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Carricarte T, Iamshchinina P, Trampel R, Chaimow D, Weiskopf N, Cichy RM. Laminar dissociation of feedforward and feedback in high-level ventral visual cortex during imagery and perception. iScience 2024; 27:110229. [PMID: 39006482 PMCID: PMC11246059 DOI: 10.1016/j.isci.2024.110229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 01/26/2024] [Accepted: 06/06/2024] [Indexed: 07/16/2024] Open
Abstract
Visual imagery and perception share neural machinery but rely on different information flow. While perception is driven by the integration of sensory feedforward and internally generated feedback information, imagery relies on feedback only. This suggests that although imagery and perception may activate overlapping brain regions, they do so in informationally distinctive ways. Using lamina-resolved MRI at 7 T, we measured the neural activity during imagery and perception of faces and scenes in high-level ventral visual cortex at the mesoscale of laminar organization that distinguishes feedforward from feedback signals. We found distinctive laminar profiles for imagery and perception of scenes and faces in the parahippocampal place area and the fusiform face area, respectively. Our findings provide insight into the neural basis of the phenomenology of visual imagery versus perception and shed new light into the mesoscale organization of feedforward and feedback information flow in high-level ventral visual cortex.
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Affiliation(s)
- Tony Carricarte
- Department of Education and Psychology, Freie Universität Berlin, 14195 Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin, 10117 Berlin, Germany
| | - Polina Iamshchinina
- Princeton Neuroscience Institute, Princeton University, New Jersey 08544, USA
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
| | - Denis Chaimow
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Universität Leipzig, 04103 Leipzig, Germany
| | - Radoslaw M. Cichy
- Department of Education and Psychology, Freie Universität Berlin, 14195 Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, 10117 Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin, 10117 Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, 10117 Berlin, Germany
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2
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Shao X, Guo F, Kim J, Ress D, Zhao C, Shou Q, Jann K, Wang DJJ. Laminar multi-contrast fMRI at 7T allows differentiation of neuronal excitation and inhibition underlying positive and negative BOLD responses. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.01.24305167. [PMID: 39040201 PMCID: PMC11261924 DOI: 10.1101/2024.04.01.24305167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
A major challenge for human neuroimaging using functional MRI is the differentiation of neuronal excitation and inhibition which may induce positive and negative BOLD responses. Here we present an innovative multi-contrast laminar functional MRI technique that offers comprehensive and quantitative imaging of neurovascular (CBF, CBV, BOLD) and metabolic (CMRO2) responses across cortical layers at 7 Tesla. This technique was first validated through a finger-tapping experiment, revealing 'double-peak' laminar activation patterns within the primary motor cortex. By employing a ring-shaped visual stimulus that elicited positive and negative BOLD responses, we further observed distinct neurovascular and metabolic responses across cortical layers and eccentricities in the primary visual cortex. This suggests potential feedback inhibition of neuronal activities in both superficial and deep cortical layers underlying the negative BOLD signals in the fovea, and also illustrates the neuronal activities in visual areas adjacent to the activated eccentricities.
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Affiliation(s)
- Xingfeng Shao
- Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California
| | - Fanhua Guo
- Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California
| | - JungHwan Kim
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, University of Texas Health Science Center at Houston
| | - David Ress
- Department of Neuroscience, Baylor College of Medicine
| | - Chenyang Zhao
- Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California
| | - Qinyang Shou
- Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California
| | - Kay Jann
- Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California
| | - Danny JJ Wang
- Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California
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3
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Kutten KS, Trieu J, Dawson J, Hou L, Sollmann L, Kral A, Hubka P, Ratnanather JT. Multidimensional Alternating Kernel Method for cortical layer segmentation in 3D reconstructed histology. MethodsX 2024; 12:102674. [PMID: 38660047 PMCID: PMC11041843 DOI: 10.1016/j.mex.2024.102674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 03/22/2024] [Indexed: 04/26/2024] Open
Abstract
The neocortex of the brain can be divided into six layers each with a distinct cell composition and connectivity pattern. Recently, sensory deprivation, including congenital deafness, has been shown to alter cortical structure (e.g. the cortical thickness) of the feline auditory cortex with variable and inconsistent results. Thus, understanding these complex changes will require further study of the constituent cortical layers in three-dimensional space. Further progress crucially depends on the use of objective computational techniques that can reliably characterize spatial properties of the complex cortical structure. Here a method for cortical laminar segmentation is derived and applied to the three-dimensional cortical areas reconstructed from a series of histological sections from four feline brains. In this approach, the Alternating Kernel Method was extended to fit a multi-variate Gaussian mixture model to a feature space consisting of both staining intensity and a biologically plausible equivolumetric depth map. This research method•Extends the Alternating Kernel Method to multi-dimensional feature spaces.•Uses it to segment the cortical layers in reconstructed histology volume. Segmentation features include staining intensity and a biologically plausible equivolumetric depth map.•Validates results in auditory cortical areas of feline brains, two with normal hearing and two with congenital deafness.
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Affiliation(s)
| | - Jenny Trieu
- Johns Hopkins University, Baltimore, MD, USA
| | | | - Lisa Hou
- Johns Hopkins University, Baltimore, MD, USA
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Renton AI, Dao TT, Johnstone T, Civier O, Sullivan RP, White DJ, Lyons P, Slade BM, Abbott DF, Amos TJ, Bollmann S, Botting A, Campbell MEJ, Chang J, Close TG, Dörig M, Eckstein K, Egan GF, Evas S, Flandin G, Garner KG, Garrido MI, Ghosh SS, Grignard M, Halchenko YO, Hannan AJ, Heinsfeld AS, Huber L, Hughes ME, Kaczmarzyk JR, Kasper L, Kuhlmann L, Lou K, Mantilla-Ramos YJ, Mattingley JB, Meier ML, Morris J, Narayanan A, Pestilli F, Puce A, Ribeiro FL, Rogasch NC, Rorden C, Schira MM, Shaw TB, Sowman PF, Spitz G, Stewart AW, Ye X, Zhu JD, Narayanan A, Bollmann S. Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging. Nat Methods 2024; 21:804-808. [PMID: 38191935 PMCID: PMC11180540 DOI: 10.1038/s41592-023-02145-x] [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: 03/02/2023] [Accepted: 11/27/2023] [Indexed: 01/10/2024]
Abstract
Neuroimaging research requires purpose-built analysis software, which is challenging to install and may produce different results across computing environments. The community-oriented, open-source Neurodesk platform ( https://www.neurodesk.org/ ) harnesses a comprehensive and growing suite of neuroimaging software containers. Neurodesk includes a browser-accessible virtual desktop, command-line interface and computational notebook compatibility, allowing for accessible, flexible, portable and fully reproducible neuroimaging analysis on personal workstations, high-performance computers and the cloud.
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Affiliation(s)
- Angela I Renton
- The University of Queensland, Queensland Brain Institute, St Lucia, Brisbane, Queensland, Australia.
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia.
| | - Thuy T Dao
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Tom Johnstone
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Oren Civier
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Ryan P Sullivan
- The University of Sydney, School of Biomedical Engineering, Sydney, New South Wales, Australia
| | - David J White
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Paris Lyons
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Benjamin M Slade
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - David F Abbott
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Toluwani J Amos
- School of Life Science and Technology, University of Electronic Science and Technology, Chengdu, China
| | - Saskia Bollmann
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Andy Botting
- Australian Research Data Commons (ARDC), Sydney, New South Wales, Australia
| | - Megan E J Campbell
- School of Psychological Sciences, University of Newcastle, Newcastle, New South Wales, Australia
- Hunter Medical Research Institute Imaging Centre, Newcastle, New South Wales, Australia
| | - Jeryn Chang
- The University of Queensland, School of Biomedical Sciences, St Lucia, Brisbane, Queensland, Australia
| | - Thomas G Close
- The University of Sydney, School of Biomedical Engineering, Sydney, New South Wales, Australia
| | - Monika Dörig
- Integrative Spinal Research, Department of Chiropractic Medicine, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Korbinian Eckstein
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Gary F Egan
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia
| | - Stefanie Evas
- School of Psychology, University of Adelaide, Adelaide, South Australia, Australia
- Human Health, Health & Biosecurity, CSIRO, Adelaide, South Australia, Australia
| | - Guillaume Flandin
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Kelly G Garner
- School of Psychology, University of New South Wales, Sydney, New South Wales, Australia
- The University of Queensland, School of Psychology, St Lucia, Brisbane, Queensland, Australia
| | - Marta I Garrido
- Melbourne School of Psychological Sciences, he University of Melbourne, Melbourne, Victoria, Australia
- Graeme Clark Institute for Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia
| | - Satrajit S Ghosh
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Otolaryngology - Head and Neck Surgery, Harvard Medical School, Boston, MA, USA
| | - Martin Grignard
- GIGA CRC In-Vivo Imaging, University of Liège, Liège, Belgium
| | - Yaroslav O Halchenko
- Center for Open Neuroscience, Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Anthony J Hannan
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Anibal S Heinsfeld
- Department of Psychology, Center for Perceptual Systems, Institute for Neuroscience, Center For Learning and Memory, The University of Texas at Austin, Austin, TX, USA
| | - Laurentius Huber
- National Institute of Mental Health (NIMH), National Institutes Health, Bethesda, MD, USA
| | - Matthew E Hughes
- Centre for Mental Health & Brain Sciences, Swinburne University of Technology, Hawthorn, Victoria, Australia
| | - Jakub R Kaczmarzyk
- Department of Biomedical Informatics, Stony Brook University, New York, NY, USA
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, New York, NY, USA
| | - Lars Kasper
- BRAIN-TO Lab, Krembil Brain Institute, University Health Network, Toronto, Ontario, Canada
- Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Levin Kuhlmann
- Department of Data Science and AI, Faculty of Information Technology, Monash University, Melbourne, Victoria, Australia
| | - Kexin Lou
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
- Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Yorguin-Jose Mantilla-Ramos
- Grupo Neuropsicología y Conducta (GRUNECO), Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia
| | - Jason B Mattingley
- The University of Queensland, Queensland Brain Institute, St Lucia, Brisbane, Queensland, Australia
- The University of Queensland, School of Psychology, St Lucia, Brisbane, Queensland, Australia
| | - Michael L Meier
- Integrative Spinal Research, Department of Chiropractic Medicine, Balgrist University Hospital, University of Zurich, Zurich, Switzerland
| | - Jo Morris
- Australian Research Data Commons (ARDC), Sydney, New South Wales, Australia
| | - Akshaiy Narayanan
- School of Computer Science, The University of Auckland, Auckland, New Zealand
| | - Franco Pestilli
- Department of Psychology, Center for Perceptual Systems, Institute for Neuroscience, Center For Learning and Memory, The University of Texas at Austin, Austin, TX, USA
| | - Aina Puce
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Fernanda L Ribeiro
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Nigel C Rogasch
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
- Discipline of Psychiatry, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
- Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, South Australia, Australia
| | - Chris Rorden
- McCausland Center for Brain Imaging, Department of Psychology, University of South Carolina, Columbia, SC, USA
| | - Mark M Schira
- School of Psychology, University of Wollongong, Wollongong, New South Wales, Australia
| | - Thomas B Shaw
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
- The University of Queensland, Centre for Advanced Imaging, St Lucia, Brisbane, Queensland, Australia
- Department of Neurology, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
| | - Paul F Sowman
- Macquarie University, School of Psychological Sciences, Sydney, New South Wales, Australia
| | - Gershon Spitz
- Department of Neuroscience, Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
- Monash-Epworth Rehabilitation Research Centre, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Ashley W Stewart
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia
| | - Xincheng Ye
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia
| | - Judy D Zhu
- Macquarie University, School of Psychological Sciences, Sydney, New South Wales, Australia
| | - Aswin Narayanan
- The University of Queensland, Centre for Advanced Imaging, St Lucia, Brisbane, Queensland, Australia
| | - Steffen Bollmann
- The University of Queensland, School of Electrical Engineering and Computer Science, St Lucia, Brisbane, Queensland, Australia.
