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Subramaniyan M, Reifman J. Can electroencephalography reveal network connectivity alterations in insomnia disorder? Sleep 2024; 47:zsae111. [PMID: 38746993 DOI: 10.1093/sleep/zsae111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2024] Open
Affiliation(s)
- Manivannan Subramaniyan
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Jaques Reifman
- Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD, USA
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2
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Kamagata K, Andica C, Uchida W, Takabayashi K, Saito Y, Lukies M, Hagiwara A, Fujita S, Akashi T, Wada A, Hori M, Kamiya K, Zalesky A, Aoki S. Advancements in Diffusion MRI Tractography for Neurosurgery. Invest Radiol 2024; 59:13-25. [PMID: 37707839 DOI: 10.1097/rli.0000000000001015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2023]
Abstract
ABSTRACT Diffusion magnetic resonance imaging tractography is a noninvasive technique that enables the visualization and quantification of white matter tracts within the brain. It is extensively used in preoperative planning for brain tumors, epilepsy, and functional neurosurgical procedures such as deep brain stimulation. Over the past 25 years, significant advancements have been made in imaging acquisition, fiber direction estimation, and tracking methods, resulting in considerable improvements in tractography accuracy. The technique enables the mapping of functionally critical pathways around surgical sites to avoid permanent functional disability. When the limitations are adequately acknowledged and considered, tractography can serve as a valuable tool to safeguard critical white matter tracts and provides insight regarding changes in normal white matter and structural connectivity of the whole brain beyond local lesions. In functional neurosurgical procedures such as deep brain stimulation, it plays a significant role in optimizing stimulation sites and parameters to maximize therapeutic efficacy and can be used as a direct target for therapy. These insights can aid in patient risk stratification and prognosis. This article aims to discuss state-of-the-art tractography methodologies and their applications in preoperative planning and highlight the challenges and new prospects for the use of tractography in daily clinical practice.
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Affiliation(s)
- Koji Kamagata
- From the Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan (K.K., C.A., W.U., K.T., Y.S., A.H., S.F., T.A., A.W., S.A.); Faculty of Health Data Science, Juntendo University, Chiba, Japan (C.A., S.A.); Department of Radiology, Alfred Health, Melbourne, Victoria, Australia (M.L.); Department of Radiology, University of Tokyo, Tokyo, Japan (S.F.); Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan (M.H., K.K.); Melbourne Neuropsychiatry Center, Department of Psychiatry, The University of Melbourne and Melbourne Health, Parkville, Victoria, Australia (A.Z.); and Melbourne School of Engineering, University of Melbourne, Melbourne, Victoria, Australia (A.Z.)
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Zeng X, Puonti O, Sayeed A, Herisse R, Mora J, Evancic K, Varadarajan D, Balbastre Y, Costantini I, Scardigli M, Ramazzotti J, DiMeo D, Mazzamuto G, Pesce L, Brady N, Cheli F, Pavone FS, Hof PR, Frost R, Augustinack J, van der Kouwe A, Iglesias JE, Fischl B. Segmentation of supragranular and infragranular layers in ultra-high resolution 7T ex vivo MRI of the human cerebral cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.06.570416. [PMID: 38106176 PMCID: PMC10723438 DOI: 10.1101/2023.12.06.570416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Accurate labeling of specific layers in the human cerebral cortex is crucial for advancing our understanding of neurodevelopmental and neurodegenerative disorders. Leveraging recent advancements in ultra-high resolution ex vivo MRI, we present a novel semi-supervised segmentation model capable of identifying supragranular and infragranular layers in ex vivo MRI with unprecedented precision. On a dataset consisting of 17 whole-hemisphere ex vivo scans at 120 μm, we propose a multi-resolution U-Nets framework (MUS) that integrates global and local structural information, achieving reliable segmentation maps of the entire hemisphere, with Dice scores over 0.8 for supra- and infragranular layers. This enables surface modeling, atlas construction, anomaly detection in disease states, and cross-modality validation, while also paving the way for finer layer segmentation. Our approach offers a powerful tool for comprehensive neuroanatomical investigations and holds promise for advancing our mechanistic understanding of progression of neurodegenerative diseases.
