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Duan Y, Zhan J, Gross J, Ince RAA, Schyns PG. Pre-frontal cortex guides dimension-reducing transformations in the occipito-ventral pathway for categorization behaviors. Curr Biol 2024; 34:3392-3404.e5. [PMID: 39029470 DOI: 10.1016/j.cub.2024.06.050] [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: 02/14/2024] [Revised: 05/10/2024] [Accepted: 06/20/2024] [Indexed: 07/21/2024]
Abstract
To interpret our surroundings, the brain uses a visual categorization process. Current theories and models suggest that this process comprises a hierarchy of different computations that transforms complex, high-dimensional inputs into lower-dimensional representations (i.e., manifolds) in support of multiple categorization behaviors. Here, we tested this hypothesis by analyzing these transformations reflected in dynamic MEG source activity while individual participants actively categorized the same stimuli according to different tasks: face expression, face gender, pedestrian gender, and vehicle type. Results reveal three transformation stages guided by the pre-frontal cortex. At stage 1 (high-dimensional, 50-120 ms), occipital sources represent both task-relevant and task-irrelevant stimulus features; task-relevant features advance into higher ventral/dorsal regions, whereas task-irrelevant features halt at the occipital-temporal junction. At stage 2 (121-150 ms), stimulus feature representations reduce to lower-dimensional manifolds, which then transform into the task-relevant features underlying categorization behavior over stage 3 (161-350 ms). Our findings shed light on how the brain's network mechanisms transform high-dimensional inputs into specific feature manifolds that support multiple categorization behaviors.
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Affiliation(s)
- Yaocong Duan
- School of Psychology and Neuroscience, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK
| | - Jiayu Zhan
- School of Psychology and Neuroscience, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK
| | - Joachim Gross
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Malmedyweg 15, Münster 48149, Germany
| | - Robin A A Ince
- School of Psychology and Neuroscience, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK
| | - Philippe G Schyns
- School of Psychology and Neuroscience, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK.
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2
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Miyashita Y. Cortical Layer-Dependent Signaling in Cognition: Three Computational Modes of the Canonical Circuit. Annu Rev Neurosci 2024; 47:211-234. [PMID: 39115926 DOI: 10.1146/annurev-neuro-081623-091311] [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] [Indexed: 08/10/2024]
Abstract
The cerebral cortex performs computations via numerous six-layer modules. The operational dynamics of these modules were studied primarily in early sensory cortices using bottom-up computation for response selectivity as a model, which has been recently revolutionized by genetic approaches in mice. However, cognitive processes such as recall and imagery require top-down generative computation. The question of whether the layered module operates similarly in top-down generative processing as in bottom-up sensory processing has become testable by advances in the layer identification of recorded neurons in behaving monkeys. This review examines recent advances in laminar signaling in these two computations, using predictive coding computation as a common reference, and shows that each of these computations recruits distinct laminar circuits, particularly in layer 5, depending on the cognitive demands. These findings highlight many open questions, including how different interareal feedback pathways, originating from and terminating at different layers, convey distinct functional signals.
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Affiliation(s)
- Yasushi Miyashita
- Department of Physiology, The University of Tokyo School of Medicine, Tokyo, Japan;
- Juntendo University Graduate School of Medicine, Tokyo, Japan
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3
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Herthum H, Hetzer S. Tensor denoising of quantitative multi-parameter mapping. Magn Reson Med 2024; 92:145-157. [PMID: 38368616 DOI: 10.1002/mrm.30050] [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: 10/13/2023] [Revised: 01/12/2024] [Accepted: 01/25/2024] [Indexed: 02/20/2024]
Abstract
PURPOSE Quantitative multi-parameter mapping (MPM) provides maps of physical quantities representing physiologically meaningful tissue characteristics, which allows to investigate microstructure-function relationships reflecting normal or pathologic processes in the brain. However, the achievable spatial resolution and stability of MPM for basic research or clinical applications is severely constrained by SNR limits of the MR acquisition process, resulting in relatively long acquisition times. To increase SNR, we denoise MPM acquisitions using principal component analysis along tensors exploiting the Marchenko-Pastur law (tMPPCA). METHODS tMPPCA denoising was applied to three sets of MPM raw data before the quantification of maps of proton density, magnetization transfer saturation, R1, and R2*. The regional SNR gain for high-resolution MPM was investigated as well as reproducibility gains for clinically optimized protocols with moderate and high acceleration factors at different image resolutions. RESULTS Substantial noise reduction in raw data was achieved, resulting in reduced noise for quantitative mapping up to sixfold without introducing bias of mean values (below 1%). Scan-rescan fluctuations were reduced up to threefold. Denoising allowed to decrease the voxel volume fourfold at the same scan time or reduce the scan time twofold at same voxel volume without loss of sensitivity. CONCLUSIONS tMPPCA denoising can (a) improve of fine spatial and temporal patterns, (b) considerably reduce scan time for clinical applications, or (c) increase resolution to potentially push cutting-edge MPM protocols from the upper to the lower limit of the mesoscopic scale.
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Affiliation(s)
- Helge Herthum
- Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
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4
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Waks M, Lagore RL, Auerbach E, Grant A, Sadeghi-Tarakameh A, DelaBarre L, Jungst S, Tavaf N, Lattanzi R, Giannakopoulos I, Moeller S, Wu X, Yacoub E, Vizioli L, Schmidt S, Metzger GJ, Eryaman Y, Adriany G, Uğurbil K. RF coil design strategies for improving SNR at the ultrahigh magnetic field of 10.5 Tesla. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.23.595628. [PMID: 38826245 PMCID: PMC11142186 DOI: 10.1101/2024.05.23.595628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Purpose To develop multichannel transmit and receive arrays towards capturing the ultimate-intrinsic-SNR (uiSNR) at 10.5 Tesla (T) and to demonstrate the feasibility and potential of whole-brain, high-resolution human brain imaging at this high field strength. Methods A dual row 16-channel self-decoupled transmit (Tx) array was converted to a 16Tx/Rx transceiver using custom transmit/receive switches. A 64-channel receive-only (64Rx) array was built to fit into the 16Tx/Rx array. Electromagnetic modeling and experiments were employed to define safe operation limits of the resulting 16Tx/80Rx array and obtain FDA approval for human use. Results The 64Rx array alone captured approximately 50% of the central uiSNR at 10.5T while the identical 7T 64Rx array captured ∼76% of uiSNR at this lower field strength. The 16Tx/80Rx configuration brought the fraction of uiSNR captured at 10.5T to levels comparable to the performance of the 64Rx array at 7T. SNR data obtained at the two field strengths with these arrays displayed dependent increases over a large central region. Whole-brain high resolution T 2 * and T 1 weighted anatomical and gradient-recalled echo EPI BOLD fMRI images were obtained at 10.5T for the first time with such an advanced array, illustrating the promise of >10T fields in studying the human brain. Conclusion We demonstrated the ability to approach the uiSNR at 10.5T over the human brain with a novel, high channel count array, achieving large SNR gains over 7T, currently the most commonly employed ultrahigh field platform, and demonstrate high resolution and high contrast anatomical and functional imaging at 10.5T.
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5
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Petersen SE, Seitzman BA, Nelson SM, Wig GS, Gordon EM. Principles of cortical areas and their implications for neuroimaging. Neuron 2024:S0896-6273(24)00355-6. [PMID: 38834069 DOI: 10.1016/j.neuron.2024.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 04/11/2024] [Accepted: 05/08/2024] [Indexed: 06/06/2024]
Abstract
Cortical organization should constrain the study of how the brain performs behavior and cognition. A fundamental concept in cortical organization is that of arealization: that the cortex is parceled into discrete areas. In part one of this report, we review how non-human animal studies have illuminated principles of cortical arealization by revealing: (1) what defines a cortical area, (2) how cortical areas are formed, (3) how cortical areas interact with one another, and (4) what "computations" or "functions" areas perform. In part two, we discuss how these principles apply to neuroimaging research. In doing so, we highlight several examples where the commonly accepted interpretation of neuroimaging observations requires assumptions that violate the principles of arealization, including nonstationary areas that move on short time scales, large-scale gradients as organizing features, and cortical areas with singular functionality that perfectly map psychological constructs. Our belief is that principles of neurobiology should strongly guide the nature of computational explanations.
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Affiliation(s)
- Steven E Petersen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA; Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Benjamin A Seitzman
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Steven M Nelson
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN 55455, USA; Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55455, USA
| | - Gagan S Wig
- Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX 75235, USA; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Evan M Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA.
