affiliation(s)
- Shanshan Cao
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Jun Zhang
- Department of Neurology, the Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Chen Chen
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Xiaojing Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Yang Ji
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Jiajia Nie
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
| | - Yanghua Tian
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,The College of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Bensheng Qiu
- Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Qiang Wei
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
| | - Kai Wang
- Department of Neurology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.,Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China.,The College of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, China.,Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.,Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei, China
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10
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Hawkins PCT, Zelaya FO, O'Daly O, Holiga S, Dukart J, Umbricht D, Mehta MA. The effect of risperidone on reward-related brain activity is robust to drug-induced vascular changes. Hum Brain Mapp 2021; 42:2766-2777. [PMID: 33666305 PMCID: PMC8127149 DOI: 10.1002/hbm.25400] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 01/22/2021] [Accepted: 02/16/2021] [Indexed: 12/20/2022] Open
Abstract
Dopamine (DA) mediated brain activity is intimately linked to reward‐driven cerebral responses, while aberrant reward processing has been implicated in several psychiatric disorders. fMRI has been a valuable tool in understanding the mechanism by which DA modulators alter reward‐driven responses and how they may exert their therapeutic effect. However, the potential effects of a pharmacological compound on aspects of neurovascular coupling may cloud the interpretability of the BOLD contrast. Here, we assess the effects of risperidone on reward driven BOLD signals produced by reward anticipation and outcome, while attempting to control for potential drug effects on regional cerebral blood flow (CBF) and cerebrovascular reactivity (CVR). Healthy male volunteers (n = 21) each received a single oral dose of either 0.5 mg, 2 mg of risperidone or placebo in a double‐blind, placebo‐controlled, randomised, three‐period cross‐over study design. Participants underwent fMRI scanning while performing the widely used Monetary Incentive Delay (MID) task to assess drug impact on reward function. Measures of CBF (Arterial Spin Labelling) and breath‐hold challenge induced BOLD signal changes (as a proxy for CVR) were also acquired and included as covariates. Risperidone produced divergent, dose‐dependent effects on separate phases of reward processing, even after controlling for potential nonneuronal influences on the BOLD signal. These data suggest the D2 antagonist risperidone has a wide‐ranging influence on DA‐mediated reward function independent of nonneuronal factors. We also illustrate that assessment of potential vascular confounds on the BOLD signal may be advantageous when investigating CNS drug action and advocate for the inclusion of these additional measures into future study designs.
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Affiliation(s)
- Peter C T Hawkins
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Fernando O Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Owen O'Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Stefan Holiga
- Roche Pharma Research and Early Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Juergen Dukart
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Daniel Umbricht
- Roche Pharma Research and Early Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Mitul A Mehta
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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11
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Zou P, Scoggins MA, Li Y, Jones M, Helton KJ, Ogg RJ. Developmental patterns of CBF and BOLD responses to visual stimulus. J Cereb Blood Flow Metab 2021; 41:630-640. [PMID: 32436777 PMCID: PMC7922748 DOI: 10.1177/0271678x20925303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
To investigate the developmental changes of cerebral blood flow (CBF) and hemodynamic responses to changing neural activity, we used the arterial spin label (ASL) technique to measure resting CBF and simultaneous CBF / blood-oxygen-level dependent (BOLD) signal changes during visual stimulation in 97 typically developing children and young adults (age 13.35 [6.02, 25.25] (median [min, max]) years old at the first time point). The longitudinal study protocol included three MRIs (2.7 ± 0.06 obtained), one year apart, for each participant. Mixed-effect linear and non-linear statistical models were used to analyze age effects on CBF and BOLD signals. Resting CBF decreased exponentially with age (p = 0.0001) throughout the brain, and developmental trajectories differed across brain lobes. The absolute CBF increase in visual cortex during stimulation was constant over the age range, but the fractional CBF change increased with age (p = 0.0001) and the fractional BOLD signal increased with age (p = 0.0001) correspondingly. These findings suggest that the apparent neural hemodynamic coupling in visual cortex does not change after age six years, but age-related BOLD signal changes continue through adolescence primarily due to the changes with age in resting CBF.
