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Foster SL, Breukelaar IA, Ekanayake K, Lewis S, Korgaonkar MS. Functional Magnetic Resonance Imaging of the Amygdala and Subregions at 3 Tesla: A Scoping Review. J Magn Reson Imaging 2024; 59:361-375. [PMID: 37352130 DOI: 10.1002/jmri.28836] [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: 03/05/2023] [Revised: 05/18/2023] [Accepted: 05/18/2023] [Indexed: 06/25/2023] Open
Abstract
The amygdalae are a pair of small brain structures, each of which is composed of three main subregions and whose function is implicated in neuropsychiatric conditions. Functional Magnetic Resonance Imaging (fMRI) has been utilized extensively in investigation of amygdala activation and functional connectivity (FC) with most clinical research sites now utilizing 3 Tesla (3T) MR systems. However, accurate imaging and analysis remains challenging not just due to the small size of the amygdala, but also its location deep in the temporal lobe. Selection of imaging parameters can significantly impact data quality with implications for the accuracy of study results and validity of conclusions. Wide variation exists in acquisition protocols with spatial resolution of some protocols suboptimal for accurate assessment of the amygdala as a whole, and for measuring activation and FC of the three main subregions, each of which contains multiple nuclei with specialized roles. The primary objective of this scoping review is to provide a broad overview of 3T fMRI protocols in use to image the activation and FC of the amygdala with particular reference to spatial resolution. The secondary objective is to provide context for a discussion culminating in recommendations for a standardized protocol for imaging activation of the amygdala and its subregions. As the advantages of big data and protocol harmonization in imaging become more apparent so, too, do the disadvantages of data heterogeneity. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Sheryl L Foster
- Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
- Department of Radiology, Westmead Hospital, Westmead, New South Wales, Australia
| | - Isabella A Breukelaar
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Westmead, New South Wales, Australia
| | - Kanchana Ekanayake
- University Library, The University of Sydney, Sydney, New South Wales, Australia
| | - Sarah Lewis
- Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Mayuresh S Korgaonkar
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Westmead, New South Wales, Australia
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2
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Schallmo MP, Weldon KB, Kamath RS, Moser HR, Montoya SA, Killebrew KW, Demro C, Grant AN, Marjańska M, Sponheim SR, Olman CA. The Psychosis Human Connectome Project: Design and rationale for studies of visual neurophysiology. Neuroimage 2023; 272:120060. [PMID: 36997137 PMCID: PMC10153004 DOI: 10.1016/j.neuroimage.2023.120060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 04/01/2023] Open
Abstract
Visual perception is abnormal in psychotic disorders such as schizophrenia. In addition to hallucinations, laboratory tests show differences in fundamental visual processes including contrast sensitivity, center-surround interactions, and perceptual organization. A number of hypotheses have been proposed to explain visual dysfunction in psychotic disorders, including an imbalance between excitation and inhibition. However, the precise neural basis of abnormal visual perception in people with psychotic psychopathology (PwPP) remains unknown. Here, we describe the behavioral and 7 tesla MRI methods we used to interrogate visual neurophysiology in PwPP as part of the Psychosis Human Connectome Project (HCP). In addition to PwPP (n = 66) and healthy controls (n = 43), we also recruited first-degree biological relatives (n = 44) in order to examine the role of genetic liability for psychosis in visual perception. Our visual tasks were designed to assess fundamental visual processes in PwPP, whereas MR spectroscopy enabled us to examine neurochemistry, including excitatory and inhibitory markers. We show that it is feasible to collect high-quality data across multiple psychophysical, functional MRI, and MR spectroscopy experiments with a sizable number of participants at a single research site. These data, in addition to those from our previously described 3 tesla experiments, will be made publicly available in order to facilitate further investigations by other research groups. By combining visual neuroscience techniques and HCP brain imaging methods, our experiments offer new opportunities to investigate the neural basis of abnormal visual perception in PwPP.
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Affiliation(s)
- Michael-Paul Schallmo
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN.
| | - Kimberly B Weldon
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN; Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Rohit S Kamath
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Hannah R Moser
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Samantha A Montoya
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Kyle W Killebrew
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Caroline Demro
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN; Department of Psychology, University of Minnesota, Minneapolis, MN
| | - Andrea N Grant
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Małgorzata Marjańska
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
| | - Scott R Sponheim
- Veterans Affairs Medical Center, Minneapolis, MN; Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Cheryl A Olman
- Department of Psychology, University of Minnesota, Minneapolis, MN; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN
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3
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Huang P, Correia MM, Rua C, Rodgers CT, Henson RN, Carlin JD. Correcting for Superficial Bias in 7T Gradient Echo fMRI. Front Neurosci 2021; 15:715549. [PMID: 34630010 PMCID: PMC8494131 DOI: 10.3389/fnins.2021.715549] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 08/17/2021] [Indexed: 11/29/2022] Open
Abstract
The arrival of submillimeter ultra high-field fMRI makes it possible to compare activation profiles across cortical layers. However, the blood oxygenation level dependent (BOLD) signal measured by gradient echo (GE) fMRI is biased toward superficial layers of the cortex, which is a serious confound for laminar analysis. Several univariate and multivariate analysis methods have been proposed to correct this bias. We compare these methods using computational simulations of 7T fMRI data from regions of interest (ROI) during a visual attention paradigm. We also tested the methods on a pilot dataset of human 7T fMRI data. The simulations show that two methods–the ratio of ROI means across conditions and a novel application of Deming regression–offer the most robust correction for superficial bias. Deming regression has the additional advantage that it does not require that the conditions differ in their mean activation over voxels within an ROI. When applied to the pilot dataset, we observed strikingly different layer profiles when different attention metrics were used, but were unable to discern any differences in laminar attention across layers when Deming regression or ROI ratio was applied. Our simulations demonstrates that accurate correction of superficial bias is crucial to avoid drawing erroneous conclusions from laminar analyses of GE fMRI data, and this is affirmed by the results from our pilot 7T fMRI data.