- The University of Queensland, Centre for Advanced Imaging, St Lucia, Brisbane, Queensland, Australia.
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, Queensland, Australia.
- Queensland Digital Health Centre, The University of Queensland, Brisbane, Queensland, Australia.
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5
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Wagstyl K, Adler S, Seidlitz J, Vandekar S, Mallard TT, Dear R, DeCasien AR, Satterthwaite TD, Liu S, Vértes PE, Shinohara RT, Alexander-Bloch A, Geschwind DH, Raznahan A. Transcriptional cartography integrates multiscale biology of the human cortex. eLife 2024; 12:RP86933. [PMID: 38324465 PMCID: PMC10945526 DOI: 10.7554/elife.86933] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024] Open
Abstract
The cerebral cortex underlies many of our unique strengths and vulnerabilities, but efforts to understand human cortical organization are challenged by reliance on incompatible measurement methods at different spatial scales. Macroscale features such as cortical folding and functional activation are accessed through spatially dense neuroimaging maps, whereas microscale cellular and molecular features are typically measured with sparse postmortem sampling. Here, we integrate these distinct windows on brain organization by building upon existing postmortem data to impute, validate, and analyze a library of spatially dense neuroimaging-like maps of human cortical gene expression. These maps allow spatially unbiased discovery of cortical zones with extreme transcriptional profiles or unusually rapid transcriptional change which index distinct microstructure and predict neuroimaging measures of cortical folding and functional activation. Modules of spatially coexpressed genes define a family of canonical expression maps that integrate diverse spatial scales and temporal epochs of human brain organization - ranging from protein-protein interactions to large-scale systems for cognitive processing. These module maps also parse neuropsychiatric risk genes into subsets which tag distinct cyto-laminar features and differentially predict the location of altered cortical anatomy and gene expression in patients. Taken together, the methods, resources, and findings described here advance our understanding of human cortical organization and offer flexible bridges to connect scientific fields operating at different spatial scales of human brain research.
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Affiliation(s)
- Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
| | - Sophie Adler
- UCL Great Ormond Street Institute for Child HealthHolbornUnited Kingdom
| | - Jakob Seidlitz
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt UniversityNashvilleUnited States
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General HospitalBostonUnited States
- Department of Psychiatry, Harvard Medical SchoolBostonUnited States
| | - Richard Dear
- Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Alex R DeCasien
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Theodore D Satterthwaite
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of MedicinePhiladelphiaUnited States
| | - Siyuan Liu
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Petra E Vértes
- Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Aaron Alexander-Bloch
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Daniel H Geschwind
- Center for Autism Research and Treatment, Semel Institute, Program in Neurogenetics, Department of Neurology and Department of Human Genetics, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
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Gomez DEP, Polimeni JR, Lewis LD. The temporal specificity of BOLD fMRI is systematically related to anatomical and vascular features of the human brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.01.578428. [PMID: 38352610 PMCID: PMC10862860 DOI: 10.1101/2024.02.01.578428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
The ability to detect fast responses with functional MRI depends on the speed of hemodynamic responses to neural activity, because hemodynamic responses act as a temporal low-pass filter smoothing out rapid changes. However, hemodynamic responses (their shape and timing) are highly variable across the brain and across stimuli. This heterogeneity of responses implies that the temporal specificity of fMRI signals, or the ability of fMRI to preserve fast information, should also vary substantially across the cortex. In this work we investigated how local differences in hemodynamic response timing impact the temporal specificity of fMRI. We conducted our research using ultra-high field (7T) fMRI at high spatiotemporal resolution, using the primary visual cortex (V1) as a model area for investigation. We used visual stimuli oscillating at slow and fast frequencies to probe the temporal specificity of individual voxels. As expected, we identified substantial variability in temporal specificity, with some voxels preserving their responses to fast neural activity more effectively than others. We investigated which voxels had the highest temporal specificity and related those to anatomical and vascular features of V1. We found that low temporal specificity is only weakly explained by the presence of large veins or cerebral cortical depth. Notably, however, temporal specificity depended strongly on a voxel's position along the anterior-posterior anatomical axis of V1, with voxels within the calcarine sulcus being capable of preserving close to 25% of their amplitude as the frequency of stimulation increased from 0.05-Hz to 0.20-Hz, and voxels nearest to the occipital pole preserving less than 18%. These results indicate that detection biases in high-resolution fMRI will depend on the anatomical and vascular features of the area being imaged, and that these biases will differ depending on the timing of the underlying neuronal activity. Importantly, this spatial heterogeneity of temporal specificity suggests that it could be exploited to achieve higher specificity in some locations, and that tailored data analysis strategies may help improve the detection and interpretation of fast fMRI responses.
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Affiliation(s)
- Daniel E. P. Gomez
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Laura D. Lewis
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States
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7
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Dresbach S, Huber R, Gulban OF, Pizzuti A, Trampel R, Ivanov D, Weiskopf N, Goebel R. Characterisation of laminar and vascular spatiotemporal dynamics of CBV and BOLD signals using VASO and ME-GRE at 7T in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.25.576050. [PMID: 38410457 PMCID: PMC10896347 DOI: 10.1101/2024.01.25.576050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Interpretation of cortical laminar functional magnetic resonance imaging (fMRI) activity requires detailed knowledge of the spatiotemporal haemodynamic response across vascular compartments due to the well-known vascular biases (e.g. the draining veins). Further complications arise from the spatiotemporal hemodynamic response that differs depending on the duration of stimulation. This information is crucial for future studies using depth-dependent cerebral blood volume (CBV) measurements, which promise higher specificity for the cortical microvasculature than the blood oxygenation level dependent (BOLD) contrast. To date, direct information about CBV dynamics with respect to stimulus duration, cortical depth and vasculature is missing in humans. Therefore, we characterized the cortical depth-dependent CBV-haemodynamic responses across a wide set of stimulus durations with 0.9 mm isotropic spatial and 0.785 seconds effective temporal resolution in humans using slice-selective slab-inversion vascular space occupancy (SS-SI VASO). Additionally, we investigated signal contributions from macrovascular compartments using fine-scale vascular information from multi-echo gradient-echo (ME-GRE) data at 0.35 mm isotropic resolution. In total, this resulted in >7.5h of scanning per participant (n=5). We have three major findings: (I) While we could demonstrate that 1 second stimulation is viable using VASO, more than 12 seconds stimulation provides better CBV responses in terms of specificity to microvasculature, but durations beyond 24 seconds of stimulation may be wasteful for certain applications. (II) We observe that CBV responses show dilation patterns across the cortex. (III) While we found increasingly strong BOLD signal responses in vessel-dominated voxels with longer stimulation durations, we found increasingly strong CBV signal responses in vessel-dominated voxels only until 4 second stimulation durations. After 4 seconds, only the signal from non-vessel dominated voxels kept increasing. This might explain why CBV responses are more specific to the underlying neuronal activity for long stimulus durations.
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Affiliation(s)
- Sebastian Dresbach
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Renzo Huber
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- National Institutes of Health, Bethesda, MD, USA
| | - Omer Faruk Gulban
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Brain innovation, Maastricht, the Netherlands
| | - Alessandra Pizzuti
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Brain innovation, Maastricht, the Netherlands
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Dimo Ivanov
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth System Sciences, Leipzig University, Linnéstraße 5, 04103 Leipzig, Germany
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3AR, UK
| | - Rainer Goebel
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Brain innovation, Maastricht, the Netherlands
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8
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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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9
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Kotlarz P, Lankinen K, Hakonen M, Turpin T, Polimeni JR, Ahveninen J. Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.23.573208. [PMID: 38187540 PMCID: PMC10769454 DOI: 10.1101/2023.12.23.573208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
In graph theory, "multilayer networks" represent systems involving several interconnected topological levels. A neuroscience example is the hierarchy of connections between different cortical depths or "lamina". This hierarchy is becoming non-invasively accessible in humans using ultra-high-resolution functional MRI (fMRI). Here, we applied multilayer graph theory to examine functional connectivity across different cortical depths in humans, using 7T fMRI (1-mm3 voxels; 30 participants). Blood oxygenation level dependent (BOLD) signals were derived from five depths between the white matter and pial surface. We then compared networks where the inter-regional connections were limited to a single cortical depth only ("layer-by-layer matrices") to those considering all possible connections between regions and cortical depths ("multilayer matrix"). We utilized global and local graph theory features that quantitatively characterize network attributes such as network composition, nodal centrality, path-based measures, and hub segregation. Detecting functional differences between cortical depths was improved using multilayer connectomics compared to the layer-by-layer versions. Superficial aspects of the cortex dominated information transfer and deeper aspects clustering. These differences were largest in frontotemporal and limbic brain regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information. Multilayer connectomics could provide a methodological framework for studies on how information flows across this hierarchy.