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6
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Zhao F, Lv K, Ye S, Chen X, Chen H, Fan S, Mao N, Ren Y. Integration of temporal & spatial properties of dynamic functional connectivity based on two-directional two-dimensional principal component analysis for disease analysis. PeerJ 2024; 12:e17078. [PMID: 38618569 PMCID: PMC11011592 DOI: 10.7717/peerj.17078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 02/19/2024] [Indexed: 04/16/2024] Open
Abstract
Dynamic functional connectivity, derived from resting-state functional magnetic resonance imaging (rs-fMRI), has emerged as a crucial instrument for investigating and supporting the diagnosis of neurological disorders. However, prevalent features of dynamic functional connectivity predominantly capture either temporal or spatial properties, such as mean and global efficiency, neglecting the significant information embedded in the fusion of spatial and temporal attributes. In addition, dynamic functional connectivity suffers from the problem of temporal mismatch, i.e., the functional connectivity of different subjects at the same time point cannot be matched. To address these problems, this article introduces a novel feature extraction framework grounded in two-directional two-dimensional principal component analysis. This framework is designed to extract features that integrate both spatial and temporal properties of dynamic functional connectivity. Additionally, we propose to use Fourier transform to extract temporal-invariance properties contained in dynamic functional connectivity. Experimental findings underscore the superior performance of features extracted by this framework in classification experiments compared to features capturing individual properties.
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Affiliation(s)
- Feng Zhao
- School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China
| | - Ke Lv
- School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China
| | - Shixin Ye
- School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China
| | - Xiaobo Chen
- School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China
| | - Hongyu Chen
- School Hospital, Shandong Technology and Business University, Yantai, China
| | - Sizhe Fan
- Canada Qingdao Secondary School (CQSS), Qingdao, China
| | - Ning Mao
- Department of Radiology, Yantai Yuhuangding Hospital, Yantai, China
| | - Yande Ren
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
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7
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Yun SD, Küppers F, Shah NJ. Submillimeter fMRI Acquisition Techniques for Detection of Laminar and Columnar Level Brain Activation. J Magn Reson Imaging 2024; 59:747-766. [PMID: 37589385 DOI: 10.1002/jmri.28911] [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: 01/27/2023] [Revised: 07/07/2023] [Accepted: 07/07/2023] [Indexed: 08/18/2023] Open
Abstract
Since the first demonstration in the early 1990s, functional MRI (fMRI) has emerged as one of the most powerful, noninvasive neuroimaging tools to probe brain functions. Subsequently, fMRI techniques have advanced remarkably, enabling the acquisition of functional signals with a submillimeter voxel size. This innovation has opened the possibility of investigating subcortical neural activities with respect to the cortical depths or cortical columns. For this purpose, numerous previous works have endeavored to design suitable functional contrast mechanisms and dedicated imaging techniques. Depending on the choice of the functional contrast, functional signals can be detected with high sensitivity or with improved spatial specificity to the actual activation site, and the pertaining issues have been discussed in a number of earlier works. This review paper primarily aims to provide an overview of the subcortical fMRI techniques that allow the acquisition of functional signals with a submillimeter resolution. Here, the advantages and disadvantages of the imaging techniques will be described and compared. We also summarize supplementary imaging techniques that assist in the analysis of the subcortical brain activation for more accurate mapping with reduced geometric deformation. This review suggests that there is no single universally accepted method as the gold standard for subcortical fMRI. Instead, the functional contrast and the corresponding readout imaging technique should be carefully determined depending on the purpose of the study. Due to the technical limitations of current fMRI techniques, most subcortical fMRI studies have only targeted partial brain regions. As a future prospect, the spatiotemporal resolution of fMRI will be pushed to satisfy the community's need for a deeper understanding of whole-brain functions and the underlying connectivity in order to achieve the ultimate goal of a time-resolved and layer-specific spatial scale. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Seong Dae Yun
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany
| | - Fabian Küppers
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany
- RWTH Aachen University, Aachen, Germany
- Institute of Neuroscience and Medicine 11, INM-11, JARA, Forschungszentrum Jülich, Jülich, Germany
| | - N Jon Shah
- Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum Jülich, Jülich, Germany
- Institute of Neuroscience and Medicine 11, INM-11, JARA, Forschungszentrum Jülich, Jülich, Germany
- JARA - BRAIN - Translational Medicine, Aachen, Germany
- Department of Neurology, RWTH Aachen University, Aachen, Germany
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8
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Papo D, Buldú JM. Does the brain behave like a (complex) network? I. Dynamics. Phys Life Rev 2024; 48:47-98. [PMID: 38145591 DOI: 10.1016/j.plrev.2023.12.006] [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: 12/08/2023] [Accepted: 12/10/2023] [Indexed: 12/27/2023]
Abstract
Graph theory is now becoming a standard tool in system-level neuroscience. However, endowing observed brain anatomy and dynamics with a complex network structure does not entail that the brain actually works as a network. Asking whether the brain behaves as a network means asking whether network properties count. From the viewpoint of neurophysiology and, possibly, of brain physics, the most substantial issues a network structure may be instrumental in addressing relate to the influence of network properties on brain dynamics and to whether these properties ultimately explain some aspects of brain function. Here, we address the dynamical implications of complex network, examining which aspects and scales of brain activity may be understood to genuinely behave as a network. To do so, we first define the meaning of networkness, and analyse some of its implications. We then examine ways in which brain anatomy and dynamics can be endowed with a network structure and discuss possible ways in which network structure may be shown to represent a genuine organisational principle of brain activity, rather than just a convenient description of its anatomy and dynamics.
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Affiliation(s)
- D Papo
- Department of Neuroscience and Rehabilitation, Section of Physiology, University of Ferrara, Ferrara, Italy; Center for Translational Neurophysiology, Fondazione Istituto Italiano di Tecnologia, Ferrara, Italy.
| | - J M Buldú
- Complex Systems Group & G.I.S.C., Universidad Rey Juan Carlos, Madrid, Spain
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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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Yan Y, Zhan J, Garrod O, Cui X, Ince RAA, Schyns PG. Strength of predicted information content in the brain biases decision behavior. Curr Biol 2023; 33:5505-5514.e6. [PMID: 38065096 DOI: 10.1016/j.cub.2023.10.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 10/11/2023] [Accepted: 10/23/2023] [Indexed: 12/21/2023]
Abstract
Prediction-for-perception theories suggest that the brain predicts incoming stimuli to facilitate their categorization.1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17 However, it remains unknown what the information contents of these predictions are, which hinders mechanistic explanations. This is because typical approaches cast predictions as an underconstrained contrast between two categories18,19,20,21,22,23,24-e.g., faces versus cars, which could lead to predictions of features specific to faces or cars, or features from both categories. Here, to pinpoint the information contents of predictions and thus their mechanistic processing in the brain, we identified the features that enable two different categorical perceptions of the same stimuli. We then trained multivariate classifiers to discern, from dynamic MEG brain responses, the features tied to each perception. With an auditory cueing design, we reveal where, when, and how the brain reactivates visual category features (versus the typical category contrast) before the stimulus is shown. We demonstrate that the predictions of category features have a more direct influence (bias) on subsequent decision behavior in participants than the typical category contrast. Specifically, these predictions are more precisely localized in the brain (lateralized), are more specifically driven by the auditory cues, and their reactivation strength before a stimulus presentation exerts a greater bias on how the individual participant later categorizes this stimulus. By characterizing the specific information contents that the brain predicts and then processes, our findings provide new insights into the brain's mechanisms of prediction for perception.
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Affiliation(s)
- Yuening Yan
- School of Psychology and Neuroscience, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK
| | - Jiayu Zhan
- School of Psychological and Cognitive Sciences, Peking University, 5 Yiheyuan Road, Beijing 100871, China
| | - Oliver Garrod
- School of Psychology and Neuroscience, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK
| | - Xuan Cui
- School of Psychology and Neuroscience, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK
| | - Robin A A Ince
- School of Psychology and Neuroscience, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK
| | - Philippe G Schyns
- School of Psychology and Neuroscience, University of Glasgow, 62 Hillhead Street, Glasgow G12 8QB, UK.
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11
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Feinberg DA, Beckett AJS, Vu AT, Stockmann J, Huber L, Ma S, Ahn S, Setsompop K, Cao X, Park S, Liu C, Wald LL, Polimeni JR, Mareyam A, Gruber B, Stirnberg R, Liao C, Yacoub E, Davids M, Bell P, Rummert E, Koehler M, Potthast A, Gonzalez-Insua I, Stocker S, Gunamony S, Dietz P. Next-generation MRI scanner designed for ultra-high-resolution human brain imaging at 7 Tesla. Nat Methods 2023; 20:2048-2057. [PMID: 38012321 PMCID: PMC10703687 DOI: 10.1038/s41592-023-02068-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 10/09/2023] [Indexed: 11/29/2023]
Abstract
To increase granularity in human neuroimaging science, we designed and built a next-generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200 mT m-1, 900 T m-1s-1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35-0.45 mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.