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Affiliation(s)
- Pei Huang
- Singapore Institute for Clinical Sciences, A∗STAR, Singapore, Singapore.,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Marta M Correia
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Catarina Rua
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, United Kingdom
| | | | - Richard N Henson
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Johan D Carlin
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
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Chen Z, Chen Z. Spatiotemporal multiscale ICA could invariantly extract task (motor) modes from wavelet subbands of fMRI data. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 208:106249. [PMID: 34218171 DOI: 10.1016/j.cmpb.2021.106249] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 06/18/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND AND OBJECTIVE . Given a timeseries of task-evoked functional MRI (fMRI) images (4D spatiotemporal data), we can extract the task mode by statistical independent component analysis (ICA). If the 4D data are spatiotemporally decomposed into subbands (multiresolutions in both time and space), is ICA still capable of extracting the task modes at multiscales? We answer this question using the well-established fingertapping motor-task experiments at 3T and 7T. The positive answer informs that a brain task is spatiotemporal separable at ICA decomposition and shift invariant at multiscales during activation over a finite region. METHODS . We collected a set of task fMRI datasets from sixteen subjects performing fingertapping at 3T and one single dataset from a different subject at 7T. For each 4D fMRI dataset, we first performed temporal wavelet transform (1D WT) at 3 levels using different wavelets (e.g. 'db1','db2', and 'sym4'), then extracted the task modes from the WT subbands via ICA (as called multi-timescale ICA). Meanwhile, we also performed task mode extraction by applying ICA to 3D spatial WT subbands (as called multi-spacescale ICA). Upon the multiscale ICA results, we identified the primary motor task modes in the motor cortex, in comparison to the raw fMRI data analysis (at level 0). RESULTS . In the 7T experiment, the multiscale ICA across 3 timescale levels and 2 spacescale levels could extract the primary task modes at a tasktcorr of 0.90 and 0.86, respectively, compared to 0.87 for the ICA task extraction from raw data. In the 3T experiment, the multiscale could extract the primary task mode with 0.92 and 0.91, while the ICA task extraction from raw data was 0.91. CONCLUSION . ICA could extract the primary motor task modes from wavelet-decomposed multi-timescale and multi-spacescale subbands, construing the broad spatial activation (extent >>voxel size) of the brain motor task performed in a long duration (>>TR). Our experimental results show the brain functional activity signal is spatiotemporal separable as well as shift invariant at multiscales in both time and space.
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Affiliation(s)
- Zeyuan Chen
- Department of Computer Sciences, University of California-Davis, CA 95616, United States
| | - Zikuan Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, CA 91010, United States; Zinv LLC, Albuquerque, NM 87108, United States.
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Schallmo MP, Weldon KB, Burton PC, Sponheim SR, Olman CA. Assessing methods for geometric distortion compensation in 7 T gradient echo functional MRI data. Hum Brain Mapp 2021; 42:4205-4223. [PMID: 34156132 PMCID: PMC8356998 DOI: 10.1002/hbm.25540] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 04/22/2021] [Accepted: 04/26/2021] [Indexed: 11/13/2022] Open
Abstract
Echo planar imaging (EPI) is widely used in functional and diffusion‐weighted MRI, but suffers from significant geometric distortions in the phase encoding direction caused by inhomogeneities in the static magnetic field (B0). This is a particular challenge for EPI at very high field (≥7 T), as distortion increases with higher field strength. A number of techniques for distortion correction exist, including those based on B0 field mapping and acquiring EPI scans with opposite phase encoding directions. However, few quantitative comparisons of distortion compensation methods have been performed using human EPI data, especially at very high field. Here, we compared distortion compensation using B0 field maps and opposite phase encoding scans in two different software packages (FSL and AFNI) applied to 7 T gradient echo (GE) EPI data from 31 human participants. We assessed distortion compensation quality by quantifying alignment to anatomical reference scans using Dice coefficients and mutual information. Performance between FSL and AFNI was equivalent. In our whole‐brain analyses, we found superior distortion compensation using GE scans with opposite phase encoding directions, versus B0 field maps or spin echo (SE) opposite phase encoding scans. However, SE performed better when analyses were limited to ventromedial prefrontal cortex, a region with substantial dropout. Matching the type of opposite phase encoding scans to the EPI data being corrected (e.g., SE‐to‐SE) also yielded better distortion correction. While the ideal distortion compensation approach likely varies depending on methodological differences across experiments, this study provides a framework for quantitative comparison of different distortion compensation methods.
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Affiliation(s)
- Michael-Paul Schallmo
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, Minnesota, USA
| | - Kimberly B Weldon
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, Minnesota, USA.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Philip C Burton
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA.,Office of the College of Liberal Arts Associate Dean for Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Scott R Sponheim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, Minnesota, USA.,Veterans Affairs Medical Center, Minneapolis, Minnesota, USA
| | - Cheryl A Olman
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA.,Department of Psychology, University of Minnesota, Minneapolis, Minnesota, USA
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6
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Pal A, Ogren JA, Aguila AP, Aysola R, Kumar R, Henderson LA, Harper RM, Macey PM. Functional organization of the insula in men and women with obstructive sleep apnea during Valsalva. Sleep 2021; 44:5864015. [PMID: 32592491 DOI: 10.1093/sleep/zsaa124] [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: 02/24/2020] [Revised: 05/11/2020] [Indexed: 12/26/2022] Open
Abstract
STUDY OBJECTIVES Obstructive sleep apnea (OSA) patients show impaired autonomic regulation, perhaps related to functional reorganization of the insula, which in healthy individuals shows sex-specific anterior and right dominance during sympathetic activation. We examined insular organization of responses to a Valsalva maneuver in OSA with functional magnetic resonance imaging (fMRI). METHODS We studied 43 newly diagnosed OSA (age mean ± SD: 46.8 ± 8.7 years; apnea-hypopnea index (AHI) ± SD: 32.1 ± 20.1 events/hour; 34 males) and 63 healthy (47.2 ± 8.8 years; 40 males) participants. Participants performed four 18-second Valsalva maneuvers (1-minute intervals, pressure ≥ 30 mmHg) during scanning. fMRI time trends from five insular gyri-anterior short (ASG); mid short (MSG); posterior short (PSG); anterior long (ALG); and posterior long (PLG)-were assessed for within-group responses and between-group differences with repeated measures ANOVA (p < 0.05); age and resting heart rate (HR) influences were also assessed. RESULTS Right and anterior fMRI signal dominance appeared in OSA and controls, with no between-group differences. Separation by sex revealed group differences. Left ASG anterior signal dominance was lower in OSA versus control males. Left ASG and ALG anterior dominance was higher in OSA versus control females. In all right gyri, only OSA females showed greater anterior dominance than controls. Right dominance was apparent in PSG and ALG in all groups; females showed right dominance in MSG and PLG. OSA males did not show PLG right dominance. Responses were influenced substantially by HR but modestly by age. CONCLUSIONS Anterior and right insular fMRI dominance appears similar in OSA versus control participants during the sympathetic phase of the Valsalva maneuver. OSA and control similarities were present in just males, but not necessarily females, which may reflect sex-specific neural injury.