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Affiliation(s)
- Parker Kotlarz
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Kaisu Lankinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Maria Hakonen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, 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
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
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10
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Kalyani A, Contier O, Klemm L, Azañon E, Schreiber S, Speck O, Reichert C, Kuehn E. Reduced dimension stimulus decoding and column-based modeling reveal architectural differences of primary somatosensory finger maps between younger and older adults. Neuroimage 2023; 283:120430. [PMID: 37923281 DOI: 10.1016/j.neuroimage.2023.120430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 09/28/2023] [Accepted: 10/25/2023] [Indexed: 11/07/2023] Open
Abstract
The primary somatosensory cortex (SI) contains fine-grained tactile representations of the body, arranged in an orderly fashion. The use of ultra-high resolution fMRI data to detect group differences, for example between younger and older adults' SI maps, is challenging, because group alignment often does not preserve the high spatial detail of the data. Here, we use robust-shared response modeling (rSRM) that allows group analyses by mapping individual stimulus-driven responses to a lower dimensional shared feature space, to detect age-related differences in tactile representations between younger and older adults using 7T-fMRI data. Using this method, we show that finger representations are more precise in Brodmann-Area (BA) 3b and BA1 compared to BA2 and motor areas, and that this hierarchical processing is preserved across age groups. By combining rSRM with column-based decoding (C-SRM), we further show that the number of columns that optimally describes finger maps in SI is higher in younger compared to older adults in BA1, indicating a greater columnar size in older adults' SI. Taken together, we conclude that rSRM is suitable for finding fine-grained group differences in ultra-high resolution fMRI data, and we provide first evidence that the columnar architecture in SI changes with increasing age.
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Affiliation(s)
- Avinash Kalyani
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, 39120, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, 39120, Germany.
| | - Oliver Contier
- Vision and Computational Cognition Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04103, Germany; Max Planck School of Cognition, Stephanstrasse 1a, Leipzig, 04103, Germany
| | - Lisa Klemm
- Leibniz Institute for Neurobiology (LIN), Otto-von-Guericke University Magdeburg, Germany; Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg, 39120, Germany; Clinic for Neurology, Otto-von-Guericke University Magdeburg, 39120, Germany
| | - Elena Azañon
- Leibniz Institute for Neurobiology (LIN), Otto-von-Guericke University Magdeburg, Germany; Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg, 39120, Germany; Clinic for Neurology, Otto-von-Guericke University Magdeburg, 39120, Germany
| | - Stefanie Schreiber
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, 39120, Germany; Clinic for Neurology, Otto-von-Guericke University Magdeburg, 39120, Germany
| | - Oliver Speck
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, 39120, Germany; Leibniz Institute for Neurobiology (LIN), Otto-von-Guericke University Magdeburg, Germany; Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg, 39120, Germany; Department Biomedical Magnetic Resonance (BMMR), Otto-von-Guericke University Magdeburg, Germany; Research Campus STIMULATE, Otto von Guericke University, Magdeburg, Germany
| | - Christoph Reichert
- Leibniz Institute for Neurobiology (LIN), Otto-von-Guericke University Magdeburg, Germany; Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg, 39120, Germany; Research Campus STIMULATE, Otto von Guericke University, Magdeburg, Germany
| | - Esther Kuehn
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, 39120, Germany; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, 39120, Germany; Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg, 39120, Germany; Hertie Institute for Clinical Brain Research, 72076 Tübingen, Germany
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11
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Chang WT, Lin W, Giovanello KS. Enabling brain-wide mapping of directed functional connectivity at 3T via layer-dependent fMRI with draining-vein suppression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.24.563835. [PMID: 37961360 PMCID: PMC10634801 DOI: 10.1101/2023.10.24.563835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Layer-dependent functional magnetic resonance imaging (fMRI) offers a compelling avenue for investigating directed functional connectivity (FC). To construct a comprehensive map of brain-wide directed FC, several technical criteria must be met, including sub-mm spatial resolution, adequate temporal resolution, functional sensitivity, global brain coverage, and high spatial specificity. Although gradient echo (GE)-based echo planar imaging (EPI) is commonly used for rapid fMRI acquisition, it faces significant challenges due to the draining-vein effect, particularly when utilizing blood oxygen level-dependent (BOLD) contrast. In this study, we mitigated this effect by incorporating velocity-nulling (VN) gradients into a GE-BOLD fMRI sequence, opting for a 3T magnetic field strength over 7T. We also integrated several advanced techniques, such as simultaneous multi-slice (SMS) acceleration and NORDIC denoising, to enhance temporal resolution, spatial coverage, and signal sensitivity. Collectively, the VN fMRI method exhibited notable spatial specificity, as evidenced by the identification of double-peak activation patterns within the primary motor cortex (M1) during a finger-tapping task. Additionally, the technique demonstrated BOLD sensitivity in the lateral geniculate nucleus (LGN). Furthermore, our VN fMRI technique displayed superior robustness when compared to conventional fMRI approaches across participants. Our findings of directed FC elucidate several layer-specific functional relationships between different brain regions and align closely with existing literature. Given the widespread availability of 3T scanners, this technical advancement has the potential for significant impact across multiple domains of neuroscience research.
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Affiliation(s)
- Wei-Tang Chang
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, NC, USA
- Department of Radiology, University of North Carolina at Chapel Hill, NC, USA
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, NC, USA
| | - Weili Lin
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, NC, USA
- Department of Radiology, University of North Carolina at Chapel Hill, NC, USA
| | - Kelly S. Giovanello
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, NC, USA
- Department of Psychology & Neuroscience, University of North Carolina at Chapel Hill, NC, USA
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12
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Dresbach S, Huber LR, Gulban OF, Goebel R. Layer-fMRI VASO with short stimuli and event-related designs at 7 T. Neuroimage 2023; 279:120293. [PMID: 37562717 DOI: 10.1016/j.neuroimage.2023.120293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 07/06/2023] [Accepted: 07/22/2023] [Indexed: 08/12/2023] Open
Abstract
Layers and columns are the dominant processing units in the human (neo)cortex at the mesoscopic scale. While the blood oxygenation dependent (BOLD) signal has a high detection sensitivity, it is biased towards unwanted signals from large draining veins at the cortical surface. The additional fMRI contrast of vascular space occupancy (VASO) has the potential to augment the neuroscientific interpretability of layer-fMRI results by means of capturing complementary information of locally specific changes in cerebral blood volume (CBV). Specifically, VASO is not subject to unwanted sensitivity amplifications of large draining veins. Because of constrained sampling efficiency, it has been mainly applied in combination with efficient block task designs and long trial durations. However, to study cognitive processes in neuroscientific contexts, or probe vascular reactivity, short stimulation periods are often necessary. Here, we developed a VASO acquisition procedure with a short acquisition period and sub-millimeter resolution. During visual event-related stimulation, we show reliable responses in visual cortices within a reasonable number of trials (∼20). Furthermore, the short TR and high spatial specificity of our VASO implementation enabled us to show differences in laminar reactivity and onset times. Finally, we explore the generalizability to a different stimulus modality (somatosensation). With this, we showed that CBV-sensitive VASO provides the means to capture layer-specific haemodynamic responses with high spatio-temporal resolution and is able to be used with event-related paradigms.
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Affiliation(s)
- Sebastian Dresbach
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
| | - Laurentius Renzo Huber
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; National Institute of Health, Bethesda, DC, USA
| | - Omer Faruk Gulban
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; Brain Innovation, Maastricht, Netherlands
| | - Rainer Goebel
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; Brain Innovation, Maastricht, Netherlands
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13
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Jia K, Goebel R, Kourtzi Z. Ultra-High Field Imaging of Human Visual Cognition. Annu Rev Vis Sci 2023; 9:479-500. [PMID: 37137282 DOI: 10.1146/annurev-vision-111022-123830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Functional magnetic resonance imaging (fMRI), the key methodology for mapping the functions of the human brain in a noninvasive manner, is limited by low temporal and spatial resolution. Recent advances in ultra-high field (UHF) fMRI provide a mesoscopic (i.e., submillimeter resolution) tool that allows us to probe laminar and columnar circuits, distinguish bottom-up versus top-down pathways, and map small subcortical areas. We review recent work demonstrating that UHF fMRI provides a robust methodology for imaging the brain across cortical depths and columns that provides insights into the brain's organization and functions at unprecedented spatial resolution, advancing our understanding of the fine-scale computations and interareal communication that support visual cognition.