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Affiliation(s)
- Ping Zou
- Departments of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Matthew A Scoggins
- Departments of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Yimei Li
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Melissa Jones
- Departments of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Kathleen J Helton
- Departments of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Robert J Ogg
- Departments of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, USA
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12
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Hubbard NA, Turner MP, Sitek KR, West KL, Kaczmarzyk JR, Himes L, Thomas BP, Lu H, Rypma B. Resting cerebral oxygen metabolism exhibits archetypal network features. Hum Brain Mapp 2021; 42:1952-1968. [PMID: 33544446 PMCID: PMC8046048 DOI: 10.1002/hbm.25352] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 12/04/2020] [Accepted: 01/12/2021] [Indexed: 12/23/2022] Open
Abstract
Standard magnetic resonance imaging approaches offer high‐resolution but indirect measures of neural activity, limiting understanding of the physiological processes associated with imaging findings. Here, we used calibrated functional magnetic resonance imaging during the resting state to recover low‐frequency fluctuations of the cerebral metabolic rate of oxygen (CMRO2). We tested whether functional connections derived from these fluctuations exhibited organization properties similar to those established by previous standard functional and anatomical connectivity studies. Seventeen participants underwent 20 min of resting imaging during dual‐echo, pseudocontinuous arterial spin labeling, and blood‐oxygen‐level dependent (BOLD) signal acquisition. Participants also underwent a 10 min normocapnic and hypercapnic procedure. Brain‐wide, CMRO2 low‐frequency fluctuations were subjected to graph‐based and voxel‐wise functional connectivity analyses. Results demonstrated that connections derived from resting CMRO2 fluctuations exhibited complex, small‐world topological properties (i.e., high integration and segregation, cost efficiency) consistent with those observed in previous studies using functional and anatomical connectivity approaches. Voxel‐wise CMRO2 connectivity also exhibited spatial patterns consistent with four targeted resting‐state subnetworks: two association (i.e., frontoparietal and default mode) and two perceptual (i.e., auditory and occipital‐visual). These are the first findings to support the use of calibration‐derived CMRO2 low‐frequency fluctuations for detecting brain‐wide organizational properties typical of healthy participants. We discuss interpretations, advantages, and challenges in using calibration‐derived oxygen metabolism signals for examining the intrinsic organization of the human brain.
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Affiliation(s)
- Nicholas A Hubbard
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,Center for Brain, Biology, and Behavior, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Monroe P Turner
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, USA
| | - Kevin R Sitek
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts, USA
| | - Kathryn L West
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, USA
| | - Jakub R Kaczmarzyk
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Lyndahl Himes
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, USA
| | - Binu P Thomas
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, USA.,Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Hanzhang Lu
- Department of Radiology, John's Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Bart Rypma
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Texas, USA.,Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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13
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Slutsky-Ganesh AB, Etnier JL, Labban JD. Acute exercise, memory, and neural activation in young adults. Int J Psychophysiol 2020; 158:299-309. [PMID: 33164850 DOI: 10.1016/j.ijpsycho.2020.09.018] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 09/03/2020] [Accepted: 09/09/2020] [Indexed: 01/13/2023]
Abstract
Acute exercise benefits memory, and the temporal placement of exercise relative to exposure can affect the magnitude of benefits observed. Although the temporal placement appears to be important, there is a limited understanding as to how cognitive benefits in response to acute exercise are achieved. Hence, we conducted a two-part study including a behavioral study and a follow-up functional magnetic resonance imaging (fMRI) study to advance our understanding of the potential role of the effects of exercise on memory and neural activation. For Study One, we assessed the effect of acute exercise on memory in young adults. Participants were randomized to exercise before exposure for 20 min (before only, BO), after exposure for 20 min (After Only, AO), before and after exposure for 10 min at each time (before and after, BA), or to receive no exercise (No-exercise Control, NC). Similar to previous findings, any exercise prior to exposure (BO, BA) benefited some aspects of memory performance. Interestingly, the more consistent and larger benefits were seen with a shorter duration of exercise both before and after exposure (BA). Study Two replicated the methods of Study One comparing the BA condition (which had the most robust benefits) to the NC condition while collecting fMRI data during the memory task. Analyses assessed condition differences of activation during encoding and recall. There were no condition differences during memory encoding, however there was a condition effect on activation in occipito-temporal regions during the memory recall trials. Consistent with previous research, exercise appears to benefit memory with some exercise prior to exposure being important for the benefits achieved. Further, exercise affects neural activation and the results appear complementary to the behavior findings. Future research should use a within-subjects design to control for heterogeneity in behavior and neural activation.
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Affiliation(s)
| | - Jennifer L Etnier
- University of North Carolina at Greensboro, Greensboro, NC, United States of America
| | - Jeffrey D Labban
- University of North Carolina at Greensboro, Greensboro, NC, United States of America
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14
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Sasai S, Koike T, Sugawara SK, Hamano YH, Sumiya M, Okazaki S, Takahashi HK, Taga G, Sadato N. Frequency-specific task modulation of human brain functional networks: A fast fMRI study. Neuroimage 2020; 224:117375. [PMID: 32950690 DOI: 10.1016/j.neuroimage.2020.117375] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 09/02/2020] [Accepted: 09/11/2020] [Indexed: 12/20/2022] Open
Abstract
How coherent neural oscillations are involved in task execution is a fundamental question in neuroscience. Although several electrophysiological studies have tackled this issue, the brain-wide task modulation of neural coherence remains uncharacterized. Here, with a fast fMRI technique, we studied shifts of brain-wide neural coherence across different task states in the ultraslow frequency range (0.01-0.7 Hz). First, we examined whether the shifts of the brain-wide neural coherence occur in a frequency-dependent manner. We quantified the shift of a region's average neural coherence by the inter-state variance of the mean coherence between the region and the rest of the brain. A clustering analysis based on the variance's spatial correlation between frequency components revealed four frequency bands (0.01-0.15 Hz, 0.15-0.37 Hz, 0.37-0.53 Hz, and 0.53-0.7 Hz) showing band-specific shifts of the brain-wide neural coherence. Next, we investigated the similarity of the inter-state variance's spectra between all pairs of regions. We found that regions showing similar spectra correspond to those forming functional modules of the brain network. Then, we investigated the relationship between identified frequency bands and modules' inter-state variances. We found that modules showing the highest variance are those made up of parieto-occipital regions at 0.01-0.15 Hz, while it is replaced with another consisting of frontal regions above 0.15 Hz. Furthermore, these modules showed specific shifting patterns of the mean coherence across states at 0.01-0.15 Hz and above 0.15 Hz, suggesting that identified frequency bands differentially contribute to neural interactions during task execution. Our results highlight that usage of the fast fMRI enables brain-wide investigation of neural coherence up to 0.7 Hz, which opens a promising track for assessment of the large-scale neural interactions in the ultraslow frequency range.