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Affiliation(s)
- Amrita Pal
- UCLA School of Nursing, University of California, Los Angeles, CA
| | - Jennifer A Ogren
- Department of Neurobiology, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA
| | - Andrea P Aguila
- UCLA School of Nursing, University of California, Los Angeles, CA
| | - Ravi Aysola
- Division of Pulmonary and Critical Care, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA
| | - Rajesh Kumar
- Department of Anesthesiology, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA.,Department of Radiological Sciences, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA
| | - Luke A Henderson
- Department of Anatomy and Histology, Sydney Medical School, University of Sydney, Sydney, Australia
| | - Ronald M Harper
- Department of Neurobiology, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA
| | - Paul M Macey
- UCLA School of Nursing, University of California, Los Angeles, CA
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7
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Berman AJL, Grissom WA, Witzel T, Nasr S, Park DJ, Setsompop K, Polimeni JR. Ultra-high spatial resolution BOLD fMRI in humans using combined segmented-accelerated VFA-FLEET with a recursive RF pulse design. Magn Reson Med 2020; 85:120-139. [PMID: 32705723 DOI: 10.1002/mrm.28415] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 06/15/2020] [Accepted: 06/16/2020] [Indexed: 11/08/2022]
Abstract
PURPOSE To alleviate the spatial encoding limitations of single-shot echo-planar imaging (EPI) by developing multi-shot segmented EPI for ultra-high-resolution functional MRI (fMRI) with reduced ghosting artifacts from subject motion and respiration. THEORY AND METHODS Segmented EPI can reduce readout duration and reduce acceleration factors, however, the time elapsed between segment acquisitions (on the order of seconds) can result in intermittent ghosting, limiting its use for fMRI. Here, "FLEET" segment ordering, where segments are looped over before slices, was combined with a variable flip angle progression (VFA-FLEET) to improve inter-segment fidelity and maximize signal for fMRI. Scaling a sinc pulse's flip angle for each segment (VFA-FLEET-Sinc) produced inconsistent slice profiles and ghosting, therefore, a recursive Shinnar-Le Roux (SLR) radiofrequency (RF) pulse design was developed (VFA-FLEET-SLR) to generate unique pulses for every segment that together produce consistent slice profiles and signals. RESULTS The temporal stability of VFA-FLEET-SLR was compared against conventional-segmented EPI and VFA-FLEET-Sinc at 3T and 7T. VFA-FLEET-SLR showed reductions in both intermittent and stable ghosting compared to conventional-segmented and VFA-FLEET-Sinc, resulting in improved image quality with a minor trade-off in temporal SNR. Combining VFA-FLEET-SLR with acceleration, we achieved a 0.6-mm isotropic acquisition at 7T, without zoomed imaging or partial Fourier, demonstrating reliable detection of blood oxygenation level-dependent (BOLD) responses to a visual stimulus. To counteract the increased repetition time from segmentation, simultaneous multi-slice VFA-FLEET-SLR was demonstrated using RF-encoded controlled aliasing. CONCLUSIONS VFA-FLEET with a recursive RF pulse design supports acquisitions with low levels of artifact and spatial blur, enabling fMRI at previously inaccessible spatial resolutions with a "full-brain" field of view.
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Affiliation(s)
- Avery J L Berman
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - William A Grissom
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Thomas Witzel
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Shahin Nasr
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Daniel J Park
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.,Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.,Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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Han S, Liao C, Manhard MK, Park DJ, Bilgic B, Fair MJ, Wang F, Blazejewska AI, Grissom WA, Polimeni JR, Setsompop K. Accelerated spin-echo functional MRI using multisection excitation by simultaneous spin-echo interleaving (MESSI) with complex-encoded generalized slice dithered enhanced resolution (cgSlider) simultaneous multislice echo-planar imaging. Magn Reson Med 2020; 84:206-220. [PMID: 31840295 PMCID: PMC7083698 DOI: 10.1002/mrm.28108] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 10/29/2019] [Accepted: 11/14/2019] [Indexed: 12/14/2022]
Abstract
PURPOSE Spin-echo functional MRI (SE-fMRI) has the potential to improve spatial specificity when compared with gradient-echo fMRI. However, high spatiotemporal resolution SE-fMRI with large slice-coverage is challenging as SE-fMRI requires a long echo time to generate blood oxygenation level-dependent (BOLD) contrast, leading to long repetition times. The aim of this work is to develop an acquisition method that enhances the slice-coverage of SE-fMRI at high spatiotemporal resolution. THEORY AND METHODS An acquisition scheme was developed entitled multisection excitation by simultaneous spin-echo interleaving (MESSI) with complex-encoded generalized slice dithered enhanced resolution (cgSlider). MESSI uses the dead-time during the long echo time by interleaving the excitation and readout of 2 slices to enable 2× slice-acceleration, while cgSlider uses the stable temporal background phase in SE-fMRI to encode/decode 2 adjacent slices simultaneously with a "phase-constrained" reconstruction method. The proposed cgSlider-MESSI was also combined with simultaneous multislice (SMS) to achieve further slice-acceleration. This combined approach was used to achieve 1.5-mm isotropic whole-brain SE-fMRI with a temporal resolution of 1.5 s and was evaluated using sensory stimulation and breath-hold tasks at 3T. RESULTS Compared with conventional SE-SMS, cgSlider-MESSI-SMS provides 4-fold increase in slice-coverage for the same repetition time, with comparable temporal signal-to-noise ratio. Corresponding fMRI activation from cgSlider-MESSI-SMS for both fMRI tasks were consistent with those from conventional SE-SMS. Overall, cgSlider-MESSI-SMS achieved a 32× encoding-acceleration by combining Rinplane × MB × cgSlider × MESSI = 4 × 2 × 2 × 2. CONCLUSION High-quality, high-resolution whole-brain SE-fMRI was acquired at a short repetition time using cgSlider-MESSI-SMS. This method should be beneficial for high spatiotemporal resolution SE-fMRI studies requiring whole-brain coverage.
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Affiliation(s)
- SoHyun Han
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Congyu Liao
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Mary Kate Manhard
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Daniel Joseph Park
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Merlin J. Fair
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Medical Engineering & Medical Physics, Harvard-MIT Division of Health Sciences and Technology, Cambridge, Massachusetts
| | - Anna I. Blazejewska
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - William A. Grissom
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, Massachusetts
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, Massachusetts
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Kamimura HAS, Conti A, Toschi N, Konofagou EE. Ultrasound neuromodulation: mechanisms and the potential of multimodal stimulation for neuronal function assessment. FRONTIERS IN PHYSICS 2020; 8:150. [PMID: 32509757 PMCID: PMC7274478 DOI: 10.3389/fphy.2020.00150] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Focused ultrasound (FUS) neuromodulation has shown that mechanical waves can interact with cell membranes and mechanosensitive ion channels, causing changes in neuronal activity. However, the thorough understanding of the mechanisms involved in these interactions are hindered by different experimental conditions for a variety of animal scales and models. While the lack of complete understanding of FUS neuromodulation mechanisms does not impede benefiting from the current known advantages and potential of this technique, a precise characterization of its mechanisms of action and their dependence on experimental setup (e.g., tuning acoustic parameters and characterizing safety ranges) has the potential to exponentially improve its efficacy as well as spatial and functional selectivity. This could potentially reach the cell type specificity typical of other, more invasive techniques e.g., opto- and chemogenetics or at least orientation-specific selectivity afforded by transcranial magnetic stimulation. Here, the mechanisms and their potential overlap are reviewed along with discussions on the potential insights into mechanisms that magnetic resonance imaging sequences along with a multimodal stimulation approach involving electrical, magnetic, chemical, light, and mechanical stimuli can provide.
