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Jia K, Wang M, Steinwurzel C, Ziminski JJ, Xi Y, Emir U, Kourtzi Z. Recurrent inhibition refines mental templates to optimize perceptual decisions. SCIENCE ADVANCES 2024; 10:eado7378. [PMID: 39083601 PMCID: PMC11290482 DOI: 10.1126/sciadv.ado7378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 06/26/2024] [Indexed: 08/02/2024]
Abstract
Translating sensory inputs to perceptual decisions relies on building internal representations of features critical for solving complex tasks. Yet, we still lack a mechanistic account of how the brain forms these mental templates of task-relevant features to optimize decision-making. Here, we provide evidence for recurrent inhibition: an experience-dependent plasticity mechanism that refines mental templates by enhancing γ-aminobutyric acid (GABA)-mediated (GABAergic) inhibition and recurrent processing in superficial visual cortex layers. We combine ultrahigh-field (7 T) functional magnetic resonance imaging at submillimeter resolution with magnetic resonance spectroscopy to investigate the fine-scale functional and neurochemical plasticity mechanisms for optimized perceptual decisions. We demonstrate that GABAergic inhibition increases following training on a visual (i.e., fine orientation) discrimination task, enhancing the discriminability of orientation representations in superficial visual cortex layers that are known to support recurrent processing. Modeling functional and neurochemical plasticity interactions reveals that recurrent inhibitory processing optimizes brain computations for perpetual decisions and adaptive behavior.
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Affiliation(s)
- Ke Jia
- Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Mengxin Wang
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | | | - Joseph J. Ziminski
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Yinghua Xi
- Interdisciplinary Institute of Neuroscience and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Uzay Emir
- Purdue University School of Health Sciences, West Lafayette, IN 47906, USA
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
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Godbersen GM, Falb P, Klug S, Silberbauer LR, Reed MB, Nics L, Hacker M, Lanzenberger R, Hahn A. Non-invasive assessment of stimulation-specific changes in cerebral glucose metabolism with functional PET. Eur J Nucl Med Mol Imaging 2024; 51:2283-2292. [PMID: 38491215 PMCID: PMC11178598 DOI: 10.1007/s00259-024-06675-0] [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: 11/21/2023] [Accepted: 03/02/2024] [Indexed: 03/18/2024]
Abstract
PURPOSE Functional positron emission tomography (fPET) with [18F]FDG allows quantification of stimulation-induced changes in glucose metabolism independent of neurovascular coupling. However, the gold standard for quantification requires invasive arterial blood sampling, limiting its widespread use. Here, we introduce a novel fPET method without the need for an input function. METHODS We validated the approach using two datasets (DS). For DS1, 52 volunteers (23.2 ± 3.3 years, 24 females) performed Tetris® during a [18F]FDG fPET scan (bolus + constant infusion). For DS2, 18 participants (24.2 ± 4.3 years, 8 females) performed an eyes-open/finger tapping task (constant infusion). Task-specific changes in metabolism were assessed with the general linear model (GLM) and cerebral metabolic rate of glucose (CMRGlu) was quantified with the Patlak plot as reference. We then estimated simplified outcome parameters, including GLM beta values and percent signal change (%SC), and compared them, region and whole-brain-wise. RESULTS We observed higher agreement with the reference for DS1 than DS2. Both DS resulted in strong correlations between regional task-specific beta estimates and CMRGlu (r = 0.763…0.912). %SC of beta values exhibited strong agreement with %SC of CMRGlu (r = 0.909…0.999). Average activation maps showed a high spatial similarity between CMRGlu and beta estimates (Dice = 0.870…0.979) as well as %SC (Dice = 0.932…0.997), respectively. CONCLUSION The non-invasive method reliably estimates task-specific changes in glucose metabolism without blood sampling. This streamlines fPET, albeit with the trade-off of being unable to quantify baseline metabolism. The simplification enhances its applicability in research and clinical settings.
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Affiliation(s)
- Godber Mathis Godbersen
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Pia Falb
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Sebastian Klug
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Leo R Silberbauer
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Murray Bruce Reed
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
- Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria
| | - Lukas Nics
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Marcus Hacker
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
- Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria.
| | - Andreas Hahn
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
- Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Vienna, Austria.
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Seghier ML. 7 T and beyond: toward a synergy between fMRI-based presurgical mapping at ultrahigh magnetic fields, AI, and robotic neurosurgery. Eur Radiol Exp 2024; 8:73. [PMID: 38945979 PMCID: PMC11214939 DOI: 10.1186/s41747-024-00472-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Accepted: 04/22/2024] [Indexed: 07/02/2024] Open
Abstract
Presurgical evaluation with functional magnetic resonance imaging (fMRI) can reduce postsurgical morbidity. Here, we discuss presurgical fMRI mapping at ultra-high magnetic fields (UHF), i.e., ≥ 7 T, in the light of the current growing interest in artificial intelligence (AI) and robot-assisted neurosurgery. The potential of submillimetre fMRI mapping can help better appreciate uncertainty on resection margins, though geometric distortions at UHF might lessen the accuracy of fMRI maps. A useful trade-off for UHF fMRI is to collect data with 1-mm isotropic resolution to ensure high sensitivity and subsequently a low risk of false negatives. Scanning at UHF might yield a revival interest in slow event-related fMRI, thereby offering a richer depiction of the dynamics of fMRI responses. The potential applications of AI concern denoising and artefact removal, generation of super-resolution fMRI maps, and accurate fusion or coregistration between anatomical and fMRI maps. The latter can benefit from the use of T1-weighted echo-planar imaging for better visualization of brain activations. Such AI-augmented fMRI maps would provide high-quality input data to robotic surgery systems, thereby improving the accuracy and reliability of robot-assisted neurosurgery. Ultimately, the advancement in fMRI at UHF would promote clinically useful synergies between fMRI, AI, and robotic neurosurgery.Relevance statement This review highlights the potential synergies between fMRI at UHF, AI, and robotic neurosurgery in improving the accuracy and reliability of fMRI-based presurgical mapping.Key points• Presurgical fMRI mapping at UHF improves spatial resolution and sensitivity.• Slow event-related designs offer a richer depiction of fMRI responses dynamics.• AI can support denoising, artefact removal, and generation of super-resolution fMRI maps.• AI-augmented fMRI maps can provide high-quality input data to robotic surgery systems.
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Affiliation(s)
- Mohamed L Seghier
- Department of Biomedical Engineering and Biotechnology, Khalifa University of Science and Technology, Abu Dhabi, UAE.
- Healtcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, UAE.
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Iyer RR, Applegate CC, Arogundade OH, Bangru S, Berg IC, Emon B, Porras-Gomez M, Hsieh PH, Jeong Y, Kim Y, Knox HJ, Moghaddam AO, Renteria CA, Richard C, Santaliz-Casiano A, Sengupta S, Wang J, Zambuto SG, Zeballos MA, Pool M, Bhargava R, Gaskins HR. Inspiring a convergent engineering approach to measure and model the tissue microenvironment. Heliyon 2024; 10:e32546. [PMID: 38975228 PMCID: PMC11226808 DOI: 10.1016/j.heliyon.2024.e32546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 05/22/2024] [Accepted: 06/05/2024] [Indexed: 07/09/2024] Open
Abstract
Understanding the molecular and physical complexity of the tissue microenvironment (TiME) in the context of its spatiotemporal organization has remained an enduring challenge. Recent advances in engineering and data science are now promising the ability to study the structure, functions, and dynamics of the TiME in unprecedented detail; however, many advances still occur in silos that rarely integrate information to study the TiME in its full detail. This review provides an integrative overview of the engineering principles underlying chemical, optical, electrical, mechanical, and computational science to probe, sense, model, and fabricate the TiME. In individual sections, we first summarize the underlying principles, capabilities, and scope of emerging technologies, the breakthrough discoveries enabled by each technology and recent, promising innovations. We provide perspectives on the potential of these advances in answering critical questions about the TiME and its role in various disease and developmental processes. Finally, we present an integrative view that appreciates the major scientific and educational aspects in the study of the TiME.
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Affiliation(s)
- Rishyashring R. Iyer
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Catherine C. Applegate
- Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Opeyemi H. Arogundade
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Sushant Bangru
- Department of Biochemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Ian C. Berg
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Bashar Emon
- Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Marilyn Porras-Gomez
- Department of Materials Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Pei-Hsuan Hsieh
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Yoon Jeong
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Yongdeok Kim
- Department of Materials Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Hailey J. Knox
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Amir Ostadi Moghaddam
- Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Carlos A. Renteria
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Craig Richard
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Ashlie Santaliz-Casiano
- Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Sourya Sengupta
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Jason Wang
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Samantha G. Zambuto
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Maria A. Zeballos
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - Marcia Pool
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Rohit Bhargava
- Department of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Chemical and Biochemical Engineering, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- NIH/NIBIB P41 Center for Label-free Imaging and Multiscale Biophotonics (CLIMB), University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
| | - H. Rex Gaskins
- Division of Nutritional Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Animal Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Biomedical and Translational Sciences, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
- Department of Pathobiology, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA
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5
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Luo Q, Sun K, Dan G, Zhou XJ. Fast 3D fMRI acquisition with high spatial resolutions over a reduced FOV. Magn Reson Med 2024. [PMID: 38888135 DOI: 10.1002/mrm.30191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 04/29/2024] [Accepted: 05/21/2024] [Indexed: 06/20/2024]
Abstract
PURPOSE To develop and demonstrate a fast 3D fMRI acquisition technique with high spatial resolution over a reduced FOV, named k-t 3D reduced FOV imaging (3D-rFOVI). METHODS Based on 3D gradient-echo EPI, k-t 3D-rFOVI used a 2D RF pulse to reduce the FOV in the in-plane phase-encoding direction, boosting spatial resolution without increasing echo train length. For image acceleration, full sampling was applied in the central k-space region along the through-slab direction (kz) for all time frames, while randomized undersampling was used in outer kz regions at different time frames. Images were acquired at 3T and reconstructed using a method based on partial separability. fMRI detection sensitivity of k-t 3D-rFOVI was quantitively analyzed with simulation data. Human visual fMRI experiments were performed to evaluate k-t 3D-rFOVI and compare it with a commercial multiband EPI sequence. RESULTS The simulation data showed that k-t 3D-rFOVI can detect 100% of fMRI activations with an acceleration factor (R) of 2 and ˜80% with R = 6. In the human fMRI data acquired with 1.5-mm spatial resolution and 800-ms volume TR (TRvol), k-t 3D-rFOVI with R = 4 detected 46% more activated voxels in the visual cortex than the multiband EPI. Additional fMRI experiments showed that k-t 3D-rFOVI can achieve TRvol of 480 ms with R = 6, while reliably detecting visual activation. CONCLUSIONS k-t 3D-rFOVI can simultaneously achieve a high spatial resolution (1.5-mm isotropically) and short TRvol (480-ms) at 3T. It offers a robust acquisition technique for fast fMRI studies over a focused brain volume.
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Affiliation(s)
- Qingfei Luo
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Kaibao Sun
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Guangyu Dan
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Xiaohong Joe Zhou
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Neurosurgery, University of Illinois at Chicago, Chicago, Illinois, USA
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6
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Moffat R, Caruana N, Cross ES. Inhibiting responses under the watch of a recently synchronized peer increases self-monitoring: evidence from functional near-infrared spectroscopy. Open Biol 2024; 14:230382. [PMID: 38378138 PMCID: PMC10878812 DOI: 10.1098/rsob.230382] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 01/30/2024] [Indexed: 02/22/2024] Open
Abstract
Developing motor synchrony with a peer (through interventions such as the mirror game) can yield collaborative, cognitive and social benefits. However, it is also well established that observation by an audience can improve cognition. The combined and relative advantages offered by motor synchronization and audience effects are not yet understood. It is important to address this gap to determine the extent to which synchronizing activities might interact with the positive effects of an audience. In this preregistered study, we investigate the extent to which response inhibition may be improved when observed by a peer after motor synchronization with this peer. We compare behavioural and cortical (functional near-infrared spectroscopy; fNIRS) measures of inhibition between synchronized and non-synchronized dyads and find that the presence of a synchronized peer-audience introduces a speed-accuracy trade-off, consisting of slower reaction times and improved accuracy. This co-occurs with cortical activation in bilateral inferior frontal and middle prefrontal cortices, which are implicated in monitoring and maintenance of social alignment. Our findings have implications for carers and support people, who may benefit from synchronizing activities for rehabilitating inhibition and social skills in clinical settings.