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Affiliation(s)
- Ke Jia
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom;
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom;
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14
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Pais-Roldán P, Yun SD, Palomero-Gallagher N, Shah NJ. Cortical depth-dependent human fMRI of resting-state networks using EPIK. Front Neurosci 2023; 17:1151544. [PMID: 37274214 PMCID: PMC10232833 DOI: 10.3389/fnins.2023.1151544] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 04/26/2023] [Indexed: 06/06/2023] Open
Abstract
Introduction Recent laminar-fMRI studies have substantially improved understanding of the evoked cortical responses in multiple sub-systems; in contrast, the laminar component of resting-state networks spread over the whole brain has been less studied due to technical limitations. Animal research strongly suggests that the supragranular layers of the cortex play a critical role in maintaining communication within the default mode network (DMN); however, whether this is true in this and other human cortical networks remains unclear. Methods Here, we used EPIK, which offers unprecedented coverage at sub-millimeter resolution, to investigate cortical broad resting-state dynamics with depth specificity in healthy volunteers. Results Our results suggest that human DMN connectivity is primarily supported by intermediate and superficial layers of the cortex, and furthermore, the preferred cortical depth used for communication can vary from one network to another. In addition, the laminar connectivity profile of some networks showed a tendency to change upon engagement in a motor task. In line with these connectivity changes, we observed that the amplitude of the low-frequency-fluctuations (ALFF), as well as the regional homogeneity (ReHo), exhibited a different laminar slope when subjects were either performing a task or were in a resting state (less variation among laminae, i.e., lower slope, during task performance compared to rest). Discussion The identification of varied laminar profiles concerning network connectivity, ALFF, and ReHo, observed across two brain states (task vs. rest) has major implications for the characterization of network-related diseases and suggests the potential diagnostic value of laminar fMRI in psychiatric disorders, e.g., to differentiate the cortical dynamics associated with disease stages linked, or not linked, to behavioral changes. The evaluation of laminar-fMRI across the brain encompasses computational challenges; nonetheless, it enables the investigation of a new dimension of the human neocortex, which may be key to understanding neurological disorders from a novel perspective.
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Affiliation(s)
- Patricia Pais-Roldán
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Seong Dae Yun
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Nicola Palomero-Gallagher
- Institute of Neuroscience and Medicine 1, Structural and Functional Organisation of the Brain, Forschungszentrum Jülich, Jülich, Germany
- C. and O. Vogt Institute for Brain Research, Heinrich-Heine-University, Düsseldorf, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Aachen, Germany
| | - N. Jon Shah
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
- Institute of Neuroscience and Medicine 11, Molecular Neuroscience and Neuroimaging, JARA, Forschungszentrum Jülich, Jülich, Germany
- JARA–BRAIN–Translational Medicine, Aachen, Germany
- Department of Neurology, RWTH Aachen University, Aachen, Germany
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15
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Zhang K, Chen L, Li Y, Paez AG, Miao X, Cao D, Gu C, Pekar JJ, van Zijl PCM, Hua J, Bakker A. Differential Laminar Activation Dissociates Encoding and Retrieval in the Human Medial and Lateral Entorhinal Cortex. J Neurosci 2023; 43:2874-2884. [PMID: 36948584 PMCID: PMC10124959 DOI: 10.1523/jneurosci.1488-22.2023] [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: 07/31/2022] [Revised: 02/28/2023] [Accepted: 03/12/2023] [Indexed: 03/24/2023] Open
Abstract
The hierarchically organized structures of the medial temporal lobe are critically important for episodic memory function. Accumulating evidence suggests dissociable information processing pathways are maintained throughout these structures including in the medial and lateral entorhinal cortex. Cortical layers provide an additional dimension of dissociation as the primary input to the hippocampus derives from layer 2 neurons in the entorhinal cortex, whereas the deeper layers primarily receive output from the hippocampus. Here, novel high-resolution T2-prepared functional MRI methods were successfully used to mitigate susceptibility artifacts typically affecting MRI signals in this region providing uniform sensitivity across the medial and lateral entorhinal cortex. During the performance of a memory task, healthy human subjects (age 25-33 years, mean age 28.2 ± 3.3 years, 4 female) showed differential functional activation in the superficial and deep layers of the entorhinal cortex associated with task-related encoding and retrieval conditions, respectively. The methods provided here offer an approach to probe layer-specific activation in normal cognition and conditions contributing to memory impairment.SIGNIFICANCE STATEMENT This study provides new evidence for differential neuronal activation in the superficial versus deep layers of the entorhinal cortex associated with encoding and retrieval memory processes, respectively, in cognitively normal adults. The study further shows that this dissociation can be observed in both the medial and the lateral entorhinal cortex. The study was achieved by using a novel functional MRI method allowing us to measure robust functional MRI signals in both the medial and lateral entorhinal cortex that was not possible in previous studies. The methodology established here in healthy human subjects lays a solid foundation for subsequent studies investigating layer-specific and region-specific changes in the entorhinal cortex associated with memory impairment in various conditions such as Alzheimer's disease.
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Affiliation(s)
- Kaihua Zhang
- School of Psychology, Shandong Normal University, Jinan 250014, China
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Liuyi Chen
- Departments of Psychiatry and Behavioral Sciences
| | - Yinghao Li
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
- Biomedical Engineering
| | - Adrian G Paez
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Xinyuan Miao
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Di Cao
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
- Biomedical Engineering
| | - Chunming Gu
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
- Biomedical Engineering
| | - James J Pekar
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Peter C M van Zijl
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Jun Hua
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland 21205
- Neurosection, Division of MRI Research, Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Arnold Bakker
- Departments of Psychiatry and Behavioral Sciences
- Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
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16
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Ma Y, Bruce IP, Yeh CH, Petrella JR, Song AW, Truong TK. Column-based cortical depth analysis of the diffusion anisotropy and radiality in submillimeter whole-brain diffusion tensor imaging of the human cortical gray matter in vivo. Neuroimage 2023; 270:119993. [PMID: 36863550 PMCID: PMC10037338 DOI: 10.1016/j.neuroimage.2023.119993] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 02/22/2023] [Accepted: 02/25/2023] [Indexed: 03/04/2023] Open
Abstract
High-resolution diffusion tensor imaging (DTI) can noninvasively probe the microstructure of cortical gray matter in vivo. In this study, 0.9-mm isotropic whole-brain DTI data were acquired in healthy subjects with an efficient multi-band multi-shot echo-planar imaging sequence. A column-based analysis that samples the fractional anisotropy (FA) and radiality index (RI) along radially oriented cortical columns was then performed to quantitatively analyze the FA and RI dependence on the cortical depth, cortical region, cortical curvature, and cortical thickness across the whole brain, which has not been simultaneously and systematically investigated in previous studies. The results showed characteristic FA and RI vs. cortical depth profiles, with an FA local maximum and minimum (or two inflection points) and a single RI maximum at intermediate cortical depths in most cortical regions, except for the postcentral gyrus where no FA peaks and a lower RI were observed. These results were consistent between repeated scans from the same subjects and across different subjects. They were also dependent on the cortical curvature and cortical thickness in that the characteristic FA and RI peaks were more pronounced i) at the banks than at the crown of gyri or at the fundus of sulci and ii) as the cortical thickness increases. This methodology can help characterize variations in microstructure along the cortical depth and across the whole brain in vivo, potentially providing quantitative biomarkers for neurological disorders.
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Affiliation(s)
- Yixin Ma
- Brain Imaging and Analysis Center, Duke University, 40 Duke Medicine Circle, Room 414, Durham, NC 27710, United States; Medical Physics Graduate Program, Duke University, Durham, NC, United States
| | - Iain P Bruce
- Brain Imaging and Analysis Center, Duke University, 40 Duke Medicine Circle, Room 414, Durham, NC 27710, United States; Department of Neurology, Duke University, Durham, NC, United States
| | - Chun-Hung Yeh
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, Taiwan; Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan
| | - Jeffrey R Petrella
- Brain Imaging and Analysis Center, Duke University, 40 Duke Medicine Circle, Room 414, Durham, NC 27710, United States; Medical Physics Graduate Program, Duke University, Durham, NC, United States; Department of Radiology, Duke University, Durham, NC, United States
| | - Allen W Song
- Brain Imaging and Analysis Center, Duke University, 40 Duke Medicine Circle, Room 414, Durham, NC 27710, United States; Medical Physics Graduate Program, Duke University, Durham, NC, United States; Department of Radiology, Duke University, Durham, NC, United States.
| | - Trong-Kha Truong
- Brain Imaging and Analysis Center, Duke University, 40 Duke Medicine Circle, Room 414, Durham, NC 27710, United States; Medical Physics Graduate Program, Duke University, Durham, NC, United States; Department of Radiology, Duke University, Durham, NC, United States.
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17
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Priovoulos N, de Oliveira IAF, Poser BA, Norris DG, van der Zwaag W. Combining arterial blood contrast with BOLD increases fMRI intracortical contrast. Hum Brain Mapp 2023; 44:2509-2522. [PMID: 36763562 PMCID: PMC10028680 DOI: 10.1002/hbm.26227] [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: 12/02/2022] [Revised: 01/20/2023] [Accepted: 01/26/2023] [Indexed: 02/11/2023] Open
Abstract
BOLD fMRI is widely applied in human neuroscience but is limited in its spatial specificity due to a cortical-depth-dependent venous bias. This reduces its localization specificity with respect to neuronal responses, a disadvantage for neuroscientific research. Here, we modified a submillimeter BOLD protocol to selectively reduce venous and tissue signal and increase cerebral blood volume weighting through a pulsed saturation scheme (dubbed Arterial Blood Contrast) at 7 T. Adding Arterial Blood Contrast on top of the existing BOLD contrast modulated the intracortical contrast. Isolating the Arterial Blood Contrast showed a response free of pial-surface bias. The results suggest that Arterial Blood Contrast can modulate the typical fMRI spatial specificity, with important applications in in-vivo neuroscience.