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Affiliation(s)
- Shuntaro Sasai
- Department of Psychiatry, University of Wisconsin-Madison, Madison, USA.
| | - Takahiko Koike
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi, Japan; Department of Physiological Sciences, School of Life Sciences, SOKENDAI (The Graduate University for Advanced Studies), Kanagawa, Japan
| | - Sho K Sugawara
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi, Japan; Neural prosthesis project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Yuki H Hamano
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi, Japan; Department of Physiological Sciences, School of Life Sciences, SOKENDAI (The Graduate University for Advanced Studies), Kanagawa, Japan
| | - Motofumi Sumiya
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi, Japan; Department of Cognitive and Psychological Sciences, Graduate School of Informatics, Nagoya University, Aichi, Japan; Japan Society for the Promotion of Science, Tokyo, Japan
| | - Shuntaro Okazaki
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi, Japan
| | - Haruka K Takahashi
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi, Japan
| | - Gentaro Taga
- Graduate School of Education, The University of Tokyo, Tokyo, Japan
| | - Norihiro Sadato
- Division of Cerebral Integration, Department of System Neuroscience, National Institute for Physiological Sciences (NIPS), Aichi, Japan; Department of Physiological Sciences, School of Life Sciences, SOKENDAI (The Graduate University for Advanced Studies), Kanagawa, Japan.
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15
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Archila-Meléndez ME, Sorg C, Preibisch C. Modeling the impact of neurovascular coupling impairments on BOLD-based functional connectivity at rest. Neuroimage 2020; 218:116871. [DOI: 10.1016/j.neuroimage.2020.116871] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 04/17/2020] [Accepted: 04/20/2020] [Indexed: 12/12/2022] Open
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16
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Knolle F, Garofalo S, Viviani R, Justicia A, Ermakova AO, Blank H, Williams GB, Arrondo G, Ramachandra P, Tudor-Sfetea C, Bunzeck N, Duezel E, Robbins TW, Barker RA, Murray GK. Altered subcortical emotional salience processing differentiates Parkinson's patients with and without psychotic symptoms. NEUROIMAGE-CLINICAL 2020; 27:102277. [PMID: 32540629 PMCID: PMC7298672 DOI: 10.1016/j.nicl.2020.102277] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 03/30/2020] [Accepted: 05/05/2020] [Indexed: 01/03/2023]
Abstract
Emotional salience processing differentiates PD patients with and without psychosis. Enhanced striatal, hippocampal and midbrain responses in PD patients with psychosis. Indication for ‘jumping to conclusions’ bias in the same PD patients with psychosis. Aberrant top-down and salience processing associated with PD psychosis. Similar deficits as proposed in ‘aberrant salience hypothesis’ of schizophrenia.
Objective Current research does not provide a clear explanation for why some patients with Parkinson’s Disease (PD) develop psychotic symptoms. The ‘aberrant salience hypothesis’ of psychosis has been influential and proposes that dopaminergic dysregulation leads to inappropriate attribution of salience to irrelevant/non-informative stimuli, facilitating the formation of hallucinations and delusions. The aim of this study is to investigate whether non-motivational salience is altered in PD patients and possibly linked to the development of psychotic symptoms. Methods We investigated salience processing in 14 PD patients with psychotic symptoms, 23 PD patients without psychotic symptoms and 19 healthy controls. All patients were on dopaminergic medication for their PD. We examined emotional salience using a visual oddball fMRI paradigm that has been used to investigate early stages of schizophrenia spectrum psychosis, controlling for resting cerebral blood flow as assessed with arterial spin labelling fMRI. Results We found significant differences between patient groups in brain responses to emotional salience. PD patients with psychotic symptoms had enhanced brain responses in the striatum, dopaminergic midbrain, hippocampus and amygdala compared to patients without psychotic symptoms. PD patients with psychotic symptoms showed significant correlations between the levels of dopaminergic drugs they were taking and BOLD signalling, as well as psychotic symptom scores. Conclusion Our study suggests that enhanced signalling in the striatum, dopaminergic midbrain, the hippocampus and amygdala is associated with the development of psychotic symptoms in PD, in line with that proposed in the ‘aberrant salience hypothesis’ of psychosis in schizophrenia.
