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Báez-Yáñez MG, Siero JCW, Curcic V, van Osch MJP, Petridou N. On the influence of the vascular architecture on Gradient Echo and Spin Echo BOLD fMRI signals across cortical depth: a simulation approach based on realistic 3D vascular networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.30.596593. [PMID: 38853905 PMCID: PMC11160811 DOI: 10.1101/2024.05.30.596593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
GE-BOLD contrast stands out as the predominant technique in functional MRI experiments for its high sensitivity and straightforward implementation. GE-BOLD exhibits rather similar sensitivity to vessels independent of their size at submillimeter resolution studies like those examining cortical columns and laminae. However, the presence of nonspecific macrovascular contributions poses a challenge to accurately isolate neuronal activity. SE-BOLD increases specificity towards small vessels, thereby enhancing its specificity to neuronal activity, due to the effective suppression of extravascular contributions caused by macrovessels with its refocusing pulse. However, even SE-BOLD measurements may not completely remove these macrovascular contributions. By simulating hemodynamic signals across cortical depth, we gain insights into vascular contributions to the laminar BOLD signal. In this study, we employed four realistic 3D vascular models to simulate oxygen saturation states in various vascular compartments, aiming to characterize both intravascular and extravascular contributions to GE and SE signals, and corresponding BOLD signal changes, across cortical depth at 7T. Simulations suggest that SE-BOLD cannot completely reduce the macrovascular contribution near the pial surface. Simulations also show that both the specificity and signal amplitude of BOLD signals at 7T depend on the spatial arrangement of large vessels throughout cortical depth and on the pial surface.
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Affiliation(s)
- Mario Gilberto Báez-Yáñez
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Jeroen C W Siero
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
- Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, the Netherlands
| | - Vanja Curcic
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Matthias J P van Osch
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Natalia Petridou
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
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2
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Báez-Yáñez MG, Schellekens W, Bhogal AA, Roefs ECA, van Osch MJP, Siero JCW, Petridou N. A fully synthetic three-dimensional human cerebrovascular model based on histological characteristics to investigate the hemodynamic fingerprint of the layer BOLD fMRI signal formation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.24.595716. [PMID: 38826311 PMCID: PMC11142244 DOI: 10.1101/2024.05.24.595716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Recent advances in functional magnetic resonance imaging (fMRI) at ultra-high field (≥7 tesla), novel hardware, and data analysis methods have enabled detailed research on neurovascular function, such as cortical layer-specific activity, in both human and nonhuman species. A widely used fMRI technique relies on the blood oxygen level-dependent (BOLD) signal. BOLD fMRI offers insights into brain function by measuring local changes in cerebral blood volume, cerebral blood flow, and oxygen metabolism induced by increased neuronal activity. Despite its potential, interpreting BOLD fMRI data is challenging as it is only an indirect measurement of neuronal activity. Computational modeling can help interpret BOLD data by simulating the BOLD signal formation. Current developments have focused on realistic 3D vascular models based on rodent data to understand the spatial and temporal BOLD characteristics. While such rodent-based vascular models highlight the impact of the angioarchitecture on the BOLD signal amplitude, anatomical differences between the rodent and human vasculature necessitate the development of human-specific models. Therefore, a computational framework integrating human cortical vasculature, hemodynamic changes, and biophysical properties is essential. Here, we present a novel computational approach: a three-dimensional VAscular MOdel based on Statistics (3D VAMOS), enabling the investigation of the hemodynamic fingerprint of the BOLD signal within a model encompassing a fully synthetic human 3D cortical vasculature and hemodynamics. Our algorithm generates microvascular and macrovascular architectures based on morphological and topological features from the literature on human cortical vasculature. By simulating specific oxygen saturation states and biophysical interactions, our framework characterizes the intravascular and extravascular signal contributions across cortical depth and voxel-wise levels for gradient-echo and spin-echo readouts. Thereby, the 3D VAMOS computational framework demonstrates that using human characteristics significantly affects the BOLD fingerprint, making it an essential step in understanding the fundamental underpinnings of layer-specific fMRI experiments.
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Affiliation(s)
- Mario Gilberto Báez-Yáñez
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Wouter Schellekens
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
- Donders Centre for Cognitive Neuroimaging, Radboud UMC, Nijmegen, Netherlands
| | - Alex A Bhogal
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Emiel C A Roefs
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Matthias J P van Osch
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Jeroen C W Siero
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
- Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, the Netherlands
| | - Natalia Petridou
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
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3
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Amor Z, Ciuciu P, G R C, Daval-Frérot G, Mauconduit F, Thirion B, Vignaud A. Non-Cartesian 3D-SPARKLING vs Cartesian 3D-EPI encoding schemes for functional Magnetic Resonance Imaging at 7 Tesla. PLoS One 2024; 19:e0299925. [PMID: 38739571 PMCID: PMC11090341 DOI: 10.1371/journal.pone.0299925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 02/16/2024] [Indexed: 05/16/2024] Open
Abstract
The quest for higher spatial and/or temporal resolution in functional MRI (fMRI) while preserving a sufficient temporal signal-to-noise ratio (tSNR) has generated a tremendous amount of methodological contributions in the last decade ranging from Cartesian vs. non-Cartesian readouts, 2D vs. 3D acquisition strategies, parallel imaging and/or compressed sensing (CS) accelerations and simultaneous multi-slice acquisitions to cite a few. In this paper, we investigate the use of a finely tuned version of 3D-SPARKLING. This is a non-Cartesian CS-based acquisition technique for high spatial resolution whole-brain fMRI. We compare it to state-of-the-art Cartesian 3D-EPI during both a retinotopic mapping paradigm and resting-state acquisitions at 1mm3 (isotropic spatial resolution). This study involves six healthy volunteers and both acquisition sequences were run on each individual in a randomly-balanced order across subjects. The performances of both acquisition techniques are compared to each other in regards to tSNR, sensitivity to the BOLD effect and spatial specificity. Our findings reveal that 3D-SPARKLING has a higher tSNR than 3D-EPI, an improved sensitivity to detect the BOLD contrast in the gray matter, and an improved spatial specificity. Compared to 3D-EPI, 3D-SPARKLING yields, on average, 7% more activated voxels in the gray matter relative to the total number of activated voxels.
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Affiliation(s)
- Zaineb Amor
- CEA, Joliot, NeuroSpin, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Philippe Ciuciu
- CEA, Joliot, NeuroSpin, Université Paris-Saclay, Gif-sur-Yvette, France
- Inria, MIND team, Université Paris-Saclay, Palaiseau, France
| | - Chaithya G R
- CEA, Joliot, NeuroSpin, Université Paris-Saclay, Gif-sur-Yvette, France
- Inria, MIND team, Université Paris-Saclay, Palaiseau, France
| | - Guillaume Daval-Frérot
- CEA, Joliot, NeuroSpin, Université Paris-Saclay, Gif-sur-Yvette, France
- Inria, MIND team, Université Paris-Saclay, Palaiseau, France
- Siemens Heathineers, Courbevoie, France
| | - Franck Mauconduit
- CEA, Joliot, NeuroSpin, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Bertrand Thirion
- CEA, Joliot, NeuroSpin, Université Paris-Saclay, Gif-sur-Yvette, France
- Inria, MIND team, Université Paris-Saclay, Palaiseau, France
| | - Alexandre Vignaud
- CEA, Joliot, NeuroSpin, Université Paris-Saclay, Gif-sur-Yvette, France
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4
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Faes LK, Lage-Castellanos A, Valente G, Yu Z, Cloos MA, Vizioli L, Moeller S, Yacoub E, De Martino F. Evaluating the effect of denoising submillimeter auditory fMRI data with NORDIC. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.24.577070. [PMID: 38328173 PMCID: PMC10849717 DOI: 10.1101/2024.01.24.577070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Functional magnetic resonance imaging (fMRI) has emerged as an essential tool for exploring human brain function. Submillimeter fMRI, in particular, has emerged as a tool to study mesoscopic computations. The inherently low signal-to-noise ratio (SNR) at submillimeter resolutions warrants the use of denoising approaches tailored at reducing thermal noise - the dominant contributing noise component in high resolution fMRI. NORDIC PCA is one of such approaches, and has been benchmarked against other approaches in several applications. Here, we investigate the effects that two versions of NORDIC denoising have on auditory submillimeter data. As investigating auditory functional responses poses unique challenges, we anticipated that the benefit of this technique would be especially pronounced. Our results show that NORDIC denoising improves the detection sensitivity and the reliability of estimates in submillimeter auditory fMRI data. These effects can be explained by the reduction of the noise-induced signal variability. However, we also observed a reduction in the average response amplitude (percent signal), which may suggest that a small amount of signal was also removed. We conclude that, while evaluating the effects of the signal reduction induced by NORDIC may be necessary for each application, using NORDIC in high resolution auditory fMRI studies may be advantageous because of the large reduction in variability of the estimated responses.
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Affiliation(s)
- Lonike K. Faes
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, The Netherlands
| | - Agustin Lage-Castellanos
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, The Netherlands
- Department of Neuroinformatics, Cuban Neuroscience Center, Havana City 11600, Cuba
| | - Giancarlo Valente
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, The Netherlands
| | - Zidan Yu
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, USA
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- MRI Research Center, University of Hawaii, United States
| | - Martijn A. Cloos
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, USA
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
- Australian Institute for Bioengineering and Nanotechnology, University of Queensland, St Lucia 4066, Australia
| | - Luca Vizioli
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Steen Moeller
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Federico De Martino
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD, Maastricht, The Netherlands
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
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5
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Feinberg DA, Beckett AJS, Vu AT, Stockmann J, Huber L, Ma S, Ahn S, Setsompop K, Cao X, Park S, Liu C, Wald LL, Polimeni JR, Mareyam A, Gruber B, Stirnberg R, Liao C, Yacoub E, Davids M, Bell P, Rummert E, Koehler M, Potthast A, Gonzalez-Insua I, Stocker S, Gunamony S, Dietz P. Next-generation MRI scanner designed for ultra-high-resolution human brain imaging at 7 Tesla. Nat Methods 2023; 20:2048-2057. [PMID: 38012321 PMCID: PMC10703687 DOI: 10.1038/s41592-023-02068-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 10/09/2023] [Indexed: 11/29/2023]
Abstract
To increase granularity in human neuroimaging science, we designed and built a next-generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200 mT m-1, 900 T m-1s-1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35-0.45 mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.