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Affiliation(s)
- R. Moffat
- School of Psychological Sciences, Macquarie University, Sydney, New South Wales 2109, Australia
- Professorship for Social Brain Sciences, ETH Zurich, Zurich 8092, Switzerland
| | - N. Caruana
- School of Psychological Sciences, Macquarie University, Sydney, New South Wales 2109, Australia
- College of Education, Psychology and Social Work, Flinders University, Bedford Park, South Australia, Australia
| | - E. S. Cross
- School of Psychological Sciences, Macquarie University, Sydney, New South Wales 2109, Australia
- MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Westmead Innovation Quarter Building U, Westmead New South Wales 2145, Australia
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QB, UK
- Professorship for Social Brain Sciences, ETH Zurich, Zurich 8092, Switzerland
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7
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Choi S, Hike D, Pohmann R, Avdievich N, Gomez-Cid L, Man W, Scheffler K, Yu X. Alpha-180 spin-echo based line-scanning method for high resolution laminar-specific fMRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.05.09.540065. [PMID: 37214920 PMCID: PMC10197646 DOI: 10.1101/2023.05.09.540065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Laminar-specific functional magnetic resonance imaging (fMRI) has been widely used to study circuit-specific neuronal activity by mapping spatiotemporal fMRI response patterns across cortical layers. Hemodynamic responses reflect indirect neuronal activity given limit of spatial and temporal resolution. Previous gradient-echo based line-scanning fMRI (GELINE) method was proposed with high temporal (50 ms) and spatial (50 µm) resolution to better characterize the fMRI onset time across cortical layers by employing 2 saturation RF pulses. However, the imperfect RF saturation performance led to poor boundary definition of the reduced region of interest (ROI) and aliasing problems outside of the ROI. Here, we propose α (alpha)-180 spin-echo-based line-scanning fMRI (SELINE) method to resolve this issue by employing a refocusing 180° RF pulse perpendicular to the excitation slice. In contrast to GELINE signals peaked at the superficial layer, we detected varied peaks of laminar-specific BOLD signals across deeper cortical layers with the SELINE method, indicating the well-defined exclusion of the large drain-vein effect with the spin-echo sequence. Furthermore, we applied the SELINE method with 200 ms TR to sample the fast hemodynamic changes across cortical layers with a less draining vein effect. In summary, this SELINE method provides a novel acquisition scheme to identify microvascular-sensitive laminar-specific BOLD responses across cortical depth.
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Bohraus Y, Merkle H, Logothetis NK, Goense J. Laminar differences in functional oxygen metabolism in monkey visual cortex measured with calibrated fMRI. Cell Rep 2023; 42:113341. [PMID: 37897728 DOI: 10.1016/j.celrep.2023.113341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 08/23/2023] [Accepted: 10/10/2023] [Indexed: 10/30/2023] Open
Abstract
Blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD fMRI) of cortical layers relies on the hemodynamic response and is biased toward large veins on the cortical surface. Functional changes in the cerebral metabolic rate of oxygen (ΔCMRO2) may reflect neural cortical function better than BOLD fMRI, but it is unknown whether the calibrated BOLD model for functional CMRO2 measurement remains valid at high resolution. Here, we measure laminar ΔCMRO2 elicited by visual stimulation in macaque primary visual cortex (V1) and find that ΔCMRO2 peaks in the middle of the cortex, in agreement with autoradiographic measures of metabolism. ΔCMRO2 values in gray matter are similar as found previously. Reductions in CMRO2 are associated with veins at the cortical surface, suggesting that techniques for vein removal may improve the accuracy of the model at very high resolution. However, our results show feasibility of laminar ΔCMRO2 measurement, providing a physiologically meaningful metric of laminar functional metabolism.
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Affiliation(s)
- Yvette Bohraus
- Department of Physiology of Cognitive Processes, Max-Planck Institute for Biological Cybernetics, 72076 Tübingen, Germany
| | | | - Nikos K Logothetis
- Department of Physiology of Cognitive Processes, Max-Planck Institute for Biological Cybernetics, 72076 Tübingen, Germany; Department of Physiology of Cognitive Processes, International Center for Primate Brain Research, Songjiang District, Shanghai 201602, China; Centre for Imaging Sciences, University of Manchester, Manchester M13 9PT, UK
| | - Jozien Goense
- Department of Physiology of Cognitive Processes, Max-Planck Institute for Biological Cybernetics, 72076 Tübingen, Germany; Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana-Champaign, Urbana, IL 61801, USA; Department of Psychology, University of Illinois, Urbana-Champaign, Champaign, IL 61820, USA; Department of Bioengineering, University of Illinois, Urbana-Champaign, Urbana, IL 61801, USA; Neuroscience Program, University of Illinois, Urbana-Champaign, Urbana, IL 61801, USA.
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9
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Jia K, Goebel R, Kourtzi Z. Ultra-High Field Imaging of Human Visual Cognition. Annu Rev Vis Sci 2023; 9:479-500. [PMID: 37137282 DOI: 10.1146/annurev-vision-111022-123830] [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] [Indexed: 05/05/2023]
Abstract
Functional magnetic resonance imaging (fMRI), the key methodology for mapping the functions of the human brain in a noninvasive manner, is limited by low temporal and spatial resolution. Recent advances in ultra-high field (UHF) fMRI provide a mesoscopic (i.e., submillimeter resolution) tool that allows us to probe laminar and columnar circuits, distinguish bottom-up versus top-down pathways, and map small subcortical areas. We review recent work demonstrating that UHF fMRI provides a robust methodology for imaging the brain across cortical depths and columns that provides insights into the brain's organization and functions at unprecedented spatial resolution, advancing our understanding of the fine-scale computations and interareal communication that support visual cognition.
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Affiliation(s)
- Ke Jia
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom;
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom;
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10
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Schellekens W, Bhogal AA, Roefs ECA, Báez-Yáñez MG, Siero JCW, Petridou N. The many layers of BOLD. The effect of hypercapnic and hyperoxic stimuli on macro- and micro-vascular compartments quantified by CVR, M, and CBV across cortical depth. J Cereb Blood Flow Metab 2023; 43:419-432. [PMID: 36262088 PMCID: PMC9941862 DOI: 10.1177/0271678x221133972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 09/01/2022] [Accepted: 09/05/2022] [Indexed: 11/16/2022]
Abstract
Ultra-high field functional magnetic resonance imaging (fMRI) offers the spatial resolution to measure neuronal activity at the scale of cortical layers. However, cortical depth dependent vascularization differences, such as a higher prevalence of macro-vascular compartments near the pial surface, have a confounding effect on depth-resolved blood-oxygen-level dependent (BOLD) fMRI signals. In the current study, we use hypercapnic and hyperoxic breathing conditions to quantify the influence of all venous vascular and micro-vascular compartments on laminar BOLD fMRI, as measured with gradient-echo (GE) and spin-echo (SE) scan sequences, respectively. We find that all venous vascular and micro-vascular compartments are capable of comparable theoretical maximum signal intensities, as represented by the M-value parameter. However, the capacity for vessel dilation, as reflected by the cerebrovascular reactivity (CVR), is approximately two and a half times larger for all venous vascular compartments combined compared to the micro-vasculature at superficial layers. Finally, there is roughly a 35% difference in estimates of CBV changes between all venous vascular and micro-vascular compartments, although this relative difference was approximately uniform across cortical depth. Thus, our results suggest that fMRI BOLD signal differences across cortical depth are likely caused by differences in dilation properties between macro- and micro-vascular compartments.
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Affiliation(s)
- Wouter Schellekens
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Alex A Bhogal
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Emiel CA Roefs
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Mario G Báez-Yáñez
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Jeroen CW Siero
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
- Spinoza Centre for Neuroimaging, Amsterdam, The
Netherlands
| | - Natalia Petridou
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
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Hranilovich JA, Legget KT, Dodd KC, Wylie KP, Tregellas JR. Functional magnetic resonance imaging of headache: Issues, best-practices, and new directions, a narrative review. Headache 2023; 63:309-321. [PMID: 36942411 PMCID: PMC10089616 DOI: 10.1111/head.14487] [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: 11/14/2022] [Revised: 12/26/2022] [Accepted: 01/20/2023] [Indexed: 03/23/2023]
Abstract
OBJECTIVE To ensure readers are informed consumers of functional magnetic resonance imaging (fMRI) research in headache, to outline ongoing challenges in this area of research, and to describe potential considerations when asked to collaborate on fMRI research in headache, as well as to suggest future directions for improvement in the field. BACKGROUND Functional MRI has played a key role in understanding headache pathophysiology, and mapping networks involved with headache-related brain activity have the potential to identify intervention targets. Some investigators have also begun to explore its use for diagnosis. METHODS/RESULTS The manuscript is a narrative review of the current best practices in fMRI in headache research, including guidelines on transparency and reproducibility. It also contains an outline of the fundamentals of MRI theory, task-related study design, resting-state functional connectivity, relevant statistics and power analysis, image preprocessing, and other considerations essential to the field. CONCLUSION Best practices to increase reproducibility include methods transparency, eliminating error, using a priori hypotheses and power calculations, using standardized instruments and diagnostic criteria, and developing large-scale, publicly available datasets.
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Affiliation(s)
- Jennifer A Hranilovich
- Division of Child Neurology, Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Kristina T Legget
- Department of Psychiatry, University of Colorado School of Medicine, Aurora, Colorado, USA
- Research Service, Rocky Mountain Regional VA Medical Center, Aurora, Colorado, USA
| | - Keith C Dodd
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Korey P Wylie
- Department of Psychiatry, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Jason R Tregellas
- Department of Psychiatry, University of Colorado School of Medicine, Aurora, Colorado, USA
- Research Service, Rocky Mountain Regional VA Medical Center, Aurora, Colorado, USA
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12
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Huber L, Kassavetis P, Gulban OF, Hallett M, Horovitz SG. Laminar VASO fMRI in focal hand dystonia patients. DYSTONIA 2023; 2. [PMID: 37035517 PMCID: PMC10081516 DOI: 10.3389/dyst.2023.10806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Focal Hand Dystonia (FHD) is a disabling movement disorder characterized by involuntary movements, cramps and spasms. It is associated with pathological neural microcircuits in the cortical somatosensory system. While invasive preclinical modalities allow researchers to probe specific neural microcircuits of cortical layers and columns, conventional functional magnetic resonance imaging (fMRI) cannot resolve such small neural computational units. In this study, we take advantage of recent developments in ultra-high-field MRI hardware and MR-sequences to capture altered digit representations and laminar processing in FHD patients. We aim to characterize the capability and challenges of layer-specific imaging and analysis tools in resolving laminar and columnar structures in clinical research setups. We scanned N = 4 affected and N = 5 unaffected hemispheres at 7T and found consistent results of altered neural microcircuitry in FHD patients: 1) In affected hemispheres of FHD patients, we found a breakdown of ordered finger representation in the primary somatosensory cortex, as suggested from previous low-resolution fMRI. 2) In affected primary motor cortices of FHD patients, we furthermore found increased fMRI activity in superficial cortico-cortical neural input layers (II/III), compared to relatively weaker activity in the cortico-spinal output layers (Vb/VI). Overall, we show that layer-fMRI acquisition and analysis tools have the potential to address clinically-driven neuroscience research questions about altered computational mechanisms at the spatial scales that were previously only accessible in animal models. We believe that this study paves the way for easier translation of preclinical work into clinical research in focal hand dystonia and beyond.
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Affiliation(s)
- Laurentius Huber
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Panagiotis Kassavetis
- Department of Neurology, University of Utah, Salt Lake City, UT, United States
- Human Motor Control Section, NINDS, NIH, Bethesda, MD, United States
| | - Omer Faruk Gulban
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Brain Innovation, Maastricht, Netherlands
| | - Mark Hallett
- Human Motor Control Section, NINDS, NIH, Bethesda, MD, United States
| | - Silvina G. Horovitz
- Human Motor Control Section, NINDS, NIH, Bethesda, MD, United States
- CORRESPONDENCE Silvina G. Horovitz,
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13
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Li Q, Gong D, Shen J, Rao C, Ni L, Zhang H. SF-MVPA: A from raw data to statistical results and surface space-based MVPA toolbox. Front Neurosci 2022; 16:1046752. [DOI: 10.3389/fnins.2022.1046752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 10/21/2022] [Indexed: 11/22/2022] Open
Abstract
Compared with traditional volume space-based multivariate pattern analysis (MVPA), surface space-based MVPA has many advantages and has received increasing attention. However, surface space-based MVPA requires considerable programming and is therefore difficult for people without a programming foundation. To address this, we developed a MATLAB toolbox based on a graphical interactive interface (GUI) called surface space-based multivariate pattern analysis (SF-MVPA) in this manuscript. Unlike the traditional MVPA toolboxes, which often only include MVPA calculation processes after data preprocessing, SF-MVPA covers the complete pipeline of surface space-based MVPA, including raw data format conversion, surface reconstruction, functional magnetic resonance (fMRI) data preprocessing, comparative analysis, surface space-based MVPA, leave one-run out cross validation, and family-wise error correction. With SF-MVPA, users can complete the complete pipeline of surface space-based MVPA without programming. In addition, SF-MVPA is designed for parallel computing and hence has high computational efficiency. After introducing SF-MVPA, we analyzed a sample dataset of tonal working memory load. By comparison with another surface space-based MVPA toolbox named CoSMoMVPA, we found that the two toolboxes obtained consistent results. We hope that through this toolbox, users can more easily implement surface space-based MVPA.