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Affiliation(s)
- David A Feinberg
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
- Advanced MRI Technologies, Sebastopol, CA, USA.
| | - Alexander J S Beckett
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Advanced MRI Technologies, Sebastopol, CA, USA
| | - An T Vu
- Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
- San Francisco Veteran Affairs Health Care System, San Francisco, CA, USA
| | - Jason Stockmann
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Laurentius Huber
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | | | | | - Kawin Setsompop
- Radiological Sciences Laboratory, Stanford University, Stanford, CA, USA
| | - Xiaozhi Cao
- Radiological Sciences Laboratory, Stanford University, Stanford, CA, USA
| | - Suhyung Park
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Department of Computer Engineering, Chonnam National University, Gwangju, Republic of Korea
- Department of ICT Convergence System Engineering, Chonnam National University, Gwangju, Republic of Korea
| | - Chunlei Liu
- Erwin Hahn 7T MRI Laboratory, Henry H. Wheeler Brain Imaging Center, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Lawrence L Wald
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Jonathan R Polimeni
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Azma Mareyam
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Bernhard Gruber
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
- BARNLabs, Muenzkirchen, Austria
| | | | - Congyu Liao
- Radiological Sciences Laboratory, Stanford University, Stanford, CA, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Mathias Davids
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Paul Bell
- Siemens Medical Solutions, Malvern, PA, USA
| | | | | | | | | | | | - Shajan Gunamony
- Imaging Centre of Excellence, University of Glasgow, Glasgow, UK
- MR CoilTech Limited, Glasgow, UK
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12
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Heij J, Raimondo L, Siero JCW, Dumoulin SO, van der Zwaag W, Knapen T. A selection and targeting framework of cortical locations for line-scanning fMRI. Hum Brain Mapp 2023; 44:5471-5484. [PMID: 37608563 PMCID: PMC10543358 DOI: 10.1002/hbm.26459] [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: 04/19/2023] [Revised: 07/15/2023] [Accepted: 08/02/2023] [Indexed: 08/24/2023] Open
Abstract
Depth-resolved functional magnetic resonance imaging (fMRI) is an emerging field growing in popularity given the potential of separating signals from different computational processes in cerebral cortex. Conventional acquisition schemes suffer from low spatial and temporal resolutions. Line-scanning methods allow depth-resolved fMRI by sacrificing spatial coverage to sample blood oxygenated level-dependent (BOLD) responses at ultra-high temporal and spatial resolution. For neuroscience applications, it is critical to be able to place the line accurately to (1) sample the right neural population and (2) target that neural population with tailored stimuli or tasks. To this end, we devised a multi-session framework where a target cortical location is selected based on anatomical and functional properties. The line is then positioned according to this information in a separate second session, and we tailor the experiment to focus on the target location. Anatomically, the precision of the line placement was confirmed by projecting a nominal representation of the acquired line back onto the surface. Functional estimates of neural selectivities in the line, as quantified by a visual population-receptive field model, resembled the target selectivities well for most subjects. This functional precision was quantified in detail by estimating the distance between the visual field location of the targeted vertex and the location in visual cortex (V1) that most closely resembled the line-scanning estimates; this distance was on average ~5.5 mm. Given the dimensions of the line, differences in acquisition, session, and stimulus design, this validates that line-scanning can be used to probe local neural sensitivities across sessions. In summary, we present an accurate framework for line-scanning MRI; we believe such a framework is required to harness the full potential of line-scanning and maximize its utility. Furthermore, this approach bridges canonical fMRI experiments with electrophysiological experiments, which in turn allows novel avenues for studying human physiology non-invasively.
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Affiliation(s)
- Jurjen Heij
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Experimental and Applied PsychologyVU UniversityAmsterdamNetherlands
| | - Luisa Raimondo
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Experimental and Applied PsychologyVU UniversityAmsterdamNetherlands
| | - Jeroen C. W. Siero
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of RadiologyUniversity Medical Center UtrechtUtrechtthe Netherlands
| | - Serge O. Dumoulin
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Experimental and Applied PsychologyVU UniversityAmsterdamNetherlands
- Department of Experimental PsychologyUtrecht UniversityUtrechtNetherlands
| | - Wietske van der Zwaag
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Tomas Knapen
- Spinoza Centre for NeuroimagingAmsterdamNetherlands
- Department of Computational Cognitive Neuroscience and NeuroimagingNetherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Experimental and Applied PsychologyVU UniversityAmsterdamNetherlands
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13
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Finn ES, Poldrack RA, Shine JM. Functional neuroimaging as a catalyst for integrated neuroscience. Nature 2023; 623:263-273. [PMID: 37938706 DOI: 10.1038/s41586-023-06670-9] [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: 03/16/2023] [Accepted: 09/22/2023] [Indexed: 11/09/2023]
Abstract
Functional magnetic resonance imaging (fMRI) enables non-invasive access to the awake, behaving human brain. By tracking whole-brain signals across a diverse range of cognitive and behavioural states or mapping differences associated with specific traits or clinical conditions, fMRI has advanced our understanding of brain function and its links to both normal and atypical behaviour. Despite this headway, progress in human cognitive neuroscience that uses fMRI has been relatively isolated from rapid advances in other subdomains of neuroscience, which themselves are also somewhat siloed from one another. In this Perspective, we argue that fMRI is well-placed to integrate the diverse subfields of systems, cognitive, computational and clinical neuroscience. We first summarize the strengths and weaknesses of fMRI as an imaging tool, then highlight examples of studies that have successfully used fMRI in each subdomain of neuroscience. We then provide a roadmap for the future advances that will be needed to realize this integrative vision. In this way, we hope to demonstrate how fMRI can help usher in a new era of interdisciplinary coherence in neuroscience.
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Affiliation(s)
- Emily S Finn
- Department of Psychological and Brain Sciences, Dartmouth College, Dartmouth, NH, USA.
| | | | - James M Shine
- School of Medical Sciences, University of Sydney, Sydney, New South Wales, Australia.
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14
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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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15
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Kraus B, Zinbarg R, Braga RM, Nusslock R, Mittal VA, Gratton C. Insights from personalized models of brain and behavior for identifying biomarkers in psychiatry. Neurosci Biobehav Rev 2023; 152:105259. [PMID: 37268180 PMCID: PMC10527506 DOI: 10.1016/j.neubiorev.2023.105259] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 05/22/2023] [Accepted: 05/30/2023] [Indexed: 06/04/2023]
Abstract
A main goal in translational neuroscience is to identify neural correlates of psychopathology ("biomarkers") that can be used to facilitate diagnosis, prognosis, and treatment. This goal has led to substantial research into how psychopathology symptoms relate to large-scale brain systems. However, these efforts have not yet resulted in practical biomarkers used in clinical practice. One reason for this underwhelming progress may be that many study designs focus on increasing sample size instead of collecting additional data within each individual. This focus limits the reliability and predictive validity of brain and behavioral measures in any one person. As biomarkers exist at the level of individuals, an increased focus on validating them within individuals is warranted. We argue that personalized models, estimated from extensive data collection within individuals, can address these concerns. We review evidence from two, thus far separate, lines of research on personalized models of (1) psychopathology symptoms and (2) fMRI measures of brain networks. We close by proposing approaches uniting personalized models across both domains to improve biomarker research.
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Affiliation(s)
- Brian Kraus
- Department of Psychology, Northwestern University, Evanston, IL, USA.
| | - Richard Zinbarg
- Department of Psychology, Northwestern University, Evanston, IL, USA; The Family Institute at Northwestern University, Evanston, IL, USA
| | - Rodrigo M Braga
- Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Robin Nusslock
- Department of Psychology, Northwestern University, Evanston, IL, USA; Institute for Policy Research, Northwestern University, Evanston, IL, USA
| | - Vijay A Mittal
- Department of Psychology, Northwestern University, Evanston, IL, USA; Institute for Policy Research, Northwestern University, Evanston, IL, USA; Institute for Innovations in Developmental Sciences (DevSci), Northwestern University, Chicago, IL, USA; Northwestern University, Department of Psychiatry, Chicago, IL, USA; Northwestern University, Medical Social Sciences, Chicago, IL, USA
| | - Caterina Gratton
- Department of Psychology, Northwestern University, Evanston, IL, USA; Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Interdepartmental Neuroscience Program, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Department of Psychology, Florida State University, Tallahassee, FL, USA; Program in Neuroscience, Florida State University, Tallahassee, FL, USA
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16
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Valk SL, Kanske P, Park BY, Hong SJ, Böckler A, Trautwein FM, Bernhardt BC, Singer T. Functional and microstructural plasticity following social and interoceptive mental training. eLife 2023; 12:e85188. [PMID: 37417306 PMCID: PMC10414971 DOI: 10.7554/elife.85188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 07/01/2023] [Indexed: 07/08/2023] Open
Abstract
The human brain supports social cognitive functions, including Theory of Mind, empathy, and compassion, through its intrinsic hierarchical organization. However, it remains unclear how the learning and refinement of social skills shapes brain function and structure. We studied if different types of social mental training induce changes in cortical function and microstructure, investigating 332 healthy adults (197 women, 20-55 years) with repeated multimodal neuroimaging and behavioral testing. Our neuroimaging approach examined longitudinal changes in cortical functional gradients and myelin-sensitive T1 relaxometry, two complementary measures of cortical hierarchical organization. We observed marked changes in intrinsic cortical function and microstructure, which varied as a function of social training content. In particular, cortical function and microstructure changed as a result of attention-mindfulness and socio-cognitive training in regions functionally associated with attention and interoception, including insular and parietal cortices. Conversely, socio-affective and socio-cognitive training resulted in differential microstructural changes in regions classically implicated in interoceptive and emotional processing, including insular and orbitofrontal areas, but did not result in functional reorganization. Notably, longitudinal changes in cortical function and microstructure predicted behavioral change in attention, compassion and perspective-taking. Our work demonstrates functional and microstructural plasticity after the training of social-interoceptive functions, and illustrates the bidirectional relationship between brain organisation and human social skills.