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Affiliation(s)
- David A Feinberg
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
- Advanced MRI Technologies, Sebastopol, CA, USA.
| | - Alexander J S Beckett
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Advanced MRI Technologies, Sebastopol, CA, USA
| | - An T Vu
- Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
- San Francisco Veteran Affairs Health Care System, San Francisco, CA, USA
| | - Jason Stockmann
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Laurentius Huber
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | | | | | - Kawin Setsompop
- Radiological Sciences Laboratory, Stanford University, Stanford, CA, USA
| | - Xiaozhi Cao
- Radiological Sciences Laboratory, Stanford University, Stanford, CA, USA
| | - Suhyung Park
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Department of Computer Engineering, Chonnam National University, Gwangju, Republic of Korea
- Department of ICT Convergence System Engineering, Chonnam National University, Gwangju, Republic of Korea
| | - Chunlei Liu
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Lawrence L Wald
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Jonathan R Polimeni
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Azma Mareyam
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Bernhard Gruber
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
- BARNLabs, Muenzkirchen, Austria
| | | | - Congyu Liao
- Radiological Sciences Laboratory, Stanford University, Stanford, CA, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Mathias Davids
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Paul Bell
- Siemens Medical Solutions, Malvern, PA, USA
| | | | | | | | | | | | - Shajan Gunamony
- Imaging Centre of Excellence, University of Glasgow, Glasgow, UK
- MR CoilTech Limited, Glasgow, UK
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6
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Kam KY, Chang DHF. Sensory eye dominance plasticity in the human adult visual cortex. Front Neurosci 2023; 17:1250493. [PMID: 37746154 PMCID: PMC10513037 DOI: 10.3389/fnins.2023.1250493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 08/17/2023] [Indexed: 09/26/2023] Open
Abstract
Sensory eye dominance occurs when the visual cortex weighs one eye's data more heavily than those of the other. Encouragingly, mechanisms underlying sensory eye dominance in human adults retain a certain degree of plasticity. Notably, perceptual training using dichoptically presented motion signal-noise stimuli has been shown to elicit changes in sensory eye dominance both in visually impaired and normal observers. However, the neural mechanisms underlying these learning-driven improvements are not well understood. Here, we measured changes in fMRI responses before and after a five-day visual training protocol to determine the neuroplastic changes along the visual cascade. Fifty visually normal observers received training on a dichoptic or binocular variant of a signal-in-noise (left-right) motion discrimination task over five consecutive days. We show significant shifts in sensory eye dominance following training, but only for those who received dichoptic training. Pattern analysis of fMRI responses revealed that responses of V1 and hMT+ predicted sensory eye dominance for both groups, but only before training. After dichoptic (but not binocular) visual training, responses of V1 changed significantly, and were no longer able to predict sensory eye dominance. Our data suggest that perceptual training-driven changes in eye dominance are driven by a reweighting of the two eyes' data in the primary visual cortex. These findings may provide insight into developing region-targeted rehabilitative paradigms for the visually impaired, particularly those with severe binocular imbalance.
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Affiliation(s)
- Ka Yee Kam
- Department of Psychology, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Dorita H. F. Chang
- Department of Psychology, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
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7
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Olman CA. What multiplexing means for the interpretation of functional MRI data. Front Hum Neurosci 2023; 17:1134811. [PMID: 37091812 PMCID: PMC10117671 DOI: 10.3389/fnhum.2023.1134811] [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: 12/30/2022] [Accepted: 03/20/2023] [Indexed: 04/08/2023] Open
Abstract
Despite technology advances that have enabled routine acquisition of functional MRI data with sub-millimeter resolution, the inferences that cognitive neuroscientists must make to link fMRI data to behavior are complicated. Thus, a single dataset subjected to different analyses can be interpreted in different ways. This article presents two optical analogies that can be useful for framing fMRI analyses in a way that allows for multiple interpretations of fMRI data to be valid simultaneously without undermining each other. The first is reflection: when an object is reflected in a mirrored surface, it appears as if the reflected object is sharing space with the mirrored object, but of course it is not. This analogy can be a good guide for interpreting the fMRI signal, since even at sub-millimeter resolutions the signal is determined by a mixture of local and long-range neural computations. The second is refraction. If we view an object through a multi-faceted prism or gemstone, our view will change-sometimes dramatically-depending on our viewing angle. In the same way, interpretation of fMRI data (inference of underlying neuronal activity) can and should be different depending on the analysis approach. Rather than representing a weakness of the methodology, or the superiority of one approach over the other (for example, simple regression analysis versus multi-voxel pattern analysis), this is an expected consequence of how information is multiplexed in the neural networks of the brain: multiple streams of information are simultaneously present in each location. The fact that any one analysis typically shows only one view of the data also puts some parentheses around fMRI practitioners' constant search for ground truth against which to compare their data. By holding our interpretations lightly and understanding that many interpretations of the data can all be true at the same time, we do a better job of preparing ourselves to appreciate, and eventually understand, the complexity of the brain and the behavior it produces.
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Affiliation(s)
- Cheryl A. Olman
- Department of Psychology, University of Minnesota, Minneapolis, MN, United States
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8
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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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9
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Faes LK, De Martino F, Huber L(R. Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7T: Challenges and capabilities. PLoS One 2023; 18:e0280855. [PMID: 36758009 PMCID: PMC9910709 DOI: 10.1371/journal.pone.0280855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 01/09/2023] [Indexed: 02/10/2023] Open
Abstract
The development of ultra high field fMRI signal readout strategies and contrasts has led to the possibility of imaging the human brain in vivo and non-invasively at increasingly higher spatial resolutions of cortical layers and columns. One emergent layer-fMRI acquisition method with increasing popularity is the cerebral blood volume sensitive sequence named vascular space occupancy (VASO). This approach has been shown to be mostly sensitive to locally-specific changes of laminar microvasculature, without unwanted biases of trans-laminar draining veins. Until now, however, VASO has not been applied in the technically challenging cortical area of the auditory cortex. Here, we describe the main challenges we encountered when developing a VASO protocol for auditory neuroscientific applications and the solutions we have adopted. With the resulting protocol, we present preliminary results of laminar responses to sounds and as a proof of concept for future investigations, we map the topographic representation of frequency preference (tonotopy) in the auditory cortex.
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Affiliation(s)
- Lonike K. Faes
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- * E-mail:
| | - Federico De Martino
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Laurentius (Renzo) Huber
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
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10
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Avram AV, Saleem KS, Basser PJ. COnstrained Reference frame diffusion TEnsor Correlation Spectroscopic (CORTECS) MRI: A practical framework for high-resolution diffusion tensor distribution imaging. Front Neurosci 2022; 16:1054509. [PMID: 36590291 PMCID: PMC9798222 DOI: 10.3389/fnins.2022.1054509] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 11/25/2022] [Indexed: 12/23/2022] Open
Abstract
High-resolution imaging studies have consistently shown that in cortical tissue water diffuses preferentially along radial and tangential orientations with respect to the cortical surface, in agreement with histology. These dominant orientations do not change significantly even if the relative contributions from microscopic water pools to the net voxel signal vary across experiments that use different diffusion times, b-values, TEs, and TRs. With this in mind, we propose a practical new framework for imaging non-parametric diffusion tensor distributions (DTDs) by constraining the microscopic diffusion tensors of the DTD to be diagonalized using the same orthonormal reference frame of the mesoscopic voxel. In each voxel, the constrained DTD (cDTD) is completely determined by the correlation spectrum of the microscopic principal diffusivities associated with the axes of the voxel reference frame. Consequently, all cDTDs are inherently limited to the domain of positive definite tensors and can be reconstructed efficiently using Inverse Laplace Transform methods. Moreover, the cDTD reconstruction can be performed using only data acquired efficiently with single diffusion encoding, although it also supports datasets with multiple diffusion encoding. In tissues with a well-defined architecture, such as the cortex, we can further constrain the cDTD to contain only cylindrically symmetric diffusion tensors and measure the 2D correlation spectra of principal diffusivities along the radial and tangential orientation with respect to the cortical surface. To demonstrate this framework, we perform numerical simulations and analyze high-resolution dMRI data from a fixed macaque monkey brain. We estimate 2D cDTDs in the cortex and derive, in each voxel, the marginal distributions of the microscopic principal diffusivities, the corresponding distributions of the microscopic fractional anisotropies and mean diffusivities along with their 2D correlation spectra to quantify the cDTD shape-size characteristics. Signal components corresponding to specific bands in these cDTD-derived spectra show high specificity to cortical laminar structures observed with histology. Our framework drastically simplifies the measurement of non-parametric DTDs in high-resolution datasets with mesoscopic voxel sizes much smaller than the radius of curvature of the underlying anatomy, e.g., cortical surface, and can be applied retrospectively to analyze existing diffusion MRI data from fixed cortical tissues.