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Affiliation(s)
- F Knolle
- Department of Psychiatry, University of Cambridge, Cambridge, UK; Department of Neuroradiology, Technical University Munich, Munich, Germany.
| | - S Garofalo
- University of Bologna, Department of Psychology, Bologna, Italy
| | - R Viviani
- Institute of Psychology, University of Innsbruck, Innsbruck, Austria; Psychiatry and Psychotherapy Clinic III, University of Ulm, Ulm, Germany
| | - A Justicia
- Department of Psychiatry, University of Cambridge, Cambridge, UK; IMIM (Hospital del Mar Medical Research Institute), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Barcelona, Spain
| | - A O Ermakova
- Faculty of Natural Sciences, Imperial College London, UK
| | - H Blank
- Institute of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - G B Williams
- Department of Clinical Neuroscience and WT-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - G Arrondo
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - P Ramachandra
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - C Tudor-Sfetea
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - N Bunzeck
- Institute of Psychology I, University of Lübeck, Lübeck, Germany
| | - E Duezel
- Otto-von-Guericke University Magdeburg, Institute of Cognitive Neurology and Dementia Research, Magdeburg, Germany; German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - T W Robbins
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - R A Barker
- Department of Clinical Neuroscience and WT-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - G K Murray
- Department of Psychiatry, University of Cambridge, Cambridge, UK
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17
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Lan PS, Glaser KJ, Ehman RL, Glover GH. Imaging brain function with simultaneous BOLD and viscoelasticity contrast: fMRI/fMRE. Neuroimage 2020; 211:116592. [PMID: 32014553 DOI: 10.1016/j.neuroimage.2020.116592] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2019] [Revised: 12/25/2019] [Accepted: 01/28/2020] [Indexed: 01/10/2023] Open
Abstract
Magnetic resonance elastography (MRE) is emerging as a new tool for studying viscoelastic changes in the brain resulting from functional processes. Here, we demonstrate a novel time series method to generate robust functional magnetic resonance elastography (fMRE) activation maps in response to a visual task with a flashing checkerboard stimulus. Using a single-shot spin-echo (SS-SE) pulse sequence, the underlying raw images inherently contain blood-oxygen-level dependent (BOLD) contrast, allowing simultaneous generation of functional magnetic resonance imaging (fMRI) activation maps from the magnitude and functional magnetic resonance elastography (fMRE) maps from the phase. This allows an accurate comparison of the spatially localized stiffness (fMRE) and BOLD (fMRI) changes within a single scan, eliminating confounds inherent in separately acquired scans. Results indicate that tissue stiffness within the visual cortex increases 6-11% with visual stimuli, whereas the BOLD signal change was 1-2%. Furthermore, the fMRE and fMRI activation maps have strong spatial overlap within the visual cortex, providing convincing evidence that fMRE is possible in the brain. However, the fMRE temporal SNR (tSNRfMRE) maps are heterogeneous across the brain. Using a dictionary matching approach to characterize the time series, the viscoelastic changes are consistent with a viscoelastic response function (VRF) time constant of 12.1 s ± 3.0 s for a first-order exponential decay, or a shape parameter of 8.1 s ± 1.4 s for a gamma-variate.
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Affiliation(s)
- Patricia S Lan
- Department of Bioengineering, Stanford University, 443 Via Ortega, Stanford, CA, 94305, USA.
| | - Kevin J Glaser
- Department of Radiology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Richard L Ehman
- Department of Radiology, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, USA
| | - Gary H Glover
- Department of Radiology, Stanford University, 1201 Welch Road, Stanford, CA, 94305, USA
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18
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Fultz NE, Bonmassar G, Setsompop K, Stickgold RA, Rosen BR, Polimeni JR, Lewis LD. Coupled electrophysiological, hemodynamic, and cerebrospinal fluid oscillations in human sleep. Science 2019; 366:628-631. [PMID: 31672896 PMCID: PMC7309589 DOI: 10.1126/science.aax5440] [Citation(s) in RCA: 486] [Impact Index Per Article: 97.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 09/18/2019] [Indexed: 12/14/2022]
Abstract
Sleep is essential for both cognition and maintenance of healthy brain function. Slow waves in neural activity contribute to memory consolidation, whereas cerebrospinal fluid (CSF) clears metabolic waste products from the brain. Whether these two processes are related is not known. We used accelerated neuroimaging to measure physiological and neural dynamics in the human brain. We discovered a coherent pattern of oscillating electrophysiological, hemodynamic, and CSF dynamics that appears during non-rapid eye movement sleep. Neural slow waves are followed by hemodynamic oscillations, which in turn are coupled to CSF flow. These results demonstrate that the sleeping brain exhibits waves of CSF flow on a macroscopic scale, and these CSF dynamics are interlinked with neural and hemodynamic rhythms.