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Affiliation(s)
- Nikos Priovoulos
- Spinoza Center for Neuroimaging, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Icaro Agenor Ferreira de Oliveira
- Spinoza Center for Neuroimaging, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
- Experimental and Applied Psychology, VU University, Amsterdam, The Netherlands
| | - Benedikt A Poser
- MR-Methods Group, Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - David G Norris
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
- Erwin L. Hahn Institute for MRI, University of Duisburg-Essen, Essen, Germany
| | - Wietske van der Zwaag
- Spinoza Center for Neuroimaging, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
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18
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Dowdle LT, Vizioli L, Moeller S, Akçakaya M, Olman C, Ghose G, Yacoub E, Uğurbil K. Evaluating increases in sensitivity from NORDIC for diverse fMRI acquisition strategies. Neuroimage 2023; 270:119949. [PMID: 36804422 DOI: 10.1016/j.neuroimage.2023.119949] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 01/27/2023] [Accepted: 02/15/2023] [Indexed: 02/19/2023] Open
Abstract
As the neuroimaging field moves towards detecting smaller effects at higher spatial resolutions, and faster sampling rates, there is increased attention given to the deleterious contribution of unstructured, thermal noise. Here, we critically evaluate the performance of a recently developed reconstruction method, termed NORDIC, for suppressing thermal noise using datasets acquired with various field strengths, voxel sizes, sampling rates, and task designs. Following minimal preprocessing, statistical activation (t-values) of NORDIC processed data was compared to the results obtained with alternative denoising methods. Additionally, we examined the consistency of the estimates of task responses at the single-voxel, single run level, using a finite impulse response (FIR) model. To examine the potential impact on effective image resolution, the overall smoothness of the data processed with different methods was estimated. Finally, to determine if NORDIC alters or removes temporal information important for modeling responses, we employed an exhaustive leave-p-out cross validation approach, using FIR task responses to predict held out timeseries, quantified using R2. After NORDIC, the t-values are increased, an improvement comparable to what could be achieved by 1.5 voxels smoothing, and task events are clearly visible and have less cross-run error. These advantages are achieved with smoothness estimates increasing by less than 4%, while 1.5 voxel smoothing is associated with increases of over 140%. Cross-validated R2s based on the FIR models show that NORDIC is not measurably distorting the temporal structure of the data under this approach and is the best predictor of non-denoised time courses. The results demonstrate that analyzing 1 run of data after NORDIC produces results equivalent to using 2 to 3 original runs and that NORDIC performs equally well across a diverse array of functional imaging protocols. Significance Statement: For functional neuroimaging, the increasing availability of higher field strengths and ever higher spatiotemporal resolutions has led to concomitant increase in concerns about the deleterious effects of thermal noise. Historically this noise source was suppressed using methods that reduce spatial precision such as image blurring or averaging over a large number of trials or sessions, which necessitates large data collection efforts. Here, we critically evaluate the performance of a recently developed reconstruction method, termed NORDIC, which suppresses thermal noise. Across datasets varying in field strength, voxel sizes, sampling rates, and task designs, NORDIC produces substantial gains in data quality. Both conventional t-statistics derived from general linear models and coefficients of determination for predicting unseen data are improved. These gains match or even exceed those associated with 1 voxel Full Width Half Max image smoothing, however, even such small amounts of smoothing are associated with a 52% reduction in estimates of spatial precision, whereas the measurable difference in spatial precision is less than 4% following NORDIC.
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Affiliation(s)
- Logan T Dowdle
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States; Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States.
| | - Luca Vizioli
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States
| | - Steen Moeller
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States
| | - Mehmet Akçakaya
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States; Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Cheryl Olman
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States; Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | - Geoffrey Ghose
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States; Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States; Department of Psychology, University of Minnesota, Minneapolis, MN, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States
| | - Kâmil Uğurbil
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, 2021 6th Street SE, MN 55455, United States
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19
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Fernandes FF, Olesen JL, Jespersen SN, Shemesh N. MP-PCA denoising of fMRI time-series data can lead to artificial activation "spreading". Neuroimage 2023; 273:120118. [PMID: 37062372 DOI: 10.1016/j.neuroimage.2023.120118] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 04/10/2023] [Accepted: 04/13/2023] [Indexed: 04/18/2023] Open
Abstract
MP-PCA denoising has become the method of choice for denoising MRI data since it provides an objective threshold to separate the signal components from unwanted thermal noise components. In rodents, thermal noise in the coils is an important source of noise that can reduce the accuracy of activation mapping in fMRI. Further confounding this problem, vendor data often contains zero-filling and other post-processing steps that may violate MP-PCA assumptions. Here, we develop an approach to denoise vendor data and assess activation "spreading" caused by MP-PCA denoising in rodent task-based fMRI data. Data was obtained from N = 3 mice using conventional multislice and ultrafast acquisitions (1 s and 50 ms temporal resolution, respectively), during visual stimulation. MP-PCA denoising produced SNR gains of 64% and 39% and Fourier Spectral Amplitude (FSA) increases in BOLD maps of 9% and 7% for multislice and ultrafast data, respectively, when using a small [2 2] denoising window. Larger windows provided higher SNR and FSA gains with increased spatial extent of activation that may or may not represent real activation. Simulations showed that MP-PCA denoising can incur activation "spreading" with increased false positive rate and smoother functional maps due to local "bleeding" of principal components, and that the optimal denoising window for improved specificity of functional mapping, based on Dice score calculations, depends on the data's tSNR and functional CNR. This "spreading" effect applies also to another recently proposed low-rank denoising method (NORDIC), although to a lesser degree. Our results bode well for enhancing spatial and/or temporal resolution in future fMRI work, while taking into account the sensitivity/specificity trade-offs of low-rank denoising methods.
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Affiliation(s)
| | - Jonas L Olesen
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
| | - Sune N Jespersen
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
| | - Noam Shemesh
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal.
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20
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Teves JB, Gonzalez-Castillo J, Holness M, Spurney M, Bandettini PA, Handwerker DA. The art and science of using quality control to understand and improve fMRI data. Front Neurosci 2023; 17:1100544. [PMID: 37090794 PMCID: PMC10117661 DOI: 10.3389/fnins.2023.1100544] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 03/17/2023] [Indexed: 04/08/2023] Open
Abstract
Designing and executing a good quality control (QC) process is vital to robust and reproducible science and is often taught through hands on training. As FMRI research trends toward studies with larger sample sizes and highly automated processing pipelines, the people who analyze data are often distinct from those who collect and preprocess the data. While there are good reasons for this trend, it also means that important information about how data were acquired, and their quality, may be missed by those working at later stages of these workflows. Similarly, an abundance of publicly available datasets, where people (not always correctly) assume others already validated data quality, makes it easier for trainees to advance in the field without learning how to identify problematic data. This manuscript is designed as an introduction for researchers who are already familiar with fMRI, but who did not get hands on QC training or who want to think more deeply about QC. This could be someone who has analyzed fMRI data but is planning to personally acquire data for the first time, or someone who regularly uses openly shared data and wants to learn how to better assess data quality. We describe why good QC processes are important, explain key priorities and steps for fMRI QC, and as part of the FMRI Open QC Project, we demonstrate some of these steps by using AFNI software and AFNI’s QC reports on an openly shared dataset. A good QC process is context dependent and should address whether data have the potential to answer a scientific question, whether any variation in the data has the potential to skew or hide key results, and whether any problems can potentially be addressed through changes in acquisition or data processing. Automated metrics are essential and can often highlight a possible problem, but human interpretation at every stage of a study is vital for understanding causes and potential solutions.
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Affiliation(s)
- Joshua B. Teves
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Javier Gonzalez-Castillo
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Micah Holness
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Megan Spurney
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Peter A. Bandettini
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
- Functional MRI Core Facility, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Daniel A. Handwerker
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
- *Correspondence: Daniel A. Handwerker,
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21
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Schellekens W, Bhogal AA, Roefs ECA, Báez-Yáñez MG, Siero JCW, Petridou N. The many layers of BOLD. The effect of hypercapnic and hyperoxic stimuli on macro- and micro-vascular compartments quantified by CVR, M, and CBV across cortical depth. J Cereb Blood Flow Metab 2023; 43:419-432. [PMID: 36262088 PMCID: PMC9941862 DOI: 10.1177/0271678x221133972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 09/01/2022] [Accepted: 09/05/2022] [Indexed: 11/16/2022]
Abstract
Ultra-high field functional magnetic resonance imaging (fMRI) offers the spatial resolution to measure neuronal activity at the scale of cortical layers. However, cortical depth dependent vascularization differences, such as a higher prevalence of macro-vascular compartments near the pial surface, have a confounding effect on depth-resolved blood-oxygen-level dependent (BOLD) fMRI signals. In the current study, we use hypercapnic and hyperoxic breathing conditions to quantify the influence of all venous vascular and micro-vascular compartments on laminar BOLD fMRI, as measured with gradient-echo (GE) and spin-echo (SE) scan sequences, respectively. We find that all venous vascular and micro-vascular compartments are capable of comparable theoretical maximum signal intensities, as represented by the M-value parameter. However, the capacity for vessel dilation, as reflected by the cerebrovascular reactivity (CVR), is approximately two and a half times larger for all venous vascular compartments combined compared to the micro-vasculature at superficial layers. Finally, there is roughly a 35% difference in estimates of CBV changes between all venous vascular and micro-vascular compartments, although this relative difference was approximately uniform across cortical depth. Thus, our results suggest that fMRI BOLD signal differences across cortical depth are likely caused by differences in dilation properties between macro- and micro-vascular compartments.
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Affiliation(s)
- Wouter Schellekens
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Alex A Bhogal
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Emiel CA Roefs
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Mario G Báez-Yáñez
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
| | - Jeroen CW Siero
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
- Spinoza Centre for Neuroimaging, Amsterdam, The
Netherlands
| | - Natalia Petridou
- Radiology Department, Center for Image Sciences, UMC Utrecht,
Netherlands
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22
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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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23
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Huber L, Kassavetis P, Gulban OF, Hallett M, Horovitz SG. Laminar VASO fMRI in focal hand dystonia patients. DYSTONIA 2023; 2. [PMID: 37035517 PMCID: PMC10081516 DOI: 10.3389/dyst.2023.10806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Focal Hand Dystonia (FHD) is a disabling movement disorder characterized by involuntary movements, cramps and spasms. It is associated with pathological neural microcircuits in the cortical somatosensory system. While invasive preclinical modalities allow researchers to probe specific neural microcircuits of cortical layers and columns, conventional functional magnetic resonance imaging (fMRI) cannot resolve such small neural computational units. In this study, we take advantage of recent developments in ultra-high-field MRI hardware and MR-sequences to capture altered digit representations and laminar processing in FHD patients. We aim to characterize the capability and challenges of layer-specific imaging and analysis tools in resolving laminar and columnar structures in clinical research setups. We scanned N = 4 affected and N = 5 unaffected hemispheres at 7T and found consistent results of altered neural microcircuitry in FHD patients: 1) In affected hemispheres of FHD patients, we found a breakdown of ordered finger representation in the primary somatosensory cortex, as suggested from previous low-resolution fMRI. 2) In affected primary motor cortices of FHD patients, we furthermore found increased fMRI activity in superficial cortico-cortical neural input layers (II/III), compared to relatively weaker activity in the cortico-spinal output layers (Vb/VI). Overall, we show that layer-fMRI acquisition and analysis tools have the potential to address clinically-driven neuroscience research questions about altered computational mechanisms at the spatial scales that were previously only accessible in animal models. We believe that this study paves the way for easier translation of preclinical work into clinical research in focal hand dystonia and beyond.