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Affiliation(s)
- Hermes A. S. Kamimura
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New Yor, NY, USA
| | - Allegra Conti
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
- Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Charlestown, MA, USA
| | - Elisa E. Konofagou
- Ultrasound Elasticity Imaging Laboratory, Department of Biomedical Engineering, Columbia University, New Yor, NY, USA
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10
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Huck J, Wanner Y, Fan AP, Jäger AT, Grahl S, Schneider U, Villringer A, Steele CJ, Tardif CL, Bazin PL, Gauthier CJ. High resolution atlas of the venous brain vasculature from 7 T quantitative susceptibility maps. Brain Struct Funct 2019; 224:2467-2485. [PMID: 31278570 DOI: 10.1007/s00429-019-01919-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 06/26/2019] [Indexed: 02/03/2023]
Abstract
The vascular organization of the human brain can determine neurological and neurophysiological functions, yet thus far it has not been comprehensively mapped. Aging and diseases such as dementia are known to be associated with changes to the vasculature and normative data could help detect these vascular changes in neuroimaging studies. Furthermore, given the well-known impact of venous vessels on the blood oxygen level dependent (BOLD) signal, information about the common location of veins could help detect biases in existing datasets. In this work, a quantitative atlas of the venous vasculature using quantitative susceptibility maps (QSM) acquired with a 0.6-mm isotropic resolution is presented. The Venous Neuroanatomy (VENAT) atlas was created from 5 repeated 7 Tesla MRI measurements in young and healthy volunteers (n = 20, 10 females, mean age = 25.1 ± 2.5 years) using a two-step registration method on 3D segmentations of the venous vasculature. This cerebral vein atlas includes the average vessel location, diameter (mean: 0.84 ± 0.33 mm) and curvature (0.11 ± 0.05 mm-1) from all participants and provides an in vivo measure of the angio-architectonic organization of the human brain and its variability. This atlas can be used as a basis to understand changes in the vasculature during aging and neurodegeneration, as well as vascular and physiological effects in neuroimaging.
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Affiliation(s)
- Julia Huck
- Department of Physics, Concordia University, 1455 Boulevard de Maisonneuve O, Montreal, QC, H3G 1M8, Canada.
| | - Yvonne Wanner
- Department of Physics, Concordia University, 1455 Boulevard de Maisonneuve O, Montreal, QC, H3G 1M8, Canada
- Universität Stuttgart, Stuttgart, Germany
| | | | - Anna-Thekla Jäger
- Max-Planck-Institut fur Kognitions- und Neurowissenschaften, Leipzig, Germany
| | - Sophia Grahl
- Max-Planck-Institut fur Kognitions- und Neurowissenschaften, Leipzig, Germany
| | - Uta Schneider
- Max-Planck-Institut fur Kognitions- und Neurowissenschaften, Leipzig, Germany
| | - Arno Villringer
- Max-Planck-Institut fur Kognitions- und Neurowissenschaften, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig, Leipzig, Germany
- Leipzig University Medical Centre, IFB Adiposity Diseases, Leipzig, Germany
- Leipzig University Medical Centre, Collaborative Research Centre, 1052-A5, Leipzig, Germany
| | - Christopher J Steele
- Max-Planck-Institut fur Kognitions- und Neurowissenschaften, Leipzig, Germany
- Department of Psychology, Concordia University, Montreal, Canada
| | - Christine L Tardif
- Department of Biomedical Engineering, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, Canada
| | - Pierre-Louis Bazin
- Max-Planck-Institut fur Kognitions- und Neurowissenschaften, Leipzig, Germany
- Faculty of Social and Behavioural Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Claudine J Gauthier
- Department of Physics, Concordia University, 1455 Boulevard de Maisonneuve O, Montreal, QC, H3G 1M8, Canada
- Montreal Heart Institute, Montreal, Canada
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11
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Sklerov M, Dayan E, Browner N. Functional neuroimaging of the central autonomic network: recent developments and clinical implications. Clin Auton Res 2018; 29:555-566. [PMID: 30470943 PMCID: PMC6858471 DOI: 10.1007/s10286-018-0577-0] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 11/07/2018] [Indexed: 12/08/2023]
Abstract
Purpose The central autonomic network (CAN) is an intricate system of brainstem, subcortical, and cortical structures that play key roles in the function of the autonomic nervous system. Prior to the advent of functional neuroimaging, in vivo studies of the human CAN were limited. The purpose of this review is to highlight the contribution of functional neuroimaging, specifically functional magnetic resonance imaging (fMRI), to the study of the CAN, and to discuss recent advances in this area. Additionally, we aim to emphasize exciting areas for future research. Methods We reviewed the existing literature in functional neuroimaging of the CAN. Here, we focus on fMRI research conducted in healthy human subjects, as well as research that has been done in disease states, to understand CAN function. To minimize confounding, papers examining CAN function in the context of cognition, emotion, pain, and affective disorders were excluded. Results fMRI has led to significant advances in the understanding of human CAN function. The CAN is composed of widespread brainstem and forebrain structures that are intricately connected and play key roles in reflexive and modulatory control of autonomic function. Conclusions fMRI technology has contributed extensively to current knowledge of CAN function. It holds promise to serve as a biomarker in disease states. With ongoing advancements in fMRI technology, there is great opportunity and need for future research involving the CAN.