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Affiliation(s)
- Xiangrui Zeng
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Oula Puonti
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Areej Sayeed
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Rogeny Herisse
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Jocelyn Mora
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Kathryn Evancic
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Divya Varadarajan
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Yael Balbastre
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Irene Costantini
- National Research Council - National Institute of Optics (CNR-INO), Sesto Fiorentino, Italy
- European Laboratory for Non-Linear Spectroscopy (LENS), Sesto Fiorentino, Italy
- Department of Biology, University of Florence, Italy
| | - Marina Scardigli
- European Laboratory for Non-Linear Spectroscopy (LENS), Sesto Fiorentino, Italy
| | | | - Danila DiMeo
- European Laboratory for Non-Linear Spectroscopy (LENS), Sesto Fiorentino, Italy
| | - Giacomo Mazzamuto
- National Research Council - National Institute of Optics (CNR-INO), Sesto Fiorentino, Italy
- European Laboratory for Non-Linear Spectroscopy (LENS), Sesto Fiorentino, Italy
- Department of Physics and Astronomy, University of Florence, Italy
| | - Luca Pesce
- European Laboratory for Non-Linear Spectroscopy (LENS), Sesto Fiorentino, Italy
| | - Niamh Brady
- European Laboratory for Non-Linear Spectroscopy (LENS), Sesto Fiorentino, Italy
| | - Franco Cheli
- European Laboratory for Non-Linear Spectroscopy (LENS), Sesto Fiorentino, Italy
| | - Francesco Saverio Pavone
- National Research Council - National Institute of Optics (CNR-INO), Sesto Fiorentino, Italy
- European Laboratory for Non-Linear Spectroscopy (LENS), Sesto Fiorentino, Italy
- Department of Physics and Astronomy, University of Florence, Italy
| | - Patrick R. Hof
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert Frost
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Jean Augustinack
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - André van der Kouwe
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Juan Eugenio Iglesias
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Bruce Fischl
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
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Boeken OJ, Cieslik EC, Langner R, Markett S. Characterizing functional modules in the human thalamus: coactivation-based parcellation and systems-level functional decoding. Brain Struct Funct 2023; 228:1811-1834. [PMID: 36547707 PMCID: PMC10516793 DOI: 10.1007/s00429-022-02603-w] [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: 08/31/2022] [Accepted: 12/08/2022] [Indexed: 12/24/2022]
Abstract
The human thalamus relays sensory signals to the cortex and facilitates brain-wide communication. The thalamus is also more directly involved in sensorimotor and various cognitive functions but a full characterization of its functional repertoire, particularly in regard to its internal anatomical structure, is still outstanding. As a putative hub in the human connectome, the thalamus might reveal its functional profile only in conjunction with interconnected brain areas. We therefore developed a novel systems-level Bayesian reverse inference decoding that complements the traditional neuroinformatics approach towards a network account of thalamic function. The systems-level decoding considers the functional repertoire (i.e., the terms associated with a brain region) of all regions showing co-activations with a predefined seed region in a brain-wide fashion. Here, we used task-constrained meta-analytic connectivity-based parcellation (MACM-CBP) to identify thalamic subregions as seed regions and applied the systems-level decoding to these subregions in conjunction with functionally connected cortical regions. Our results confirm thalamic structure-function relationships known from animal and clinical studies and revealed further associations with language, memory, and locomotion that have not been detailed in the cognitive neuroscience literature before. The systems-level decoding further uncovered large systems engaged in autobiographical memory and nociception. We propose this novel decoding approach as a useful tool to detect previously unknown structure-function relationships at the brain network level, and to build viable starting points for future studies.