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Affiliation(s)
- Laurentius Huber
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Panagiotis Kassavetis
- Department of Neurology, University of Utah, Salt Lake City, UT, United States
- Human Motor Control Section, NINDS, NIH, Bethesda, MD, United States
| | - Omer Faruk Gulban
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Brain Innovation, Maastricht, Netherlands
| | - Mark Hallett
- Human Motor Control Section, NINDS, NIH, Bethesda, MD, United States
| | - Silvina G. Horovitz
- Human Motor Control Section, NINDS, NIH, Bethesda, MD, United States
- CORRESPONDENCE Silvina G. Horovitz,
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24
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Pfaffenrot V, Koopmans PJ. Magnetization transfer weighted laminar fMRI with multi-echo FLASH. Neuroimage 2022; 264:119725. [PMID: 36328273 DOI: 10.1016/j.neuroimage.2022.119725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 10/13/2022] [Accepted: 10/30/2022] [Indexed: 11/06/2022] Open
Abstract
Laminar functional magnetic resonance imaging (fMRI) using the gradient echo (GRE) blood oxygenation level dependent (BOLD) contrast is prone to signal changes arising from large unspecific venous vessels. Alternatives based on changes of cerebral blood volume (CBV) become more popular since it is expected that this hemodynamic response is dominant in microvasculature. One approach to sensitize the signal toward changes in CBV, and to simultaneously reduce unwanted extravascular (EV) BOLD blurring, is to selectively reduce gray matter (GM) signal via magnetization transfer (MT). In this work, we use off-resonant MT-pulses with a 3D FLASH readout to perform MT-prepared (MT-prep) laminar fMRI of the primary visual cortex (V1) at multiple echo times at 7 T. With a GRE-BOLD contrast without additional MT-weighting as reference, we investigated the influence of the MT-preparation on the shape and the echo time dependency of laminar profiles. Through numerical simulations, we optimized the sequence parameters to increase the sensitivity toward signal changes induced by changes in arterial CBV and to delineate the contributions of different compartments to the signal. We show that at 7 T, GM signals can be reduced by 30 %. Our laminar fMRI responses exhibit an increased signal change in the parenchyma at very short TE compared to a BOLD-only reference as a result of reduced EV signal intensity. By varying echo times, we could show that MT-prep results in less sensitivity toward unwanted signal changes based on changes in T2*. We conclude that when accounting for nuclear overhauser enhancement effects in blood, off-resonant MT-prep combined with efficient short TE readouts can become a promising method to reduce unwanted EV venous contributions in GRE-BOLD and/or to allow scanning at much shorter echo times without incurring a sensitivity penalty in laminar fMRI.
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Affiliation(s)
- Viktor Pfaffenrot
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, 45141 Essen, Germany; High Field and Hybrid MR Imaging, University Hospital Essen, University of Duisburg-Essen, 45147 Essen, Germany.
| | - Peter J Koopmans
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, 45141 Essen, Germany; High Field and Hybrid MR Imaging, University Hospital Essen, University of Duisburg-Essen, 45147 Essen, Germany; Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, the Netherlands
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25
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Mesoscopic in vivo human T 2* dataset acquired using quantitative MRI at 7 Tesla. Neuroimage 2022; 264:119733. [PMID: 36375782 DOI: 10.1016/j.neuroimage.2022.119733] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 10/15/2022] [Accepted: 11/03/2022] [Indexed: 11/13/2022] Open
Abstract
Mesoscopic (0.1-0.5 mm) interrogation of the living human brain is critical for advancing neuroscience and bridging the resolution gap with animal models. Despite the variety of MRI contrasts measured in recent years at the mesoscopic scale, in vivo quantitative imaging of T2* has not been performed. Here we provide a dataset containing empirical T2* measurements acquired at 0.35 × 0.35 × 0.35 mm3 voxel resolution using 7 Tesla MRI. To demonstrate unique features and high quality of this dataset, we generate flat map visualizations that reveal fine-scale cortical substructures such as layers and vessels, and we report quantitative depth-dependent T2* (as well as R2*) values in primary visual cortex and auditory cortex that are highly consistent across subjects. This dataset is freely available at https://doi.org/10.17605/OSF.IO/N5BJ7, and may prove useful for anatomical investigations of the human brain, as well as for improving our understanding of the basis of the T2*-weighted (f)MRI signal.
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26
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Bok’s equi-volume principle: Translation, historical context, and a modern perspective. BRAIN MULTIPHYSICS 2022. [DOI: 10.1016/j.brain.2022.100057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
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27
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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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28
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Graedel NN, Miller KL, Chiew M. Ultrahigh Resolution fMRI at 7T Using Radial-Cartesian TURBINE Sampling. Magn Reson Med 2022; 88:2058-2073. [PMID: 35785429 PMCID: PMC9546489 DOI: 10.1002/mrm.29359] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 04/21/2022] [Accepted: 05/23/2022] [Indexed: 12/05/2022]
Abstract
Purpose We investigate the use of TURBINE, a 3D radial‐Cartesian acquisition scheme in which EPI planes are rotated about the phase‐encoding axis to acquire a cylindrical k‐space for high‐fidelity ultrahigh isotropic resolution fMRI at 7 Tesla with minimal distortion and blurring. Methods An improved, completely self‐navigated version of the TURBINE sampling scheme was designed for fMRI at 7 Telsa. To demonstrate the image quality and spatial specificity of the acquisition, thin‐slab visual and motor BOLD fMRI at 0.67 mm isotropic resolution (16 mm slab, TRvol = 2.32 s), and 0.8 × 0.8 × 2.0 mm (whole‐brain, TRvol = 2.4 s) data were acquired. To prioritize the high spatial fidelity, we employed a temporally regularized reconstruction to improve sensitivity without any spatial bias. Results TURBINE images provide high structural fidelity with almost no distortion, dropout, or T2* blurring for the thin‐slab acquisitions compared to conventional 3D EPI owing to the radial sampling in‐plane and the short echo train used. This results in activation that can be localized to pre‐ and postcentral gyri in a motor task, for example, with excellent correspondence to brain structure measured by a T1‐MPRAGE. The benefits of TURBINE (low distortion, dropout, blurring) are reduced for the whole‐brain acquisition due to the longer EPI train. We demonstrate robust BOLD activation at 0.67 mm isotropic resolution (thin‐slab) and also anisotropic 0.8 × 0.8 × 2.0 mm (whole‐brain) acquisitions. Conclusion TURBINE is a promising acquisition approach for high‐resolution, minimally distorted fMRI at 7 Tesla and could be particularly useful for fMRI in areas of high B0 inhomogeneity. Click here for author‐reader discussions
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Affiliation(s)
- Nadine N Graedel
- Wellcome Centre for Integrative Neuroscience, FMRIB Centre, University of Oxford, Oxford, United Kingdom.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroscience, FMRIB Centre, University of Oxford, Oxford, United Kingdom
| | - Mark Chiew
- Wellcome Centre for Integrative Neuroscience, FMRIB Centre, University of Oxford, Oxford, United Kingdom
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29
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Zhang J, Sun Z, Duan F, Shi L, Zhang Y, Solé‐Casals J, Caiafa CF. Cerebral cortex layer segmentation using diffusion magnetic resonance imaging in vivo with applications to laminar connections and working memory analysis. Hum Brain Mapp 2022; 43:5220-5234. [PMID: 35778791 PMCID: PMC9812233 DOI: 10.1002/hbm.25998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 06/10/2022] [Accepted: 06/15/2022] [Indexed: 01/15/2023] Open
Abstract
Understanding the laminar brain structure is of great help in further developing our knowledge of the functions of the brain. However, since most layer segmentation methods are invasive, it is difficult to apply them to the human brain in vivo. To systematically explore the human brain's laminar structure noninvasively, the K-means clustering algorithm was used to automatically segment the left hemisphere into two layers, the superficial and deep layers, using a 7 Tesla (T) diffusion magnetic resonance imaging (dMRI)open dataset. The obtained layer thickness was then compared with the layer thickness of the BigBrain reference dataset, which segmented the neocortex into six layers based on the von Economo atlas. The results show a significant correlation not only between our automatically segmented superficial layer thickness and the thickness of layers 1-3 from the reference histological data, but also between our automatically segmented deep layer thickness and the thickness of layers 4-6 from the reference histological data. Second, we constructed the laminar connections between two pairs of unidirectional connected regions, which is consistent with prior research. Finally, we conducted the laminar analysis of the working memory, which was challenging to do in the past, and explained the conclusions of the functional analysis. Our work successfully demonstrates that it is possible to segment the human cortex noninvasively into layers using dMRI data and further explores the mechanisms of the human brain.