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Affiliation(s)
- Alexandru V. Avram
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States,Center for Neuroscience and Regenerative Medicine, Bethesda, MD, United States,Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., Bethesda, MD, United States,*Correspondence: Alexandru V. Avram
| | - Kadharbatcha S. Saleem
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States,Center for Neuroscience and Regenerative Medicine, Bethesda, MD, United States,Henry M. Jackson Foundation for the Advancement of Military Medicine Inc., Bethesda, MD, United States
| | - Peter J. Basser
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, United States
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11
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Improved laminar specificity and sensitivity by combining SE and GE BOLD signals. Neuroimage 2022; 264:119675. [PMID: 36243267 DOI: 10.1016/j.neuroimage.2022.119675] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 09/20/2022] [Accepted: 10/06/2022] [Indexed: 11/06/2022] Open
Abstract
The most widely used gradient-echo (GE) blood oxygenation level-dependent (BOLD) contrast has high sensitivity, but low specificity due to draining vein contributions, while spin-echo (SE) BOLD approach at ultra-high magnetic fields is highly specific to neural active sites but has lower sensitivity. To obtain high specificity and sensitivity, we propose to utilize a vessel-size-sensitive filter to the GE-BOLD signal, which suppresses macrovascular contributions and to combine selectively retained microvascular GE-BOLD signals with the SE-BOLD signals. To investigate our proposed idea, fMRI with 0.8 mm isotropic resolution was performed on the primary motor and sensory cortices in humans at 7 T by implementing spin- and gradient-echo (SAGE) echo planar imaging (EPI) acquisition. Microvascular-passed sigmoidal filters were designed based upon the vessel-size-sensitive ΔR2*/ΔR2 value for retaining GE-BOLD signals originating from venous vessels with ≤ 45 μm and ≤ 65 μm diameter. Unlike GE-BOLD fMRI, the laminar profile of SAGE-BOLD fMRI with the vessel-size-sensitive filter peaked at ∼ 1.0 mm from the surface of the primary motor and sensory cortices, demonstrating an improvement of laminar specificity over GE-BOLD fMRI. Also, the functional sensitivity of SAGE BOLD at middle layers (0.75-1.5 mm) was improved by ∼ 80% to ∼100% when compared with SE BOLD. In summary, we showed that combined GE- and SE-BOLD fMRI with the vessel-size-sensitive filter indeed yielded improved laminar specificity and sensitivity and is therefore an excellent tool for high spatial resolution ultra-high filed (UHF)-fMRI studies for resolving mesoscopic functional units.
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12
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Akbari A, Bollmann S, Ali TS, Barth M. Modelling the depth-dependent VASO and BOLD responses in human primary visual cortex. Hum Brain Mapp 2022; 44:710-726. [PMID: 36189837 PMCID: PMC9842911 DOI: 10.1002/hbm.26094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/05/2022] [Accepted: 08/07/2022] [Indexed: 01/25/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) using a blood-oxygenation-level-dependent (BOLD) contrast is a common method for studying human brain function noninvasively. Gradient-echo (GRE) BOLD is highly sensitive to the blood oxygenation change in blood vessels; however, the spatial signal specificity can be degraded due to signal leakage from activated lower layers to superficial layers in depth-dependent (also called laminar or layer-specific) fMRI. Alternatively, physiological variables such as cerebral blood volume using the VAscular-Space-Occupancy (VASO) contrast have shown higher spatial specificity compared to BOLD. To better understand the physiological mechanisms such as blood volume and oxygenation changes and to interpret the measured depth-dependent responses, models are needed which reflect vascular properties at this scale. For this purpose, we extended and modified the "cortical vascular model" previously developed to predict layer-specific BOLD signal changes in human primary visual cortex to also predict a layer-specific VASO response. To evaluate the model, we compared the predictions with experimental results of simultaneous VASO and BOLD measurements in a group of healthy participants. Fitting the model to our experimental data provided an estimate of CBV change in different vascular compartments upon neural activity. We found that stimulus-evoked CBV change mainly occurs in small arterioles, capillaries, and intracortical arteries and that the contribution from venules and ICVs is smaller. Our results confirm that VASO is less susceptible to large vessel effects compared to BOLD, as blood volume changes in intracortical arteries did not substantially affect the resulting depth-dependent VASO profiles, whereas depth-dependent BOLD profiles showed a bias towards signal contributions from intracortical veins.
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Affiliation(s)
- Atena Akbari
- Centre for Advanced ImagingUniversity of QueenslandBrisbaneAustralia
| | - Saskia Bollmann
- Centre for Advanced ImagingUniversity of QueenslandBrisbaneAustralia
| | - Tonima S. Ali
- Centre for Advanced ImagingUniversity of QueenslandBrisbaneAustralia
| | - Markus Barth
- Centre for Advanced ImagingUniversity of QueenslandBrisbaneAustralia,ARC Training Centre for Innovation in Biomedical Imaging TechnologyThe University of QueenslandBrisbaneAustralia,School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneQueenslandAustralia
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13
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Himmelberg MM, Gardner JL, Winawer J. What has vision science taught us about functional MRI? Neuroimage 2022; 261:119536. [PMID: 35931310 DOI: 10.1016/j.neuroimage.2022.119536] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 07/21/2022] [Accepted: 08/02/2022] [Indexed: 10/31/2022] Open
Abstract
In the domain of human neuroimaging, much attention has been paid to the question of whether and how the development of functional magnetic resonance imaging (fMRI) has advanced our scientific knowledge of the human brain. However, the opposite question is also important; how has our knowledge of the visual system advanced our understanding of fMRI? Here, we discuss how and why scientific knowledge about the human and animal visual system has been used to answer fundamental questions about fMRI as a brain measurement tool and how these answers have contributed to scientific discoveries beyond vision science.
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Affiliation(s)
- Marc M Himmelberg
- Department of Psychology, New York University, NY, USA; Center for Neural Science, New York University, NY, USA.
| | | | - Jonathan Winawer
- Department of Psychology, New York University, NY, USA; Center for Neural Science, New York University, NY, USA
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14
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Deshpande G, Zhao X, Robinson J. Functional Parcellation of the Hippocampus based on its Layer-specific Connectivity with Default Mode and Dorsal Attention Networks. Neuroimage 2022; 254:119078. [PMID: 35276366 DOI: 10.1016/j.neuroimage.2022.119078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 01/29/2022] [Accepted: 03/07/2022] [Indexed: 12/25/2022] Open
Abstract
Recent neuroimaging evidence suggests that there might be an anterior-posterior functional differentiation of the hippocampus along the long-axis. The HERNET (hippocampal encoding/retrieval and network) model proposed an encoding/retrieval dichotomy with the anterior hippocampus more connected to the dorsal attention network (DAN) during memory encoding, and the posterior portions more connected to the default mode network (DMN) during retrieval. Evidence both for and against the HERNET model has been reported. In this study, we test the validity of the HERNET model non-invasively in humans by computing functional connectivity (FC) in layer-specific cortico-hippocampal microcircuits. This was achieved by acquiring sub-millimeter functional magnetic resonance imaging (fMRI) data during encoding/retrieval tasks at 7T. Specifically, FC between infra-granular output layers of DAN with hippocampus during encoding and FC between supra-granular input layers of DMN with hippocampus during retrieval were computed to test the predictions of the HERNET model. Our results support some predictions of the HERNET model including anterior-posterior gradient along the long axis of the hippocampus. While preferential relationships between the entire hippocampus and DAN/DMN during encoding/retrieval, respectively, were observed as predicted, anterior-posterior specificity in these network relationships could not be confirmed. The strength and clarity of evidence for/against the HERNET model were superior with layer-specific data compared to conventional volume data.
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Affiliation(s)
- Gopikrishna Deshpande
- AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL 36849, USA; Department of Psychological Sciences, Auburn University, Auburn, AL, USA; Alabama Advanced Imaging Consortium, Birmingham, AL, USA; Center for Neuroscience, Auburn University, Auburn, AL, USA; Key Laboratory for Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China; Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India; Centre for Brain Research, Indian Institute of Science, Bangalore, India.
| | - Xinyu Zhao
- AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL 36849, USA; Quora Inc., Mountain View, CA, USA
| | - Jennifer Robinson
- AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL 36849, USA; Department of Psychological Sciences, Auburn University, Auburn, AL, USA; Alabama Advanced Imaging Consortium, Birmingham, AL, USA; Center for Neuroscience, Auburn University, Auburn, AL, USA
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15
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Deshpande G, Wang Y, Robinson J. Resting state fMRI connectivity is sensitive to laminar connectional architecture in the human brain. Brain Inform 2022; 9:2. [PMID: 35038072 PMCID: PMC8764001 DOI: 10.1186/s40708-021-00150-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 12/28/2021] [Indexed: 11/10/2022] Open
Abstract
Previous invasive studies indicate that human neocortical graymatter contains cytoarchitectonically distinct layers, with notable differences in their structural connectivity with the rest of the brain. Given recent improvements in the spatial resolution of anatomical and functional magnetic resonance imaging (fMRI), we hypothesize that resting state functional connectivity (FC) derived from fMRI is sensitive to layer-specific thalamo-cortical and cortico-cortical microcircuits. Using sub-millimeter resting state fMRI data obtained at 7 T, we found that: (1) FC between the entire thalamus and cortical layers I and VI was significantly stronger than between the thalamus and other layers. Furthermore, FC between somatosensory thalamus (ventral posterolateral nucleus, VPL) and layers IV, VI of the primary somatosensory cortex were stronger than with other layers; (2) Inter-hemispheric cortico-cortical FC between homologous regions in superficial layers (layers I-III) was stronger compared to deep layers (layers V-VI). These findings are in agreement with structural connections inferred from previous invasive studies that showed that: (i) M-type neurons in the entire thalamus project to layer-I; (ii) Pyramidal neurons in layer-VI target all thalamic nuclei, (iii) C-type neurons in the VPL project to layer-IV and receive inputs from layer-VI of the primary somatosensory cortex, and (iv) 80% of collosal projecting neurons between homologous cortical regions connect superficial layers. Our results demonstrate for the first time that resting state fMRI is sensitive to structural connections between cortical layers (previously inferred through invasive studies), specifically in thalamo-cortical and cortico-cortical networks.