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14
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Purohit R, Bhatt T. Mobile Brain Imaging to Examine Task-Related Cortical Correlates of Reactive Balance: A Systematic Review. Brain Sci 2022; 12:1487. [PMID: 36358413 PMCID: PMC9688648 DOI: 10.3390/brainsci12111487] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 10/23/2022] [Accepted: 10/25/2022] [Indexed: 02/18/2024] Open
Abstract
This systematic review examined available findings on spatial and temporal characteristics of cortical activity in response to unpredicted mechanical perturbations. Secondly, this review investigated associations between cortical activity and behavioral/biomechanical measures. Databases were searched from 1980-2021 and a total of 35 cross-sectional studies (31 EEG and 4 fNIRS) were included. Majority of EEG studies assessed perturbation-evoked potentials (PEPs), whereas other studies assessed changes in cortical frequencies. Further, fNIRS studies assessed hemodynamic changes. The PEP-N1, commonly identified at sensorimotor areas, was most examined and was influenced by context prediction, perturbation magnitude, motor adaptation and age. Other PEPs were identified at frontal, parietal and sensorimotor areas and were influenced by task position. Further, changes in cortical frequencies were observed at prefrontal, sensorimotor and parietal areas and were influenced by task difficulty. Lastly, hemodynamic changes were observed at prefrontal and frontal areas and were influenced by task prediction. Limited studies reported associations between cortical and behavioral outcomes. This review provided evidence regarding the involvement of cerebral cortex for sensory processing of unpredicted perturbations, error-detection of expected versus actual postural state, and planning and execution of compensatory stepping responses. There is still limited evidence examining cortical activity during reactive balance tasks in populations with high fall-risk.
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Affiliation(s)
- Rudri Purohit
- Department of Physical Therapy, University of Illinois at Chicago, Chicago, IL 60612, USA
- Ph.D. Program in Rehabilitation Sciences, College of Applied Health Sciences, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - Tanvi Bhatt
- Department of Physical Therapy, University of Illinois at Chicago, Chicago, IL 60612, USA
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15
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Zhu W, Ma X, Zhu XH, Ugurbil K, Chen W, Wu X. Denoise Functional Magnetic Resonance Imaging With Random Matrix Theory Based Principal Component Analysis. IEEE Trans Biomed Eng 2022; 69:3377-3388. [PMID: 35439125 PMCID: PMC9579216 DOI: 10.1109/tbme.2022.3168592] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
High-resolution functional MRI (fMRI) is largely hindered by random thermal noise. Random matrix theory (RMT)-based principal component analysis (PCA) is promising to reduce such noise in fMRI data. However, there is no consensus about the optimal strategy and practice in implementation. In this work, we propose a comprehensive RMT-based denoising method that consists of 1) rank and noise estimation based on a set of newly derived multiple criteria, and 2) optimal singular value shrinkage, with each module explained and implemented based on the RMT. By incorporating the variance stabilizing approach, the denoising method can deal with low signal-to-noise ratio (SNR) (such as <5) magnitude fMRI data with favorable performance compared to other state-of-the-art methods. Results from both simulation and in-vivo high-resolution fMRI data show that the proposed denoising method dramatically improves image restoration quality, promoting functional sensitivity at the same level of functional mapping blurring compared to existing denoising methods. Moreover, the denoising method can serve as a drop-in step in data preprocessing pipelines along with other procedures aimed at removal of structured physiological noises. We expect that the proposed denoising method will play an important role in leveraging high-quality, high-resolution task fMRI, which is desirable in many neuroscience and clinical applications.
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16
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Mächler P, Fomin-Thunemann N, Thunemann M, Sætra MJ, Desjardins M, Kılıç K, Amra LN, Martin EA, Chen IA, Şencan-Eğilmez I, Li B, Saisan P, Jiang JX, Cheng Q, Weldy KL, Boas DA, Buxton RB, Einevoll GT, Dale AM, Sakadžić S, Devor A. Baseline oxygen consumption decreases with cortical depth. PLoS Biol 2022; 20:e3001440. [PMID: 36301995 PMCID: PMC9642908 DOI: 10.1371/journal.pbio.3001440] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 11/08/2022] [Accepted: 09/30/2022] [Indexed: 11/05/2022] Open
Abstract
The cerebral cortex is organized in cortical layers that differ in their cellular density, composition, and wiring. Cortical laminar architecture is also readily revealed by staining for cytochrome oxidase-the last enzyme in the respiratory electron transport chain located in the inner mitochondrial membrane. It has been hypothesized that a high-density band of cytochrome oxidase in cortical layer IV reflects higher oxygen consumption under baseline (unstimulated) conditions. Here, we tested the above hypothesis using direct measurements of the partial pressure of O2 (pO2) in cortical tissue by means of 2-photon phosphorescence lifetime microscopy (2PLM). We revisited our previously developed method for extraction of the cerebral metabolic rate of O2 (CMRO2) based on 2-photon pO2 measurements around diving arterioles and applied this method to estimate baseline CMRO2 in awake mice across cortical layers. To our surprise, our results revealed a decrease in baseline CMRO2 from layer I to layer IV. This decrease of CMRO2 with cortical depth was paralleled by an increase in tissue oxygenation. Higher baseline oxygenation and cytochrome density in layer IV may serve as an O2 reserve during surges of neuronal activity or certain metabolically active brain states rather than reflecting baseline energy needs. Our study provides to our knowledge the first quantification of microscopically resolved CMRO2 across cortical layers as a step towards better understanding of brain energy metabolism.
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Affiliation(s)
- Philipp Mächler
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Natalie Fomin-Thunemann
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Martin Thunemann
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Marte Julie Sætra
- Department of Numerical Analysis and Scientific Computing, Simula Research Laboratory, Oslo, Norway
| | - Michèle Desjardins
- Département de Physique, de Génie Physique et d’Optique and Axe Oncologie, Centre de Recherche du CHU de Québec–Université Laval, Université Laval, Québec, Canada
| | - Kıvılcım Kılıç
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Layth N. Amra
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Emily A. Martin
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Ichun Anderson Chen
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Ikbal Şencan-Eğilmez
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America
| | - Baoqiang Li
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America
| | - Payam Saisan
- Department of Neurosciences, University of California San Diego, La Jolla, California, United States of America
| | - John X. Jiang
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Qun Cheng
- Department of Neurosciences, University of California San Diego, La Jolla, California, United States of America
| | - Kimberly L. Weldy
- Department of Neurosciences, University of California San Diego, La Jolla, California, United States of America
| | - David A. Boas
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Richard B. Buxton
- Department of Radiology, University of California San Diego, La Jolla, California, United States of America
| | - Gaute T. Einevoll
- Department of Physics, University of Oslo, Oslo, Norway
- Department of Physics, Norwegian University of Life Sciences, Ås, Norway
| | - Anders M. Dale
- Department of Neurosciences, University of California San Diego, La Jolla, California, United States of America
- Department of Radiology, University of California San Diego, La Jolla, California, United States of America
| | - Sava Sakadžić
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America
- * E-mail: (SS); (AD)
| | - Anna Devor
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, Massachusetts, United States of America
- * E-mail: (SS); (AD)
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17
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Choi S, Zeng H, Chen Y, Sobczak F, Qian C, Yu X. Laminar-specific functional connectivity mapping with multi-slice line-scanning fMRI. Cereb Cortex 2022; 32:4492-4501. [PMID: 35107125 PMCID: PMC9574235 DOI: 10.1093/cercor/bhab497] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 11/30/2021] [Accepted: 12/01/2021] [Indexed: 11/13/2022] Open
Abstract
Despite extensive studies detecting laminar functional magnetic resonance imaging (fMRI) signals to illustrate the canonical microcircuit, the spatiotemporal characteristics of laminar-specific information flow across cortical regions remain to be fully investigated in both evoked and resting conditions at different brain states. Here, we developed a multislice line-scanning fMRI (MS-LS) method to detect laminar fMRI signals in adjacent cortical regions with high spatial (50 μm) and temporal resolution (100 ms) in anesthetized rats. Across different trials, we detected either laminar-specific positive or negative blood-oxygen-level-dependent (BOLD) responses in the surrounding cortical region adjacent to the most activated cortex under the evoked condition. Specifically, in contrast to typical Layer (L) 4 correlation across different regions due to the thalamocortical projections for trials with positive BOLD, a strong correlation pattern specific in L2/3 was detected for trials with negative BOLD in adjacent regions, which indicated brain state-dependent laminar-fMRI responses based on corticocortical interaction. Also, in resting-state (rs-) fMRI study, robust lag time differences in L2/3, 4, and 5 across multiple cortices represented the low-frequency rs-fMRI signal propagation from caudal to rostral slices. In summary, our study provided a unique laminar fMRI mapping scheme to better characterize trial-specific intra- and inter-laminar functional connectivity in evoked and resting-state MS-LS.
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Affiliation(s)
- Sangcheon Choi
- Department of High-field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen 72076, Germany
- Graduate Training Centre of Neuroscience, University of Tübingen, Tübingen 72074, Germany
| | - Hang Zeng
- Department of High-field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen 72076, Germany
- Graduate Training Centre of Neuroscience, University of Tübingen, Tübingen 72074, Germany
| | - Yi Chen
- Department of High-field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen 72076, Germany
| | - Filip Sobczak
- Department of High-field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen 72076, Germany
- Graduate Training Centre of Neuroscience, University of Tübingen, Tübingen 72074, Germany
| | - Chunqi Qian
- Department of Radiology, Michigan State University, East Lansing, MI 48824, USA
| | - Xin Yu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA 02129, USA
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18
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Decoding Task-Based fMRI Data with Graph Neural Networks, Considering Individual Differences. Brain Sci 2022; 12:brainsci12081094. [PMID: 36009157 PMCID: PMC9405908 DOI: 10.3390/brainsci12081094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/01/2022] [Accepted: 08/06/2022] [Indexed: 12/05/2022] Open
Abstract
Task fMRI provides an opportunity to analyze the working mechanisms of the human brain during specific experimental paradigms. Deep learning models have increasingly been applied for decoding and encoding purposes study to representations in task fMRI data. More recently, graph neural networks, or neural networks models designed to leverage the properties of graph representations, have recently shown promise in task fMRI decoding studies. Here, we propose an end-to-end graph convolutional network (GCN) framework with three convolutional layers to classify task fMRI data from the Human Connectome Project dataset. We compared the predictive performance of our GCN model across four of the most widely used node embedding algorithms—NetMF, RandNE, Node2Vec, and Walklets—to automatically extract the structural properties of the nodes in the functional graph. The empirical results indicated that our GCN framework accurately predicted individual differences (0.978 and 0.976) with the NetMF and RandNE embedding methods, respectively. Furthermore, to assess the effects of individual differences, we tested the classification performance of the model on sub-datasets divided according to gender and fluid intelligence. Experimental results indicated significant differences in the classification predictions of gender, but not high/low fluid intelligence fMRI data. Our experiments yielded promising results and demonstrated the superior ability of our GCN in modeling task fMRI data.