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Affiliation(s)
- Miriam Sklerov
- Department of Neurology, University of North Carolina, 170 Manning Drive, CB# 7025, Chapel Hill, NC, 27599, USA.
| | - Eran Dayan
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina, 130 Mason Farm Road, CB# 7513, Chapel Hill, NC, 27599, USA
| | - Nina Browner
- Department of Neurology, University of North Carolina, 170 Manning Drive, CB# 7025, Chapel Hill, NC, 27599, USA
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12
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Edwards CA, Kouzani A, Lee KH, Ross EK. Neurostimulation Devices for the Treatment of Neurologic Disorders. Mayo Clin Proc 2017; 92:1427-1444. [PMID: 28870357 DOI: 10.1016/j.mayocp.2017.05.005] [Citation(s) in RCA: 87] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Revised: 04/16/2017] [Accepted: 05/01/2017] [Indexed: 12/01/2022]
Abstract
Rapid advancements in neurostimulation technologies are providing relief to an unprecedented number of patients affected by debilitating neurologic and psychiatric disorders. Neurostimulation therapies include invasive and noninvasive approaches that involve the application of electrical stimulation to drive neural function within a circuit. This review focuses on established invasive electrical stimulation systems used clinically to induce therapeutic neuromodulation of dysfunctional neural circuitry. These implantable neurostimulation systems target specific deep subcortical, cortical, spinal, cranial, and peripheral nerve structures to modulate neuronal activity, providing therapeutic effects for a myriad of neuropsychiatric disorders. Recent advances in neurotechnologies and neuroimaging, along with an increased understanding of neurocircuitry, are factors contributing to the rapid rise in the use of neurostimulation therapies to treat an increasingly wide range of neurologic and psychiatric disorders. Electrical stimulation technologies are evolving after remaining fairly stagnant for the past 30 years, moving toward potential closed-loop therapeutic control systems with the ability to deliver stimulation with higher spatial resolution to provide continuous customized neuromodulation for optimal clinical outcomes. Even so, there is still much to be learned about disease pathogenesis of these neurodegenerative and psychiatric disorders and the latent mechanisms of neurostimulation that provide therapeutic relief. This review provides an overview of the increasingly common stimulation systems, their clinical indications, and enabling technologies.
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Affiliation(s)
- Christine A Edwards
- School of Engineering, Deakin University, Geelong, Victoria, Australia; Department of Neurologic Surgery, Mayo Clinic, Rochester, MN
| | - Abbas Kouzani
- School of Engineering, Deakin University, Geelong, Victoria, Australia
| | - Kendall H Lee
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN; Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN
| | - Erika K Ross
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN; Department of Surgery, Mayo Clinic, Rochester, MN.
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13
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Schallmo MP, Grant AN, Burton PC, Olman CA. The effects of orientation and attention during surround suppression of small image features: A 7 Tesla fMRI study. J Vis 2017; 16:19. [PMID: 27565016 PMCID: PMC5015919 DOI: 10.1167/16.10.19] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
Although V1 responses are driven primarily by elements within a neuron's receptive field, which subtends about 1° visual angle in parafoveal regions, previous work has shown that localized fMRI responses to visual elements reflect not only local feature encoding but also long-range pattern attributes. However, separating the response to an image feature from the response to the surrounding stimulus and studying the interactions between these two responses demands both spatial precision and signal independence, which may be challenging to attain with fMRI. The present study used 7 Tesla fMRI with 1.2-mm resolution to measure the interactions between small sinusoidal grating patches (targets) at 3° eccentricity and surrounds of various sizes and orientations to test the conditions under which localized, context-dependent fMRI responses could be predicted from either psychophysical or electrophysiological data. Targets were presented at 8%, 16%, and 32% contrast while manipulating (a) spatial extent of parallel (strongly suppressive) or orthogonal (weakly suppressive) surrounds, (b) locus of attention, (c) stimulus onset asynchrony between target and surround, and (d) blocked versus event-related design. In all experiments, the V1 fMRI signal was lower when target stimuli were flanked by parallel versus orthogonal context. Attention amplified fMRI responses to all stimuli but did not show a selective effect on central target responses or a measurable effect on orientation-dependent surround suppression. Suppression of the V1 fMRI response by parallel surrounds was stronger than predicted from psychophysics but showed a better match to previous electrophysiological reports.
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14
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Hemifield columns co-opt ocular dominance column structure in human achiasma. Neuroimage 2016; 164:59-66. [PMID: 28017921 DOI: 10.1016/j.neuroimage.2016.12.063] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2016] [Revised: 12/06/2016] [Accepted: 12/21/2016] [Indexed: 02/01/2023] Open
Abstract
In the absence of an optic chiasm, visual input to the right eye is represented in primary visual cortex (V1) in the right hemisphere, while visual input to the left eye activates V1 in the left hemisphere. Retinotopic mapping In V1 reveals that in each hemisphere left and right visual hemifield representations are overlaid (Hoffmann et al., 2012). To explain how overlapping hemifield representations in V1 do not impair vision, we tested the hypothesis that visual projections from nasal and temporal retina create interdigitated left and right visual hemifield representations in V1, similar to the ocular dominance columns observed in neurotypical subjects (Victor et al., 2000). We used high-resolution fMRI at 7T to measure the spatial distribution of responses to left- and right-hemifield stimulation in one achiasmic subject. T2-weighted 2D Spin Echo images were acquired at 0.8mm isotropic resolution. The left eye was occluded. To the right eye, a presentation of flickering checkerboards alternated between the left and right visual fields in a blocked stimulus design. The participant performed a demanding orientation-discrimination task at fixation. A general linear model was used to estimate the preference of voxels in V1 to left- and right-hemifield stimulation. The spatial distribution of voxels with significant preference for each hemifield showed interdigitated clusters which densely packed V1 in the right hemisphere. The spatial distribution of hemifield-preference voxels in the achiasmic subject was stable between two days of testing and comparable in scale to that of human ocular dominance columns. These results are the first in vivo evidence showing that visual hemifield representations interdigitate in achiasmic V1 following a similar developmental course to that of ocular dominance columns in V1 with intact optic chiasm.
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15
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Soares JM, Magalhães R, Moreira PS, Sousa A, Ganz E, Sampaio A, Alves V, Marques P, Sousa N. A Hitchhiker's Guide to Functional Magnetic Resonance Imaging. Front Neurosci 2016; 10:515. [PMID: 27891073 PMCID: PMC5102908 DOI: 10.3389/fnins.2016.00515] [Citation(s) in RCA: 110] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Accepted: 10/25/2016] [Indexed: 12/12/2022] Open
Abstract
Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular both with clinicians and researchers as they are capable of providing unique insights into brain functions. However, multiple technical considerations (ranging from specifics of paradigm design to imaging artifacts, complex protocol definition, and multitude of processing and methods of analysis, as well as intrinsic methodological limitations) must be considered and addressed in order to optimize fMRI analysis and to arrive at the most accurate and grounded interpretation of the data. In practice, the researcher/clinician must choose, from many available options, the most suitable software tool for each stage of the fMRI analysis pipeline. Herein we provide a straightforward guide designed to address, for each of the major stages, the techniques, and tools involved in the process. We have developed this guide both to help those new to the technique to overcome the most critical difficulties in its use, as well as to serve as a resource for the neuroimaging community.