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Affiliation(s)
- Gopikrishna Deshpande
- AU MRI Research Center, Department of Electrical & Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL, 36849, USA. .,Department of Psychological Sciences, Auburn University, Auburn, AL, USA. .,Alabama Advanced Imaging Consortium, Birmingham, AL, USA. .,Center for Neuroscience, Auburn University, Auburn, AL, USA. .,Key Laboratory for Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China. .,Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India. .,Centre for Brain Research, Indian Institute of Science, Bangalore, India.
| | - Yun Wang
- AU MRI Research Center, Department of Electrical & Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL, 36849, USA.,Department of Psychiatry, Columbia University, New York, NY, USA
| | - Jennifer Robinson
- AU MRI Research Center, Department of Electrical & Computer Engineering, Auburn University, 560 Devall Dr, Suite 266D, Auburn, AL, 36849, USA.,Department of Psychological Sciences, Auburn University, Auburn, AL, USA.,Alabama Advanced Imaging Consortium, Birmingham, AL, USA.,Center for Neuroscience, Auburn University, Auburn, AL, USA
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16
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Shao X, Guo F, Shou Q, Wang K, Jann K, Yan L, Toga AW, Zhang P, Wang DJJ. Laminar perfusion imaging with zoomed arterial spin labeling at 7 Tesla. Neuroimage 2021; 245:118724. [PMID: 34780918 PMCID: PMC8727512 DOI: 10.1016/j.neuroimage.2021.118724] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 10/23/2021] [Accepted: 11/11/2021] [Indexed: 10/19/2022] Open
Abstract
Laminar fMRI based on BOLD and CBV contrast at ultrahigh magnetic fields has been applied for studying the dynamics of mesoscopic brain networks. However, the quantitative interpretations of BOLD/CBV fMRI results are confounded by different baseline physiology across cortical layers. Here we introduce a novel 3D zoomed pseudo-continuous arterial spin labeling (pCASL) technique at 7T that offers the capability for quantitative measurements of laminar cerebral blood flow (CBF) both at rest and during task activation with high spatial specificity and sensitivity. We found arterial transit time in superficial layers is ∼100 ms shorter than in middle/deep layers revealing the time course of labeled blood flowing from pial arteries to downstream microvasculature. Resting state CBF peaked in the middle layers which is highly consistent with microvascular density measured from human cortex specimens. Finger tapping induced a robust two-peak laminar profile of CBF increases in the superficial (somatosensory and premotor input) and deep (spinal output) layers of M1, while finger brushing task induced a weaker CBF increase in superficial layers (somatosensory input). This observation is highly consistent with reported laminar profiles of CBV activation on M1. We further demonstrated that visuospatial attention induced a predominant CBF increase in deep layers and a smaller CBF increase on top of the lower baseline CBF in superficial layers of V1 (feedback cortical input), while stimulus driven activity peaked in the middle layers (feedforward thalamic input). With the capability for quantitative CBF measurements both at baseline and during task activation, high-resolution ASL perfusion fMRI at 7T provides an important tool for in vivo assessment of neurovascular function and metabolic activities of neural circuits across cortical layers.
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Affiliation(s)
- Xingfeng Shao
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave, Los Angeles, CA 90033, USA
| | - Fanhua Guo
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Qinyang Shou
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave, Los Angeles, CA 90033, USA
| | - Kai Wang
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave, Los Angeles, CA 90033, USA
| | - Kay Jann
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave, Los Angeles, CA 90033, USA; Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Lirong Yan
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave, Los Angeles, CA 90033, USA; Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Peng Zhang
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Danny J J Wang
- Laboratory of FMRI Technology (LOFT), USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, 2025 Zonal Ave, Los Angeles, CA 90033, USA; Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
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17
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Moerel M, Yacoub E, Gulban OF, Lage-Castellanos A, De Martino F. Using high spatial resolution fMRI to understand representation in the auditory network. Prog Neurobiol 2021; 207:101887. [PMID: 32745500 PMCID: PMC7854960 DOI: 10.1016/j.pneurobio.2020.101887] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 05/27/2020] [Accepted: 07/15/2020] [Indexed: 12/23/2022]
Abstract
Following rapid methodological advances, ultra-high field (UHF) functional and anatomical magnetic resonance imaging (MRI) has been repeatedly and successfully used for the investigation of the human auditory system in recent years. Here, we review this work and argue that UHF MRI is uniquely suited to shed light on how sounds are represented throughout the network of auditory brain regions. That is, the provided gain in spatial resolution at UHF can be used to study the functional role of the small subcortical auditory processing stages and details of cortical processing. Further, by combining high spatial resolution with the versatility of MRI contrasts, UHF MRI has the potential to localize the primary auditory cortex in individual hemispheres. This is a prerequisite to study how sound representation in higher-level auditory cortex evolves from that in early (primary) auditory cortex. Finally, the access to independent signals across auditory cortical depths, as afforded by UHF, may reveal the computations that underlie the emergence of an abstract, categorical sound representation based on low-level acoustic feature processing. Efforts on these research topics are underway. Here we discuss promises as well as challenges that come with studying these research questions using UHF MRI, and provide a future outlook.
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Affiliation(s)
- Michelle Moerel
- Maastricht Centre for Systems Biology, Maastricht University, Maastricht, the Netherlands; Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Maastricht Brain Imaging Center (MBIC), Maastricht, the Netherlands.
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA.
| | - Omer Faruk Gulban
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Maastricht Brain Imaging Center (MBIC), Maastricht, the Netherlands; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA; Brain Innovation B.V., Maastricht, the Netherlands.
| | - Agustin Lage-Castellanos
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Maastricht Brain Imaging Center (MBIC), Maastricht, the Netherlands; Department of NeuroInformatics, Cuban Center for Neuroscience, Cuba.
| | - Federico De Martino
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands; Maastricht Brain Imaging Center (MBIC), Maastricht, the Netherlands; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA.
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18
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Fracasso A, Dumoulin SO, Petridou N. Point-spread function of the BOLD response across columns and cortical depth in human extra-striate cortex. Prog Neurobiol 2021; 207:102187. [PMID: 34798198 DOI: 10.1016/j.pneurobio.2021.102187] [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] [Indexed: 11/28/2022]
Abstract
Columns and layers are fundamental organizational units of the brain. Well known examples of cortical columns are the ocular dominance columns (ODCs) in primary visual cortex and the column-like stripe-based arrangement in the second visual area V2. The spatial scale of columns and layers is beyond the reach of conventional neuroimaging, but the advent of high field magnetic resonance imaging (MRI) scanners (UHF, 7 Tesla and above) has opened the possibility to acquire data at this spatial scale, in-vivo and non-invasively in humans. The most prominent non-invasive technique to measure brain function is blood oxygen level dependent (BOLD) fMRI, measuring brain activity indirectly, via changes in hemodynamics. A key determinant of the ability of high-resolution BOLD fMRI to accurately resolve columns and layers is the point-spread function (PSF) of the BOLD response in relation to the spatial extent of neuronal activity. In this study we take advantage of the stripe-based arrangement present in visual area V2, coupled with sub-millimetre anatomical and gradient-echo BOLD (GE BOLD) acquisition at 7 T to obtain PSF estimates and along cortical depth in human participants. Results show that the BOLD PSF is maximal in the superficial part of the cortex (1.78 mm), and it decreases with increasing cortical depth (0.83 mm close to white matter).
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Affiliation(s)
- Alessio Fracasso
- University of Glasgow, Institute of Neuroscience and Psychology, Glasgow, Scotland, United Kingdom.
| | - 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, the Netherlands
| | - Natalia Petridou
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, 3584 CX, Utrecht, the Netherlands.
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19
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Vizioli L, Yacoub E, Lewis LD. How pushing the spatiotemporal resolution of fMRI can advance neuroscience. Prog Neurobiol 2021; 207:102184. [PMID: 34767874 DOI: 10.1016/j.pneurobio.2021.102184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Luca Vizioli
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN 55455, United States; Department of Neurosurgery, University of Minnesota, Minneapolis, MN 55455, United States.
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN 55455, United States
| | - Laura D Lewis
- Department of Biomedical Engineering, Boston University, Boston, MA United States; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA United States
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20
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Wang F, Dong Z, Wald LL, Polimeni JR, Setsompop K. Simultaneous pure T 2 and varying T 2'-weighted BOLD fMRI using Echo Planar Time-resolved Imaging for mapping cortical-depth dependent responses. Neuroimage 2021; 245:118641. [PMID: 34655771 PMCID: PMC8820652 DOI: 10.1016/j.neuroimage.2021.118641] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 10/06/2021] [Accepted: 10/07/2021] [Indexed: 12/12/2022] Open
Abstract
Spin-echo (SE) BOLD fMRI has high microvascular specificity, and thus provides a more reliable means to localize neural activity compared to conventional gradient-echo BOLD fMRI. However, the most common SE BOLD acquisition method, SE-EPI, is known to suffer from T2′ contrast contamination with undesirable draining vein bias. To address this, in this study, we extended a recently developed distortion/blurring-free multi-shot EPI technique, Echo-Planar Time-resolved Imaging (EPTI), to cortical-depth dependent SE-fMRI at 7T to test whether it could provide purer SE BOLD contrast with minimal T2′ contamination for improved neuronal specificity. From the same acquisition, the time-resolved feature of EPTI also provides a series of asymmetric SE (ASE) images with varying T2′ weightings, and enables extraction of data equivalent to conventional SE EPI with different echo train lengths (ETLs). This allows us to systematically examine how T2′-contribution affects different SE acquisition strategies using a single dataset. A low-rank spatiotemporal subspace reconstruction was implemented for the SE-EPTI acquisition, which incorporates corrections for both shot-to-shot phase variations and dynamic B0 drifts. SE-EPTI was used in a visual task fMRI experiment to demonstrate that i) the pure SE image provided by EPTI results in the highest microvascular specificity; ii) the ASE EPTI series, with a graded introduction of T2′ weightings at time points farther away from the pure SE, show a gradual sensitivity increase along with increasing draining vein bias; iii) the longer ETL seen in conventional SE EPI acquisitions will induce more draining vein bias. Consistent results were observed across multiple subjects, demonstrating the robustness of the proposed technique for SE-BOLD fMRI with high specificity.