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19
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Harauzov AK, Ivanova LE, Vasiliev PP, Podvigina DN. fMRI Studies of Opponent Interregional Interactions in the Macaca mulatta Brain. J EVOL BIOCHEM PHYS+ 2022. [DOI: 10.1134/s0022093022040068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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20
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Super-resolution generative adversarial networks with static T2*WI-based subject-specific learning to improve spatial difference sensitivity in fMRI activation. Sci Rep 2022; 12:10319. [PMID: 35725788 PMCID: PMC9209532 DOI: 10.1038/s41598-022-14421-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 06/07/2022] [Indexed: 11/18/2022] Open
Abstract
The spatial resolution of fMRI is relatively poor and improvements are needed to indicate more specific locations for functional activities. Here, we propose a novel scheme, called Static T2*WI-based Subject-Specific Super Resolution fMRI (STSS-SRfMRI), to enhance the functional resolution, or ability to discriminate spatially adjacent but functionally different responses, of fMRI. The scheme is based on super-resolution generative adversarial networks (SRGAN) that utilize a T2*-weighted image (T2*WI) dataset as a training reference. The efficacy of the scheme was evaluated through comparison with the activation maps obtained from the raw unpreprocessed functional data (raw fMRI). MRI images were acquired from 30 healthy volunteers using a 3 Tesla scanner. The modified SRGAN reconstructs a high-resolution image series from the original low-resolution fMRI data. For quantitative comparison, several metrics were calculated for both the STSS-SRfMRI and the raw fMRI activation maps. The ability to distinguish between two different finger-tapping tasks was significantly higher [p = 0.00466] for the reconstructed STSS-SRfMRI images than for the raw fMRI images. The results indicate that the functional resolution of the STSS-SRfMRI scheme is superior, which suggests that the scheme is a potential solution to realizing higher functional resolution in fMRI images obtained using 3T MRI.
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21
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Weiss Lucas C, Faymonville AM, Loução R, Schroeter C, Nettekoven C, Oros-Peusquens AM, Langen KJ, Shah NJ, Stoffels G, Neuschmelting V, Blau T, Neuschmelting H, Hellmich M, Kocher M, Grefkes C, Goldbrunner R. Surgery of Motor Eloquent Glioblastoma Guided by TMS-Informed Tractography: Driving Resection Completeness Towards Prolonged Survival. Front Oncol 2022; 12:874631. [PMID: 35692752 PMCID: PMC9186060 DOI: 10.3389/fonc.2022.874631] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 03/21/2022] [Indexed: 12/13/2022] Open
Abstract
Background Surgical treatment of patients with glioblastoma affecting motor eloquent brain regions remains critically discussed given the risk–benefit dilemma of prolonging survival at the cost of motor-functional damage. Tractography informed by navigated transcranial magnetic stimulation (nTMS-informed tractography, TIT) provides a rather robust estimate of the individual location of the corticospinal tract (CST), a highly vulnerable structure with poor functional reorganisation potential. We hypothesised that by a more comprehensive, individualised surgical decision-making using TIT, tumours in close relationship to the CST can be resected with at least equal probability of gross total resection (GTR) than less eloquently located tumours without causing significantly more gross motor function harm. Moreover, we explored whether the completeness of TIT-aided resection translates to longer survival. Methods A total of 61 patients (median age 63 years, m = 34) with primary glioblastoma neighbouring or involving the CST were operated on between 2010 and 2015. TIT was performed to inform surgical planning in 35 of the patients (group T; vs. 26 control patients). To achieve largely unconfounded group comparisons for each co-primary outcome (i.e., gross-motor functional worsening, GTR, survival), (i) uni- and multivariate regression analyses were performed to identify features of optimal outcome prediction; (ii), optimal propensity score matching (PSM) was applied to balance those features pairwise across groups, followed by (iii) pairwise group comparison. Results Patients in group T featured a significantly higher lesion-CST overlap compared to controls (8.7 ± 10.7% vs. 3.8 ± 5.7%; p = 0.022). The frequency of gross motor worsening was higher in group T, albeit non-significant (n = 5/35 vs. n = 0/26; p = 0.108). PSM-based paired-sample comparison, controlling for the confounders of preoperative tumour volume and vicinity to the delicate vasculature of the insula, showed higher GTR rates in group T (77% vs. 69%; p = 0.025), particularly in patients with a priori intended GTR (87% vs. 78%; p = 0.003). This translates into a prolonged PFS in the same PSM subgroup (8.9 vs. 5.8 months; p = 0.03), with GTR representing the strongest predictor of PFS (p = 0.001) and OS (p = 0.0003) overall. Conclusion The benefit of TIT-aided GTR appears to overcome the drawbacks of potentially elevated motor functional risk in motor eloquent tumour localisation, leading to prolonged survival of patients with primary glioblastoma close to the CST.
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Affiliation(s)
- Carolin Weiss Lucas
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Andrea Maria Faymonville
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Department of Neurosurgery, University Hospital Mannheim, Mannheim, Germany
| | - Ricardo Loução
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Department of Stereotaxy and Functional Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany
| | - Catharina Schroeter
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Charlotte Nettekoven
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | | | - Karl Josef Langen
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany
| | - N Jon Shah
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany.,JARA - BRAIN - Translational Medicine, Aachen, Germany.,Department of Neurology, RWTH Aachen University, Aachen, Germany
| | - Gabriele Stoffels
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany
| | - Volker Neuschmelting
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Tobias Blau
- Department of Neurology, RWTH Aachen University, Aachen, Germany.,Institute of Neuropathology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Hannah Neuschmelting
- Institute of Pathology and Neuropathology, University Hospital Essen, Essen, Germany
| | - Martin Hellmich
- Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Martin Kocher
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Department of Stereotaxy and Functional Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany
| | - Christian Grefkes
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Julich, Juelich, Germany.,Institute for Medical Statistics and Computational Biology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Roland Goldbrunner
- Department of General Neurosurgery, Center of Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
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22
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Wu C, Ferreira F, Fox M, Harel N, Hattangadi-Gluth J, Horn A, Jbabdi S, Kahan J, Oswal A, Sheth SA, Tie Y, Vakharia V, Zrinzo L, Akram H. Clinical applications of magnetic resonance imaging based functional and structural connectivity. Neuroimage 2021; 244:118649. [PMID: 34648960 DOI: 10.1016/j.neuroimage.2021.118649] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 09/24/2021] [Accepted: 10/10/2021] [Indexed: 12/23/2022] Open
Abstract
Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.
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Affiliation(s)
- Chengyuan Wu
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, 909 Walnut Street, Third Floor, Philadelphia, PA 19107, USA; Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut Street, First Floor, Philadelphia, PA 19107, USA.
| | - Francisca Ferreira
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
| | - Michael Fox
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, Radiology, and Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA.
| | - Noam Harel
- Center for Magnetic Resonance Research, University of Minnesota, 2021 Sixth Street S.E., Minneapolis, MN 55455, USA.
| | - Jona Hattangadi-Gluth
- Department of Radiation Medicine and Applied Sciences, Center for Precision Radiation Medicine, University of California, San Diego, 3855 Health Sciences Drive, La Jolla, CA 92037, USA.
| | - Andreas Horn
- Neurology Department, Movement Disorders and Neuromodulation Section, Charité - University Medicine Berlin, Charitéplatz 1, D-10117, Berlin, Germany.
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK.
| | - Joshua Kahan
- Department of Neurology, Weill Cornell Medicine, 525 East 68th Street, New York, NY, 10065, USA.
| | - Ashwini Oswal
- Medical Research Council Brain Network Dynamics Unit, University of Oxford, Mansfield Rd, Oxford OX1 3TH, UK.
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, 7200 Cambridge, Ninth Floor, Houston, TX 77030, USA.
| | - Yanmei Tie
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, Radiology, and Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA; Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, 60 Fenwood Road, Boston, MA 02115, USA.
| | - Vejay Vakharia
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK.
| | - Ludvic Zrinzo
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
| | - Harith Akram
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, 33 Queen Square, London WC1N 3BG, UK; Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, 33 Queen Square, London WC1N 3BG, UK.
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23
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The Global Configuration of Visual Stimuli Alters Co-Fluctuations of Cross-Hemispheric Human Brain Activity. J Neurosci 2021; 41:9756-9766. [PMID: 34663628 DOI: 10.1523/jneurosci.3214-20.2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Revised: 09/11/2021] [Accepted: 10/07/2021] [Indexed: 11/21/2022] Open
Abstract
We tested how a stimulus gestalt, defined by the neuronal interaction between local and global features of a stimulus, is represented within human primary visual cortex (V1). We used high-resolution fMRI, which serves as a surrogate of neuronal activation, to measure co-fluctuations within subregions of V1 as (male and female) subjects were presented with peripheral stimuli, each with different global configurations. We found stronger cross-hemisphere correlations when fine-scale V1 cortical subregions represented parts of the same object compared with different objects. This result was consistent with the vertical bias in global processing and, critically, was independent of the task and local discontinuities within objects. Thus, despite the relatively small receptive fields of neurons within V1, global stimulus configuration affects neuronal processing via correlated fluctuations between regions that represent different sectors of the visual field.SIGNIFICANCE STATEMENT We provide the first evidence for the impact of global stimulus configuration on cross-hemispheric fMRI fluctuations, measured in human primary visual cortex. Our results are consistent with changes in the level of γ-band synchrony, which has been shown to be affected by global stimulus configuration, being reflected in the level fMRI co-fluctuations. These data help narrow the gap between knowledge of global stimulus configuration encoding at the single-neuron level versus at the behavioral level.
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24
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Lee SH, Broadwater MA, Ban W, Wang TWW, Kim HJ, Dumas JS, Vetreno RP, Herman MA, Morrow AL, Besheer J, Kash TL, Boettiger CA, Robinson DL, Crews FT, Shih YYI. An isotropic EPI database and analytical pipelines for rat brain resting-state fMRI. Neuroimage 2021; 243:118541. [PMID: 34478824 PMCID: PMC8561231 DOI: 10.1016/j.neuroimage.2021.118541] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 08/08/2021] [Accepted: 08/30/2021] [Indexed: 12/24/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (fMRI) has drastically expanded the scope of brain research by advancing our knowledge about the topologies, dynamics, and interspecies translatability of functional brain networks. Several databases have been developed and shared in accordance with recent key initiatives in the rodent fMRI community to enhance the transparency, reproducibility, and interpretability of data acquired at various sites. Despite these pioneering efforts, one notable challenge preventing efficient standardization in the field is the customary choice of anisotropic echo planar imaging (EPI) schemes with limited spatial coverage. Imaging with anisotropic resolution and/or reduced brain coverage has significant shortcomings including reduced registration accuracy and increased deviation in brain feature detection. Here we proposed a high-spatial-resolution (0.4 mm), isotropic, whole-brain EPI protocol for the rat brain using a horizontal slicing scheme that can maintain a functionally relevant repetition time (TR), avoid high gradient duty cycles, and offer unequivocal whole-brain coverage. Using this protocol, we acquired resting-state EPI fMRI data from 87 healthy rats under the widely used dexmedetomidine sedation supplemented with low-dose isoflurane on a 9.4 T MRI system. We developed an EPI template that closely approximates the Paxinos and Watson's rat brain coordinate system and demonstrated its ability to improve the accuracy of group-level approaches and streamline fMRI data pre-processing. Using this database, we employed a multi-scale dictionary-learning approach to identify reliable spatiotemporal features representing rat brain intrinsic activity. Subsequently, we performed k-means clustering on those features to obtain spatially discrete, functional regions of interest (ROIs). Using Euclidean-based hierarchical clustering and modularity-based partitioning, we identified the topological organizations of the rat brain. Additionally, the identified group-level FC network appeared robust across strains and sexes. The "triple-network" commonly adapted in human fMRI were resembled in the rat brain. Through this work, we disseminate raw and pre-processed isotropic EPI data, a rat brain EPI template, as well as identified functional ROIs and networks in standardized rat brain coordinates. We also make our analytical pipelines and scripts publicly available, with the hope of facilitating rat brain resting-state fMRI study standardization.