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Affiliation(s)
- José M. Soares
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of MinhoBraga, Portugal
- ICVS/3B's - PT Government Associate LaboratoryBraga, Portugal
| | - Ricardo Magalhães
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of MinhoBraga, Portugal
- ICVS/3B's - PT Government Associate LaboratoryBraga, Portugal
| | - Pedro S. Moreira
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of MinhoBraga, Portugal
- ICVS/3B's - PT Government Associate LaboratoryBraga, Portugal
| | - Alexandre Sousa
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of MinhoBraga, Portugal
- ICVS/3B's - PT Government Associate LaboratoryBraga, Portugal
- Department of Informatics, University of MinhoBraga, Portugal
| | - Edward Ganz
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of MinhoBraga, Portugal
- ICVS/3B's - PT Government Associate LaboratoryBraga, Portugal
| | - Adriana Sampaio
- Neuropsychophysiology Lab, CIPsi, School of Psychology, University of MinhoBraga, Portugal
| | - Victor Alves
- Department of Informatics, University of MinhoBraga, Portugal
| | - Paulo Marques
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of MinhoBraga, Portugal
- ICVS/3B's - PT Government Associate LaboratoryBraga, Portugal
| | - Nuno Sousa
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of MinhoBraga, Portugal
- ICVS/3B's - PT Government Associate LaboratoryBraga, Portugal
- Clinical Academic Center – BragaBraga, Portugal
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16
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Abstract
The human species has developed complex mathematical skills which likely emerge from a combination of multiple foundational abilities. One of them seems to be a preverbal capacity to extract and manipulate the numerosity of sets of objects which is shared with other species and in humans is thought to be integrated with symbolic knowledge to result in a more abstract representation of numerical concepts. For what concerns the functional neuroanatomy of this capacity, neuropsychology and functional imaging have localized key substrates of numerical processing in parietal and frontal cortex. However, traditional fMRI mapping relying on a simple subtraction approach to compare numerical and nonnumerical conditions is limited to tackle with sufficient precision and detail the issue of the underlying code for number, a question which more easily lends itself to investigation by methods with higher spatial resolution, such as neurophysiology. In recent years, progress has been made through the introduction of approaches sensitive to within-category discrimination in combination with fMRI (adaptation and multivariate pattern recognition), and the present review summarizes what these have revealed so far about the neural coding of individual numbers in the human brain, the format of these representations and parallels between human and monkey neurophysiology findings.
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Affiliation(s)
- E Eger
- INSERM Cognitive Neuroimaging Unit, NeuroSpin Center, CEA DSV/I2BM, Université Paris-Sud, Université Paris-Saclay, Gif/Yvette, France.
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17
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Chang C, Raven EP, Duyn JH. Brain-heart interactions: challenges and opportunities with functional magnetic resonance imaging at ultra-high field. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2016; 374:rsta.2015.0188. [PMID: 27044994 PMCID: PMC4822447 DOI: 10.1098/rsta.2015.0188] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/05/2016] [Indexed: 05/24/2023]
Abstract
Magnetic resonance imaging (MRI) at ultra-high field (UHF) strengths (7 T and above) offers unique opportunities for studying the human brain with increased spatial resolution, contrast and sensitivity. However, its reliability can be compromised by factors such as head motion, image distortion and non-neural fluctuations of the functional MRI signal. The objective of this review is to provide a critical discussion of the advantages and trade-offs associated with UHF imaging, focusing on the application to studying brain-heart interactions. We describe how UHF MRI may provide contrast and resolution benefits for measuring neural activity of regions involved in the control and mediation of autonomic processes, and in delineating such regions based on anatomical MRI contrast. Limitations arising from confounding signals are discussed, including challenges with distinguishing non-neural physiological effects from the neural signals of interest that reflect cardiorespiratory function. We also consider how recently developed data analysis techniques may be applied to high-field imaging data to uncover novel information about brain-heart interactions.
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Affiliation(s)
- Catie Chang
- Advanced Magnetic Resonance Imaging Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Erika P Raven
- Advanced Magnetic Resonance Imaging Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA Center for Functional and Molecular Imaging, Georgetown University Medical Center, Washington, DC 20007, USA
| | - Jeff H Duyn
- Advanced Magnetic Resonance Imaging Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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18
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Abstract
Inferring neural responses from functional magnetic resonance imaging (fMRI) data is challenging. Even if we take advantage of high-field systems to acquire data with submillimeter resolution, we are still acquiring data in which a single datum summarizes the responses of tens of thousands of neurons. Excitation and inhibition, spikes and subthreshold membrane potential modulations, local and long-range computations, and tuned and nonselective responses are mixed together in one signal. With a priori knowledge of the underlying neural population responses, careful experiment design allows us to manipulate the experiment or task design so that subpopulations are selectively modulated, and our experiments can reveal those tuning functions. However, because we want to be able to use fMRI to discover new kinds of tuning functions and selectivity, we cannot limit ourselves to experiments in which we already know what we are looking for. Broadly speaking, analyses that rely on classification of responses that are distributed across the local neural population [multi-voxel pattern analyses (MVPA)] offer the ability to discover new kinds of information representation and selectivities in neural subpopulations. There is, however, no way to determine how the information discovered with MVPA or other analyses is related to the underlying neuronal tuning functions. Therefore, we must continue to rely on behavioral, computational, and animal models to develop theories of information representation in mid-tier visual cortical areas. Once encoding models exist, fMRI can be powerful for testing these a priori models of information representation. As an aide in developing these models, an important contribution that fMRI can make to our understanding of mid-tier visual areas is derived from connectivity analyses and experiments that study information sharing between visual areas. This ability to quantify localized population average responses throughout the brain is the strength we can best leverage to discover new properties of local and long-range neural networks.
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19
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Iranpour J, Morrot G, Claise B, Jean B, Bonny JM. Using High Spatial Resolution to Improve BOLD fMRI Detection at 3T. PLoS One 2015; 10:e0141358. [PMID: 26550990 PMCID: PMC4638337 DOI: 10.1371/journal.pone.0141358] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Accepted: 10/07/2015] [Indexed: 11/19/2022] Open
Abstract
For different functional magnetic resonance imaging experiments using blood oxygenation level-dependent (BOLD) contrast, the acquisition of T2*-weighted scans at a high spatial resolution may be advantageous in terms of time-course signal-to-noise ratio and of BOLD sensitivity when the regions are prone to susceptibility artifacts. In this study, we explore this solution by examining how spatial resolution influences activations elicited when appetizing food pictures are viewed. Twenty subjects were imaged at 3 T with two different voxel volumes, 3.4 μl and 27 μl. Despite the diminution of brain coverage, we found that high-resolution acquisition led to a better detection of activations. Though known to suffer to different degrees from susceptibility artifacts, the activations detected by high spatial resolution were notably consistent with those reported in published activation likelihood estimation meta-analyses, corresponding to taste-responsive regions. Furthermore, these regions were found activated bilaterally, in contrast with previous findings. Both the reduction of partial volume effect, which improves BOLD contrast, and the mitigation of susceptibility artifact, which boosts the signal to noise ratio in certain regions, explained the better detection noted with high resolution. The present study provides further evidences that high spatial resolution is a valuable solution for human BOLD fMRI, especially for studying food-related stimuli.