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Affiliation(s)
- Ole J Boeken
- Faculty of Life Sciences, Department of Molecular Psychology, Humboldt-Universität Zu Berlin, Rudower Chaussee 18, 12489, Berlin, Germany.
| | - Edna C Cieslik
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Robert Langner
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Sebastian Markett
- Faculty of Life Sciences, Department of Molecular Psychology, Humboldt-Universität Zu Berlin, Rudower Chaussee 18, 12489, Berlin, Germany
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Groot JM, Miletic S, Isherwood SJS, Tse DHY, Habli S, Håberg AK, Forstmann BU, Bazin PL, Mittner M. Echoes from Intrinsic Connectivity Networks in the Subcortex. J Neurosci 2023; 43:6609-6618. [PMID: 37562962 PMCID: PMC10538587 DOI: 10.1523/jneurosci.1020-23.2023] [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: 06/01/2023] [Revised: 07/11/2023] [Accepted: 07/28/2023] [Indexed: 08/12/2023] Open
Abstract
Decades of research have greatly improved our understanding of intrinsic human brain organization in terms of functional networks and the transmodal hubs within the cortex at which they converge. However, substrates of multinetwork integration in the human subcortex are relatively uncharted. Here, we leveraged recent advances in subcortical atlasing and ultra-high field (7 T) imaging optimized for the subcortex to investigate the functional architecture of 14 individual structures in healthy adult males and females with a fully data-driven approach. We revealed that spontaneous neural activity in subcortical regions can be decomposed into multiple independent subsignals that correlate with, or "echo," the activity in functional networks across the cortex. Distinct subregions of the thalamus, striatum, claustrum, and hippocampus showed a varied pattern of echoes from attention, control, visual, somatomotor, and default mode networks, demonstrating evidence for a heterogeneous organization supportive of functional integration. Multiple network activity furthermore converged within the globus pallidus externa, substantia nigra, and ventral tegmental area but was specific to one subregion, while the amygdala and pedunculopontine nucleus preferentially affiliated with a single network, showing a more homogeneous topography. Subregional connectivity of the globus pallidus interna, subthalamic nucleus, red nucleus, periaqueductal gray, and locus coeruleus did not resemble patterns of cortical network activity. Together, these finding describe potential mechanisms through which the subcortex participates in integrated and segregated information processing and shapes the spontaneous cognitive dynamics during rest.SIGNIFICANCE STATEMENT Despite the impact of subcortical dysfunction on brain health and cognition, large-scale functional mapping of subcortical structures severely lags behind that of the cortex. Recent developments in subcortical atlasing and imaging at ultra-high field provide new avenues for studying the intricate functional architecture of the human subcortex. With a fully data-driven analysis, we reveal subregional connectivity profiles of a large set of noncortical structures, including those rarely studied in fMRI research. The results have implications for understanding how the functional organization of the subcortex facilitates integrative processing through cross-network information convergence, paving the way for future work aimed at improving our knowledge of subcortical contributions to intrinsic brain dynamics and spontaneous cognition.