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Affiliation(s)
- Sung-Ho Lee
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Corresponding authors at: Center for Animal MRI, 125 Mason Farm Road, CB# 7513, University of North Carolina, Chapel Hill, NC 27599, USA. (S.-H. Lee), (Y.-Y.I. Shih)
| | - Margaret A. Broadwater
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
| | - Woomi Ban
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
| | - Tzu-Wen Winnie Wang
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
| | - Hyeon-Joong Kim
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Jaiden Seongmi Dumas
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Department of Quantitative Biology, University of North Carolina, Chapel Hill, NC, USA
| | - Ryan P. Vetreno
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Melissa A. Herman
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - A. Leslie Morrow
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Joyce Besheer
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Thomas L. Kash
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Charlotte A. Boettiger
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA,Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC, USA
| | - Donita L. Robinson
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Fulton T. Crews
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Corresponding authors at: Center for Animal MRI, 125 Mason Farm Road, CB# 7513, University of North Carolina, Chapel Hill, NC 27599, USA. (S.-H. Lee), (Y.-Y.I. Shih)
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25
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Suarez A, Valdés-Hernández PA, Bernal B, Dunoyer C, Khoo HM, Bosch-Bayard J, Riera JJ. Identification of Negative BOLD Responses in Epilepsy Using Windkessel Models. Front Neurol 2021; 12:659081. [PMID: 34690906 PMCID: PMC8531269 DOI: 10.3389/fneur.2021.659081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 09/03/2021] [Indexed: 11/16/2022] Open
Abstract
Alongside positive blood oxygenation level–dependent (BOLD) responses associated with interictal epileptic discharges, a variety of negative BOLD responses (NBRs) are typically found in epileptic patients. Previous studies suggest that, in general, up to four mechanisms might underlie the genesis of NBRs in the brain: (i) neuronal disruption of network activity, (ii) altered balance of neurometabolic/vascular couplings, (iii) arterial blood stealing, and (iv) enhanced cortical inhibition. Detecting and classifying these mechanisms from BOLD signals are pivotal for the improvement of the specificity of the electroencephalography–functional magnetic resonance imaging (EEG-fMRI) image modality to identify the seizure-onset zones in refractory local epilepsy. This requires models with physiological interpretation that furnish the understanding of how these mechanisms are fingerprinted by their BOLD responses. Here, we used a Windkessel model with viscoelastic compliance/inductance in combination with dynamic models of both neuronal population activity and tissue/blood O2 to classify the hemodynamic response functions (HRFs) linked to the above mechanisms in the irritative zones of epileptic patients. First, we evaluated the most relevant imprints on the BOLD response caused by variations of key model parameters. Second, we demonstrated that a general linear model is enough to accurately represent the four different types of NBRs. Third, we tested the ability of a machine learning classifier, built from a simulated ensemble of HRFs, to predict the mechanism underlying the BOLD signal from irritative zones. Cross-validation indicates that these four mechanisms can be classified from realistic fMRI BOLD signals. To demonstrate proof of concept, we applied our methodology to EEG-fMRI data from five epileptic patients undergoing neurosurgery, suggesting the presence of some of these mechanisms. We concluded that a proper identification and interpretation of NBR mechanisms in epilepsy can be performed by combining general linear models and biophysically inspired models.
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Affiliation(s)
- Alejandro Suarez
- Neuronal Mass Dynamics Laboratory, Florida International University, Miami, FL, United States
| | | | - Byron Bernal
- Nicklaus Children Hospital, Miami, FL, United States
| | | | - Hui Ming Khoo
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada.,Department of Neurosurgery, Osaka University, Suita, Japan
| | - Jorge Bosch-Bayard
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Jorge J Riera
- Neuronal Mass Dynamics Laboratory, Florida International University, Miami, FL, United States
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26
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Zoraghi M, Scherf N, Jaeger C, Sack I, Hirsch S, Hetzer S, Weiskopf N. Simulating Local Deformations in the Human Cortex Due to Blood Flow-Induced Changes in Mechanical Tissue Properties: Impact on Functional Magnetic Resonance Imaging. Front Neurosci 2021; 15:722366. [PMID: 34621151 PMCID: PMC8490675 DOI: 10.3389/fnins.2021.722366] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 08/23/2021] [Indexed: 01/06/2023] Open
Abstract
Investigating human brain tissue is challenging due to the complexity and the manifold interactions between structures across different scales. Increasing evidence suggests that brain function and microstructural features including biomechanical features are related. More importantly, the relationship between tissue mechanics and its influence on brain imaging results remains poorly understood. As an important example, the study of the brain tissue response to blood flow could have important theoretical and experimental consequences for functional magnetic resonance imaging (fMRI) at high spatial resolutions. Computational simulations, using realistic mechanical models can predict and characterize the brain tissue behavior and give us insights into the consequent potential biases or limitations of in vivo, high-resolution fMRI. In this manuscript, we used a two dimensional biomechanical simulation of an exemplary human gyrus to investigate the relationship between mechanical tissue properties and the respective changes induced by focal blood flow changes. The model is based on the changes in the brain’s stiffness and volume due to the vasodilation evoked by neural activity. Modeling an exemplary gyrus from a brain atlas we assessed the influence of different potential mechanisms: (i) a local increase in tissue stiffness (at the level of a single anatomical layer), (ii) an increase in local volume, and (iii) a combination of both effects. Our simulation results showed considerable tissue displacement because of these temporary changes in mechanical properties. We found that the local volume increase causes more deformation and consequently higher displacement of the gyrus. These displacements introduced considerable artifacts in our simulated fMRI measurements. Our results underline the necessity to consider and characterize the tissue displacement which could be responsible for fMRI artifacts.
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Affiliation(s)
- Mahsa Zoraghi
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nico Scherf
- Methods and Development Group Neural Data Science and Statistical Computing, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Carsten Jaeger
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ingolf Sack
- Department of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Sebastian Hirsch
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Berlin Center for Computational Neuroscience, Berlin, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Berlin Center for Computational Neuroscience, Berlin, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Faculty of Physics and Earth Sciences, Felix Bloch Institute for Solid State Physics, Leipzig University, Leipzig, Germany
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27
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Ultra-High-Field Neuroimaging Reveals Fine-Scale Processing for 3D Perception. J Neurosci 2021; 41:8362-8374. [PMID: 34413206 PMCID: PMC8496197 DOI: 10.1523/jneurosci.0065-21.2021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 06/08/2021] [Accepted: 07/07/2021] [Indexed: 11/21/2022] Open
Abstract
Binocular disparity provides critical information about three-dimensional (3D) structures to support perception and action. In the past decade significant progress has been made in uncovering human brain areas engaged in the processing of binocular disparity signals. Yet, the fine-scale brain processing underlying 3D perception remains unknown. Here, we use ultra-high-field (7T) functional imaging at submillimeter resolution to examine fine-scale BOLD fMRI signals involved in 3D perception. In particular, we sought to interrogate the local circuitry involved in disparity processing by sampling fMRI responses at different positions relative to the cortical surface (i.e., across cortical depths corresponding to layers). We tested for representations related to 3D perception by presenting participants (male and female, N = 8) with stimuli that enable stable stereoscopic perception [i.e., correlated random dot stereograms (RDS)] versus those that do not (i.e., anticorrelated RDS). Using multivoxel pattern analysis (MVPA), we demonstrate cortical depth-specific representations in areas V3A and V7 as indicated by stronger pattern responses for correlated than for anticorrelated stimuli in upper rather than deeper layers. Examining informational connectivity, we find higher feedforward layer-to-layer connectivity for correlated than anticorrelated stimuli between V3A and V7. Further, we observe disparity-specific feedback from V3A to V1 and from V7 to V3A. Our findings provide evidence for the role of V3A as a key nexus for disparity processing, which is implicated in feedforward and feedback signals related to the perceptual estimation of 3D structures.SIGNIFICANCE STATEMENT Binocular vision plays a significant role in supporting our interactions with the surrounding environment. The fine-scale neural mechanisms that underlie the brain's skill in extracting 3D structures from binocular signals are poorly understood. Here, we capitalize on recent advances in ultra-high-field functional imaging to interrogate human brain circuits involved in 3D perception at submillimeter resolution. We provide evidence for the role of area V3A as a key nexus for disparity processing, which is implicated in feedforward and feedback signals related to the perceptual estimation of 3D structures from binocular signals. These fine-scale measurements help bridge the gap between animal neurophysiology and human fMRI studies investigating cross-scale circuits, from micro circuits to global brain networks for 3D perception.
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28
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Control of low flow regions in the cortical vasculature determines optimal arterio-venous ratios. Proc Natl Acad Sci U S A 2021; 118:2021840118. [PMID: 34413186 DOI: 10.1073/pnas.2021840118] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The energy demands of neurons are met by a constant supply of glucose and oxygen via the cerebral vasculature. The cerebral cortex is perfused by dense, parallel arterioles and venules, consistently in imbalanced ratios. Whether and how arteriole-venule arrangement and ratio affect the efficiency of energy delivery to the cortex has remained an unanswered question. Here, we show by mathematical modeling and analysis of the mapped mouse sensory cortex that the perfusive efficiency of the network is predicted to be limited by low-flow regions produced between pairs of arterioles or pairs of venules. Increasing either arteriole or venule density decreases the size of these low-flow regions, but increases their number, setting an optimal ratio between arterioles and venules that matches closely that observed across mammalian cortical vasculature. Low-flow regions are reshaped in complex ways by changes in vascular conductance, creating geometric challenges for matching cortical perfusion with neuronal activity.
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29
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Fracasso A, Gaglianese A, Vansteensel MJ, Aarnoutse EJ, Ramsey NF, Dumoulin SO, Petridou N. FMRI and intra-cranial electrocorticography recordings in the same human subjects reveals negative BOLD signal coupled with silenced neuronal activity. Brain Struct Funct 2021; 227:1371-1384. [PMID: 34363092 PMCID: PMC9046332 DOI: 10.1007/s00429-021-02342-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 07/09/2021] [Indexed: 12/27/2022]
Abstract
Positive blood oxygenation level-dependent (BOLD) responses (PBR), as measured by functional Magnetic Resonance Imaging (fMRI), are the most utilized measurements to non-invasively map activity in the brain. Recent studies have consistently shown that BOLD responses are not exclusively positive. Negative BOLD responses (NBR) have been reported in response to specific sensory stimulations and tasks. However, the exact relationship between NBR and the underlying metabolic and neuronal demand is still under debate. In this study, we investigated the neurophysiological basis of negative BOLD using fMRI and intra-cranial electrophysiology (electrocorticography, ECoG) measurements from the same human participants. We show that, for those electrodes that responded to visual stimulation, PBR are correlated with high-frequency band (HFB) responses. Crucially, NBR were associated with an absence of HFB power responses and an unpredicted decrease in the alpha power responses.
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Affiliation(s)
- Alessio Fracasso
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, Scotland.
| | - Anna Gaglianese
- The Laboratory for Investigative Neurophysiology (The LINE), Department of Radiology, University Hospital Center, University of Lausanne, Rue Centrale 7, 1003, Lausanne, Switzerland
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
- Department of Neurosurgery and Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Mariska J Vansteensel
- Department of Neurosurgery and Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Erik J Aarnoutse
- Department of Neurosurgery and Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Nick F Ramsey
- Department of Neurosurgery and Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Serge O Dumoulin
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
- Spinoza Center for Neuroimaging, Amsterdam, The Netherlands
- Experimental and Applied Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Natalia Petridou
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
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30
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Yang J, Huber L, Yu Y, Bandettini PA. Linking cortical circuit models to human cognition with laminar fMRI. Neurosci Biobehav Rev 2021; 128:467-478. [PMID: 34245758 DOI: 10.1016/j.neubiorev.2021.07.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 06/29/2021] [Accepted: 07/05/2021] [Indexed: 10/20/2022]
Abstract
Laboratory animal research has provided significant knowledge into the function of cortical circuits at the laminar level, which has yet to be fully leveraged towards insights about human brain function on a similar spatiotemporal scale. The use of functional magnetic resonance imaging (fMRI) in conjunction with neural models provides new opportunities to gain important insights from current knowledge. During the last five years, human studies have demonstrated the value of high-resolution fMRI to study laminar-specific activity in the human brain. This is mostly performed at ultra-high-field strengths (≥ 7 T) and is known as laminar fMRI. Advancements in laminar fMRI are beginning to open new possibilities for studying questions in basic cognitive neuroscience. In this paper, we first review recent methodological advances in laminar fMRI and describe recent human laminar fMRI studies. Then, we discuss how the use of laminar fMRI can help bridge the gap between cortical circuit models and human cognition.