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Affiliation(s)
- Sofie Louise Valk
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- INM-7, FZ JülichJülichGermany
| | - Philipp Kanske
- Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, Technische Universität DresdenDresdenGermany
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Bo-yong Park
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
- Department of Data Science, Inha UniversityIncheonRepublic of Korea
- Center for Neuroscience Imaging Research, Institute for Basic ScienceSuwonRepublic of Korea
| | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic ScienceSuwonRepublic of Korea
- Center for the Developing Brain, Child Mind InstituteNew YorkUnited States
- Department of Biomedical Engineering, Sungkyunkwan UniversitySuwonRepublic of Korea
| | - Anne Böckler
- Department of Psychology, Wurzburg UniversityWurzburgGermany
| | - Fynn-Mathis Trautwein
- Department of Psychosomatic Medicine and Psychotherapy, Medical Center – University of Freiburg, Faculty of Medicine, University of FreiburgFreiburgGermany
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill UniversityMontrealCanada
| | - Tania Singer
- Social Neuroscience Lab, Max Planck SocietyBerlinGermany
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17
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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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18
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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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19
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Scheeringa R, Bonnefond M, van Mourik T, Jensen O, Norris DG, Koopmans PJ. Relating neural oscillations to laminar fMRI connectivity in visual cortex. Cereb Cortex 2023; 33:1537-1549. [PMID: 35512361 PMCID: PMC9977363 DOI: 10.1093/cercor/bhac154] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 03/30/2022] [Accepted: 03/31/2022] [Indexed: 11/13/2022] Open
Abstract
Laminar functional magnetic resonance imaging (fMRI) holds the potential to study connectivity at the laminar level in humans. Here we analyze simultaneously recorded electroencephalography (EEG) and high-resolution fMRI data to investigate how EEG power modulations, induced by a task with an attentional component, relate to changes in fMRI laminar connectivity between and within brain regions in visual cortex. Our results indicate that our task-induced decrease in beta power relates to an increase in deep-to-deep layer coupling between regions and to an increase in deep/middle-to-superficial layer connectivity within brain regions. The attention-related alpha power decrease predominantly relates to reduced connectivity between deep and superficial layers within brain regions, since, unlike beta power, alpha power was found to be positively correlated to connectivity. We observed no strong relation between laminar connectivity and gamma band oscillations. These results indicate that especially beta band, and to a lesser extent, alpha band oscillations relate to laminar-specific fMRI connectivity. The differential effects for alpha and beta bands indicate that they relate to different feedback-related neural processes that are differentially expressed in intra-region laminar fMRI-based connectivity.
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Affiliation(s)
- René Scheeringa
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, UNESCO-Weltkulturerbe Zollverein, University of Duisburg-Essen, Kokereiallee 7, 45141 Essen, Germany.,High-Field and Hybrid MR Imaging, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany.,Lyon Neuroscience Research Center; CRNL, INSERM U1028, CNRS UMR5292, University of Lyon 1, Université de Lyon, Bâtiment 462 - Neurocampus, 95 Bd Pinel, 69500 Bron, France.,Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Trigon 204, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands
| | - Mathilde Bonnefond
- Lyon Neuroscience Research Center; CRNL, INSERM U1028, CNRS UMR5292, University of Lyon 1, Université de Lyon, Bâtiment 462 - Neurocampus, 95 Bd Pinel, 69500 Bron, France
| | - Tim van Mourik
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Trigon 204, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands
| | - Ole Jensen
- School of Psychology, Centre for Human Brain Health, University of Birmingham, Hills Building, Birmingham B15 2TT, United Kingdom
| | - David G Norris
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, UNESCO-Weltkulturerbe Zollverein, University of Duisburg-Essen, Kokereiallee 7, 45141 Essen, Germany.,Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Trigon 204, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands
| | - Peter J Koopmans
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, UNESCO-Weltkulturerbe Zollverein, University of Duisburg-Essen, Kokereiallee 7, 45141 Essen, Germany.,High-Field and Hybrid MR Imaging, University Hospital Essen, University of Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany.,Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Trigon 204, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.,Department of Radiation Oncology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands
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20
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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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21
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Towards functional spin-echo BOLD line-scanning in humans at 7T. MAGMA (NEW YORK, N.Y.) 2023; 36:317-327. [PMID: 36625959 PMCID: PMC10140128 DOI: 10.1007/s10334-022-01059-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 12/22/2022] [Accepted: 12/23/2022] [Indexed: 01/11/2023]
Abstract
OBJECTIVE Neurons cluster into sub-millimeter spatial structures and neural activity occurs at millisecond resolutions; hence, ultimately, high spatial and high temporal resolutions are required for functional MRI. In this work, we implemented a spin-echo line-scanning (SELINE) sequence to use in high spatial and temporal resolution fMRI. MATERIALS AND METHODS A line is formed by simply rotating the spin-echo refocusing gradient to a plane perpendicular to the excited slice and by removing the phase-encoding gradient. This technique promises a combination of high spatial and temporal resolution (250 μm, 500 ms) and microvascular specificity of functional responses. We compared SELINE data to a corresponding gradient-echo version (GELINE). RESULTS We demonstrate that SELINE showed much-improved line selection (i.e. a sharper line profile) compared to GELINE, albeit at the cost of a significant drop in functional sensitivity. DISCUSSION This low functional sensitivity needs to be addressed before SELINE can be applied for neuroscientific purposes.
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22
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Liu TT, Fu JZ, Chai Y, Japee S, Chen G, Ungerleider LG, Merriam EP. Layer-specific, retinotopically-diffuse modulation in human visual cortex in response to viewing emotionally expressive faces. Nat Commun 2022; 13:6302. [PMID: 36273204 PMCID: PMC9588045 DOI: 10.1038/s41467-022-33580-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 09/22/2022] [Indexed: 12/25/2022] Open
Abstract
Viewing faces that are perceived as emotionally expressive evokes enhanced neural responses in multiple brain regions, a phenomenon thought to depend critically on the amygdala. This emotion-related modulation is evident even in primary visual cortex (V1), providing a potential neural substrate by which emotionally salient stimuli can affect perception. How does emotional valence information, computed in the amygdala, reach V1? Here we use high-resolution functional MRI to investigate the layer profile and retinotopic distribution of neural activity specific to emotional facial expressions. Across three experiments, human participants viewed centrally presented face stimuli varying in emotional expression and performed a gender judgment task. We found that facial valence sensitivity was evident only in superficial cortical layers and was not restricted to the retinotopic location of the stimuli, consistent with diffuse feedback-like projections from the amygdala. Together, our results provide a feedback mechanism by which the amygdala directly modulates activity at the earliest stage of visual processing.
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Affiliation(s)
- Tina T. Liu
- grid.416868.50000 0004 0464 0574Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892 MD USA
| | - Jason Z Fu
- grid.416868.50000 0004 0464 0574Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892 MD USA
| | - Yuhui Chai
- grid.416868.50000 0004 0464 0574Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892 MD USA
| | - Shruti Japee
- grid.416868.50000 0004 0464 0574Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892 MD USA
| | - Gang Chen
- grid.416868.50000 0004 0464 0574Scientific and Statistical Computing Core, National Institute of Mental Health, NIH, Bethesda, 20892 MD USA
| | - Leslie G. Ungerleider
- grid.416868.50000 0004 0464 0574Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892 MD USA
| | - Elisha P. Merriam
- grid.416868.50000 0004 0464 0574Laboratory of Brain and Cognition, National Institute of Mental Health, NIH, Bethesda, 20892 MD USA
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23
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Habibey R, Striebel J, Schmieder F, Czarske J, Busskamp V. Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays. Front Neurosci 2022; 16:951964. [PMID: 36267241 PMCID: PMC9578684 DOI: 10.3389/fnins.2022.951964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 09/06/2022] [Indexed: 11/13/2022] Open
Abstract
Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.