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Affiliation(s)
- Josephine M Groot
- Department of Psychology, UiT-Arctic University of Norway, Tromsø, 9037, Norway
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, 1001 NK, The Netherlands
| | - Steven Miletic
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, 1001 NK, The Netherlands
| | - Scott J S Isherwood
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, 1001 NK, The Netherlands
| | - Desmond H Y Tse
- Department of Neuropsychology and Psychopharmacology, Maastricht University, Maastricht, 6200 MD, The Netherlands
| | - Sarah Habli
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, 8900, Norway
| | - Asta K Håberg
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, 8900, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim, 7006, Norway
| | - Birte U Forstmann
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, 1001 NK, The Netherlands
| | - Pierre-Louis Bazin
- Department of Psychology, UiT-Arctic University of Norway, Tromsø, 9037, Norway
- Departments of Neurophysics and Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04303, Germany
| | - Matthias Mittner
- Department of Psychology, UiT-Arctic University of Norway, Tromsø, 9037, Norway
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Kirstein CF, Güntürkün O, Ocklenburg S. Ultra-high field imaging of the amygdala - A narrative review. Neurosci Biobehav Rev 2023; 152:105245. [PMID: 37230235 DOI: 10.1016/j.neubiorev.2023.105245] [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: 01/30/2023] [Revised: 05/11/2023] [Accepted: 05/21/2023] [Indexed: 05/27/2023]
Abstract
The amygdala is an evolutionarily conserved core structure in emotion processing and one of the key regions of interest in affective neuroscience. Results of neuroimaging studies focusing on the amygdala are, however, often heterogeneous since it is composed of functionally and neuroanatomically distinct subnuclei. Fortunately, ultra-high-field imaging offers several advances for amygdala research, most importantly more accurate representation of functional and structural properties of subnuclei and their connectivity. Most clinical studies using ultra-high-field imaging focused on major depression, suggesting either overall rightward amygdala atrophy or distinct bilateral patterns of subnuclear atrophy and hypertrophy. Other pathologies are only sparsely covered. Connectivity analyses identified widespread networks for learning and memory, stimulus processing, cognition, and social processes. They provide evidence for distinct roles of the central, basal, and basolateral nucleus, and the extended amygdala in fear and emotion processing. Amid largely sparse and ambiguous evidence, we propose theoretical and methodological considerations that will guide ultra-high-field imaging in comprehensive investigations to help disentangle the ambiguity of the amygdala's function, structure, connectivity, and clinical relevance.
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Affiliation(s)
- Cedric Fabian Kirstein
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Germany.
| | - Onur Güntürkün
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Germany; Research Center One Health Ruhr, Research Alliance Ruhr, Ruhr-University Bochum, Bochum, Germany
| | - Sebastian Ocklenburg
- Department of Biopsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Germany; Department of Psychology, MSH Medical School Hamburg, Germany; Institute for Cognitive and Affective Neuroscience, MSH Medical School Hamburg, Germany
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Fountain C, Ghuman H, Paldino M, Tamber M, Panigrahy A, Modo M. Acquisition and Analysis of Excised Neocortex from Pediatric Patients with Focal Cortical Dysplasia Using Mesoscale Diffusion MRI. Diagnostics (Basel) 2023; 13:1529. [PMID: 37174921 PMCID: PMC10177920 DOI: 10.3390/diagnostics13091529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 04/01/2023] [Accepted: 04/15/2023] [Indexed: 05/15/2023] Open
Abstract
Non-invasive classification of focal cortical dysplasia (FCD) subtypes remains challenging from a radiology perspective. Quantitative imaging biomarkers (QIBs) have the potential to distinguish subtypes that lack pathognomonic features and might help in defining the extent of abnormal connectivity associated with each FCD subtype. A key motivation of diagnostic imaging is to improve the localization of a "lesion" that can guide the surgical resection of affected tissue, which is thought to cause seizures. Conversely, surgical resections to eliminate or reduce seizures provided unique opportunities to develop magnetic resonance imaging (MRI)-based QIBs by affording long scan times to evaluate multiple contrast mechanisms at the mesoscale (0.5 mm isotropic voxel dimensions). Using ex vivo hybrid diffusion tensor imaging on a 9.4 T MRI scanner, the grey to white matter ratio of scalar indices was lower in the resected middle temporal gyrus (MTG) of two neuropathologically confirmed cases of FCD compared to non-diseased control postmortem fixed temporal lobes. In contrast, fractional anisotropy was increased within FCD and also adjacent white matter tracts. Connectivity (streamlines/mm3) in the MTG was higher in FCD, suggesting that an altered connectivity at the lesion locus can potentially provide a tangible QIB to distinguish and characterize FCD abnormalities. However, as illustrated here, a major challenge for a robust tractographical comparison lies in the considerable differences in the ex vivo processing of bioptic and postmortem samples. Mesoscale diffusion MRI has the potential to better define and characterize epileptic tissues obtained from surgical resection to advance our understanding of disease etiology and treatment.