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Affiliation(s)
- Jiajia Yang
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan; Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA.
| | - Laurentius Huber
- MR-Methods Group, Faculty of Psychology and Neuroscience, University of Maastricht, Maastricht, the Netherlands
| | - Yinghua Yu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan; Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA
| | - Peter A Bandettini
- Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA; Functional MRI Core Facility, National Institute of Mental Health, Bethesda, MD, USA
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31
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Baxter L, Moultrie F, Fitzgibbon S, Aspbury M, Mansfield R, Bastiani M, Rogers R, Jbabdi S, Duff E, Slater R. Functional and diffusion MRI reveal the neurophysiological basis of neonates' noxious-stimulus evoked brain activity. Nat Commun 2021; 12:2744. [PMID: 33980860 PMCID: PMC8115252 DOI: 10.1038/s41467-021-22960-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 04/05/2021] [Indexed: 11/20/2022] Open
Abstract
Understanding the neurophysiology underlying neonatal responses to noxious stimulation is central to improving early life pain management. In this neonatal multimodal MRI study, we use resting-state and diffusion MRI to investigate inter-individual variability in noxious-stimulus evoked brain activity. We observe that cerebral haemodynamic responses to experimental noxious stimulation can be predicted from separately acquired resting-state brain activity (n = 18). Applying this prediction model to independent Developing Human Connectome Project data (n = 215), we identify negative associations between predicted noxious-stimulus evoked responses and white matter mean diffusivity. These associations are subsequently confirmed in the original noxious stimulation paradigm dataset, validating the prediction model. Here, we observe that noxious-stimulus evoked brain activity in healthy neonates is coupled to resting-state activity and white matter microstructure, that neural features can be used to predict responses to noxious stimulation, and that the dHCP dataset could be utilised for future exploratory research of early life pain system neurophysiology.
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Affiliation(s)
- Luke Baxter
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Fiona Moultrie
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Sean Fitzgibbon
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | | | | | - Matteo Bastiani
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Richard Rogers
- Nuffield Department of Anaesthetics, John Radcliffe Hospital, Oxford, UK
| | - Saad Jbabdi
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Eugene Duff
- Department of Paediatrics, University of Oxford, Oxford, UK
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Rebeccah Slater
- Department of Paediatrics, University of Oxford, Oxford, UK.
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Perkins GA, Eggebrecht AT, Dehghani H. Quantitative evaluation of frequency domain measurements in high density diffuse optical tomography. JOURNAL OF BIOMEDICAL OPTICS 2021; 26:JBO-210034RR. [PMID: 33949158 PMCID: PMC8094378 DOI: 10.1117/1.jbo.26.5.056001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 04/19/2021] [Indexed: 05/15/2023]
Abstract
SIGNIFICANCE High density diffuse optical tomography (HD-DOT) as applied in functional near-infrared spectroscopy (fNIRS) is largely limited to continuous wave (CW) data. Using a single modulation frequency, frequency domain (FD) HD-DOT has recently demonstrated better localization of focal activation as compared to CW data. We show that combining CW and FD measurements and multiple modulation frequencies increases imaging performance in fNIRS. AIM We evaluate the benefits of multiple modulation frequencies, combining different frequencies as well as CW data in fNIRS HD-DOT. APPROACH A layered model was used, with activation occurring within a cortex layer. CW and FD measurements were simulated at 78, 141, and 203 MHz with and without noise. The localization error, full width half maximum, and effective resolution were evaluated. RESULTS Across the average of the three metrics, at 141 MHz, FD performed 8.4% better than CW, and the combination of CW and FD was 21.7% better than CW. FD measurements at 203 MHz performed 5% better than 78 MHz. Moreover, the three combined modulation frequencies of FD and CW performed up to 3.92% better than 141 MHz alone. CONCLUSIONS We show that combining CW and FD measurements offers better performance than FD alone, with higher modulation frequencies increasing accuracy. Combining CW and FD measurements at multiple modulation frequencies yields the best overall performance.
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Affiliation(s)
- Guy A. Perkins
- University of Birmingham, Sci-Phy-4-Health Centre for Doctoral Training, College of Engineering and Physical Sciences, Birmingham, United Kingdom
- University of Birmingham, College of Engineering and Physical Sciences, School of Computer Science, Birmingham, United Kingdom
| | - Adam T. Eggebrecht
- Washington University School of Medicine, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
| | - Hamid Dehghani
- University of Birmingham, College of Engineering and Physical Sciences, School of Computer Science, Birmingham, United Kingdom
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Kashyap S, Ivanov D, Havlicek M, Huber L, Poser BA, Uludağ K. Sub-millimetre resolution laminar fMRI using Arterial Spin Labelling in humans at 7 T. PLoS One 2021; 16:e0250504. [PMID: 33901230 PMCID: PMC8075193 DOI: 10.1371/journal.pone.0250504] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 04/07/2021] [Indexed: 12/02/2022] Open
Abstract
Laminar fMRI at ultra-high magnetic field strength is typically carried out using the Blood Oxygenation Level-Dependent (BOLD) contrast. Despite its unrivalled sensitivity to detecting activation, the BOLD contrast is limited in its spatial specificity due to signals stemming from intra-cortical ascending and pial veins. Alternatively, regional changes in perfusion (i.e., cerebral blood flow through tissue) are colocalised to neuronal activation, which can be non-invasively measured using Arterial Spin Labelling (ASL) MRI. In addition, ASL provides a quantitative marker of neuronal activation in terms of perfusion signal, which is simultaneously acquired along with the BOLD signal. However, ASL for laminar imaging is challenging due to the lower SNR of the perfusion signal and higher RF power deposition i.e., specific absorption rate (SAR) of ASL sequences. In the present study, we present for the first time in humans, isotropic sub-millimetre spatial resolution functional perfusion images using Flow-sensitive Alternating Inversion Recovery (FAIR) ASL with a 3D-EPI readout at 7 T. We show that robust statistical activation maps can be obtained with perfusion-weighting in a single session. We observed the characteristic BOLD amplitude increase towards the superficial laminae, and, in apparent discrepancy, the relative perfusion profile shows a decrease of the amplitude and the absolute perfusion profile a much smaller increase towards the cortical surface. Considering the draining vein effect on the BOLD signal using model-based spatial “convolution”, we show that the empirically measured perfusion and BOLD profiles are, in fact, consistent with each other. This study demonstrates that laminar perfusion fMRI in humans is feasible at 7 T and that caution must be exercised when interpreting BOLD signal laminar profiles as direct representation of the cortical distribution of neuronal activity.
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Affiliation(s)
- Sriranga Kashyap
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (M-BIC), Maastricht University, Maastricht, The Netherlands
- * E-mail: (SK); (DI)
| | - Dimo Ivanov
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (M-BIC), Maastricht University, Maastricht, The Netherlands
- * E-mail: (SK); (DI)
| | - Martin Havlicek
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Laurentius Huber
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (M-BIC), Maastricht University, Maastricht, The Netherlands
| | - Benedikt A. Poser
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (M-BIC), Maastricht University, Maastricht, The Netherlands
| | - Kâmil Uludağ
- Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Suwon, South Korea
- Department of Biomedical Engineering, N Center, Sungkyunkwan University, Suwon, South Korea
- Techna Institute & Koerner Scientist in MR Imaging, University Health Network, Toronto, Canada
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34
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Garcia B, Cerrotti F, Palminteri S. The description-experience gap: a challenge for the neuroeconomics of decision-making under uncertainty. Philos Trans R Soc Lond B Biol Sci 2021; 376:20190665. [PMID: 33423626 PMCID: PMC7815421 DOI: 10.1098/rstb.2019.0665] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/30/2020] [Indexed: 01/10/2023] Open
Abstract
The experimental investigation of decision-making in humans relies on two distinct types of paradigms, involving either description- or experience-based choices. In description-based paradigms, decision variables (i.e. payoffs and probabilities) are explicitly communicated by means of symbols. In experience-based paradigms decision variables are learnt from trial-by-trial feedback. In the decision-making literature, 'description-experience gap' refers to the fact that different biases are observed in the two experimental paradigms. Remarkably, well-documented biases of description-based choices, such as under-weighting of rare events and loss aversion, do not apply to experience-based decisions. Here, we argue that the description-experience gap represents a major challenge, not only to current decision theories, but also to the neuroeconomics research framework, which relies heavily on the translation of neurophysiological findings between human and non-human primate research. In fact, most non-human primate neurophysiological research relies on behavioural designs that share features of both description- and experience-based choices. As a consequence, it is unclear whether the neural mechanisms built from non-human primate electrophysiology should be linked to description-based or experience-based decision-making processes. The picture is further complicated by additional methodological gaps between human and non-human primate neuroscience research. After analysing these methodological challenges, we conclude proposing new lines of research to address them. This article is part of the theme issue 'Existence and prevalence of economic behaviours among non-human primates'.
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Affiliation(s)
| | | | - Stefano Palminteri
- Laboratoire de Neurosciences Cognitives et Computationnelles, Ecole Normale Supérieure, Institut National de la Santé et Recherche Médicale, Université de Recherche Paris Sciences et Lettres, Paris, France
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35
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Zamboni E, Kemper VG, Goncalves NR, Jia K, Karlaftis VM, Bell SJ, Giorgio J, Rideaux R, Goebel R, Kourtzi Z. Fine-scale computations for adaptive processing in the human brain. eLife 2020; 9:e57637. [PMID: 33170124 PMCID: PMC7688307 DOI: 10.7554/elife.57637] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 11/09/2020] [Indexed: 12/02/2022] Open
Abstract
Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2, and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.
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Affiliation(s)
- Elisa Zamboni
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Valentin G Kemper
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht UniversityMaastrichtNetherlands
- Department of Cognitive Neuroscience, Maastricht Brain Imaging Center, Maastricht UniversityMaastrichtNetherlands
| | | | - Ke Jia
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | | | - Samuel J Bell
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Joseph Giorgio
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Reuben Rideaux
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht UniversityMaastrichtNetherlands
- Department of Cognitive Neuroscience, Maastricht Brain Imaging Center, Maastricht UniversityMaastrichtNetherlands
| | - Zoe Kourtzi
- Department of Psychology, University of CambridgeCambridgeUnited Kingdom
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36
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Pérez-Rodas M, Pohmann R, Scheffler K, Heule R. Intravascular BOLD signal characterization of balanced SSFP experiments in human blood at high to ultrahigh fields. Magn Reson Med 2020; 85:2055-2068. [PMID: 33140871 DOI: 10.1002/mrm.28575] [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: 07/02/2020] [Revised: 10/08/2020] [Accepted: 10/09/2020] [Indexed: 11/08/2022]
Abstract
PURPOSE To investigate the intravascular contribution to the overall balanced SSFP (bSSFP) BOLD effect in human blood at high to ultrahigh field strengths (3 T, 9.4 T, and 14.1 T). METHODS Venous blood prepared at two different oxygenation levels (deoxygenated: Y ≈ 71%, oxygenated: Y ≈ 94%) was measured with phase-cycled bSSFP for varying TRs/flip angles at 3 T, 9.4 T, and 14.1 T. The oxygen sensitivity was analyzed by intrinsic MIRACLE (motion-insensitive rapid configuration relaxometry)-R2 estimation and passband signal differences. The intravascular BOLD-related signal change was extracted from the measured data for microvasculature and macrovasculature, and compared with the extravascular contribution obtained by Monte Carlo simulations. RESULTS The MIRACLE-R2 values showed a characteristic increase with longer TRs in deoxygenated blood, corroborating that SE-R2 data cannot be used to assess the intravascular bSSFP BOLD effect. Passband bSSFP signal differences measured at optimal flip angles of 30° at 3 T and 20° at 9.4 T/14.1 T revealed considerable relative intravascular contributions of 95%/70% at 3 T, 74%/43% at 9.4 T, 66%/46% at 14.1 T for TR = 5 ms, and 90%/65% at 3 T, 36%/27% at 9.4 T, 13%/15% at 14.1 T for TR = 10 ms in macrovascular/microvascular regimes. CONCLUSION The results indicate that intravascular effects have to be considered to better understand the origin of bSSFP BOLD contrast in functional MRI experiments, especially at short TRs. The MIRACLE-R2 method demonstrated the ability to quantify the apparent decrease in R2 due to rapid RF refocusing.
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Affiliation(s)
- Marlon Pérez-Rodas
- High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Graduate Training Centre of Neuroscience, IMPRS for Cognitive and Systems Neuroscience, University of Tübingen, Tübingen, Germany
| | - Rolf Pohmann
- High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Klaus Scheffler
- High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Rahel Heule
- High Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
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37
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Bollmann S, Barth M. New acquisition techniques and their prospects for the achievable resolution of fMRI. Prog Neurobiol 2020; 207:101936. [PMID: 33130229 DOI: 10.1016/j.pneurobio.2020.101936] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 09/10/2020] [Accepted: 10/18/2020] [Indexed: 01/17/2023]
Abstract
This work reviews recent advances in technologies for functional magnetic resonance imaging (fMRI) of the human brain and highlights the push for higher functional specificity based on increased spatial resolution and specific MR contrasts to reveal previously undetectable functional properties of small-scale cortical structures. We discuss how the combination of MR hardware, advanced acquisition techniques and various MR contrast mechanisms have enabled recent progress in functional neuroimaging. However, these advanced fMRI practices have only been applied to a handful of neuroscience questions to date, with the majority of the neuroscience community still using conventional imaging techniques. We thus discuss upcoming challenges and possibilities for fMRI technology development in human neuroscience. We hope that readers interested in functional brain imaging acquire an understanding of current and novel developments and potential future applications, even if they don't have a background in MR physics or engineering. We summarize the capabilities of standard fMRI acquisition schemes with pointers to relevant literature and comprehensive reviews and introduce more recent developments.