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Affiliation(s)
- Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
| | - Zijing Dong
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, USA; Department of Electrical Engineering, Stanford University, Stanford, USA
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21
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Dowdle LT, Ghose G, Chen CCC, Ugurbil K, Yacoub E, Vizioli L. Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI. Prog Neurobiol 2021; 207:102171. [PMID: 34492308 DOI: 10.1016/j.pneurobio.2021.102171] [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: 03/01/2021] [Revised: 08/09/2021] [Accepted: 09/02/2021] [Indexed: 01/25/2023]
Abstract
Functional magnetic resonance imaging (fMRI), a non-invasive and widely used human neuroimaging method, is most known for its spatial precision. However, there is a growing interest in its temporal sensitivity. This is despite the temporal blurring of neuronal events by the blood oxygen level dependent (BOLD) signal, the peak of which lags neuronal firing by 4-6 seconds. Given this, the goal of this review is to answer a seemingly simple question - "What are the benefits of increased temporal sampling for fMRI?". To answer this, we have combined fMRI data collected at multiple temporal scales, from 323 to 1000 milliseconds, with a review of both historical and contemporary temporal literature. After a brief discussion of technological developments that have rekindled interest in temporal research, we next consider the potential statistical and methodological benefits. Most importantly, we explore how fast fMRI can uncover previously unobserved neuro-temporal dynamics - effects that are entirely missed when sampling at conventional 1 to 2 second rates. With the intrinsic link between space and time in fMRI, this temporal renaissance also delivers improvements in spatial precision. Far from producing only statistical gains, the array of benefits suggest that the continued temporal work is worth the effort.
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Affiliation(s)
- Logan T Dowdle
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN, 55455, United States.
| | - Geoffrey Ghose
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neuroscience, University of Minnesota, 321 Church St SE, Minneapolis, MN, 55455, United States
| | - Clark C C Chen
- Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States
| | - Luca Vizioli
- Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN, 55455, United States; Department of Neurosurgery, University of Minnesota, 500 SE Harvard St, Minneapolis, MN, 55455, United States.
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22
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Huber LR, Poser BA, Bandettini PA, Arora K, Wagstyl K, Cho S, Goense J, Nothnagel N, Morgan AT, van den Hurk J, Müller AK, Reynolds RC, Glen DR, Goebel R, Gulban OF. LayNii: A software suite for layer-fMRI. Neuroimage 2021; 237:118091. [PMID: 33991698 PMCID: PMC7615890 DOI: 10.1016/j.neuroimage.2021.118091] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 02/19/2021] [Accepted: 04/16/2021] [Indexed: 01/06/2023] Open
Abstract
High-resolution fMRI in the sub-millimeter regime allows researchers to resolve brain activity across cortical layers and columns non-invasively. While these high-resolution data make it possible to address novel questions of directional information flow within and across brain circuits, the corresponding data analyses are challenged by MRI artifacts, including image blurring, image distortions, low SNR, and restricted coverage. These challenges often result in insufficient spatial accuracy of conventional analysis pipelines. Here we introduce a new software suite that is specifically designed for layer-specific functional MRI: LayNii. This toolbox is a collection of command-line executable programs written in C/C++ and is distributed opensource and as pre-compiled binaries for Linux, Windows, and macOS. LayNii is designed for layer-fMRI data that suffer from SNR and coverage constraints and thus cannot be straightforwardly analyzed in alternative software packages. Some of the most popular programs of LayNii contain 'layerification' and columnarization in the native voxel space of functional data as well as many other layer-fMRI specific analysis tasks: layer-specific smoothing, model-based vein mitigation of GE-BOLD data, quality assessment of artifact dominated sub-millimeter fMRI, as well as analyses of VASO data.
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Affiliation(s)
| | - Benedikt A Poser
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | | | - Kabir Arora
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Shinho Cho
- CMRR, University of Minneapolis, MN, USA
| | | | | | | | | | | | | | | | - Rainer Goebel
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands; Brain Innovation, Maastricht, the Netherlands
| | - Omer Faruk Gulban
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands; Brain Innovation, Maastricht, the Netherlands
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23
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Han S, Eun S, Cho H, Uludaǧ K, Kim SG. Improvement of sensitivity and specificity for laminar BOLD fMRI with double spin-echo EPI in humans at 7 T. Neuroimage 2021; 241:118435. [PMID: 34324976 DOI: 10.1016/j.neuroimage.2021.118435] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 07/26/2021] [Indexed: 12/19/2022] Open
Abstract
Mapping mesoscopic cortical functional units such as columns or laminae is increasingly pursued by ultra-high field (UHF) functional magnetic resonance imaging (fMRI). The most popular approach for high-resolution fMRI is currently gradient-echo (GE) blood oxygenation level-dependent (BOLD) fMRI. However, its spatial accuracy is reduced due to its sensitivity to draining vessels, including pial veins, whereas spin-echo (SE) BOLD signal is expected to have higher spatial accuracy, albeit with lower sensitivity than the GE-BOLD signal. Here, we introduce a new double spin-echo (dSE) echo-planar imaging (EPI) method to improve the sensitivity of SE-BOLD contrast by averaging two spin-echoes using three radiofrequency pulses. Human fMRI experiments were performed with slices perpendicular to the central sulcus between motor and sensory cortices at 7 T during fist-clenching with touching. First, we evaluated the feasibility of single-shot dSE-EPI for BOLD fMRI with 1.5 mm isotropic resolution and found that dSE-BOLD fMRI has higher signal-to-noise ratio (SNR), temporal SNR (tSNR), and higher functional sensitivity than conventional SE-BOLD fMRI. Second, to investigate the laminar specificity of dSE-BOLD fMRI, we implemented a multi-shot approach to achieve 0.8-mm isotropic resolution with sliding-window reconstruction. Unlike GE-BOLD fMRI, the cortical profile of dSE-BOLD fMRI peaked at ~ 1.0 mm from the surface of the primary motor and sensory cortices, demonstrating an improvement of laminar specificity in humans over GE-BOLD fMRI. The proposed multi-shot dSE-EPI method is viable for high spatial resolution UHF-fMRI studies in the pursuit of resolving mesoscopic functional units.
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Affiliation(s)
- SoHyun Han
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Republic of Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.
| | - Seulgi Eun
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Republic of Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - HyungJoon Cho
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
| | - Kâmil Uludaǧ
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Republic of Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea; Techna Institute & Koerner Scientist in MR Imaging, University Health Network, Toronto, Canada
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Republic of Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Republic of Korea.
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24
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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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25
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Na S, Wang LV. Photoacoustic computed tomography for functional human brain imaging [Invited]. BIOMEDICAL OPTICS EXPRESS 2021; 12:4056-4083. [PMID: 34457399 PMCID: PMC8367226 DOI: 10.1364/boe.423707] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 06/05/2021] [Accepted: 06/08/2021] [Indexed: 05/02/2023]
Abstract
The successes of magnetic resonance imaging and modern optical imaging of human brain function have stimulated the development of complementary modalities that offer molecular specificity, fine spatiotemporal resolution, and sufficient penetration simultaneously. By virtue of its rich optical contrast, acoustic resolution, and imaging depth far beyond the optical transport mean free path (∼1 mm in biological tissues), photoacoustic computed tomography (PACT) offers a promising complementary modality. In this article, PACT for functional human brain imaging is reviewed in its hardware, reconstruction algorithms, in vivo demonstration, and potential roadmap.
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Affiliation(s)
- Shuai Na
- Caltech Optical Imaging Laboratory, Andrew
and Peggy Cherng Department of Medical Engineering,
California Institute of Technology, 1200
East California Boulevard, Pasadena, CA 91125, USA
| | - Lihong V. Wang
- Caltech Optical Imaging Laboratory, Andrew
and Peggy Cherng Department of Medical Engineering,
California Institute of Technology, 1200
East California Boulevard, Pasadena, CA 91125, USA
- Caltech Optical Imaging Laboratory,
Department of Electrical Engineering, California
Institute of Technology, 1200 East California Boulevard,
Pasadena, CA 91125, USA
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26
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Bang JW, Rahnev D. Awake suppression after brief exposure to a familiar stimulus. Commun Biol 2021; 4:348. [PMID: 33731846 PMCID: PMC7969731 DOI: 10.1038/s42003-021-01863-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 02/17/2021] [Indexed: 02/08/2023] Open
Abstract
Newly learned information undergoes a process of awake reactivation shortly after the learning offset and we recently demonstrated that this effect can be observed as early as area V1. However, reactivating all experiences can be wasteful and unnecessary, especially for familiar stimuli. Therefore, here we tested whether awake reactivation occurs differentially for new and familiar stimuli. Subjects completed a brief visual task on a stimulus that was either novel or highly familiar due to extensive prior training on it. Replicating our previous results, we found that awake reactivation occurred in V1 for the novel stimulus. On the other hand, brief exposure to the familiar stimulus led to 'awake suppression' such that neural activity patterns immediately after exposure to the familiar stimulus diverged from the patterns associated with that stimulus. Further, awake reactivation was observed selectively in V1, whereas awake suppression had similar strength across areas V1-V3. These results are consistent with the presence of a competition between local awake reactivation and top-down awake suppression, with suppression becoming dominant for familiar stimuli.
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Affiliation(s)
- Ji Won Bang
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, USA. .,Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, USA.
| | - Dobromir Rahnev
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, USA
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27
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Fracasso A, Dumoulin SO, Petridou N. Point-spread function of the BOLD response across columns and cortical depth in human extra-striate cortex. Prog Neurobiol 2021; 202:102034. [PMID: 33741401 DOI: 10.1016/j.pneurobio.2021.102034] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Revised: 03/08/2021] [Accepted: 03/14/2021] [Indexed: 10/21/2022]
Abstract
Columns and layers are fundamental organizational units of the brain. Well known examples of cortical columns are the ocular dominance columns (ODCs) in primary visual cortex and the column-like stripe-based arrangement in the second visual area V2. The spatial scale of columns and layers is beyond the reach of conventional neuroimaging, but the advent of high field magnetic resonance imaging (MRI) scanners (UHF, 7 T and above) has opened the possibility to acquire data at this spatial scale, in-vivo and non-invasively in humans. The most prominent non-invasive technique to measure brain function is blood oxygen level dependent (BOLD) fMRI, measuring brain activity indirectly, via changes in hemodynamics. A key determinant of the ability of high-resolution BOLD fMRI to accurately resolve columns and layers is the point-spread function (PSF) of the BOLD response in relation to the spatial extent of neuronal activity. In this study we take advantage of the stripe-based arrangement present in visual area V2, coupled with sub-millimetre anatomical and gradient-echo BOLD (GE BOLD) acquisition at 7 T to obtain PSF estimates and along cortical depth in human participants. Results show that the BOLD PSF is maximal in the superficial part of the cortex (1.78 mm), and it decreases with increasing cortical depth (0.83 mm close to white matter).