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Affiliation(s)
- Chandler Fountain
- Department of Radiology and Medical Imaging, University of Virginia Health System, 1215 Lee St, Chartlottesville, VA 22903, USA
| | - Harmanvir Ghuman
- Department of Bioengineering, University of Pittsburgh, 302 Benedum Hall, 3700 O’Hara Street, Pititsburgh, PA 15260, USA
- McGowan Institute for Regenerative Medicine, University of Pittsburgh, 450 Technology Drive, Suite 300, Pittsburgh, PA 15219, USA
| | - Michael Paldino
- Department of Radiology, University of Pittsburgh, PUH Suite E204, 200 Lothrop Street, Pittsburgh, PA 15213, USA
| | - Mandeep Tamber
- Department of Neurological Surgery, University of Pittsburgh, 200 Lothrop Street, Suite B 400, Pittsburgh, PA 15213, USA
| | - Ashok Panigrahy
- Department of Radiology, University of Pittsburgh, PUH Suite E204, 200 Lothrop Street, Pittsburgh, PA 15213, USA
| | - Michel Modo
- Department of Bioengineering, University of Pittsburgh, 302 Benedum Hall, 3700 O’Hara Street, Pititsburgh, PA 15260, USA
- McGowan Institute for Regenerative Medicine, University of Pittsburgh, 450 Technology Drive, Suite 300, Pittsburgh, PA 15219, USA
- Department of Radiology, University of Pittsburgh, PUH Suite E204, 200 Lothrop Street, Pittsburgh, PA 15213, USA
- Centre for the Neural Basis of Behavior, University of Pittsburgh and Carnegie Mellon University, 4074 Biomedical Science Tower 3, Pittsburgh, PA 15261, USA
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Bates S, Dumoulin SO, Folkers PJM, Formisano E, Goebel R, Haghnejad A, Helmich RC, Klomp D, van der Kolk AG, Li Y, Nederveen A, Norris DG, Petridou N, Roell S, Scheenen TWJ, Schoonheim MM, Voogt I, Webb A. A vision of 14 T MR for fundamental and clinical science. MAGMA (NEW YORK, N.Y.) 2023; 36:211-225. [PMID: 37036574 PMCID: PMC10088620 DOI: 10.1007/s10334-023-01081-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 03/20/2023] [Accepted: 03/21/2023] [Indexed: 04/11/2023]
Abstract
OBJECTIVE We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set. RESEARCH FIELDS The 14 Tesla system can be considered a 'mesocope': a device capable of measuring on biologically relevant scales. In neuroscience the increased spatial resolution will anatomically resolve all layers of the cortex, cerebellum, subcortical structures, and inner nuclei. Spectroscopic imaging will simultaneously measure excitatory and inhibitory activity, characterizing the excitation/inhibition balance of neural circuits. In medical research (including brain disorders) we will visualize fine-grained patterns of structural abnormalities and relate these changes to functional and molecular changes. The significantly increased spectral resolution will make it possible to detect (dynamic changes in) individual metabolites associated with pathological pathways including molecular interactions and dynamic disease processes. CONCLUSIONS The 14 Tesla system will offer new perspectives in neuroscience and fundamental research. We anticipate that this initiative will usher in a new era of ultra-high-field MR.
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Affiliation(s)
- Steve Bates
- Tesla Engineering Ltd., Water Lane, Storrington, West Sussex, RH20 3EA, UK
| | - Serge O Dumoulin
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
- Experimental and Applied Psychology, Vrije University Amsterdam, Amsterdam, The Netherlands
- Experimental Psychology, Utrecht University, Utrecht, The Netherlands
| | | | - Elia Formisano
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | | | - Rick C Helmich
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands
- Department of Neurology, Center of Expertise for Parkinson and Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Dennis Klomp
- Radiology Department, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anja G van der Kolk
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yi Li
- Independent Researcher, Magdeburg, Germany
| | - Aart Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - David G Norris
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands.