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Affiliation(s)
- Rouhollah Habibey
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Bonn, Germany
| | - Johannes Striebel
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Bonn, Germany
| | - Felix Schmieder
- Laboratory of Measurement and Sensor System Technique, Faculty of Electrical and Computer Engineering, TU Dresden, Dresden, Germany
| | - Jürgen Czarske
- Laboratory of Measurement and Sensor System Technique, Faculty of Electrical and Computer Engineering, TU Dresden, Dresden, Germany
- Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany
- Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany
- School of Science, Institute of Applied Physics, TU Dresden, Dresden, Germany
| | - Volker Busskamp
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Bonn, Germany
- *Correspondence: Volker Busskamp,
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24
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John YJ, Sawyer KS, Srinivasan K, Müller EJ, Munn BR, Shine JM. It's about time: Linking dynamical systems with human neuroimaging to understand the brain. Netw Neurosci 2022; 6:960-979. [PMID: 36875012 PMCID: PMC9976648 DOI: 10.1162/netn_a_00230] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 01/04/2022] [Indexed: 11/04/2022] Open
Abstract
Most human neuroscience research to date has focused on statistical approaches that describe stationary patterns of localized neural activity or blood flow. While these patterns are often interpreted in light of dynamic, information-processing concepts, the static, local, and inferential nature of the statistical approach makes it challenging to directly link neuroimaging results to plausible underlying neural mechanisms. Here, we argue that dynamical systems theory provides the crucial mechanistic framework for characterizing both the brain's time-varying quality and its partial stability in the face of perturbations, and hence, that this perspective can have a profound impact on the interpretation of human neuroimaging results and their relationship with behavior. After briefly reviewing some key terminology, we identify three key ways in which neuroimaging analyses can embrace a dynamical systems perspective: by shifting from a local to a more global perspective, by focusing on dynamics instead of static snapshots of neural activity, and by embracing modeling approaches that map neural dynamics using "forward" models. Through this approach, we envisage ample opportunities for neuroimaging researchers to enrich their understanding of the dynamic neural mechanisms that support a wide array of brain functions, both in health and in the setting of psychopathology.
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Affiliation(s)
- Yohan J. John
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, MA, USA
| | - Kayle S. Sawyer
- Departments of Anatomy and Neurobiology, Boston University, Boston University, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
- Boston VA Healthcare System, Boston, MA, USA
- Sawyer Scientific, LLC, Boston, MA, USA
| | - Karthik Srinivasan
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Eli J. Müller
- Brain and Mind Center, University of Sydney, Sydney, NSW, Australia
| | - Brandon R. Munn
- Brain and Mind Center, University of Sydney, Sydney, NSW, Australia
| | - James M. Shine
- Brain and Mind Center, University of Sydney, Sydney, NSW, Australia
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25
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Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex. PLoS Biol 2022; 20:e3001735. [PMID: 35914002 PMCID: PMC9371256 DOI: 10.1371/journal.pbio.3001735] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 08/11/2022] [Accepted: 06/30/2022] [Indexed: 11/21/2022] Open
Abstract
Whole-brain neural communication is typically estimated from statistical associations among electromagnetic or haemodynamic time-series. The relationship between functional network architectures recovered from these 2 types of neural activity remains unknown. Here, we map electromagnetic networks (measured using magnetoencephalography (MEG)) to haemodynamic networks (measured using functional magnetic resonance imaging (fMRI)). We find that the relationship between the 2 modalities is regionally heterogeneous and systematically follows the cortical hierarchy, with close correspondence in unimodal cortex and poor correspondence in transmodal cortex. Comparison with the BigBrain histological atlas reveals that electromagnetic–haemodynamic coupling is driven by laminar differentiation and neuron density, suggesting that the mapping between the 2 modalities can be explained by cytoarchitectural variation. Importantly, haemodynamic connectivity cannot be explained by electromagnetic activity in a single frequency band, but rather arises from the mixing of multiple neurophysiological rhythms. Correspondence between the two is largely driven by MEG functional connectivity at the beta (15 to 29 Hz) frequency band. Collectively, these findings demonstrate highly organized but only partly overlapping patterns of connectivity in MEG and fMRI functional networks, opening fundamentally new avenues for studying the relationship between cortical microarchitecture and multimodal connectivity patterns. What is the relationship between functional network architectures inferred from electromagnetic and haemodynamic data? This study shows that superposition of electromagnetic networks at canonical frequency bands manifests as highly structured patterns of haemodynamic functional connectivity in the human brain, reflecting systematic variation in cytoarchitecture.
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26
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Guilbert J, Légaré A, De Koninck P, Desrosiers P, Desjardins M. Toward an integrative neurovascular framework for studying brain networks. NEUROPHOTONICS 2022; 9:032211. [PMID: 35434179 PMCID: PMC8989057 DOI: 10.1117/1.nph.9.3.032211] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 03/11/2022] [Indexed: 05/28/2023]
Abstract
Brain functional connectivity based on the measure of blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals has become one of the most widely used measurements in human neuroimaging. However, the nature of the functional networks revealed by BOLD fMRI can be ambiguous, as highlighted by a recent series of experiments that have suggested that typical resting-state networks can be replicated from purely vascular or physiologically driven BOLD signals. After going through a brief review of the key concepts of brain network analysis, we explore how the vascular and neuronal systems interact to give rise to the brain functional networks measured with BOLD fMRI. This leads us to emphasize a view of the vascular network not only as a confounding element in fMRI but also as a functionally relevant system that is entangled with the neuronal network. To study the vascular and neuronal underpinnings of BOLD functional connectivity, we consider a combination of methodological avenues based on multiscale and multimodal optical imaging in mice, used in combination with computational models that allow the integration of vascular information to explain functional connectivity.
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Affiliation(s)
- Jérémie Guilbert
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Université Laval, Centre de recherche du CHU de Québec, Québec, Canada
| | - Antoine Légaré
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Centre de recherche CERVO, Québec, Canada
- Université Laval, Department of Biochemistry, Microbiology, and Bioinformatics, Québec, Canada
| | - Paul De Koninck
- Centre de recherche CERVO, Québec, Canada
- Université Laval, Department of Biochemistry, Microbiology, and Bioinformatics, Québec, Canada
| | - Patrick Desrosiers
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Centre de recherche CERVO, Québec, Canada
| | - Michèle Desjardins
- Université Laval, Department of Physics, Physical Engineering, and Optics, Québec, Canada
- Université Laval, Centre de recherche du CHU de Québec, Québec, Canada
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27
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Haarsma J, Kok P, Browning M. The promise of layer-specific neuroimaging for testing predictive coding theories of psychosis. Schizophr Res 2022; 245:68-76. [PMID: 33199171 PMCID: PMC9241988 DOI: 10.1016/j.schres.2020.10.009] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 10/03/2020] [Accepted: 10/28/2020] [Indexed: 12/24/2022]
Abstract
Predictive coding potentially provides an explanatory model for understanding the neurocognitive mechanisms of psychosis. It proposes that cognitive processes, such as perception and inference, are implemented by a hierarchical system, with the influence of each level being a function of the estimated precision of beliefs at that level. However, predictive coding models of psychosis are insufficiently constrained-any phenomenon can be explained in multiple ways by postulating different changes to precision at different levels of processing. One reason for the lack of constraint in these models is that the core processes are thought to be implemented by the function of specific cortical layers, and the technology to measure layer specific neural activity in humans has until recently been lacking. As a result, our ability to constrain the models with empirical data has been limited. In this review we provide a brief overview of predictive processing models of psychosis and then describe the potential for newly developed, layer specific neuroimaging techniques to test and thus constrain these models. We conclude by discussing the most promising avenues for this research as well as the technical and conceptual challenges which may limit its application.
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Affiliation(s)
- J. Haarsma
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom,Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Corresponding author at: Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom.
| | - P. Kok
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
| | - M. Browning
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Oxford Health NHS Trust, Oxford, United Kingdom
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28
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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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29
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Wang F, Dong Z, Wald LL, Polimeni JR, Setsompop K. Simultaneous pure T 2 and varying T 2'-weighted BOLD fMRI using Echo Planar Time-resolved Imaging for mapping cortical-depth dependent responses. Neuroimage 2021; 245:118641. [PMID: 34655771 PMCID: PMC8820652 DOI: 10.1016/j.neuroimage.2021.118641] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 10/06/2021] [Accepted: 10/07/2021] [Indexed: 12/12/2022] Open
Abstract
Spin-echo (SE) BOLD fMRI has high microvascular specificity, and thus provides a more reliable means to localize neural activity compared to conventional gradient-echo BOLD fMRI. However, the most common SE BOLD acquisition method, SE-EPI, is known to suffer from T2' contrast contamination with undesirable draining vein bias. To address this, in this study, we extended a recently developed distortion/blurring-free multi-shot EPI technique, Echo-Planar Time-resolved Imaging (EPTI), to cortical-depth dependent SE-fMRI at 7T to test whether it could provide purer SE BOLD contrast with minimal T2' contamination for improved neuronal specificity. From the same acquisition, the time-resolved feature of EPTI also provides a series of asymmetric SE (ASE) images with varying T2' weightings, and enables extraction of data equivalent to conventional SE EPI with different echo train lengths (ETLs). This allows us to systematically examine how T2'-contribution affects different SE acquisition strategies using a single dataset. A low-rank spatiotemporal subspace reconstruction was implemented for the SE-EPTI acquisition, which incorporates corrections for both shot-to-shot phase variations and dynamic B0 drifts. SE-EPTI was used in a visual task fMRI experiment to demonstrate that i) the pure SE image provided by EPTI results in the highest microvascular specificity; ii) the ASE EPTI series, with a graded introduction of T2' weightings at time points farther away from the pure SE, show a gradual sensitivity increase along with increasing draining vein bias; iii) the longer ETL seen in conventional SE EPI acquisitions will induce more draining vein bias. Consistent results were observed across multiple subjects, demonstrating the robustness of the proposed technique for SE-BOLD fMRI with high specificity.