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Affiliation(s)
- Nina E Fultz
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA
| | - Giorgio Bonmassar
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA
- Department of Radiology, Harvard Medical School, Boston, MA 02115, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA
- Department of Radiology, Harvard Medical School, Boston, MA 02115, USA
| | - Robert A Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA
- Department of Radiology, Harvard Medical School, Boston, MA 02115, USA
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA
- Department of Radiology, Harvard Medical School, Boston, MA 02115, USA
| | - Laura D Lewis
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02129, USA
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19
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Non-BOLD contrast for laminar fMRI in humans: CBF, CBV, and CMRO2. Neuroimage 2019; 197:742-760. [DOI: 10.1016/j.neuroimage.2017.07.041] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Revised: 07/10/2017] [Accepted: 07/19/2017] [Indexed: 12/22/2022] Open
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20
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Zhang YN, Huo JW, Huang YR, Hao Y, Chen ZY. Altered amplitude of low-frequency fluctuation and regional cerebral blood flow in females with primary dysmenorrhea: a resting-state fMRI and arterial spin labeling study. J Pain Res 2019; 12:1243-1250. [PMID: 31114306 PMCID: PMC6489567 DOI: 10.2147/jpr.s177502] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2018] [Accepted: 02/14/2019] [Indexed: 12/12/2022] Open
Abstract
Purpose: The current study aimed to explore the central mechanism of primary dysmenorrhea (PD) by investigating the alterations in resting state amplitude of low-frequency fluctuation (ALFF) and regional cerebral blood flow (CBF) between PD patients and healthy controls (HCs). Patients and methods: A total of 34 female subjects including 20 PD patients and 14 HCs underwent resting-state functional magnetic resonance imaging (rs-fMRI) and arterial spin labeling technique (ASL) MRI during menstrual phase. Subsequently, the differences in ALFF and CBF were compared in the two groups. The visual analog scores for pain (VAS-P) and for anxiety (VAS-A) were applied to assess cramping pain and related symptoms in PD patients. Finally, Pearson's correlation analysis was performed to analyze relationships between the neuroimaging findings and clinical characteristics. Results: Compared to HCs, PD patients had decreased ALFF in the right cerebellum posterior lobe, right middle temporal gyrus, right parahippocampal gyrus, right hippocampus, right brainstem and left parietal lobe. In addition, elevated CBF values were observed in the right inferior frontal gyrus, right precentral gyrus, and right superior temporal gyrus. There was no significant correlation between ALFF, CBF values and clinical characteristics including onset age of dysmenorrhea, VAS-A, and VAS-P in PD patients. Conclusion: The preliminary alterations of ALFF and CBF values in PD patients were observed in different pain-related brain regions, which were involved in multiple dimensions of pain and pain modulation. The combination of rs-fMRI and ASL MRI might provide complementary information for a better understanding of the central mechanism in PD.
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Affiliation(s)
- Ya-Nan Zhang
- Department of Radiology, Beijing Hospital of Traditional Chinese Medicine Affiliated to Capital Medical University, Beijing100010, People’s Republic of China
| | - Jian-Wei Huo
- Department of Radiology, Beijing Hospital of Traditional Chinese Medicine Affiliated to Capital Medical University, Beijing100010, People’s Republic of China
| | - Yi-Ran Huang
- School of Acupuncture-Moxibustion & Tuina, Beijing University of Chinese Medicine, Beijing, 100029, People’s Republic of China
| | - Ying Hao
- Beijing International Center for Mathematical Research, Peking University, Beijing100871, People’s Republic of China
| | - Zi-Yue Chen
- Department of Acupuncture and Moxibustion, Yanshan Hospital, Beijing102500, People’s Republic of China
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21
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Yang L, Dun W, Li K, Yang J, Wang K, Liu H, Liu J, Zhang M. Altered amygdalar volume and functional connectivity in primary dysmenorrhoea during the menstrual cycle. Eur J Pain 2019; 23:994-1005. [PMID: 30664322 DOI: 10.1002/ejp.1368] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2018] [Revised: 11/27/2018] [Accepted: 01/17/2019] [Indexed: 01/25/2023]
Affiliation(s)
- Ling Yang
- Department of Medical Imaging; First Affiliated Hospital of Xi'an Jiaotong University; Xi'an China
- Radiology Department; Chong Qing General Hospital; Chong Qing China
| | - Wanghuan Dun
- Department of Medical Imaging; First Affiliated Hospital of Xi'an Jiaotong University; Xi'an China
| | - Kang Li
- Radiology Department; Chong Qing General Hospital; Chong Qing China
| | - Jing Yang
- Department of Medical Imaging; First Affiliated Hospital of Xi'an Jiaotong University; Xi'an China
| | - Ke Wang
- Department of Medical Imaging; First Affiliated Hospital of Xi'an Jiaotong University; Xi'an China
| | - Hongjuan Liu
- Department of Medical Imaging; First Affiliated Hospital of Xi'an Jiaotong University; Xi'an China
| | - Jixin Liu
- Center for Brain Imaging; School of Life Science and Technology; Xidian University; Xi'an China
| | - Ming Zhang
- Department of Medical Imaging; First Affiliated Hospital of Xi'an Jiaotong University; Xi'an China
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22
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Liu EY, Haist F, Dubowitz DJ, Buxton RB. Cerebral blood volume changes during the BOLD post-stimulus undershoot measured with a combined normoxia/hyperoxia method. Neuroimage 2019; 185:154-163. [PMID: 30315908 PMCID: PMC6292691 DOI: 10.1016/j.neuroimage.2018.10.032] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Revised: 10/09/2018] [Accepted: 10/09/2018] [Indexed: 10/28/2022] Open
Abstract