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Affiliation(s)
- Saskia Bollmann
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Markus Barth
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, QLD, Australia.
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38
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Malekian V, Rastegar F, Shafieizargar B, Nasiraei-Moghaddam A. SSFP fMRI at 3 tesla: Efficiency of polar acquisition-reconstruction technique. Magn Reson Imaging 2020; 74:171-180. [PMID: 32898650 DOI: 10.1016/j.mri.2020.09.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Revised: 08/20/2020] [Accepted: 09/02/2020] [Indexed: 12/31/2022]
Abstract
SSFP-based fMRI techniques, known for their high specificity and low geometrical distortion, look promising for high-resolution brain mapping. Nevertheless, they suffer from lack of speed and sensitivity, leading them to be exploited mostly in high-field scanners. Radial acquisition can help with these inefficiencies through better tSNR and more effective coverage of the spatial frequencies. Here, we present a SSFP-fMRI approach and experimentally investigate it at 3 T scanners using radial readout for acquisition. In particular, the visual activity is mapped through three bSSFP techniques: 1- Cartesian, 2- Radial with re-gridding reconstruction, 3- Radial with Polar Fourier Transform (PFT) reconstruction. In the PFT technique streaking artifacts, generated at high acceleration rates by re-gridding reconstruction, are avoided and pixel size in the final framework is retrospectively selectable. General agreement, but better tSNR of Radial reading, was first confirmed for these techniques in detection of neural activities at 2 × 2 mm2 in-plane resolution for all 28 subjects,. Next the outcome of the PFT algorithm with 1 × 1 mm2 pixel size was compared to images reconstructed by re-gridding (from the same raw data) with the identical pixel size through interpolation. The localization of the activity showed improvement in PFT over interpolation both qualitatively (i.e., well-fitting in gray-matter) and quantitatively (i.e., higher z-scores and tSNR). The proposed technique can therefore be considered as a remedy for lack of speed and sensitivity in SSFP-based fMRI, in conventional field strengths. The proposed approach is particularly useful in task-based studies when we concentrate on a ROI considerably smaller than FOV, without sacrificing spatial resolution.
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Affiliation(s)
- Vahid Malekian
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran; Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Iran
| | - Fatemeh Rastegar
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Iran; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Banafshe Shafieizargar
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Iran; imec-Vision Lab, Department of Physics, University of Antwerp, Belgium
| | - Abbas Nasiraei-Moghaddam
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran; Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Iran.
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39
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Jia K, Zamboni E, Kemper V, Rua C, Goncalves NR, Ng AKT, Rodgers CT, Williams G, Goebel R, Kourtzi Z. Recurrent Processing Drives Perceptual Plasticity. Curr Biol 2020; 30:4177-4187.e4. [PMID: 32888488 PMCID: PMC7658806 DOI: 10.1016/j.cub.2020.08.016] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 07/30/2020] [Accepted: 08/05/2020] [Indexed: 11/06/2022]
Abstract
Learning and experience are critical for translating ambiguous sensory information from our environments to perceptual decisions. Yet evidence on how training molds the adult human brain remains controversial, as fMRI at standard resolution does not allow us to discern the finer scale mechanisms that underlie sensory plasticity. Here, we combine ultra-high-field (7T) functional imaging at sub-millimeter resolution with orientation discrimination training to interrogate experience-dependent plasticity across cortical depths that are known to support dissociable brain computations. We demonstrate that learning alters orientation-specific representations in superficial rather than middle or deeper V1 layers, consistent with recurrent plasticity mechanisms via horizontal connections. Further, learning increases feedforward rather than feedback layer-to-layer connectivity in occipito-parietal regions, suggesting that sensory plasticity gates perceptual decisions. Our findings reveal finer scale plasticity mechanisms that re-weight sensory signals to inform improved decisions, bridging the gap between micro- and macro-circuits of experience-dependent plasticity. Discrimination training alters orientation representations in superficial V1 layers Orientation-specific V1 plasticity is independent of task context Discrimination training alters orientation representations in middle IPS layers Learning enhances feedforward connectivity from visual to parietal cortex
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Affiliation(s)
- Ke Jia
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Elisa Zamboni
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Valentin Kemper
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht 6229 ER, The Netherlands
| | - Catarina Rua
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | | | - Adrian Ka Tsun Ng
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK; Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong SAR, China
| | - Christopher T Rodgers
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Guy Williams
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht 6229 ER, The Netherlands
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK.
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40
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Secomb TW, Bullock KV, Boas DA, Sakadžić S. The mass transfer coefficient for oxygen transport from blood to tissue in cerebral cortex. J Cereb Blood Flow Metab 2020; 40:1634-1646. [PMID: 31423930 PMCID: PMC7370375 DOI: 10.1177/0271678x19870068] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The functioning of cerebral cortex depends on adequate tissue oxygenation. MRI-based techniques allow estimation of blood oxygen levels, tissue perfusion, and oxygen consumption rate (CMRO2), but do not directly measure partial pressure of oxygen (PO2) in tissue. To address the estimation of tissue PO2, the oxygen mass transfer coefficient (KTO2) is here defined as the CMRO2 divided by the difference in spatially averaged PO2 between blood and tissue, and is estimated by analyzing Krogh-cylinder type models. Resistance to radial diffusion of oxygen from microvessels to tissue is distributed within vessels and in the extravascular tissue. The value of KTO2 is shown to depend strongly on vascular length density and also on microvessel tube hematocrits and diameters, but to be insensitive to blood flow rate and to transient changes in flow or oxygen consumption. Estimated values of KTO2 are higher than implied by previous studies, implying smaller declines in PO2 from blood to tissue. Average tissue PO2 can be estimated from MRI-based measurements as average blood PO2 minus the product of KTO2 and CMRO2. For oxygen consumption rates and vascular densities typical of mouse cortex, the predicted difference between average blood and tissue PO2 is about 10 mmHg.
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Affiliation(s)
- Timothy W Secomb
- Department of Physiology, University of Arizona, Tucson, AZ, USA.,Program in Applied Mathematics, University of Arizona, Tucson, AZ, USA.,Physiological Sciences Graduate Program, University of Arizona, Tucson, AZ, USA
| | - Katherine V Bullock
- Physiological Sciences Graduate Program, University of Arizona, Tucson, AZ, USA
| | - David A Boas
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.,Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Sava Sakadžić
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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41
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Zhang L, Wang XH, Li L. Diagnosing autism spectrum disorder using brain entropy: A fast entropy method. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2020; 190:105240. [PMID: 31806393 DOI: 10.1016/j.cmpb.2019.105240] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 11/07/2019] [Accepted: 11/25/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND AND OBJECTIVE Previous resting-state fMRI-based diagnostic models for autism spectrum disorder (ASD) were based on traditional linear features. The complexity of the ASD brain remains unexplored. METHODS To increase our understanding of the nonlinear neural mechanisms in ASD, entropy (i.e., approximate entropy (ApEn) and sample entropy (SampEn)) method was used to analyze the resting-state fMRI datasets collected from 21 ASD patients and 26 typically developing (TD) individuals. Here, a fast entropy algorithm was proposed through matrix computation. We combined entropy with a support-vector machine and selected "important entropy" as features to diagnose ASD. The classification performance of the fast entropy method was compared to the state-of-the-art functional connectivity (FC) method. RESULTS The area under the receiver operating characteristic curve based on FC was 0.62. The areas under the receiver operating characteristic curves based on ApEn and SampEn were 0.79 and 0.89, respectively. The results showed that the proposed fast entropy method was more efficacious than the FC method. In addition, lower entropy was found in the ASD patients. The ApEn of the left postcentral gyrus (rs = -0.556, p = 0.009) and the SampEn of the right lingual gyrus (rs = -0.526, p = 0.014) were both significantly negatively related to Autism Diagnostic Observation Schedule total scores in the ASD patients. The proposed algorithm for entropy computation was faster than the traditional entropy method. CONCLUSIONS Our study provides a new perspective to better understand the neural mechanisms of ASD. Brain entropy based on a fast algorithm was applied to distinguish ASD patients from TD individuals. ApEn and SampEn could be potential biomarkers in ASD investigations.
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Affiliation(s)
- Liangliang Zhang
- School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Xun-Heng Wang
- Institute of Biomedical Engineering and Instrumentation, School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Lihua Li
- School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China; Institute of Biomedical Engineering and Instrumentation, School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.
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42
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Beckett AJS, Dadakova T, Townsend J, Huber L, Park S, Feinberg DA. Comparison of BOLD and CBV using 3D EPI and 3D GRASE for cortical layer functional MRI at 7 T. Magn Reson Med 2020; 84:3128-3145. [PMID: 32557752 DOI: 10.1002/mrm.28347] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 05/12/2020] [Accepted: 05/14/2020] [Indexed: 01/27/2023]
Abstract
PURPOSE Functional MRI (fMRI) at the mesoscale of cortical layers and columns requires both sensitivity and specificity, the latter of which can be compromised if the imaging method is affected by vascular artifacts, particularly cortical draining veins at the pial surface. Recent studies have shown that cerebral blood volume (CBV) imaging is more specific to the actual laminar locus of neural activity than BOLD imaging using standard gradient-echo EPI sequences. Gradient and spin-echo (GRASE) BOLD imaging has also shown greater specificity when compared with standard gradient-echo EPI BOLD. Here we directly compare CBV and BOLD contrasts in high-resolution imaging of the primary motor cortex for laminar functional MRI in four combinations of signal labeling, CBV using slice-selective slab-inversion vascular space occupancy (VASO) and BOLD, each with 3D gradient-echo EPI and zoomed 3D-GRASE image readouts. METHODS Activations were measured using each sequence and contrast combination during a motor task. Activation profiles across cortical depth were measured to assess the sensitivity and specificity (pial bias) of each method. RESULTS Both CBV imaging using gradient-echo 3D-EPI and BOLD imaging using 3D-GRASE show similar specificity and sensitivity and are therefore useful tools for mesoscopic functional MRI in the human cortex. The combination of GRASE and VASO did not demonstrate high levels of sensitivity, nor show increased specificity. CONCLUSION Three-dimensional EPI with VASO contrast and 3D-GRASE with BOLD contrast both demonstrate sufficient sensitivity and specificity for laminar functional MRI to be used by neuroscientists in a wide range of investigations of depth-dependent neural circuitry in the human brain.
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Affiliation(s)
- Alexander J S Beckett
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA.,Advanced MRI Technologies, Sebastopol, California, USA
| | - Tetiana Dadakova
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA
| | - Jennifer Townsend
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA.,Advanced MRI Technologies, Sebastopol, California, USA
| | - Laurentius Huber
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Suhyung Park
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA.,Advanced MRI Technologies, Sebastopol, California, USA
| | - David A Feinberg
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA.,Advanced MRI Technologies, Sebastopol, California, USA
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Jafarian A, Litvak V, Cagnan H, Friston KJ, Zeidman P. Comparing dynamic causal models of neurovascular coupling with fMRI and EEG/MEG. Neuroimage 2020; 216:116734. [PMID: 32179105 PMCID: PMC7322559 DOI: 10.1016/j.neuroimage.2020.116734] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 03/06/2020] [Accepted: 03/10/2020] [Indexed: 01/09/2023] Open
Abstract
This technical note presents a dynamic causal modelling (DCM) procedure for evaluating different models of neurovascular coupling in the human brain - using combined electromagnetic (M/EEG) and functional magnetic resonance imaging (fMRI) data. This procedure compares the evidence for biologically informed models of neurovascular coupling using Bayesian model comparison. First, fMRI data are used to localise regionally specific neuronal responses. The coordinates of these responses are then used as the location priors in a DCM of electrophysiological responses elicited by the same paradigm. The ensuing estimates of model parameters are then used to generate neuronal drive functions, which model pre- or post-synaptic activity for each experimental condition. These functions form the input to a model of neurovascular coupling, whose parameters are estimated from the fMRI data. Crucially, this enables one to evaluate different models of neurovascular coupling, using Bayesian model comparison - asking, for example, whether instantaneous or delayed, pre- or post-synaptic signals mediate haemodynamic responses. We provide an illustrative application of the procedure using a single-subject auditory fMRI and MEG dataset. The code and exemplar data accompanying this technical note are available through the statistical parametric mapping (SPM) software.