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Affiliation(s)
- Jie Zhang
- College of Artificial IntelligenceNankai UniversityTianjinChina
| | - Zhe Sun
- Computational Engineering Applications UnitHead Office for Information Systems and Cybersecurity, RIKENSaitamaJapan
| | - Feng Duan
- College of Artificial IntelligenceNankai UniversityTianjinChina
| | - Liang Shi
- College of Artificial IntelligenceNankai UniversityTianjinChina
| | - Yu Zhang
- Department of Bioengineering and Department of Electrical and Computer EngineeringLehigh UniversityBethlehemPennsylvaniaUSA
| | - Jordi Solé‐Casals
- College of Artificial IntelligenceNankai UniversityTianjinChina,Department of PsychiatryUniversity of CambridgeCambridgeUK,Data and Signal Processing Research GroupUniversity of Vic‐Central University of CataloniaVicCataloniaSpain
| | - Cesar F. Caiafa
- College of Artificial IntelligenceNankai UniversityTianjinChina,Instituto Argentino de Radioastronomía‐ CCT La Plata, CONICET/CIC‐PBA/UNLP, 1894 V.ElisaArgentina
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30
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Pais-Roldán P, Yun SD, Shah NJ. Pre-processing of Sub-millimeter GE-BOLD fMRI Data for Laminar Applications. FRONTIERS IN NEUROIMAGING 2022; 1:869454. [PMID: 37555171 PMCID: PMC10406219 DOI: 10.3389/fnimg.2022.869454] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 03/31/2022] [Indexed: 08/10/2023]
Abstract
Over the past 30 years, brain function has primarily been evaluated non-invasively using functional magnetic resonance imaging (fMRI) with gradient-echo (GE) sequences to measure blood-oxygen-level-dependent (BOLD) signals. Despite the multiple advantages of GE sequences, e.g., higher signal-to-noise ratio, faster acquisitions, etc., their relatively inferior spatial localization compromises the routine use of GE-BOLD in laminar applications. Here, in an attempt to rescue the benefits of GE sequences, we evaluated the effect of existing pre-processing methods on the spatial localization of signals obtained with EPIK, a GE sequence that affords voxel volumes of 0.25 mm3 with near whole-brain coverage. The methods assessed here apply to both task and resting-state fMRI data assuming the availability of reconstructed magnitude and phase images.
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Affiliation(s)
- Patricia Pais-Roldán
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - Seong Dae Yun
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
| | - N. Jon Shah
- Institute of Neuroscience and Medicine 4, Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany
- Institute of Neuroscience and Medicine 11, Molecular Neuroscience and Neuroimaging, Jülich Aachen Research Alliance, Forschungszentrum Jülich, Jülich, Germany
- Jlich Aachen Research Alliance, Brain - Translational Medicine, Aachen, Germany
- Department of Neurology, Rheinisch-Westfälische Technische Hochschule Aachen University, Aachen, Germany
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31
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Cho S, Roy A, Liu CJ, Idiyatullin D, Zhu W, Zhang Y, Zhu XH, O'Herron P, Leikvoll A, Chen W, Kara P, Uğurbil K. Cortical layer-specific differences in stimulus selectivity revealed with high-field fMRI and single-vessel resolution optical imaging of the primary visual cortex. Neuroimage 2022; 251:118978. [PMID: 35143974 PMCID: PMC9048976 DOI: 10.1016/j.neuroimage.2022.118978] [Citation(s) in RCA: 3] [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: 08/05/2021] [Revised: 01/26/2022] [Accepted: 02/05/2022] [Indexed: 11/23/2022] Open
Abstract
The mammalian neocortex exhibits a stereotypical laminar organization, with feedforward inputs arriving primarily into layer 4, local computations shaping response selectivity in layers 2/3, and outputs to other brain areas emanating via layers 2/3, 5 and 6. It cannot be assumed a priori that these signatures of laminar differences in neuronal circuitry are reflected in hemodynamic signals that form the basis of functional magnetic resonance imaging (fMRI). Indeed, optical imaging of single-vessel functional responses has highlighted the potential limits of using vascular signals as surrogates for mapping the selectivity of neural responses. Therefore, before fMRI can be employed as an effective tool for studying critical aspects of laminar processing, validation with single-vessel resolution is needed. The primary visual cortex (V1) in cats, with its precise neuronal functional micro-architecture, offers an ideal model system to examine laminar differences in stimulus selectivity across imaging modalities. Here we used cerebral blood volume weighted (wCBV) fMRI to examine if layer-specific orientation-selective responses could be detected in cat V1. We found orientation preference maps organized tangential to the cortical surface that typically extended across depth in a columnar fashion. We then examined arterial dilation and blood velocity responses to identical visual stimuli by using two- and three- photon optical imaging at single-vessel resolution-which provides a measure of the hemodynamic signals with the highest spatial resolution. Both fMRI and optical imaging revealed a consistent laminar response pattern in which orientation selectivity in cortical layer 4 was significantly lower compared to layer 2/3. This systematic change in selectivity across cortical layers has a clear underpinning in neural circuitry, particularly when comparing layer 4 to other cortical layers.
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Affiliation(s)
- Shinho Cho
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, MN 55455, United States; Department of Radiology, University of Minnesota, MN 55455, United States
| | - Arani Roy
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, MN 55455, United States; Department of Neuroscience, University of Minnesota, MN 55455, United States
| | - Chao J Liu
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, MN 55455, United States; Department of Neuroscience, University of Minnesota, MN 55455, United States
| | - Djaudat Idiyatullin
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, MN 55455, United States; Department of Radiology, University of Minnesota, MN 55455, United States
| | - Wei Zhu
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, MN 55455, United States; Department of Radiology, University of Minnesota, MN 55455, United States
| | - Yi Zhang
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, MN 55455, United States; Department of Radiology, University of Minnesota, MN 55455, United States
| | - Xiao-Hong Zhu
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, MN 55455, United States; Department of Radiology, University of Minnesota, MN 55455, United States
| | - Phillip O'Herron
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC 29425, United States
| | - Austin Leikvoll
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, MN 55455, United States; Department of Neuroscience, University of Minnesota, MN 55455, United States
| | - Wei Chen
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, MN 55455, United States; Department of Radiology, University of Minnesota, MN 55455, United States
| | - Prakash Kara
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, MN 55455, United States; Department of Neuroscience, University of Minnesota, MN 55455, United States; Department of Neuroscience, Medical University of South Carolina, Charleston, SC 29425, United States.
| | - Kâmil Uğurbil
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, MN 55455, United States; Department of Radiology, University of Minnesota, MN 55455, United States.
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32
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Yu Y, Huber L, Yang J, Fukunaga M, Chai Y, Jangraw DC, Chen G, Handwerker DA, Molfese PJ, Ejima Y, Sadato N, Wu J, Bandettini PA. Layer-specific activation in human primary somatosensory cortex during tactile temporal prediction error processing. Neuroimage 2021; 248:118867. [PMID: 34974114 DOI: 10.1016/j.neuroimage.2021.118867] [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: 07/21/2021] [Revised: 12/27/2021] [Accepted: 12/29/2021] [Indexed: 10/19/2022] Open
Abstract
The human brain continuously generates predictions of incoming sensory input and calculates corresponding prediction errors from the perceived inputs to update internal predictions. In human primary somatosensory cortex (area 3b), different cortical layers are involved in receiving the sensory input and generation of error signals. It remains unknown, however, how the layers in the human area 3b contribute to the temporal prediction error processing. To investigate prediction error representation in the area 3b across layers, we acquired layer-specific functional magnetic resonance imaging (fMRI) data at 7T from human area 3b during a task of index finger poking with no-delay, short-delay and long-delay touching sequences. We demonstrate that all three tasks increased activity in both superficial and deep layers of area 3b compared to the random sensory input. The fMRI signal was differentially modulated solely in the deep layers rather than the superficial layers of area 3b by the delay time. Compared with the no-delay stimuli, activity was greater in the deep layers of area 3b during the short-delay stimuli but lower during the long-delay stimuli. This difference activity features in the superficial and deep layers suggest distinct functional contributions of area 3b layers to tactile temporal prediction error processing. The functional segregation in area 3b across layers may reflect that the excitatory and inhibitory interplay in the sensory cortex contributions to flexible communication between cortical layers or between cortical areas.
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Affiliation(s)
- Yinghua Yu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama 700-8530, Japan; Section on Functional Imaging Methods, National Institute of Mental Health, Building 10, 10 Center Dr Bethesda, MD 20892, USA.
| | - Laurentius Huber
- MR-Methods Group, MBIC, Cognitive Neuroscience Department, Faculty of Psychology and Neuroscience, University of Maastricht, Cognitive Neuroscience, Room 1.014, Oxfordlaan 55, 6229 EV Maastricht, The Netherlands
| | - Jiajia Yang
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama 700-8530, Japan; Section on Functional Imaging Methods, National Institute of Mental Health, Building 10, 10 Center Dr Bethesda, MD 20892, USA
| | - Masaki Fukunaga
- Division of Cerebral Research, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi, 444-8585 Japan
| | - Yuhui Chai
- Section on Functional Imaging Methods, National Institute of Mental Health, Building 10, 10 Center Dr Bethesda, MD 20892, USA
| | - David C Jangraw
- Section on Functional Imaging Methods, National Institute of Mental Health, Building 10, 10 Center Dr Bethesda, MD 20892, USA
| | - Gang Chen
- Scientific and Statistical Computational Core, National Institute of Mental Health, Building 10, 10 Center Dr Bethesda, MD 20892, USA
| | - Daniel A Handwerker
- Section on Functional Imaging Methods, National Institute of Mental Health, Building 10, 10 Center Dr Bethesda, MD 20892, USA
| | - Peter J Molfese
- Section on Functional Imaging Methods, National Institute of Mental Health, Building 10, 10 Center Dr Bethesda, MD 20892, USA
| | - Yoshimichi Ejima
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama 700-8530, Japan
| | - Norihiro Sadato
- Division of Cerebral Research, National Institute for Physiological Sciences, 38 Nishigonaka, Myodaiji, Okazaki, Aichi, 444-8585 Japan
| | - Jinglong Wu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama 700-8530, Japan; Beijing Institute of Technology, 5 South Zhongguancun Street, Hiadian District, Beijing 100081, China
| | - Peter A Bandettini
- Section on Functional Imaging Methods, National Institute of Mental Health, Building 10, 10 Center Dr Bethesda, MD 20892, USA; Functional MRI Core Facility, National Institute of Mental Health, Building 10, 10 Center Dr Bethesda, MD 20892, USA
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33
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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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34
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Chai Y, Li L, Wang Y, Huber L, Poser BA, Duyn J, Bandettini PA. Magnetization transfer weighted EPI facilitates cortical depth determination in native fMRI space. Neuroimage 2021; 242:118455. [PMID: 34364993 PMCID: PMC8520138 DOI: 10.1016/j.neuroimage.2021.118455] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 07/23/2021] [Accepted: 08/03/2021] [Indexed: 11/25/2022] Open
Abstract
The increased availability of ultra-high field scanners provides an opportunity to perform fMRI at sub-millimeter spatial scales and enables in vivo probing of laminar function in the human brain. In most previous studies, the definition of cortical layers, or depths, is based on an anatomical reference image that is collected by a different acquisition sequence and exhibits different geometric distortion compared to the functional images. Here, we propose to generate the anatomical image with the fMRI acquisition technique by incorporating magnetization transfer (MT) weighted imaging. Small flip angle binomial pulse trains are used as MT preparation, with a flexible duration (several to tens of milliseconds), which can be applied before each EPI segment without constraining the acquisition length (segment or slice number). The method's feasibility was demonstrated at 7T for coverage of either a small slab or the near-whole brain at 0.8 mm isotropic resolution. Tissue contrast was found to be similar to that obtained with a state-of-art anatomical reference based on MP2RAGE. This MT-weighted EPI image allows an automatic reconstruction of the cortical surface to support laminar analysis in native fMRI space, obviating the need for distortion correction and registration.