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Affiliation(s)
| | - Gil Morrot
- Laboratoire Charles Coulomb—UMR 5221 CNRS, Université des Sciences et Techniques—Montpellier 2, place Eugène-Bataillon, 34090, Montpellier, France
| | - Béatrice Claise
- Neuroradiologie A, Plateforme Recherche IRM—CHU Gabriel-Montpied, F63000, Clermont-Ferrand, France
| | - Betty Jean
- Neuroradiologie A, Plateforme Recherche IRM—CHU Gabriel-Montpied, F63000, Clermont-Ferrand, France
| | - Jean-Marie Bonny
- UR370 QuaPA—INRA, F-63122, Saint-Genès-Champanelle, France
- * E-mail:
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20
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Baecke S, Lützkendorf R, Mallow J, Luchtmann M, Tempelmann C, Stadler J, Bernarding J. A proof-of-principle study of multi-site real-time functional imaging at 3T and 7T: Implementation and validation. Sci Rep 2015; 5:8413. [PMID: 25672521 PMCID: PMC4325335 DOI: 10.1038/srep08413] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2014] [Accepted: 01/19/2015] [Indexed: 11/09/2022] Open
Abstract
Real-time functional Magnetic Resonance Imaging (rtfMRI) is used mainly for neurofeedback or for brain-computer interfaces (BCI). But multi-site rtfMRI could in fact help in the application of new interactive paradigms such as the monitoring of mutual information flow or the controlling of objects in shared virtual environments. For that reason, a previously developed framework that provided an integrated control and data analysis of rtfMRI experiments was extended to enable multi-site rtfMRI. Important new components included a data exchange platform for analyzing the data of both MR scanners independently and/or jointly. Information related to brain activation can be displayed separately or in a shared view. However, a signal calibration procedure had to be developed and integrated in order to permit the connecting of sites that had different hardware and to account for different inter-individual brain activation levels. The framework was successfully validated in a proof-of-principle study with twelve volunteers. Thus the overall concept, the calibration of grossly differing signals, and BCI functionality on each site proved to work as required. To model interactions between brains in real-time, more complex rules utilizing mutual activation patterns could easily be implemented to allow for new kinds of social fMRI experiments.
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Affiliation(s)
- Sebastian Baecke
- Institute for Biometry and Medical Informatics, Otto-von-Guericke-University Magdeburg
| | - Ralf Lützkendorf
- Institute for Biometry and Medical Informatics, Otto-von-Guericke-University Magdeburg
| | - Johannes Mallow
- Institute for Biometry and Medical Informatics, Otto-von-Guericke-University Magdeburg
| | | | | | | | - Johannes Bernarding
- Institute for Biometry and Medical Informatics, Otto-von-Guericke-University Magdeburg
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21
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Baeck A, Kravitz D, Baker C, Op de Beeck HP. Influence of lexical status and orthographic similarity on the multi-voxel response of the visual word form area. Neuroimage 2015; 111:321-328. [PMID: 25665965 DOI: 10.1016/j.neuroimage.2015.01.060] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2014] [Revised: 01/06/2015] [Accepted: 01/30/2015] [Indexed: 10/24/2022] Open
Abstract
Previous studies demonstrated that a region in the left fusiform gyrus, often referred to as the 'visual word form area' (VWFA), is responsive to written words, but the precise functional role of VWFA remains unclear. In the present study, we investigated the influence of orthographic similarity, and lexical factors on the multivoxel response patterns to written stimuli. Using high-resolution fMRI at 7 T, we compared the organization of visual word representations in VWFA to the organization in early visual cortex and a language region in the superior temporal gyrus. Sets of four letter words and pseudowords were presented, in which orthographic similarity was parametrically manipulated. We found that during a lexical decision task VWFA is responsive to the lexical status of a stimulus, but both real words and pseudowords were further processed in terms of orthographic similarity. In contrast, early visual cortex was only responsive to the visual aspects of the stimuli and in the left superior temporal gyrus there was an interaction between lexical status and orthography such that only real words were processed in terms of orthographic similarity. These findings indicate that VWFA represents the word/non-word status of letter strings as well as their orthographic similarity.
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Affiliation(s)
- Annelies Baeck
- Laboratory of Biological Psychology, University of Leuven (KULeuven), Tiensestraat 102, 3000 Leuven, Belgium Laboratory of Experimental Psychology, University of Leuven (KULeuven), Tiensestraat 102, 3000 Leuven, Belgium Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 30901 USA
| | - Dwight Kravitz
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 30901 USA
| | - Chris Baker
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 30901 USA
| | - Hans P Op de Beeck
- Laboratory of Biological Psychology, University of Leuven (KULeuven), Tiensestraat 102, 3000 Leuven, Belgium
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22
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Yuan H, He B. Brain-computer interfaces using sensorimotor rhythms: current state and future perspectives. IEEE Trans Biomed Eng 2015; 61:1425-35. [PMID: 24759276 DOI: 10.1109/tbme.2014.2312397] [Citation(s) in RCA: 224] [Impact Index Per Article: 24.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Many studies over the past two decades have shown that people can use brain signals to convey their intent to a computer using brain-computer interfaces (BCIs). BCI systems extract specific features of brain activity and translate them into control signals that drive an output. Recently, a category of BCIs that are built on the rhythmic activity recorded over the sensorimotor cortex, i.e., the sensorimotor rhythm (SMR), has attracted considerable attention among the BCIs that use noninvasive neural recordings, e.g., electroencephalography (EEG), and have demonstrated the capability of multidimensional prosthesis control. This paper reviews the current state and future perspectives of SMR-based BCI and its clinical applications, in particular focusing on the EEG SMR. The characteristic features of SMR from the human brain are described and their underlying neural sources are discussed. The functional components of SMR-based BCI, together with its current clinical applications, are reviewed. Finally, limitations of SMR-BCIs and future outlooks are also discussed.