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Affiliation(s)
- Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
| | - Zijing Dong
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, USA; Department of Electrical Engineering, Stanford University, Stanford, USA
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30
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Müller-Axt C, Eichner C, Rusch H, Kauffmann L, Bazin PL, Anwander A, Morawski M, von Kriegstein K. Mapping the human lateral geniculate nucleus and its cytoarchitectonic subdivisions using quantitative MRI. Neuroimage 2021; 244:118559. [PMID: 34562697 DOI: 10.1016/j.neuroimage.2021.118559] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 09/03/2021] [Accepted: 09/04/2021] [Indexed: 11/17/2022] Open
Abstract
The human lateral geniculate nucleus (LGN) of the visual thalamus is a key subcortical processing site for visual information analysis. Due to its small size and deep location within the brain, a non-invasive characterization of the LGN and its microstructurally distinct magnocellular (M) and parvocellular (P) subdivisions in humans is challenging. Here, we investigated whether structural quantitative MRI (qMRI) methods that are sensitive to underlying microstructural tissue features enable MR-based mapping of human LGN M and P subdivisions. We employed high-resolution 7 Tesla in-vivo qMRI in N = 27 participants and ultra-high resolution 7 Tesla qMRI of a post-mortem human LGN specimen. We found that a quantitative assessment of the LGN and its subdivisions is possible based on microstructure-informed qMRI contrast alone. In both the in-vivo and post-mortem qMRI data, we identified two components of shorter and longer longitudinal relaxation time (T1) within the LGN that coincided with the known anatomical locations of a dorsal P and a ventral M subdivision, respectively. Through ground-truth histological validation, we further showed that the microstructural MRI contrast within the LGN pertains to cyto- and myeloarchitectonic tissue differences between its subdivisions. These differences were based on cell and myelin density, but not on iron content. Our qMRI-based mapping strategy paves the way for an in-depth understanding of LGN function and microstructure in humans. It further enables investigations into the selective contributions of LGN subdivisions to human behavior in health and disease.
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Affiliation(s)
- Christa Müller-Axt
- Faculty of Psychology, Technical University of Dresden, Dresden 01069, Germany; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany.
| | - Cornelius Eichner
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Henriette Rusch
- Paul Flechsig Institute of Brain Research, University of Leipzig, Leipzig 04103, Germany
| | - Louise Kauffmann
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany; LPNC, Grenoble Alpes University, Grenoble 38000, France
| | - Pierre-Louis Bazin
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany; Integrative Model-Based Cognitive Neuroscience Research Unit, Department of Psychology, University of Amsterdam, Amsterdam 1001 NK, The Netherlands
| | - Alfred Anwander
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Markus Morawski
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany; Paul Flechsig Institute of Brain Research, University of Leipzig, Leipzig 04103, Germany
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31
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Zoraghi M, Scherf N, Jaeger C, Sack I, Hirsch S, Hetzer S, Weiskopf N. Simulating Local Deformations in the Human Cortex Due to Blood Flow-Induced Changes in Mechanical Tissue Properties: Impact on Functional Magnetic Resonance Imaging. Front Neurosci 2021; 15:722366. [PMID: 34621151 PMCID: PMC8490675 DOI: 10.3389/fnins.2021.722366] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 08/23/2021] [Indexed: 01/06/2023] Open
Abstract
Investigating human brain tissue is challenging due to the complexity and the manifold interactions between structures across different scales. Increasing evidence suggests that brain function and microstructural features including biomechanical features are related. More importantly, the relationship between tissue mechanics and its influence on brain imaging results remains poorly understood. As an important example, the study of the brain tissue response to blood flow could have important theoretical and experimental consequences for functional magnetic resonance imaging (fMRI) at high spatial resolutions. Computational simulations, using realistic mechanical models can predict and characterize the brain tissue behavior and give us insights into the consequent potential biases or limitations of in vivo, high-resolution fMRI. In this manuscript, we used a two dimensional biomechanical simulation of an exemplary human gyrus to investigate the relationship between mechanical tissue properties and the respective changes induced by focal blood flow changes. The model is based on the changes in the brain’s stiffness and volume due to the vasodilation evoked by neural activity. Modeling an exemplary gyrus from a brain atlas we assessed the influence of different potential mechanisms: (i) a local increase in tissue stiffness (at the level of a single anatomical layer), (ii) an increase in local volume, and (iii) a combination of both effects. Our simulation results showed considerable tissue displacement because of these temporary changes in mechanical properties. We found that the local volume increase causes more deformation and consequently higher displacement of the gyrus. These displacements introduced considerable artifacts in our simulated fMRI measurements. Our results underline the necessity to consider and characterize the tissue displacement which could be responsible for fMRI artifacts.
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Affiliation(s)
- Mahsa Zoraghi
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nico Scherf
- Methods and Development Group Neural Data Science and Statistical Computing, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Carsten Jaeger
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ingolf Sack
- Department of Radiology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Sebastian Hirsch
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Berlin Center for Computational Neuroscience, Berlin, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Berlin Center for Computational Neuroscience, Berlin, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Faculty of Physics and Earth Sciences, Felix Bloch Institute for Solid State Physics, Leipzig University, Leipzig, Germany
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32
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Signorelli CM, Meling D. Towards new concepts for a biological neuroscience of consciousness. Cogn Neurodyn 2021; 15:783-804. [PMID: 34603542 PMCID: PMC8448820 DOI: 10.1007/s11571-020-09658-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 11/17/2020] [Accepted: 12/11/2020] [Indexed: 02/07/2023] Open
Abstract
In the search for a sound model of consciousness, we aim at introducing new concepts: closure, compositionality, biobranes and autobranes. This is important to overcome reductionism and to bring life back into the neuroscience of consciousness. Using these definitions, we conjecture that consciousness co-arises with the non-trivial composition of biological closure in the form of biobranes and autobranes: conscious processes generate closed activity at various levels and are, in turn, themselves, supported by biobranes and autobranes. This approach leads to a non-reductionist biological and simultaneously phenomenological theory of conscious experience, giving new perspectives for a science of consciousness. Future works will implement experimental definitions and computational simulations to characterize these dynamical biobranes interacting.
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Affiliation(s)
- Camilo Miguel Signorelli
- Department of Computer Science, University of Oxford, Oxford, UK
- Cognitive Neuroimaging Unit, INSERM U992, NeuroSpin, Gif-sur-Yvette, France
- Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
| | - Daniel Meling
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zurich, Zurich, Switzerland
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33
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Zhang Y, Kim JH, Brang D, Liu Z. Naturalistic Stimuli: A Paradigm for Multi-Scale Functional Characterization of the Human Brain. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2021; 19:100298. [PMID: 34423178 PMCID: PMC8376216 DOI: 10.1016/j.cobme.2021.100298] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Movies, audio stories, and virtual reality are increasingly used as stimuli for functional brain imaging. Such naturalistic paradigms are in sharp contrast to the tradition of experimental reductionism in neuroscience research. Being complex, dynamic, and diverse, naturalistic stimuli set up a more ecologically relevant condition and induce highly reproducible brain responses across a wide range of spatiotemporal scales. Here, we review recent technical advances and scientific findings on imaging the brain under naturalistic stimuli. Then we elaborate on the premise of using naturalistic paradigms for multi-scale, multi-modal, and high-throughput functional characterization of the human brain. We further highlight the growing potential of using deep learning models to infer neural information processing from brain responses to naturalistic stimuli. Lastly, we advocate large-scale collaborations to combine brain imaging and recording data across experiments, subjects, and labs that use the same set of naturalistic stimuli.