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Affiliation(s)
- Yuhui Chai
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, NIMH, NIH, Bethesda 20892, MD, United States.
| | - Linqing Li
- Functional MRI Core, NIMH, NIH, Bethesda, MD, United States
| | - Yicun Wang
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States
| | - Laurentius Huber
- Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, University of Maastricht, the Netherlands
| | - Benedikt A Poser
- Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, University of Maastricht, the Netherlands
| | - Jeff Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States
| | - Peter A Bandettini
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, NIMH, NIH, Bethesda 20892, MD, United States; Functional MRI Core, NIMH, NIH, Bethesda, MD, United States
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35
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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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36
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Chai Y, Liu TT, Marrett S, Li L, Khojandi A, Handwerker DA, Alink A, Muckli L, Bandettini PA. Topographical and laminar distribution of audiovisual processing within human planum temporale. Prog Neurobiol 2021; 205:102121. [PMID: 34273456 DOI: 10.1016/j.pneurobio.2021.102121] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 05/20/2021] [Accepted: 07/13/2021] [Indexed: 10/20/2022]
Abstract
The brain is capable of integrating signals from multiple sensory modalities. Such multisensory integration can occur in areas that are commonly considered unisensory, such as planum temporale (PT) representing the auditory association cortex. However, the roles of different afferents (feedforward vs. feedback) to PT in multisensory processing are not well understood. Our study aims to understand that by examining laminar activity patterns in different topographical subfields of human PT under unimodal and multisensory stimuli. To this end, we adopted an advanced mesoscopic (sub-millimeter) fMRI methodology at 7 T by acquiring BOLD (blood-oxygen-level-dependent contrast, which has higher sensitivity) and VAPER (integrated blood volume and perfusion contrast, which has superior laminar specificity) signal concurrently, and performed all analyses in native fMRI space benefiting from an identical acquisition between functional and anatomical images. We found a division of function between visual and auditory processing in PT and distinct feedback mechanisms in different subareas. Specifically, anterior PT was activated more by auditory inputs and received feedback modulation in superficial layers. This feedback depended on task performance and likely arose from top-down influences from higher-order multimodal areas. In contrast, posterior PT was preferentially activated by visual inputs and received visual feedback in both superficial and deep layers, which is likely projected directly from the early visual cortex. Together, these findings provide novel insights into the mechanism of multisensory interaction in human PT at the mesoscopic spatial scale.
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Affiliation(s)
- Yuhui Chai
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
| | - Tina T Liu
- Section on Neurocircuitry, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Sean Marrett
- Functional MRI Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Linqing Li
- Functional MRI Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Arman Khojandi
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Daniel A Handwerker
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Arjen Alink
- University Medical Centre Hamburg-Eppendorf, Department of Systems Neuroscience, Hamburg, Germany
| | - Lars Muckli
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Peter A Bandettini
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA; Functional MRI Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
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37
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Oliveira ÍAF, Roos T, Dumoulin SO, Siero JCW, van der Zwaag W. Can 7T MPRAGE match MP2RAGE for gray-white matter contrast? Neuroimage 2021; 240:118384. [PMID: 34265419 DOI: 10.1016/j.neuroimage.2021.118384] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 06/25/2021] [Accepted: 07/08/2021] [Indexed: 10/20/2022] Open
Abstract
Ultra-High Field (UHF) MRI provides a significant increase in Signal-to-Noise Ratio (SNR) and gains in contrast weighting in several functional and structural acquisitions. Unfortunately, an increase in field strength also induces non-uniformities in the transmit field (B1+) that can compromise image contrast non-uniformly. The MPRAGE is one of the most common T1 weighted (T1w) image acquisitions for structural imaging. It provides excellent contrast between gray and white matter and is widely used for brain segmentation. At 7T, the signal non-uniformities tend to complicate this and therefore, the self-bias-field corrected MP2RAGE is often used there. In both MPRAGE and MP2RAGE, more homogeneous image contrast can be achieved with adiabatic pulses, like the TR-FOCI inversion pulse, or special pulse design on parallel transmission systems, like Universal Pulses (UP). In the present study, we investigate different strategies to improve the bias-field for MPRAGE at 7T, comparing the contrast and GM/WM segmentability against MP2RAGE. The higher temporal efficiency of MPRAGE combined with the potential of the user-friendly UPs was the primary motivation for this MPRAGE-MP2RAGE comparison. We acquired MPRAGE data in six volunteers, adding a k-space shutter to reduce scan time, a kt-point UP approach for homogeneous signal excitation, and a TR-FOCI pulse for homogeneous inversion. Our results show remarkable signal contrast improvement throughout the brain, including regions of low B1+ such as the cerebellum. The improvements in the MPRAGE were largest following the introduction of the UPs. In addition to the CNR, both SNR and GM/WM segmentability were also assessed. Among the MPRAGEs, the combined strategy (UP + TR-FOCI) yielded highest SNR and showed highest spatial similarity between GM segments to the MP2RAGE. Interestingly, the distance between gray and white matter peaks in the intensity histograms did not increase, as better pulses and higher SNR especially benefitted the (cerebellar) gray matter. Overall, the gray-white matter contrast from MP2RAGE is higher, with higher CNR and higher intensity peak distances, even when scaled to scan time. Hence, the extra acquisition time for MP2RAGE is justified by the improved segmentability.
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Affiliation(s)
- Ícaro A F Oliveira
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands; Experimental and Applied Psychology, VU University, Amsterdam, the Netherlands.
| | - Thomas Roos
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands
| | - Serge O Dumoulin
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands; Experimental and Applied Psychology, VU University, Amsterdam, the Netherlands; Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, the Netherlands
| | - Jeroen C W Siero
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands; Radiology, Utrecht Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
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38
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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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Huber LR, Poser BA, Kaas AL, Fear EJ, Dresbach S, Berwick J, Goebel R, Turner R, Kennerley AJ. Validating layer-specific VASO across species. Neuroimage 2021; 237:118195. [PMID: 34038769 DOI: 10.1016/j.neuroimage.2021.118195] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 05/17/2021] [Accepted: 05/19/2021] [Indexed: 01/27/2023] Open
Abstract
Cerebral blood volume (CBV) has been shown to be a robust and important physiological parameter for quantitative interpretation of functional (f)MRI, capable of delivering highly localized mapping of neural activity. Indeed, with recent advances in ultra-high-field (≥7T) MRI hardware and associated sequence libraries, it has become possible to capture non-invasive CBV weighted fMRI signals across cortical layers. One of the most widely used approaches to achieve this (in humans) is through vascular-space-occupancy (VASO) fMRI. Unfortunately, the exact contrast mechanisms of layer-dependent VASO fMRI have not been validated for human fMRI and thus interpretation of such data is confounded. Here we validate the signal source of layer-dependent SS-SI VASO fMRI using multi-modal imaging in a rat model in response to neuronal activation (somatosensory cortex) and respiratory challenge (hypercapnia). In particular VASO derived CBV measures are directly compared to concurrent measures of total haemoglobin changes from high resolution intrinsic optical imaging spectroscopy (OIS). Quantified cortical layer profiling is demonstrated to be in agreement between VASO and contrast enhanced fMRI (using monocrystalline iron oxide nanoparticles, MION). Responses show high spatial localisation to layers of cortical processing independent of confounding large draining veins which can hamper BOLD fMRI studies, (depending on slice positioning). Thus, a cross species comparison is enabled using VASO as a common measure. We find increased VASO based CBV reactivity (3.1 ± 1.2 fold increase) in humans compared to rats. Together, our findings confirm that the VASO contrast is indeed a reliable estimate of layer-specific CBV changes. This validation study increases the neuronal interpretability of human layer-dependent VASO fMRI as an appropriate method in neuroscience application studies, in which the presence of large draining intracortical and pial veins limits neuroscientific inference with BOLD fMRI.
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Affiliation(s)
- Laurentius Renzo Huber
- MBIC, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands.
| | - Benedikt A Poser
- MBIC, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Amanda L Kaas
- MBIC, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Elizabeth J Fear
- Hull-York-Medical-School (HYMS), University of York, York, United Kingdom
| | - Sebastian Dresbach
- MBIC, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Jason Berwick
- Department of Psychology, University of Sheffield, Sheffield, United Kingdom
| | - Rainer Goebel
- MBIC, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Robert Turner
- Neurophysics Department Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
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