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23
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Naselaris T, Olman CA, Stansbury DE, Ugurbil K, Gallant JL. A voxel-wise encoding model for early visual areas decodes mental images of remembered scenes. Neuroimage 2014; 105:215-28. [PMID: 25451480 DOI: 10.1016/j.neuroimage.2014.10.018] [Citation(s) in RCA: 161] [Impact Index Per Article: 16.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2014] [Revised: 09/24/2014] [Accepted: 10/08/2014] [Indexed: 01/14/2023] Open
Abstract
Recent multi-voxel pattern classification (MVPC) studies have shown that in early visual cortex patterns of brain activity generated during mental imagery are similar to patterns of activity generated during perception. This finding implies that low-level visual features (e.g., space, spatial frequency, and orientation) are encoded during mental imagery. However, the specific hypothesis that low-level visual features are encoded during mental imagery is difficult to directly test using MVPC. The difficulty is especially acute when considering the representation of complex, multi-object scenes that can evoke multiple sources of variation that are distinct from low-level visual features. Therefore, we used a voxel-wise modeling and decoding approach to directly test the hypothesis that low-level visual features are encoded in activity generated during mental imagery of complex scenes. Using fMRI measurements of cortical activity evoked by viewing photographs, we constructed voxel-wise encoding models of tuning to low-level visual features. We also measured activity as subjects imagined previously memorized works of art. We then used the encoding models to determine if putative low-level visual features encoded in this activity could pick out the imagined artwork from among thousands of other randomly selected images. We show that mental images can be accurately identified in this way; moreover, mental image identification accuracy depends upon the degree of tuning to low-level visual features in the voxels selected for decoding. These results directly confirm the hypothesis that low-level visual features are encoded during mental imagery of complex scenes. Our work also points to novel forms of brain-machine interaction: we provide a proof-of-concept demonstration of an internet image search guided by mental imagery.
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Affiliation(s)
- Thomas Naselaris
- Department of Neurosciences, Medical University of South Carolina, SC, USA.
| | - Cheryl A Olman
- Department of Psychology, University of Minnesota, MN, USA; Center for Magnetic Resonance Research, University of Minnesota, MN, USA
| | | | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, MN, USA
| | - Jack L Gallant
- Vision Science Group, University of California, Berkeley, CA, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA; Department of Psychology, University of California, Berkeley, CA, USA
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24
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Functional network mirrored in the prefrontal cortex, caudate nucleus, and thalamus: high-resolution functional imaging and structural connectivity. J Neurosci 2014; 34:9202-12. [PMID: 25009254 DOI: 10.1523/jneurosci.0228-14.2014] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Despite myriads of studies on a parallel organization of cortico-striatal-thalamo-cortical loops, direct evidence of this has been lacking for the healthy human brain. Here, we scrutinize the functional specificity of the cortico-subcortical loops depending on varying levels of cognitive hierarchy as well as their structural connectivity with high-resolution fMRI and diffusion-weighted MRI (dMRI) at 7 tesla. Three levels of cognitive hierarchy were implemented in two domains: second language and nonlanguage. In fMRI, for the higher level, activations were found in the ventroanterior portion of the prefrontal cortex (PFC), the head of the caudate nucleus (CN), and the ventral anterior nucleus (VA) in the thalamus. Conversely, for the lower level, activations were located in the posterior region of the PFC, the body of the CN, and the medial dorsal nucleus (MD) in the thalamus. This gradient pattern of activations was furthermore shown to be tenable by the parallel connectivity in dMRI tractography connecting the anterior regions of the PFC with the head of the CN and the VA in the thalamus, whereas the posterior activations of the PFC were linked to the body of the CN and the MD in the thalamus. This is the first human in vivo study combining fMRI and dMRI showing that the functional specificity is mirrored within the cortico-subcortical loop substantiated by parallel networks.
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Boyacioğlu R, Schulz J, Müller NC, Koopmans PJ, Barth M, Norris DG. Whole brain, high resolution multiband spin-echo EPI fMRI at 7T: A comparison with gradient-echo EPI using a color-word Stroop task. Neuroimage 2014; 97:142-50. [DOI: 10.1016/j.neuroimage.2014.04.011] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2013] [Revised: 03/24/2014] [Accepted: 04/04/2014] [Indexed: 11/28/2022] Open
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Use of functional imaging across clinical phases in CNS drug development. Transl Psychiatry 2013; 3:e282. [PMID: 23860483 PMCID: PMC3731782 DOI: 10.1038/tp.2013.43] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2013] [Accepted: 03/15/2013] [Indexed: 12/20/2022] Open
Abstract
The use of novel brain biomarkers using nuclear magnetic resonance imaging holds potential of making central nervous system (CNS) drug development more efficient. By evaluating changes in brain function in the disease state or drug effects on brain function, the technology opens up the possibility of obtaining objective data on drug effects in the living awake brain. By providing objective data, imaging may improve the probability of success of identifying useful drugs to treat CNS diseases across all clinical phases (I-IV) of drug development. The evolution of functional imaging and the promise it holds to contribute to drug development will require the development of standards (including good imaging practice), but, if well integrated into drug development, functional imaging can define markers of CNS penetration, drug dosing and target engagement (even for drugs that are not amenable to positron emission tomography imaging) in phase I; differentiate objective measures of efficacy and side effects and responders vs non-responders in phase II, evaluate differences between placebo and drug in phase III trials and provide insights into disease modification in phase IV trials.
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Olman CA, Harel N, Feinberg DA, He S, Zhang P, Ugurbil K, Yacoub E. Layer-specific fMRI reflects different neuronal computations at different depths in human V1. PLoS One 2012; 7:e32536. [PMID: 22448223 PMCID: PMC3308958 DOI: 10.1371/journal.pone.0032536] [Citation(s) in RCA: 138] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2011] [Accepted: 01/31/2012] [Indexed: 11/19/2022] Open
Abstract
Recent work has established that cerebral blood flow is regulated at a spatial scale that can be resolved by high field fMRI to show cortical columns in humans. While cortical columns represent a cluster of neurons with similar response properties (spanning from the pial surface to the white matter), important information regarding neuronal interactions and computational processes is also contained within a single column, distributed across the six cortical lamina. A basic understanding of underlying neuronal circuitry or computations may be revealed through investigations of the distribution of neural responses at different cortical depths. In this study, we used T2-weighted imaging with 0.7 mm (isotropic) resolution to measure fMRI responses at different depths in the gray matter while human subjects observed images with either recognizable or scrambled (physically impossible) objects. Intact and scrambled images were partially occluded, resulting in clusters of activity distributed across primary visual cortex. A subset of the identified clusters of voxels showed a preference for scrambled objects over intact; in these clusters, the fMRI response in middle layers was stronger during the presentation of scrambled objects than during the presentation of intact objects. A second experiment, using stimuli targeted at either the magnocellular or the parvocellular visual pathway, shows that laminar profiles in response to parvocellular-targeted stimuli peak in more superficial layers. These findings provide new evidence for the differential sensitivity of high-field fMRI to modulations of the neural responses at different cortical depths.
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Affiliation(s)
- Cheryl A. Olman
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America
- Department of Neurosurgery, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - David A. Feinberg
- Advanced MRI Technologies, Sebastopol, California, United States of America
| | - Sheng He
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Peng Zhang
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America
- * E-mail:
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