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Affiliation(s)
- Alessio Fracasso
- University of Glasgow, Institute of Neuroscience and Psychology, Glasgow, Scotland, United Kingdom.
| | - 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, the Netherlands
| | - Natalia Petridou
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, 3584 CX, Utrecht, the Netherlands.
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28
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Tian Q, Zaretskaya N, Fan Q, Ngamsombat C, Bilgic B, Polimeni JR, Huang SY. Improved cortical surface reconstruction using sub-millimeter resolution MPRAGE by image denoising. Neuroimage 2021; 233:117946. [PMID: 33711484 PMCID: PMC8421085 DOI: 10.1016/j.neuroimage.2021.117946] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 02/28/2021] [Accepted: 03/03/2021] [Indexed: 11/24/2022] Open
Abstract
Automatic cerebral cortical surface reconstruction is a useful tool for cortical anatomy quantification, analysis and visualization. Recently, the Human Connectome Project and several studies have shown the advantages of using T1-weighted magnetic resonance (MR) images with sub-millimeter isotropic spatial resolution instead of the standard 1-mm isotropic resolution for improved accuracy of cortical surface positioning and thickness estimation. Nonetheless, sub-millimeter resolution images are noisy by nature and require averaging multiple repetitions to increase the signal-to-noise ratio for precisely delineating the cortical boundary. The prolonged acquisition time and potential motion artifacts pose significant barriers to the wide adoption of cortical surface reconstruction at sub-millimeter resolution for a broad range of neuroscientific and clinical applications. We address this challenge by evaluating the cortical surface reconstruction resulting from denoised single-repetition sub-millimeter T1-weighted images. We systematically characterized the effects of image denoising on empirical data acquired at 0.6 mm isotropic resolution using three classical denoising methods, including denoising convolutional neural network (DnCNN), block-matching and 4-dimensional filtering (BM4D) and adaptive optimized non-local means (AONLM). The denoised single-repetition images were found to be highly similar to 6-repetition averaged images, with a low whole-brain averaged mean absolute difference of ~0.016, high whole-brain averaged peak signal-to-noise ratio of ~33.5 dB and structural similarity index of ~0.92, and minimal gray matter–white matter contrast loss (2% to 9%). The whole-brain mean absolute discrepancies in gray matter–white matter surface placement, gray matter–cerebrospinal fluid surface placement and cortical thickness estimation were lower than 165 μm, 155 μm and 145 μm—sufficiently accurate for most applications. These discrepancies were approximately one third to half of those from 1-mm isotropic resolution data. The denoising performance was equivalent to averaging ~2.5 repetitions of the data in terms of image similarity, and 1.6–2.2 repetitions in terms of the cortical surface placement accuracy. The scan-rescan variability of the cortical surface positioning and thickness estimation was lower than 170 μm. Our unique dataset and systematic characterization support the use of denoising methods for improved cortical surface reconstruction at sub-millimeter resolution.
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Affiliation(s)
- Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States.
| | - Natalia Zaretskaya
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States; Institute of Psychology, University of Graz, Graz, Austria; BioTechMed-Graz, Austria
| | - Qiuyun Fan
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States
| | - Chanon Ngamsombat
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Department of Radiology, Faculty of Medicine, Siriraj Hospital, Mahidol University, Thailand
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
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29
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Zooming-in on higher-level vision: High-resolution fMRI for understanding visual perception and awareness. Prog Neurobiol 2021; 207:101998. [PMID: 33497652 DOI: 10.1016/j.pneurobio.2021.101998] [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] [Received: 01/30/2020] [Revised: 11/11/2020] [Accepted: 01/16/2021] [Indexed: 12/24/2022]
Abstract
One of the central questions in visual neuroscience is how the sparse retinal signals leaving our eyes are transformed into a rich subjective visual experience of the world. Invasive physiology studies, which offers the highest spatial resolution, have revealed many facts about the processing of simple visual features like contrast, color, and orientation, focusing on the early visual areas. At the same time, standard human fMRI studies with comparably coarser spatial resolution have revealed more complex, functionally specialized, and category-selective responses in higher visual areas. Although the visual system is the best understood among the sensory modalities, these two areas of research remain largely segregated. High-resolution fMRI opens up a possibility for linking them. On the one hand, it allows studying how the higher-level visual functions affect the fine-scale activity in early visual areas. On the other hand, it allows discovering the fine-scale functional organization of higher visual areas and exploring their functional connectivity with visual areas lower in the hierarchy. In this review, I will discuss examples of successful work undertaken in these directions using high-resolution fMRI and discuss where this method could be applied in the future to advance our understanding of the complexity of higher-level visual processing.
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30
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Markuerkiaga I, Marques JP, Bains LJ, Norris DG. An in-vivo study of BOLD laminar responses as a function of echo time and static magnetic field strength. Sci Rep 2021; 11:1862. [PMID: 33479362 PMCID: PMC7820587 DOI: 10.1038/s41598-021-81249-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 12/22/2020] [Indexed: 11/18/2022] Open
Abstract
Layer specific functional MRI requires high spatial resolution data. To compensate the associated poor signal to noise ratio it is common to integrate the signal from voxels at a given cortical depth. If the region is sufficiently large then physiological noise will be the dominant noise source. In this work, activation profiles in response to the same visual stimulus are compared at 1.5 T, 3 T and 7 T using a multi-echo, gradient echo (GE) FLASH sequence, with a 0.75 mm isotropic voxel size and the cortical integration approach. The results show that after integrating over a cortical volume of 40, 60 and 100 mm3 (at 7 T, 3 T, and 1.5 T, respectively), the signal is in the physiological noise dominated regime. The activation profiles obtained are similar for equivalent echo times. BOLD-like noise is found to be the dominant source of physiological noise. Consequently, the functional contrast to noise ratio is not strongly echo-time or field-strength dependent. We conclude that laminar GE-BOLD fMRI at lower field strengths is feasible but that larger patches of cortex will need to be examined, and that the acquisition efficiency is reduced.
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Affiliation(s)
- Irati Markuerkiaga
- Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands
| | - José P Marques
- Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands
| | - Lauren J Bains
- Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands
| | - David G Norris
- Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands. .,Erwin L. Hahn Institute for Magnetic Resonance Imaging, 45141, Essen, Germany.
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31
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Marcar VL, Wolf M. An investigation into the relationship between stimulus property, neural response and its manifestation in the visual evoked potential involving retinal resolution. Eur J Neurosci 2021; 53:2612-2628. [PMID: 33448503 DOI: 10.1111/ejn.15112] [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: 02/17/2020] [Revised: 12/23/2020] [Accepted: 12/29/2020] [Indexed: 11/28/2022]
Abstract
The visual evoked potential (VEP) has been shown to reflect the size of the neural population activated by a processing mechanism selective to the temporal - and spatial luminance contrast property of a stimulus. We set out to better understand how the factors determining the neural response associated with these mechanisms. To do so we recorded the VEP from 14 healthy volunteers viewing two series of pattern reversing stimuli with identical temporal-and spatial luminance contrast properties. In one series the size of the elements increased towards the edge of the image, in the other it decreased. In the former element size was congruent with receptive field size across eccentricity, in the later it was incongruent. P100 amplitude to the incongruent series exceeded that obtained to the congruent series. Using electric dipoles due the excitatory neural response we accounted for this using dipole cancellation of electric dipoles of opposite polarity originating in supra- and infragranular layers of V1. The phasic neural response in granular lamina of V1 exhibited magnocellular characteristics, the neural response outside of the granular lamina exhibited parvocellular characteristics and was modulated by re-entrant projections. Using electric current density, we identified areas of the dorsal followed by areas of the ventral stream as the source of the re-entrant signal modulating infragranular activity. Our work demonstrates that the VEP does not signal reflect the overall level of a neural response but is the result of an interaction between electric dipoles originating from neural responses in different lamina of V1.
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Affiliation(s)
- Valentine L Marcar
- Biomedical Optics Research Laboratory, University Hospital Zürich, Zürich, Switzerland
| | - Martin Wolf
- Biomedical Optics Research Laboratory, University Hospital Zürich, Zürich, Switzerland
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32
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van Dijk JA, Fracasso A, Petridou N, Dumoulin SO. Validating Linear Systems Analysis for Laminar fMRI: Temporal Additivity for Stimulus Duration Manipulations. Brain Topogr 2021; 34:88-101. [PMID: 33210193 PMCID: PMC7803719 DOI: 10.1007/s10548-020-00808-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Accepted: 11/05/2020] [Indexed: 11/26/2022]
Abstract
Advancements in ultra-high field (7 T and higher) magnetic resonance imaging (MRI) scanners have made it possible to investigate both the structure and function of the human brain at a sub-millimeter scale. As neuronal feedforward and feedback information arrives in different layers, sub-millimeter functional MRI has the potential to uncover information processing between cortical micro-circuits across cortical depth, i.e. laminar fMRI. For nearly all conventional fMRI analyses, the main assumption is that the relationship between local neuronal activity and the blood oxygenation level dependent (BOLD) signal adheres to the principles of linear systems theory. For laminar fMRI, however, directional blood pooling across cortical depth stemming from the anatomy of the cortical vasculature, potentially violates these linear system assumptions, thereby complicating analysis and interpretation. Here we assess whether the temporal additivity requirement of linear systems theory holds for laminar fMRI. We measured responses elicited by viewing stimuli presented for different durations and evaluated how well the responses to shorter durations predicted those elicited by longer durations. We find that BOLD response predictions are consistently good predictors for observed responses, across all cortical depths, and in all measured visual field maps (V1, V2, and V3). Our results suggest that the temporal additivity assumption for linear systems theory holds for laminar fMRI. We thus show that the temporal additivity assumption holds across cortical depth for sub-millimeter gradient-echo BOLD fMRI in early visual cortex.