Cerebral blood flow (CBF) and blood oxygenation level dependent (BOLD) signal measurements make it possible to estimate steady-state changes in the cerebral metabolic rate of oxygen (CMRO2) with a calibrated BOLD method. However, extending this approach to measure the dynamics of CMRO2 requires an additional assumption: that deoxygenated cerebral blood volume (CBVdHb) follows CBF in a predictable way. A test-case for this assumption is the BOLD post-stimulus undershoot, for which one proposed explanation is a strong uncoupling of flow and blood volume with an elevated level of CBVdHb during the post-stimulus period compared to baseline due to slow blood volume recovery (Balloon Model). A challenge in testing this model is that CBVdHb differs from total blood volume, which can be measured with other techniques. In this study, the basic hypothesis of elevated CBVdHb during the undershoot was tested, based on the idea that the BOLD signal change when a subject switches from breathing a normoxic gas to breathing a hyperoxic gas is proportional to the absolute CBVdHb. In 19 subjects (8F), dual-echo BOLD responses were measured in primary visual cortex during a flickering radial checkerboard stimulus in normoxia, and the identical experiment was repeated in hyperoxia (50% O2/balance N2). The BOLD signal differences between normoxia and hyperoxia for the pre-stimulus baseline, stimulus, and post-stimulus periods were compared using an equivalent BOLD signal calculated from measured R2* changes to eliminate signal drifts. Relative to the pre-stimulus baseline, the average BOLD signal change from normoxia to hyperoxia was negative during the undershoot period (p = 0.0251), consistent with a reduction of CBVdHb and contrary to the prediction of the Balloon Model. Based on these results, the BOLD post-stimulus undershoot does not represent a case of strong uncoupling of CBVdHb and CBF, supporting the extension of current calibrated BOLD methods to estimate the dynamics of CMRO2.
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Affiliation(s)
- Eulanca Y Liu
- Neurosciences Graduate Program, Medical Scientist Training Program, University of California, San Diego, USA; Center for Functional MRI, University of California, San Diego, USA
| | - Frank Haist
- Psychiatry, University of California, San Diego, USA; Center for Human Development, University of California, San Diego, USA
| | - David J Dubowitz
- Center for Functional MRI, University of California, San Diego, USA; Radiology, University of California, San Diego, USA
| | - Richard B Buxton
- Center for Functional MRI, University of California, San Diego, USA; Radiology, University of California, San Diego, USA.
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23
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Ketamine and pharmacological imaging: use of functional magnetic resonance imaging to evaluate mechanisms of action. Behav Pharmacol 2018; 28:610-622. [PMID: 29049083 DOI: 10.1097/fbp.0000000000000354] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Ketamine has been used as a pharmacological model for schizophrenia as subanesthetic infusions have been shown to produce temporary schizophrenia-like symptoms in healthy humans. More recently, ketamine has emerged as a potential treatment for multiple psychiatric disorders, including treatment-resistant depression and suicidal ideation. However, the mechanisms underlying both the psychotomimetic and the therapeutic effects of ketamine remain poorly understood. This review provides an overview of what is known of the neural mechanisms underlying the effects of ketamine and details what functional MRI studies have yielded at a systems level focused on brain circuitry. Multiple analytic approaches show that ketamine exerts robust and consistent effects at the whole-brain level. These effects are highly conserved across human and nonhuman primates, validating the use of nonhuman primate models for further investigations with ketamine. Regional analysis of brain functional connectivity suggests that the therapeutic potential of ketamine may be derived from a strengthening of executive control circuitry, making it an intriguing candidate for the treatment of drug abuse. There are still important questions about the mechanism of action and the therapeutic potential of ketamine that can be addressed using appropriate functional neuroimaging techniques.
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24
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Tommasin S, Mascali D, Moraschi M, Gili T, Hassan IE, Fratini M, DiNuzzo M, Wise RG, Mangia S, Macaluso E, Giove F. Scale-invariant rearrangement of resting state networks in the human brain under sustained stimulation. Neuroimage 2018; 179:570-581. [PMID: 29908935 DOI: 10.1016/j.neuroimage.2018.06.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 06/04/2018] [Indexed: 01/09/2023] Open
Abstract
Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may not be the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation.
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Affiliation(s)
- Silvia Tommasin
- Centro Fermi - Museo storico della fisica e Centro di studi e ricerche Enrico Fermi, Roma, Italy; Dipartimento di Neuroscienze umane, Sapienza Università di Roma, Roma, Italy
| | - Daniele Mascali
- Centro Fermi - Museo storico della fisica e Centro di studi e ricerche Enrico Fermi, Roma, Italy
| | - Marta Moraschi
- Centro Fermi - Museo storico della fisica e Centro di studi e ricerche Enrico Fermi, Roma, Italy
| | - Tommaso Gili
- Centro Fermi - Museo storico della fisica e Centro di studi e ricerche Enrico Fermi, Roma, Italy; Fondazione Santa Lucia IRCCS, Roma, Italy
| | | | - Michela Fratini
- Fondazione Santa Lucia IRCCS, Roma, Italy; Istituto di Nanotecnologia, Consiglio Nazionale delle Ricerche, Roma, Italy
| | - Mauro DiNuzzo
- Center for Basic and Translational Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Richard G Wise
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK
| | - Silvia Mangia
- Center for Magnetic Resonance Research, Dept. of Radiology, University of Minnesota, Minneapolis, USA
| | | | - Federico Giove
- Centro Fermi - Museo storico della fisica e Centro di studi e ricerche Enrico Fermi, Roma, Italy; Fondazione Santa Lucia IRCCS, Roma, Italy.