- Erwin L. Hahn Institute for Magnetic Resonance Imaging UNESCO World Cultural Heritage Zollverein, Kokereiallee 7, Building C84, 45141, Essen, Germany.
- Department of Clinical Neurophysiology (CNPH), Faculty Science and Technology, University of Twente, Enschede, The Netherlands.
| | - Natalia Petridou
- Radiology Department, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Stefan Roell
- Neoscan Solutions GmbH, Joseph-von-Fraunhofer-Str. 6, 39106, Magdeburg, Germany
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Ingmar Voogt
- Wavetronica, Padualaan 8, 3584 CH, Utrecht, The Netherlands
| | - Andrew Webb
- Department of Radiology, C.J. Gorter MRI Centre, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands
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Kikuchi H, Jitsuishi T, Hirono S, Yamaguchi A, Iwadate Y. 2D and 3D structures of the whole-brain, directly visible from 100-micron slice 7TMRI images. INTERDISCIPLINARY NEUROSURGERY 2023. [DOI: 10.1016/j.inat.2023.101755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023] Open
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10
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A unified model for reconstruction and R 2* mapping of accelerated 7T data using the quantitative recurrent inference machine. Neuroimage 2022; 264:119680. [PMID: 36240989 DOI: 10.1016/j.neuroimage.2022.119680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 09/16/2022] [Accepted: 10/10/2022] [Indexed: 11/07/2022] Open
Abstract
Quantitative MRI (qMRI) acquired at the ultra-high field of 7 Tesla has been used in visualizing and analyzing subcortical structures. qMRI relies on the acquisition of multiple images with different scan settings, leading to extended scanning times. Data redundancy and prior information from the relaxometry model can be exploited by deep learning to accelerate the imaging process. We propose the quantitative Recurrent Inference Machine (qRIM), with a unified forward model for joint reconstruction and R2*-mapping from sparse data, embedded in a Recurrent Inference Machine (RIM), an iterative inverse problem-solving network. To study the dependency of the proposed extension of the unified forward model to network architecture, we implemented and compared a quantitative End-to-End Variational Network (qE2EVN). Experiments were performed with high-resolution multi-echo gradient echo data of the brain at 7T of a cohort study covering the entire adult life span. The error in reconstructed R2* from undersampled data relative to reference data significantly decreased for the unified model compared to sequential image reconstruction and parameter fitting using the RIM. With increasing acceleration factor, an increasing reduction in the reconstruction error was observed, pointing to a larger benefit for sparser data. Qualitatively, this was following an observed reduction of image blurriness in R2*-maps. In contrast, when using the U-Net as network architecture, a negative bias in R2* in selected regions of interest was observed. Compressed Sensing rendered accurate, but less precise estimates of R2*. The qE2EVN showed slightly inferior reconstruction quality compared to the qRIM but better quality than the U-Net and Compressed Sensing. Subcortical maturation over age measured by a linearly increasing interquartile range of R2* in the striatum was preserved up to an acceleration factor of 9. With the integrated prior of the unified forward model, the proposed qRIM can exploit the redundancy among repeated measurements and shared information between tasks, facilitating relaxometry in accelerated MRI.
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11
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Tian M, Xu F, Xia Q, Tang Y, Zhang Z, Lin X, Meng H, Feng L, Liu S. Morphological development of the human fetal striatum during the second trimester. Cereb Cortex 2022; 32:5072-5082. [PMID: 35078212 DOI: 10.1093/cercor/bhab532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 12/24/2021] [Accepted: 12/25/2021] [Indexed: 12/27/2022] Open
Abstract
The morphological development of the fetal striatum during the second trimester has remained poorly described. We manually segmented the striatum using 7.0-T MR images of the fetal specimens ranging from 14 to 22 gestational weeks. The global development of the striatum was evaluated by volume measurement. The absolute volume (Vabs) of the caudate nucleus (CN) increased linearly with gestational age, while the relative volume (Vrel) showed a quadratic growth. Both Vabs and Vrel of putamen increased linearly. Through shape analysis, the changes of local structure in developing striatum were specifically demonstrated. Except for the CN tail, the lateral and medial parts of the CN grew faster than the middle regions, with a clear rostral-caudal growth gradient as well as a distinct "outside-in" growth gradient. For putamen, the dorsal and ventral regions grew obviously faster than the other regions, with a dorsal-ventral bidirectional developmental pattern. The right CN was larger than the left, whereas there was no significant hemispheric asymmetry in the putamen. By establishing the developmental trajectories, spatial heterochrony, and hemispheric dimorphism of human fetal striatum, these data bring new insight into the fetal striatum development and provide detailed anatomical references for future striatal studies.