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Affiliation(s)
- Yizhen Zhang
- Department of Electrical Engineering and Computer Science, University of Michigan
| | - Jung-Hoon Kim
- Department of Biomedical Engineering, University of Michigan
- Weldon School of Biomedical Engineering, Purdue University
| | - David Brang
- Department of Psychology, University of Michigan
| | - Zhongming Liu
- Department of Electrical Engineering and Computer Science, University of Michigan
- Department of Biomedical Engineering, University of Michigan
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34
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Huber LR, Poser BA, Bandettini PA, Arora K, Wagstyl K, Cho S, Goense J, Nothnagel N, Morgan AT, van den Hurk J, Müller AK, Reynolds RC, Glen DR, Goebel R, Gulban OF. LayNii: A software suite for layer-fMRI. Neuroimage 2021; 237:118091. [PMID: 33991698 PMCID: PMC7615890 DOI: 10.1016/j.neuroimage.2021.118091] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 02/19/2021] [Accepted: 04/16/2021] [Indexed: 01/06/2023] Open
Abstract
High-resolution fMRI in the sub-millimeter regime allows researchers to resolve brain activity across cortical layers and columns non-invasively. While these high-resolution data make it possible to address novel questions of directional information flow within and across brain circuits, the corresponding data analyses are challenged by MRI artifacts, including image blurring, image distortions, low SNR, and restricted coverage. These challenges often result in insufficient spatial accuracy of conventional analysis pipelines. Here we introduce a new software suite that is specifically designed for layer-specific functional MRI: LayNii. This toolbox is a collection of command-line executable programs written in C/C++ and is distributed opensource and as pre-compiled binaries for Linux, Windows, and macOS. LayNii is designed for layer-fMRI data that suffer from SNR and coverage constraints and thus cannot be straightforwardly analyzed in alternative software packages. Some of the most popular programs of LayNii contain 'layerification' and columnarization in the native voxel space of functional data as well as many other layer-fMRI specific analysis tasks: layer-specific smoothing, model-based vein mitigation of GE-BOLD data, quality assessment of artifact dominated sub-millimeter fMRI, as well as analyses of VASO data.
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Affiliation(s)
| | - Benedikt A Poser
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | | | - Kabir Arora
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Shinho Cho
- CMRR, University of Minneapolis, MN, USA
| | | | | | | | | | | | | | | | - Rainer Goebel
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands; Brain Innovation, Maastricht, the Netherlands
| | - Omer Faruk Gulban
- MBIC, Faculty of Psychology and Neuroscience, Maastricht University, the Netherlands; Brain Innovation, Maastricht, the Netherlands
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35
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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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36
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Zimmerman B, Rypma B, Gratton G, Fabiani M. Age-related changes in cerebrovascular health and their effects on neural function and cognition: A comprehensive review. Psychophysiology 2021; 58:e13796. [PMID: 33728712 PMCID: PMC8244108 DOI: 10.1111/psyp.13796] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 01/11/2021] [Accepted: 02/08/2021] [Indexed: 12/11/2022]
Abstract
The process of aging includes changes in cellular biology that affect local interactions between cells and their environments and eventually propagate to systemic levels. In the brain, where neurons critically depend on an efficient and dynamic supply of oxygen and glucose, age-related changes in the complex interaction between the brain parenchyma and the cerebrovasculature have effects on health and functioning that negatively impact cognition and play a role in pathology. Thus, cerebrovascular health is considered one of the main mechanisms by which a healthy lifestyle, such as habitual cardiorespiratory exercise and a healthful diet, could lead to improved cognitive outcomes with aging. This review aims at detailing how the physiology of the cerebral vascular system changes with age and how these changes lead to differential trajectories of cognitive maintenance or decline. This provides a framework for generating specific mechanistic hypotheses about the efficacy of proposed interventions and lifestyle covariates that contribute to enhanced cognitive well-being. Finally, we discuss the methodological implications of age-related changes in the cerebral vasculature for human cognitive neuroscience research and propose directions for future experiments aimed at investigating age-related changes in the relationship between physiology and cognitive mechanisms.
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Affiliation(s)
- Benjamin Zimmerman
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Bart Rypma
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Gabriele Gratton
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - Monica Fabiani
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Champaign, IL, USA
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37
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Abstract
Functional magnetic resonance imaging (fMRI) has become one of the most powerful tools for investigating the human brain. Ultrahigh magnetic field (UHF) of 7 Tesla has played a critical role in enabling higher resolution and more accurate (relative to the neuronal activity) functional maps. However, even with these gains, the fMRI approach is challenged relative to the spatial scale over which brain function is organized. Therefore, going forward, significant advances in fMRI are still needed. Such advances will predominantly come from magnetic fields significantly higher than 7 Tesla, which is the most commonly used UHF platform today, and additional technologies that will include developments in pulse sequences, image reconstruction, noise suppression, and image analysis in order to further enhance and augment the gains than can be realized by going to higher magnetic fields.
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Affiliation(s)
- Kamil Uğurbil
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, 2021 6 Street SE, Minneapolis, MN 55456
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38
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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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39
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Pfaffenrot V, Voelker MN, Kashyap S, Koopmans PJ. Laminar fMRI using T 2-prepared multi-echo FLASH. Neuroimage 2021; 236:118163. [PMID: 34023449 DOI: 10.1016/j.neuroimage.2021.118163] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 05/03/2021] [Accepted: 05/11/2021] [Indexed: 02/06/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) using blood oxygenation level dependent (BOLD) contrast at a sub-millimeter scale is a promising technique to probe neural activity at the level of cortical layers. While gradient echo (GRE) BOLD sequences exhibit the highest sensitivity, their signal is confounded by unspecific extravascular (EV) and intravascular (IV) effects of large intracortical ascending veins and pial veins leading to a downstream blurring effect of local signal changes. In contrast, spin echo (SE) fMRI promises higher specificity towards signal changes near the microvascular compartment. However, the T2-weighted signal is typically sampled with a gradient echo readout imposing additional T2'-weighting. In this work, we used a T2-prepared (T2-prep) sequence with short GRE readouts to investigate its capability to acquire laminar fMRI data during a visual task in humans at 7 T. By varying the T2-prep echo time (TEprep) and acquiring multiple gradient echoes (TEGRE) per excitation, we studied the specificity of the sequence and the influence of possible confounding contributions to the shape of laminar fMRI profiles. By fitting and extrapolating the multi-echo GRE data to a TEGRE = 0 ms condition, we show for the first time laminar profiles free of T2'-pollution, confined to gray matter. This finding is independent of TEprep, except for the shortest one (31 ms) where hints of a remaining intravascular component can be seen. For TEGRE > 0 ms a prominent peak at the pial surface is observed that increases with longer TEGRE and dominates the shape of the profiles independent of the amount of T2-weighting. Simulations show that the peak at the pial surface is a result of static EV dephasing around pial vessels in CSF visible in GM due to partial voluming. Additionally, another, weaker, static dephasing effect is observed throughout all layers of the cortex, which is particularly obvious in the data with shortest T2-prep echo time. Our simulations show that this cannot be explained by intravascular dephasing but that it is likely caused by extravascular effects of the intracortical and pial veins. We conclude that even for TEGRE as short as 2.3 ms, the T2'-weighting added to the T2-weighting is enough to dramatically affect the laminar specificity of the BOLD signal change. However, the bulk of this corruption stems from CSF partial volume effects which can in principle be addressed by increasing the spatial resolution of the acquisition.
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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.
| | - Maximilian N Voelker
- 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
| | - Sriranga Kashyap
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, 6229 Maastricht, Netherlands
| | - 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
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40
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Hayashi T, Hou Y, Glasser MF, Autio JA, Knoblauch K, Inoue-Murayama M, Coalson T, Yacoub E, Smith S, Kennedy H, Van Essen DC. The nonhuman primate neuroimaging and neuroanatomy project. Neuroimage 2021; 229:117726. [PMID: 33484849 PMCID: PMC8079967 DOI: 10.1016/j.neuroimage.2021.117726] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/13/2020] [Accepted: 01/02/2021] [Indexed: 11/29/2022] Open
Abstract
Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function, connectivity, and their variability across individuals using high-quality non-invasive data from many subjects. Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, 'ground truth' validation of connectivity using invasive tracers is not feasible in humans. Studies using nonhuman primates (NHPs) enable comparisons between invasive and non-invasive measures, including exploration of how "functional connectivity" from fMRI and "tractographic connectivity" from diffusion MRI compare with long-distance connections measured using tract tracing. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior.