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Affiliation(s)
- Jelle A van Dijk
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands.
- Experimental Psychology, Utrecht University, Utrecht, The Netherlands.
| | - Alessio Fracasso
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, G12 8QB, UK
- Radiology Department, Imaging Division, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Natalia Petridou
- Radiology Department, Imaging Division, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Serge O Dumoulin
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Experimental Psychology, Utrecht University, Utrecht, The Netherlands
- Experimental and Applied Psychology, VU University, Amsterdam, The Netherlands
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33
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Tian Q, Bilgic B, Fan Q, Ngamsombat C, Zaretskaya N, Fultz NE, Ohringer NA, Chaudhari AS, Hu Y, Witzel T, Setsompop K, Polimeni JR, Huang SY. Improving in vivo human cerebral cortical surface reconstruction using data-driven super-resolution. Cereb Cortex 2021; 31:463-482. [PMID: 32887984 PMCID: PMC7727379 DOI: 10.1093/cercor/bhaa237] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 07/30/2020] [Accepted: 07/30/2020] [Indexed: 11/14/2022] Open
Abstract
Accurate and automated reconstruction of the in vivo human cerebral cortical surface from anatomical magnetic resonance (MR) images facilitates the quantitative analysis of cortical structure. Anatomical MR images with sub-millimeter isotropic spatial resolution improve the accuracy of cortical surface and thickness estimation compared to the standard 1-millimeter isotropic resolution. Nonetheless, sub-millimeter resolution acquisitions require averaging multiple repetitions to achieve sufficient signal-to-noise ratio and are therefore long and potentially vulnerable to subject motion. We address this challenge by synthesizing sub-millimeter resolution images from standard 1-millimeter isotropic resolution images using a data-driven supervised machine learning-based super-resolution approach achieved via a deep convolutional neural network. We systematically characterize our approach using a large-scale simulated dataset and demonstrate its efficacy in empirical data. The super-resolution data provide improved cortical surfaces similar to those obtained from native sub-millimeter resolution data. The whole-brain mean absolute discrepancy in cortical surface positioning and thickness estimation is below 100 μm at the single-subject level and below 50 μm at the group level for the simulated data, and below 200 μm at the single-subject level and below 100 μm at the group level for the empirical data, making the accuracy of cortical surfaces derived from super-resolution sufficient for most applications.
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Affiliation(s)
- Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
- Harvard Medical School, Boston, MA, United States
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Qiuyun Fan
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Chanon Ngamsombat
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
| | - Natalia Zaretskaya
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
- Harvard Medical School, Boston, MA, United States
- Department of Experimental Psychology and Cognitive Neuroscience, Institute of Psychology, University of Graz, Graz, Austria
- BioTechMed-Graz, Austria
| | - Nina E Fultz
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
| | - Ned A Ohringer
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
| | - Akshay S Chaudhari
- Radiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA, United States
| | - Yuxin Hu
- Radiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA, United States
| | - Thomas Witzel
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
- Harvard Medical School, Boston, MA, United States
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
- Harvard Medical School, Boston, MA, United States
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
- Harvard Medical School, Boston, MA, United States
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
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34
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Stanley OW, Kuurstra AB, Klassen LM, Menon RS, Gati JS. Effects of phase regression on high-resolution functional MRI of the primary visual cortex. Neuroimage 2020; 227:117631. [PMID: 33316391 DOI: 10.1016/j.neuroimage.2020.117631] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 12/04/2020] [Indexed: 12/14/2022] Open
Abstract
High-resolution functional MRI studies have become a powerful tool to non-invasively probe the sub-millimeter functional organization of the human cortex. Advances in MR hardware, imaging techniques and sophisticated post-processing methods have allowed high resolution fMRI to be used in both the clinical and academic neurosciences. However, consensus within the community regarding the use of gradient echo (GE) or spin echo (SE) based acquisition remains largely divided. On one hand, GE provides a high temporal signal-to-noise ratio (tSNR) technique sensitive to both the macro- and micro-vascular signal while SE based methods are more specific to microvasculature but suffer from lower tSNR and specific absorption rate limitations, especially at high field and with short repetition times. Fortunately, the phase of the GE-EPI signal is sensitive to vessel size and this provides a potential avenue to reduce the macrovascular weighting of the signal (phase regression, Menon 2002). In order to determine the efficacy of this technique at high-resolution, phase regression was applied to GE-EPI timeseries and compared to SE-EPI to determine if GE-EPI's specificity to the microvascular compartment improved. To do this, functional data was collected from seven subjects on a neuro-optimized 7 T system at 800 μm isotropic resolution with both GE-EPI and SE-EPI while observing an 8 Hz contrast reversing checkerboard. Phase data from the GE-EPI was used to create a microvasculature-weighted time series (GE-EPI-PR). Anatomical imaging (MP2RAGE) was also collected to allow for surface segmentation so that the functional results could be projected onto a surface. A multi-echo gradient echo sequence was collected and used to identify venous vasculature. The GE-EPI-PR surface activation maps showed a high qualitative similarity with SE-EPI and also produced laminar activity profiles similar to SE-EPI. When the GE-EPI and GE-EPI-PR distributions were compared to SE-EPI it was shown that GE-EPI-PR had similar distribution characteristics to SE-EPI (p < 0.05) across the top 60% of cortex. Furthermore, it was shown that GE-EPI-PR has a higher contrast-to-noise ratio (0.5 ± 0.2, mean ± std. dev. across layers) than SE-EPI (0.27 ± 0.07) demonstrating the technique has higher sensitivity than SE-EPI. Taken together this evidence suggests phase regression is a useful method in low SNR studies such as high-resolution fMRI.
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Affiliation(s)
- Olivia W Stanley
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada; Medical Biophysics, The University of Western Ontario, London, Ontario, Canada.
| | - Alan B Kuurstra
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - L Martyn Klassen
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada; Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
| | - Ravi S Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada; Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
| | - Joseph S Gati
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada; Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
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35
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Prior expectations evoke stimulus-specific activity in the deep layers of the primary visual cortex. PLoS Biol 2020; 18:e3001023. [PMID: 33284791 PMCID: PMC7746273 DOI: 10.1371/journal.pbio.3001023] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 12/17/2020] [Accepted: 11/20/2020] [Indexed: 12/23/2022] Open
Abstract
The way we perceive the world is strongly influenced by our expectations. In line with this, much recent research has revealed that prior expectations strongly modulate sensory processing. However, the neural circuitry through which the brain integrates external sensory inputs with internal expectation signals remains unknown. In order to understand the computational architecture of the cortex, we need to investigate the way these signals flow through the cortical layers. This is crucial because the different cortical layers have distinct intra- and interregional connectivity patterns, and therefore determining which layers are involved in a cortical computation can inform us on the sources and targets of these signals. Here, we used ultra-high field (7T) functional magnetic resonance imaging (fMRI) to reveal that prior expectations evoke stimulus-specific activity selectively in the deep layers of the primary visual cortex (V1). These findings are in line with predictive processing theories proposing that neurons in the deep cortical layers represent perceptual hypotheses and thereby shed light on the computational architecture of cortex. The way we perceive the world is strongly influenced by our expectations, but the neural circuitry through which the brain achieves this remains unknown. A study using ultra-high field fMRI reveals that prior expectations evoke stimulus-specific signals in the deep layers of the primary visual cortex.
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36
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Weldon KB, Olman CA. Forging a path to mesoscopic imaging success with ultra-high field functional magnetic resonance imaging. Philos Trans R Soc Lond B Biol Sci 2020; 376:20200040. [PMID: 33190599 PMCID: PMC7741029 DOI: 10.1098/rstb.2020.0040] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Functional magnetic resonance imaging (fMRI) studies with ultra-high field (UHF, 7+ Tesla) technology enable the acquisition of high-resolution images. In this work, we discuss recent achievements in UHF fMRI at the mesoscopic scale, on the order of cortical columns and layers, and examine approaches to addressing common challenges. As researchers push to smaller and smaller voxel sizes, acquisition and analysis decisions have greater potential to degrade spatial accuracy, and UHF fMRI data must be carefully interpreted. We consider the impact of acquisition decisions on the spatial specificity of the MR signal with a representative dataset with 0.8 mm isotropic resolution. We illustrate the trade-offs in contrast with noise ratio and spatial specificity of different acquisition techniques and show that acquisition blurring can increase the effective voxel size by as much as 50% in some dimensions. We further describe how different sources of degradations to spatial resolution in functional data may be characterized. Finally, we emphasize that progress in UHF fMRI depends not only on scientific discovery and technical advancement, but also on informal discussions and documentation of challenges researchers face and overcome in pursuit of their goals. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.