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Affiliation(s)
- Mimi Tian
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong 250012, China
| | - Feifei Xu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong 250012, China
| | - Qing Xia
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong 250012, China
| | - Yuchun Tang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong 250012, China
| | - Zhonghe Zhang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China.,Department of Medical Imaging, Shandong Provincial Hospital, Shandong University, Jinan, Shandong 250021, China
| | - Xiangtao Lin
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China.,Department of Medical Imaging, Shandong Provincial Hospital, Shandong University, Jinan, Shandong 250021, China
| | - Haiwei Meng
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong 250012, China
| | - Lei Feng
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong 250012, China
| | - Shuwei Liu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, China.,Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong 250012, China
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12
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Miletić S, Keuken MC, Mulder M, Trampel R, de Hollander G, Forstmann BU. 7T functional MRI finds no evidence for distinct functional subregions in the subthalamic nucleus during a speeded decision-making task. Cortex 2022; 155:162-188. [DOI: 10.1016/j.cortex.2022.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 03/18/2022] [Accepted: 06/07/2022] [Indexed: 11/03/2022]
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13
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Okada T, Fujimoto K, Fushimi Y, Akasaka T, Thuy DHD, Shima A, Sawamoto N, Oishi N, Zhang Z, Funaki T, Nakamoto Y, Murai T, Miyamoto S, Takahashi R, Isa T. Neuroimaging at 7 Tesla: a pictorial narrative review. Quant Imaging Med Surg 2022; 12:3406-3435. [PMID: 35655840 PMCID: PMC9131333 DOI: 10.21037/qims-21-969] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 02/05/2022] [Indexed: 01/26/2024]
Abstract
Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.
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Affiliation(s)
- Tomohisa Okada
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Koji Fujimoto
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Thai Akasaka
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Dinh H. D. Thuy
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Atsushi Shima
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Nobukatsu Sawamoto
- Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Oishi
- Medial Innovation Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Zhilin Zhang
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takeshi Funaki
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tadashi Isa
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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14
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Miletić S, Bazin PL, Isherwood SJS, Keuken MC, Alkemade A, Forstmann BU. Charting human subcortical maturation across the adult lifespan with in vivo 7 T MRI. Neuroimage 2022; 249:118872. [PMID: 34999202 DOI: 10.1016/j.neuroimage.2022.118872] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 12/20/2021] [Accepted: 01/03/2022] [Indexed: 12/26/2022] Open
Abstract
The human subcortex comprises hundreds of unique structures. Subcortical functioning is crucial for behavior, and disrupted function is observed in common neurodegenerative diseases. Despite their importance, human subcortical structures continue to be difficult to study in vivo. Here we provide a detailed account of 17 prominent subcortical structures and ventricles, describing their approximate iron and myelin contents, morphometry, and their age-related changes across the normal adult lifespan. The results provide compelling insights into the heterogeneity and intricate age-related alterations of these structures. They also show that the locations of many structures shift across the lifespan, which is of direct relevance for the use of standard magnetic resonance imaging atlases. The results further our understanding of subcortical morphometry and neuroimaging properties, and of normal aging processes which ultimately can improve our understanding of neurodegeneration.