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Affiliation(s)
- Takuya Hayashi
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 MI R&D Center 3F, Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan; Department of Neurobiology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yujie Hou
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France
| | - Matthew F Glasser
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA; Department of Neuroscience and Radiology, Washington University Medical School, St Louis, MO USA
| | - Joonas A Autio
- Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, 6-7-3 MI R&D Center 3F, Minatojima-minamimachi, Chuo-ku, Kobe 650-0047, Japan
| | - Kenneth Knoblauch
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France
| | | | - Tim Coalson
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, USA
| | - Stephen Smith
- Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Henry Kennedy
- Inserm, Stem Cell and Brain Research Institute U1208, Univ Lyon, Université Claude Bernard Lyon 1, Bron, France; Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences (CAS) Key Laboratory of Primate Neurobiology, CAS, Shanghai, China
| | - David C Van Essen
- Department of Neuroscience, Washington University Medical School, St Louis, MO USA
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41
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Chang C, Chen JE. Multimodal EEG-fMRI: advancing insight into large-scale human brain dynamics. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2021; 18. [PMID: 34095643 DOI: 10.1016/j.cobme.2021.100279] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Advances in the acquisition and analysis of functional magnetic resonance imaging (fMRI) data are revealing increasingly rich spatiotemporal structure across the human brain. Nonetheless, uncertainty surrounding the origins of fMRI hemodynamic signals, and in the link between large-scale fMRI patterns and ongoing functional states, presently limits the neurobiological conclusions one can draw from fMRI alone. Electroencephalography (EEG) provides complementary information about neural electrical activity and state change, and simultaneously acquiring EEG together with fMRI presents unique opportunities for studying large-scale brain activity and gaining more information from fMRI itself. Here, we discuss recent progress in the use of concurrent EEG-fMRI to enrich the investigation of neural and physiological states and clarify the origins of fMRI hemodynamic signals. Throughout, we outline perspectives on future directions and open challenges.
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Affiliation(s)
- Catie Chang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA.,Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jingyuan E Chen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
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42
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Vezoli J, Magrou L, Goebel R, Wang XJ, Knoblauch K, Vinck M, Kennedy H. Cortical hierarchy, dual counterstream architecture and the importance of top-down generative networks. Neuroimage 2021; 225:117479. [PMID: 33099005 PMCID: PMC8244994 DOI: 10.1016/j.neuroimage.2020.117479] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 09/29/2020] [Accepted: 10/15/2020] [Indexed: 12/18/2022] Open
Abstract
Hierarchy is a major organizational principle of the cortex and underscores modern computational theories of cortical function. The local microcircuit amplifies long-distance inter-areal input, which show distance-dependent changes in their laminar profiles. Statistical modeling of these changes in laminar profiles demonstrates that inputs from multiple hierarchical levels to their target areas show remarkable consistency, allowing the construction of a cortical hierarchy based on a principle of hierarchical distance. The statistical modeling that is applied to structure can also be applied to laminar differences in the oscillatory coherence between areas thereby determining a functional hierarchy of the cortex. Close examination of the anatomy of inter-areal connectivity reveals a dual counterstream architecture with well-defined distance-dependent feedback and feedforward pathways in both the supra- and infragranular layers, suggesting a multiplicity of feedback pathways with well-defined functional properties. These findings are consistent with feedback connections providing a generative network involved in a wide range of cognitive functions. A dynamical model constrained by connectivity data sheds insight into the experimentally observed signatures of frequency-dependent Granger causality for feedforward versus feedback signaling. Concerted experiments capitalizing on recent technical advances and combining tract-tracing, high-resolution fMRI, optogenetics and mathematical modeling hold the promise of a much improved understanding of lamina-constrained mechanisms of neural computation and cognition. However, because inter-areal interactions involve cortical layers that have been the target of important evolutionary changes in the primate lineage, these investigations will need to include human and non-human primate comparisons.
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Affiliation(s)
- Julien Vezoli
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Loïc Magrou
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Rainer Goebel
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, P.O. Box 616, 6200 MD, Maastricht, the Netherlands
| | - Xiao-Jing Wang
- Center for Neural Science, New York University (NYU), New York, NY 10003, USA
| | - Kenneth Knoblauch
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany.
| | - Henry Kennedy
- Univ Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France; Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences (CAS) Key Laboratory of Primate Neurobiology, CAS, Shanghai 200031, China.
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43
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Oliveira ÍAF, van der Zwaag W, Raimondo L, Dumoulin SO, Siero JCW. Comparing hand movement rate dependence of cerebral blood volume and BOLD responses at 7T. Neuroimage 2020; 226:117623. [PMID: 33301935 DOI: 10.1016/j.neuroimage.2020.117623] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 11/06/2020] [Accepted: 11/27/2020] [Indexed: 11/17/2022] Open
Abstract
Functional magnetic resonance imaging (fMRI) based on the Blood Oxygenation Level Dependent (BOLD) contrast takes advantage of the coupling between neuronal activity and the hemodynamics to allow a non-invasive localisation of the neuronal activity. In general, fMRI experiments assume a linear relationship between neuronal activation and the observed hemodynamics. However, the relationship between BOLD responses, neuronal activity, and behaviour are often nonlinear. In addition, the nonlinearity between BOLD responses and behaviour may be related to neuronal process rather than a neurovascular uncoupling. Further, part of the nonlinearity may be driven by vascular nonlinearity effects in particular from large vessel contributions. fMRI based on cerebral blood volume (CBV), promises a higher microvascular specificity, potentially without vascular nonlinearity effects and reduced contamination of the large draining vessels compared to BOLD. In this study, we aimed to investigate differences in BOLD and VASO-CBV signal changes during a hand movement task over a broad range of movement rates. We used a double readout 3D-EPI sequence at 7T to simultaneously measure VASO-CBV and BOLD responses in the sensorimotor cortex. The measured BOLD and VASO-CBV responses increased very similarly in a nonlinear fashion, plateauing for movement rates larger than 1 Hz. Our findings show a tight relationship between BOLD and VASO-CBV responses, indicating that the overall interplay of CBV and BOLD responses are similar for the assessed range of movement rates. These results suggest that the observed nonlinearity of neuronal origin is already present in VASO-CBV measurements, and consequently shows relatively unchanged BOLD responses.
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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.
| | | | - Luisa Raimondo
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands; Experimental and Applied Psychology, VU University, 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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44
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Weldon KB, Olman CA. Forging a path to mesoscopic imaging success with ultra-high field functional magnetic resonance imaging. Philos Trans R Soc Lond B Biol Sci 2020; 376:20200040. [PMID: 33190599 PMCID: PMC7741029 DOI: 10.1098/rstb.2020.0040] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Functional magnetic resonance imaging (fMRI) studies with ultra-high field (UHF, 7+ Tesla) technology enable the acquisition of high-resolution images. In this work, we discuss recent achievements in UHF fMRI at the mesoscopic scale, on the order of cortical columns and layers, and examine approaches to addressing common challenges. As researchers push to smaller and smaller voxel sizes, acquisition and analysis decisions have greater potential to degrade spatial accuracy, and UHF fMRI data must be carefully interpreted. We consider the impact of acquisition decisions on the spatial specificity of the MR signal with a representative dataset with 0.8 mm isotropic resolution. We illustrate the trade-offs in contrast with noise ratio and spatial specificity of different acquisition techniques and show that acquisition blurring can increase the effective voxel size by as much as 50% in some dimensions. We further describe how different sources of degradations to spatial resolution in functional data may be characterized. Finally, we emphasize that progress in UHF fMRI depends not only on scientific discovery and technical advancement, but also on informal discussions and documentation of challenges researchers face and overcome in pursuit of their goals. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.
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Affiliation(s)
- Kimberly B Weldon
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN 55455, USA.,Center for Magnetic Resonance Imaging, University of Minnesota, Minneapolis, MN 55455, USA
| | - Cheryl A Olman
- Center for Magnetic Resonance Imaging, University of Minnesota, Minneapolis, MN 55455, USA.,Department of Psychology, University of Minnesota, Minneapolis, MN 55455, USA
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45
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Bollmann S, Barth M. New acquisition techniques and their prospects for the achievable resolution of fMRI. Prog Neurobiol 2020; 207:101936. [PMID: 33130229 DOI: 10.1016/j.pneurobio.2020.101936] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 09/10/2020] [Accepted: 10/18/2020] [Indexed: 01/17/2023]
Abstract
This work reviews recent advances in technologies for functional magnetic resonance imaging (fMRI) of the human brain and highlights the push for higher functional specificity based on increased spatial resolution and specific MR contrasts to reveal previously undetectable functional properties of small-scale cortical structures. We discuss how the combination of MR hardware, advanced acquisition techniques and various MR contrast mechanisms have enabled recent progress in functional neuroimaging. However, these advanced fMRI practices have only been applied to a handful of neuroscience questions to date, with the majority of the neuroscience community still using conventional imaging techniques. We thus discuss upcoming challenges and possibilities for fMRI technology development in human neuroscience. We hope that readers interested in functional brain imaging acquire an understanding of current and novel developments and potential future applications, even if they don't have a background in MR physics or engineering. We summarize the capabilities of standard fMRI acquisition schemes with pointers to relevant literature and comprehensive reviews and introduce more recent developments.
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Affiliation(s)
- Saskia Bollmann
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Markus Barth
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia; ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, QLD, Australia.
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Layer-dependent multiplicative effects of spatial attention on contrast responses in human early visual cortex. Prog Neurobiol 2020; 207:101897. [DOI: 10.1016/j.pneurobio.2020.101897] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 07/05/2020] [Accepted: 08/12/2020] [Indexed: 11/19/2022]
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