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Affiliation(s)
- Kimberly B Weldon
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN 55455, USA.,Center for Magnetic Resonance Imaging, University of Minnesota, Minneapolis, MN 55455, USA
| | - Cheryl A Olman
- Center for Magnetic Resonance Imaging, University of Minnesota, Minneapolis, MN 55455, USA.,Department of Psychology, University of Minnesota, Minneapolis, MN 55455, USA
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37
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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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38
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Navarro KT, Sanchez MJ, Engel SA, Olman CA, Weldon KB. Depth-dependent functional MRI responses to chromatic and achromatic stimuli throughout V1 and V2. Neuroimage 2020; 226:117520. [PMID: 33137474 PMCID: PMC7958868 DOI: 10.1016/j.neuroimage.2020.117520] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 10/21/2020] [Accepted: 10/26/2020] [Indexed: 11/13/2022] Open
Abstract
In the primate visual system, form (shape, location) and color information are processed in separate but interacting pathways. Recent access to high-resolution neuroimaging has facilitated the exploration of the structure of these pathways at the mesoscopic level in the human visual cortex. We used 7T fMRI to observe selective activation of the primary visual cortex to chromatic versus achromatic stimuli in five participants across two scanning sessions. Achromatic checkerboards with low spatial frequency and high temporal frequency targeted the color-insensitive magnocellular pathway. Chromatic checkerboards with higher spatial frequency and low temporal frequency targeted the color-selective parvocellular pathway. This work resulted in three main findings. First, responses driven by chromatic stimuli had a laminar profile biased towards superficial layers of V1, as compared to responses driven by achromatic stimuli. Second, we found stronger preference for chromatic stimuli in parafoveal V1 compared with peripheral V1. Finally, we found alternating, stimulus-selective bands stemming from the V1 border into V2 and V3. Similar alternating patterns have been previously found in both NHP and human extrastriate cortex. Together, our findings confirm the utility of fMRI for revealing details of mesoscopic neural architecture in human cortex.
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Affiliation(s)
- Karen T Navarro
- Department of Psychology, University of Minnesota, 75 E River Rd, Minneapolis, MN 55455, United States.
| | - Marisa J Sanchez
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, 2450 Riverside Ave f275, Minneapolis, MN 55454, United States
| | - Stephen A Engel
- Department of Psychology, University of Minnesota, 75 E River Rd, Minneapolis, MN 55455, United States
| | - Cheryl A Olman
- Department of Psychology, University of Minnesota, 75 E River Rd, Minneapolis, MN 55455, United States; Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN 55455, United States
| | - Kimberly B Weldon
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, 2450 Riverside Ave f275, Minneapolis, MN 55454, United States; Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN 55455, United States
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39
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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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40
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Kay K, Jamison KW, Zhang RY, Uğurbil K. A temporal decomposition method for identifying venous effects in task-based fMRI. Nat Methods 2020; 17:1033-1039. [PMID: 32895538 DOI: 10.1038/s41592-020-0941-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 08/03/2020] [Indexed: 11/09/2022]
Abstract
The spatial resolution of functional magnetic resonance imaging (fMRI) is fundamentally limited by effects from large draining veins. Here we describe an analysis method that provides data-driven estimates of these effects in task-based fMRI. The method involves fitting a one-dimensional manifold that characterizes variation in response timecourses observed in a given dataset, and then using identified early and late timecourses as basis functions for decomposing responses into components related to the microvasculature (capillaries and small venules) and the macrovasculature (large veins), respectively. We show the removal of late components substantially reduces the superficial cortical depth bias of fMRI responses and helps eliminate artifacts in cortical activity maps. This method provides insight into the origins of the fMRI signal and can be used to improve the spatial accuracy of fMRI.
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Affiliation(s)
- Kendrick Kay
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA.
| | - Keith W Jamison
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA.,Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Ru-Yuan Zhang
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA.,Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, China
| | - Kamil Uğurbil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
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41
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Layer-dependent multiplicative effects of spatial attention on contrast responses in human early visual cortex. Prog Neurobiol 2020; 207:101897. [DOI: 10.1016/j.pneurobio.2020.101897] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 07/05/2020] [Accepted: 08/12/2020] [Indexed: 11/19/2022]
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42
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Abouelseoud G, Abouelseoud Y, Shoukry A, Ismail N, Mekky J. On the use of time division multiplexing to improve electrical brain stimulation focality. Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2020.102048] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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43
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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: 23] [Impact Index Per Article: 5.8] [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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44
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Marquardt I, De Weerd P, Schneider M, Gulban OF, Ivanov D, Wang Y, Uludağ K. Feedback contribution to surface motion perception in the human early visual cortex. eLife 2020; 9:e50933. [PMID: 32496189 PMCID: PMC7314553 DOI: 10.7554/elife.50933] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 06/03/2020] [Indexed: 01/03/2023] Open
Abstract
Human visual surface perception has neural correlates in early visual cortex, but the role of feedback during surface segmentation in human early visual cortex remains unknown. Feedback projections preferentially enter superficial and deep anatomical layers, which provides a hypothesis for the cortical depth distribution of fMRI activity related to feedback. Using ultra-high field fMRI, we report a depth distribution of activation in line with feedback during the (illusory) perception of surface motion. Our results fit with a signal re-entering in superficial depths of V1, followed by a feedforward sweep of the re-entered information through V2 and V3. The magnitude and sign of the BOLD response strongly depended on the presence of texture in the background, and was additionally modulated by the presence of illusory motion perception compatible with feedback. In summary, the present study demonstrates the potential of depth-resolved fMRI in tackling biomechanical questions on perception.
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Affiliation(s)
- Ingo Marquardt
- Department of Cognitive Neuroscience, Maastricht Brain Imaging Centre (MBIC) Faculty of Psychology and Neuroscience, Maastricht UniversityMaastrichtNetherlands
| | - Peter De Weerd
- Department of Cognitive Neuroscience, Maastricht Brain Imaging Centre (MBIC) Faculty of Psychology and Neuroscience, Maastricht UniversityMaastrichtNetherlands
- Maastricht Center of Systems Biology (MACSBIO), Faculty of Science & Engineering, Maastricht UniversityMaastrichtNetherlands
| | - Marian Schneider
- Department of Cognitive Neuroscience, Maastricht Brain Imaging Centre (MBIC) Faculty of Psychology and Neuroscience, Maastricht UniversityMaastrichtNetherlands
| | - Omer Faruk Gulban
- Department of Cognitive Neuroscience, Maastricht Brain Imaging Centre (MBIC) Faculty of Psychology and Neuroscience, Maastricht UniversityMaastrichtNetherlands
| | - Dimo Ivanov
- Department of Cognitive Neuroscience, Maastricht Brain Imaging Centre (MBIC) Faculty of Psychology and Neuroscience, Maastricht UniversityMaastrichtNetherlands
| | - Yawen Wang
- Department of Cognitive Neuroscience, Maastricht Brain Imaging Centre (MBIC) Faculty of Psychology and Neuroscience, Maastricht UniversityMaastrichtNetherlands
| | - Kâmil Uludağ
- Center for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, N Center, Sungkyunkwan UniversityJangan-guRepublic of Korea
- Techna Institute and Koerner Scientist in MR Imaging, University Health NetworkTorontoCanada
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45
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Layer-dependent functional connectivity methods. Prog Neurobiol 2020; 207:101835. [DOI: 10.1016/j.pneurobio.2020.101835] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 03/30/2020] [Accepted: 05/21/2020] [Indexed: 12/16/2022]
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46
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van Dijk JA, Fracasso A, Petridou N, Dumoulin SO. Linear systems analysis for laminar fMRI: Evaluating BOLD amplitude scaling for luminance contrast manipulations. Sci Rep 2020; 10:5462. [PMID: 32214136 PMCID: PMC7096513 DOI: 10.1038/s41598-020-62165-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 03/09/2020] [Indexed: 01/18/2023] Open
Abstract
A fundamental assumption of nearly all functional magnetic resonance imaging (fMRI) analyses is that the relationship between local neuronal activity and the blood oxygenation level dependent (BOLD) signal can be described as following linear systems theory. With the advent of ultra-high field (7T and higher) MRI scanners, it has become possible to perform sub-millimeter resolution fMRI in humans. A novel and promising application of sub-millimeter fMRI is measuring responses across cortical depth, i.e. laminar imaging. However, the cortical vasculature and associated directional blood pooling towards the pial surface strongly influence the cortical depth-dependent BOLD signal, particularly for gradient-echo BOLD. This directional pooling may potentially affect BOLD linearity across cortical depth. Here we assess whether the amplitude scaling assumption for linear systems theory holds across cortical depth. For this, we use stimuli with different luminance contrasts to elicit different BOLD response amplitudes. We find that BOLD amplitude across cortical depth scales with luminance contrast, and that this scaling is identical across cortical depth. Although nonlinearities may be present for different stimulus configurations and acquisition protocols, our results suggest that the amplitude scaling assumption for linear systems theory across cortical depth holds for luminance contrast manipulations in sub-millimeter laminar BOLD fMRI.
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Affiliation(s)
- Jelle A van Dijk
- Experimental Psychology, Utrecht University, Utrecht, NL, Netherlands.
- Spinoza Centre for Neuroimaging, Amsterdam, NL, Netherlands.
| | - Alessio Fracasso
- Spinoza Centre for Neuroimaging, Amsterdam, NL, Netherlands
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, G12 8QB, UK
- Radiology Department, Imaging Division, Center for Image Sciences, University Medical Center Utrecht, Utrecht, NL, Netherlands
| | - Natalia Petridou
- Radiology Department, Imaging Division, Center for Image Sciences, University Medical Center Utrecht, Utrecht, NL, Netherlands
| | - Serge O Dumoulin
- Experimental Psychology, Utrecht University, Utrecht, NL, Netherlands
- Spinoza Centre for Neuroimaging, Amsterdam, NL, Netherlands
- Experimental and Applied Psychology, VU University, Amsterdam, NL, Netherlands
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47
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Havlicek M, Uludağ K. A dynamical model of the laminar BOLD response. Neuroimage 2020; 204:116209. [DOI: 10.1016/j.neuroimage.2019.116209] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 08/11/2019] [Accepted: 09/17/2019] [Indexed: 12/18/2022] Open
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48
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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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49
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Strategies and prospects for cortical depth dependent T2 and T2* weighted BOLD fMRI studies. Neuroimage 2019; 197:668-676. [DOI: 10.1016/j.neuroimage.2019.03.024] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Revised: 02/28/2019] [Accepted: 03/12/2019] [Indexed: 12/15/2022] Open
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50
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Self MW, van Kerkoerle T, Goebel R, Roelfsema PR. Benchmarking laminar fMRI: Neuronal spiking and synaptic activity during top-down and bottom-up processing in the different layers of cortex. Neuroimage 2019. [DOI: 10.1016/j.neuroimage.2017.06.045] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
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