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25
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Chu PP, Golestani AM, Kwinta JB, Khatamian YB, Chen JJ. Characterizing the modulation of resting-state fMRI metrics by baseline physiology. Neuroimage 2018; 173:72-87. [DOI: 10.1016/j.neuroimage.2018.02.004] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Revised: 01/25/2018] [Accepted: 02/03/2018] [Indexed: 12/18/2022] Open
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26
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Chiacchiaretta P, Cerritelli F, Bubbico G, Perrucci MG, Ferretti A. Reduced Dynamic Coupling Between Spontaneous BOLD-CBF Fluctuations in Older Adults: A Dual-Echo pCASL Study. Front Aging Neurosci 2018; 10:115. [PMID: 29740310 PMCID: PMC5925323 DOI: 10.3389/fnagi.2018.00115] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Accepted: 04/03/2018] [Indexed: 11/13/2022] Open
Abstract
Measurement of the dynamic coupling between spontaneous Blood Oxygenation Level Dependent (BOLD) and cerebral blood flow (CBF) fluctuations has been recently proposed as a method to probe resting-state brain physiology. Here we investigated how the dynamic BOLD-CBF coupling during resting-state is affected by aging. Fifteen young subjects and 17 healthy elderlies were studied using a dual-echo pCASL sequence. We found that the dynamic BOLD-CBF coupling was markedly reduced in elderlies, in particular in the left supramarginal gyrus, an area known to be involved in verbal working memory and episodic memory. Moreover, correcting for temporal shift between BOLD and CBF timecourses resulted in an increased correlation of the two signals for both groups, but with a larger increase for elderlies. However, even after temporal shift correction, a significantly decreased correlation was still observed for elderlies in the left supramarginal gyrus, indicating that the age-related dynamic BOLD-CBF uncoupling in this region is more pronounced and can be only partially explained with a simple time-shift between the two signals. Interestingly, these results were observed in a group of elderlies with normal cognitive functions, suggesting that the study of dynamic BOLD-CBF coupling during resting-state is a promising technique, potentially able to provide early biomarkers of functional changes in the aging brain.
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Affiliation(s)
- Piero Chiacchiaretta
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies (ITAB), Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy
| | - Francesco Cerritelli
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies (ITAB), Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Clinical-Based Human Research Department-C.O.M.E. Collaboration ONLUS, Pescara, Italy
| | - Giovanna Bubbico
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies (ITAB), Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy
| | - Mauro Gianni Perrucci
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies (ITAB), Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy
| | - Antonio Ferretti
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies (ITAB), Università degli Studi G. d'Annunzio Chieti e Pescara, Chieti, Italy
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27
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Bennett MR, Farnell L, Gibson WG. Quantitative relations between BOLD responses, cortical energetics, and impulse firing. J Neurophysiol 2018; 119:979-989. [PMID: 29187550 DOI: 10.1152/jn.00352.2017] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
The blood oxygen level-dependent (BOLD) functional magnetic resonance imaging signal arises as a consequence of changes in blood flow and oxygen usage that in turn are modulated by changes in neural activity. Much attention has been given to both theoretical and experimental aspects of the energetics but not to the neural activity. Here we identify the best energetic theory for the steady-state BOLD signal on the basis of correct predictions of experimental observations. This theory is then used, together with the recently determined relationship between energetics and neural activity, to predict how the BOLD signal changes with activity. Unlike existing treatments, this new theory incorporates a nonzero baseline activity in a completely consistent way and is thus able to account for both sustained positive and negative BOLD signals. We also show that the increase in BOLD signal for a given increase in activity is significantly smaller the larger the baseline activity, as is experimentally observed. Furthermore, the decline of the positive BOLD signal arising from deeper cortical laminae in response to an increase in neural firing is shown to arise as a consequence of the larger baseline activity in deeper laminae. Finally, we provide quantitative relations integrating BOLD responses, energetics, and impulse firing, which among other predictions give the same results as existing theories when the baseline activity is zero. NEW & NOTEWORTHY We use a recently established relation between energetics and neural activity to give a quantitative account of BOLD dependence on neural activity. The incorporation of a nonzero baseline neural activity accounts for positive and negative BOLD signals, shows that changes in neural activity give BOLD changes that are smaller the larger the baseline, and provides a basis for the observed inverse relation between BOLD responses and the depth of cortical laminae giving rise to them.