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Affiliation(s)
| | - Vladimir Litvak
- The Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Hayriye Cagnan
- MRC Brain Network Dynamics Unit (BNDU) at the University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karl J Friston
- The Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Peter Zeidman
- The Wellcome Centre for Human Neuroimaging, University College London, UK
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Ultra-high-resolution fMRI of Human Ventral Temporal Cortex Reveals Differential Representation of Categories and Domains. J Neurosci 2020; 40:3008-3024. [PMID: 32094202 DOI: 10.1523/jneurosci.2106-19.2020] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 02/10/2020] [Accepted: 02/12/2020] [Indexed: 11/21/2022] Open
Abstract
Human ventral temporal cortex (VTC) is critical for visual recognition. It is thought that this ability is supported by large-scale patterns of activity across VTC that contain information about visual categories. However, it is unknown how category representations in VTC are organized at the submillimeter scale and across cortical depths. To fill this gap in knowledge, we measured BOLD responses in medial and lateral VTC to images spanning 10 categories from five domains (written characters, bodies, faces, places, and objects) at an ultra-high spatial resolution of 0.8 mm using 7 Tesla fMRI in both male and female participants. Representations in lateral VTC were organized most strongly at the general level of domains (e.g., places), whereas medial VTC was also organized at the level of specific categories (e.g., corridors and houses within the domain of places). In both lateral and medial VTC, domain-level and category-level structure decreased with cortical depth, and downsampling our data to standard resolution (2.4 mm) did not reverse differences in representations between lateral and medial VTC. The functional diversity of representations across VTC partitions may allow downstream regions to read out information in a flexible manner according to task demands. These results bridge an important gap between electrophysiological recordings in single neurons at the micron scale in nonhuman primates and standard-resolution fMRI in humans by elucidating distributed responses at the submillimeter scale with ultra-high-resolution fMRI in humans.SIGNIFICANCE STATEMENT Visual recognition is a fundamental ability supported by human ventral temporal cortex (VTC). However, the nature of fine-scale, submillimeter distributed representations in VTC is unknown. Using ultra-high-resolution fMRI of human VTC, we found differential distributed visual representations across lateral and medial VTC. Domain representations (e.g., faces, bodies, places, characters) were most salient in lateral VTC, whereas category representations (e.g., corridors/houses within the domain of places) were equally salient in medial VTC. These results bridge an important gap between electrophysiological recordings in single neurons at a micron scale and fMRI measurements at a millimeter scale.
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Malekian V, Nasiraei-Moghaddam A, Akhavan A, Hossein-Zadeh GA. Efficient de-noising of high-resolution fMRI using local and sub-band information. J Neurosci Methods 2020; 331:108497. [PMID: 31698001 DOI: 10.1016/j.jneumeth.2019.108497] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Revised: 09/24/2019] [Accepted: 10/30/2019] [Indexed: 11/16/2022]
Abstract
BACKGROUND High-resolution fMRI, useful for accurate brain mapping, suffers from low functional sensitivity at a reasonable acquisition time. Conventional smoothing techniques although reduce the noise and boost the sensitivity, but degrade the spatial resolution of fMRI. NEW METHODS We propose a novel spatial de-noising technique to increase sensitivity while preserving the boundaries of active regions in the high-resolution fMRI. A modified version of PCA that utilizes adjacent voxels information (LPCA) is first suggested for de-noising. This technique is then further empowered by its application to wavelet sub-bands (WLPCA). RESULTS Proposed techniques were assessed on both simulated and experimental data. Identifiablity index was calculated for evaluation of the denoising on the simulated data. Maximum and mean z-scores along with LAE and SSIM were reported on experimental data for two presented techniques as well as Guassian smoothing. WLPCA outperformed other techniques in Identifiablity index, for simulation, and in preserving maximum z-score, for experimental study. COMPARISON WITH EXISTING METHODS The presented technique was developed to simultaneously suppress the noise and preserve the boundaries of active areas against leakage. For first aim, its achievable mean z-score was compared to conventional Gaussian. For second aim, its maximum z-score was compared to that of no-smoothing. While Gaussian and no-smoothing can work fine with only one measure, WLPCA was able to improve both measures concurrently. CONCLUSIONS The local PCA based methods, and in particular WLPCA, is an effective noise reduction step that preserves the spatial resolution by preventing activity leakage of high-resolution fMRI data.
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Affiliation(s)
- Vahid Malekian
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Abbas Nasiraei-Moghaddam
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.
| | - Amir Akhavan
- Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran
| | - Gholam-Ali Hossein-Zadeh
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran; School of Electrical and Computer Engineering, University College of Engineering, University of Tehran, Tehran, Iran
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Armstrong LE, Kavouras SA. Thirst and Drinking Paradigms: Evolution from Single Factor Effects to Brainwide Dynamic Networks. Nutrients 2019; 11:nu11122864. [PMID: 31766680 PMCID: PMC6950074 DOI: 10.3390/nu11122864] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 11/18/2019] [Accepted: 11/19/2019] [Indexed: 01/10/2023] Open
Abstract
The motivation to seek and consume water is an essential component of human fluid–electrolyte homeostasis, optimal function, and health. This review describes the evolution of concepts regarding thirst and drinking behavior, made possible by magnetic resonance imaging, animal models, and novel laboratory techniques. The earliest thirst paradigms focused on single factors such as dry mouth and loss of water from tissues. By the end of the 19th century, physiologists proposed a thirst center in the brain that was verified in animals 60 years later. During the early- and mid-1900s, the influences of gastric distention, neuroendocrine responses, circulatory properties (i.e., blood pressure, volume, concentration), and the distinct effects of intracellular dehydration and extracellular hypovolemia were recognized. The majority of these studies relied on animal models and laboratory methods such as microinjection or lesioning/oblation of specific brain loci. Following a quarter century (1994–2019) of human brain imaging, current research focuses on networks of networks, with thirst and satiety conceived as hemispheric waves of neuronal activations that traverse the brain in milliseconds. Novel technologies such as chemogenetics, optogenetics, and neuropixel microelectrode arrays reveal the dynamic complexity of human thirst, as well as the roles of motivation and learning in drinking behavior.
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Affiliation(s)
- Lawrence E. Armstrong
- Human Performance Laboratory and Department of Nutritional Sciences, University of Connecticut, Storrs, CT 06269-1110, USA
- Correspondence:
| | - Stavros A. Kavouras
- Arizona State University, College of Health Solutions, Hydration Science Lab, Phoenix, AZ 85004, USA;
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Caballero-Gaudes C, Moia S, Panwar P, Bandettini PA, Gonzalez-Castillo J. A deconvolution algorithm for multi-echo functional MRI: Multi-echo Sparse Paradigm Free Mapping. Neuroimage 2019; 202:116081. [PMID: 31419613 DOI: 10.1016/j.neuroimage.2019.116081] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 07/01/2019] [Accepted: 08/06/2019] [Indexed: 10/26/2022] Open
Abstract
This work introduces a novel algorithm for deconvolution of the BOLD signal in multi-echo fMRI data: Multi-echo Sparse Paradigm Free Mapping (ME-SPFM). Assuming a linear dependence of the BOLD percent signal change on the echo time (TE) and using sparsity-promoting regularized least squares estimation, ME-SPFM yields voxelwise time-varying estimates of the changes in the apparent transverse relaxation (ΔR2⁎) without prior knowledge of the timings of individual BOLD events. Our results in multi-echo fMRI data collected during a multi-task event-related paradigm at 3 Tesla demonstrate that the maps of R2⁎ changes obtained with ME-SPFM at the times of the stimulus trials show high spatial and temporal concordance with the activation maps and BOLD signals obtained with standard model-based analysis. This method yields estimates of ΔR2⁎ having physiologically plausible values. Owing to its ability to blindly detect events, ME-SPFM also enables us to map ΔR2⁎ associated with spontaneous, transient BOLD responses occurring between trials. This framework is a step towards deciphering the dynamic nature of brain activity in naturalistic paradigms, resting-state or experimental paradigms with unknown timing of the BOLD events.
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Affiliation(s)
| | - Stefano Moia
- Basque Center on Cognition, Brain and Language, San Sebastian, Spain
| | - Puja Panwar
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institute of Health, Bethesda, MD, USA
| | - Peter A Bandettini
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institute of Health, Bethesda, MD, USA; Functional MRI Core, National Institute of Mental Health, National Institute of Health, Bethesda, MD, USA
| | - Javier Gonzalez-Castillo
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institute of Health, Bethesda, MD, USA
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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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Drew PJ. Vascular and neural basis of the BOLD signal. Curr Opin Neurobiol 2019; 58:61-69. [PMID: 31336326 DOI: 10.1016/j.conb.2019.06.004] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Accepted: 06/22/2019] [Indexed: 12/26/2022]
Abstract
Neural activity in the brain is usually coupled to increases in local cerebral blood flow, leading to the increase in oxygenation that generates the BOLD fMRI signal. Recent work has begun to elucidate the vascular and neural mechanisms underlying the BOLD signal. The dilatory response is distributed throughout the vascular network. Arteries actively dilate within a second following neural activity increases, while venous distensions are passive and have a time course that last tens of seconds. Vasodilation, and thus local blood flow, is controlled by the activity of both neurons and astrocytes via multiple different pathways. The relationship between sensory-driven neural activity and the vascular dynamics in sensory areas are well-captured with a linear convolution model. However, depending on the behavioral state or brain region, the coupling between neural activity and hemodynamic signals can be weak or even inverted.
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Affiliation(s)
- Patrick J Drew
- Departments of Engineering Science and Mechanics, Biomedical Engineering and Neurosurgery, Pennsylvania State University, University Park, PA 16802, United States.
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Saleh Velez FG, Pinto CB, Bailin ES, Münger M, Ellison A, Costa BT, Crandell D, Bolognini N, Merabet LB, Fregni F. Real-time Video Projection in an MRI for Characterization of Neural Correlates Associated with Mirror Therapy for Phantom Limb Pain. J Vis Exp 2019. [PMID: 31058883 DOI: 10.3791/58800] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Mirror therapy (MT) has been proposed as an effective rehabilitative strategy to alleviate pain symptoms in amputees with phantom limb pain (PLP). However, establishing the neural correlates associated with MT therapy have been challenging given that it is difficult to administer the therapy effectively within a magnetic resonance imaging (MRI) scanner environment. To characterize the functional organization of cortical regions associated with this rehabilitative strategy, we have developed a combined behavioral and functional neuroimaging protocol that can be applied in participants with a leg amputation. This novel approach allows participants to undergo MT within the MRI scanner environment by viewing real-time video images captured by a camera. The images are viewed by the participant through a system of mirrors and a monitor that the participant views while lying on the scanner bed. In this manner, functional changes in cortical areas of interest (e.g., sensorimotor cortex) can be characterized in response to the direct application of MT.
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Affiliation(s)
- Faddi G Saleh Velez
- Laboratory of Neuromodulation & Center for Clinical Research Learning, Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital; University of Chicago Medical Center, Department of Neurology, University of Chicago
| | - Camila B Pinto
- Laboratory of Neuromodulation & Center for Clinical Research Learning, Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital; Department of Neuroscience and Behavior, Psychology Institute, University of Sao Paulo
| | - Emma S Bailin
- The Laboratory for Visual Neuroplasticity, Department of Ophthalmology, Massachusetts Eye and Ear Infirmary, Harvard Medical School
| | - Marionna Münger
- Laboratory of Neuromodulation & Center for Clinical Research Learning, Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital
| | - Andrew Ellison
- Center for Biomedical Imaging, Department of Anatomy and Neurobiology, Boston University School of Medicine
| | - Beatriz T Costa
- Laboratory of Neuromodulation & Center for Clinical Research Learning, Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital
| | - David Crandell
- Spaulding Rehabilitation Hospital, Harvard Medical School
| | - Nadia Bolognini
- Department of Psychology & Milan Center for Neuroscience, University of Milano-Bicocca; Neuropsychological Laboratory, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Auxologico Italiano
| | - Lotfi B Merabet
- The Laboratory for Visual Neuroplasticity, Department of Ophthalmology, Massachusetts Eye and Ear Infirmary, Harvard Medical School
| | - Felipe Fregni
- Laboratory of Neuromodulation & Center for Clinical Research Learning, Department of Physical Medicine and Rehabilitation, Harvard Medical School, Spaulding Rehabilitation Hospital;
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