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Affiliation(s)
- M R Bennett
- Brain and Mind Research Institute, University of Sydney, Camperdown, New South Wales , Australia.,Center for Mathematical Biology, University of Sydney , Sydney, New South Wales , Australia
| | - L Farnell
- Center for Mathematical Biology, University of Sydney , Sydney, New South Wales , Australia.,The School of Mathematics and Statistics, University of Sydney, Camperdown, New South Wales , Australia
| | - W G Gibson
- Center for Mathematical Biology, University of Sydney , Sydney, New South Wales , Australia.,The School of Mathematics and Statistics, University of Sydney, Camperdown, New South Wales , Australia
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28
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Lake EMR, Bazzigaluppi P, Stefanovic B. Functional magnetic resonance imaging in chronic ischaemic stroke. Philos Trans R Soc Lond B Biol Sci 2017; 371:rstb.2015.0353. [PMID: 27574307 DOI: 10.1098/rstb.2015.0353] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/01/2016] [Indexed: 11/12/2022] Open
Abstract
Ischaemic stroke is the leading cause of adult disability worldwide. Effective rehabilitation is hindered by uncertainty surrounding the underlying mechanisms that govern long-term ischaemic injury progression. Despite its potential as a sensitive non-invasive in vivo marker of brain function that may aid in the development of new treatments, blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has found limited application in the clinical research on chronic stage stroke progression. Stroke affects each of the physiological parameters underlying the BOLD contrast, markedly complicating the interpretation of BOLD fMRI data. This review summarizes current progress on application of BOLD fMRI in the chronic stage of ischaemic injury progression and discusses means by which more information may be gained from such BOLD fMRI measurements. Concomitant measurements of vascular reactivity, neuronal activity and metabolism in preclinical models of stroke are reviewed along with illustrative examples of post-ischaemic evolution in neuronal, glial and vascular function. The realization of the BOLD fMRI potential to propel stroke research is predicated on the carefully designed preclinical research establishing an ischaemia-specific quantitative model of BOLD signal contrast to provide the framework for interpretation of fMRI findings in clinical populations.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.
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Affiliation(s)
- Evelyn M R Lake
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Paolo Bazzigaluppi
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada Fundamental Neurobiology, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Bojana Stefanovic
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada Heart and Stroke Foundation Centre for Stroke Recovery, Ottawa, Canada
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29
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Li W, Chen Z, Wu M, Zhu H, Gu L, Zhao Y, Kuang W, Bi F, Kemp GJ, Gong Q. Characterization of brain blood flow and the amplitude of low-frequency fluctuations in major depressive disorder: A multimodal meta-analysis. J Affect Disord 2017; 210:303-311. [PMID: 28068619 DOI: 10.1016/j.jad.2016.12.032] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2016] [Accepted: 12/22/2016] [Indexed: 11/30/2022]
Abstract
BACKGROUND In healthy subjects, there is an association between amplitude of low-frequency fluctuations (ALFF) and regional cerebral blood flow (rCBF). To date, no published meta-analysis has investigated changes in the regional ALFF in medication-free depressed patients. METHODS In this study, we aimed to explore whether resting-state rCBF and ALFF changes co-occur in the depressed brain without the potential confound of medication. Using signed differential mapping (SDM), we conducted two meta-analyses, one of rCBF studies and one of ALFF studies, involving medication-free patients with major depressive disorder (MDD). In addition, we conducted a multimodal meta-analysis to identify brain regions that showed abnormalities in both rCBF and ALFF. RESULTS A total of 16 studies were included in this series. We identified abnormalities in resting-state rCBF and ALFF in the left insula in medication-free MDD patients compared with healthy controls (HC). In addition, we observed altered resting-state rCBF in the limbic-subcortical-cortical circuit and altered ALFF in the default mode network (DMN) and some motor-related brain regions. LIMITATIONS The analysis techniques, patient characteristics and clinical variables of the included studies were heterogeneous. CONCLUSIONS The conjoint alterations in ALFF and rCBF in the left insula may represent core neuropathological changes in medication-free patients with MDD and merit further studying.
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Affiliation(s)
- Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Ziqi Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Min Wu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Hongyan Zhu
- Laboratory of Stem Cell Biology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
| | - Lei Gu
- Laboratory of Stem Cell Biology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Youjin Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Feng Bi
- Department of Oncology, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Graham J Kemp
- Magnetic Resonance and Image Analysis Research Centre and Institute of Ageing and Chronic Disease, University of Liverpool, United Kingdom
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Department of Psychology, School of Public Administration, Sichuan University, Chengdu, Sichuan, China
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30
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Abstract
Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity. We hypothesized that the recent development of fast fMRI techniques, combined with the extra sensitivity afforded by ultra-high-field systems, could enable precise localization of neural oscillations. We tested whether fMRI can detect neural oscillations using human visual cortex as a model system. We detected small oscillatory fMRI signals in response to stimuli oscillating at up to 0.75 Hz within single scan sessions, and these responses were an order of magnitude larger than predicted by canonical linear models. Simultaneous EEG-fMRI and simulations based on a biophysical model of the hemodynamic response to neuronal activity suggested that the blood oxygen level-dependent response becomes faster for rapidly varying stimuli, enabling the detection of higher frequencies than expected. Accounting for phase delays across voxels further improved detection, demonstrating that identifying vascular delays will be of increasing importance with higher-frequency activity. These results challenge the assumption that the hemodynamic response is slow, and demonstrate that fMRI has the potential to map neural oscillations directly throughout the brain.
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