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Affiliation(s)
- Steven Miletić
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands.
| | - Pierre-Louis Bazin
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands; Max Planck Institute for Human Cognitive and Brain Sciences, Departments of Neurophysics and Neurology, Stephanstraße 1A, Leipzig, Germany
| | - Scott J S Isherwood
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Max C Keuken
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Anneke Alkemade
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Birte U Forstmann
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands.
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15
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Functional ultrasound imaging: A useful tool for functional connectomics? Neuroimage 2021; 245:118722. [PMID: 34800662 DOI: 10.1016/j.neuroimage.2021.118722] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 09/15/2021] [Accepted: 11/10/2021] [Indexed: 12/28/2022] Open
Abstract
Functional ultrasound (fUS) is a hemodynamic-based functional neuroimaging technique, primarily used in animal models, that combines a high spatiotemporal resolution, a large field of view, and compatibility with behavior. These assets make fUS especially suited to interrogating brain activity at the systems level. In this review, we describe the technical capabilities offered by fUS and discuss how this technique can contribute to the field of functional connectomics. First, fUS can be used to study intrinsic functional connectivity, namely patterns of correlated activity between brain regions. In this area, fUS has made the most impact by following connectivity changes in disease models, across behavioral states, or dynamically. Second, fUS can also be used to map brain-wide pathways associated with an external event. For example, fUS has helped obtain finer descriptions of several sensory systems, and uncover new pathways implicated in specific behaviors. Additionally, combining fUS with direct circuit manipulations such as optogenetics is an attractive way to map the brain-wide connections of defined neuronal populations. Finally, technological improvements and the application of new analytical tools promise to boost fUS capabilities. As brain coverage and the range of behavioral contexts that can be addressed with fUS keep on increasing, we believe that fUS-guided connectomics will only expand in the future. In this regard, we consider the incorporation of fUS into multimodal studies combining diverse techniques and behavioral tasks to be the most promising research avenue.
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16
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Keuken MC, Alkemade A, Stevenson N, Innes RJ, Forstmann BU. Structure-function similarities in deep brain stimulation targets cross-species. Neurosci Biobehav Rev 2021; 131:1127-1135. [PMID: 34715147 DOI: 10.1016/j.neubiorev.2021.10.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 10/22/2021] [Accepted: 10/24/2021] [Indexed: 11/24/2022]
Abstract
Deep Brain Stimulation (DBS) is an effective neurosurgical treatment to alleviate motor symptoms of advanced Parkinson's disease. Due to its potential, DBS usage is rapidly expanding to target a large number of brain regions to treat a wide range of diseases and neuropsychiatric disorders. The identification and validation of new target regions heavily rely on the insights gained from rodent and primate models. Here we present a large-scale automatic meta-analysis in which the structure-function associations within and between species are compared for 21 DBS targets in humans. The results indicate that the structure-function association for the majority of the 21 included subcortical areas were conserved cross-species. A subset of structures showed overlapping functional association. This can potentially be attributed to shared brain networks and might explain why multiple brain areas are targeted for the same disease or neuropsychiatric disorder.
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Affiliation(s)
- Max C Keuken
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Nieuwe Achtergracht 129B, Postbus 15926, 1001 NK, Amsterdam, The Netherlands.
| | - Anneke Alkemade
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Nieuwe Achtergracht 129B, Postbus 15926, 1001 NK, Amsterdam, The Netherlands
| | - Niek Stevenson
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Nieuwe Achtergracht 129B, Postbus 15926, 1001 NK, Amsterdam, The Netherlands
| | - Reilly J Innes
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Nieuwe Achtergracht 129B, Postbus 15926, 1001 NK, Amsterdam, The Netherlands; Newcastle Cognition Lab, University of Newcastle, Callaghan, NSW, Australia
| | - Birte U Forstmann
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Nieuwe Achtergracht 129B, Postbus 15926, 1001 NK, Amsterdam, The Netherlands
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17
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Isaacs BR, Heijmans M, Kuijf ML, Kubben PL, Ackermans L, Temel Y, Keuken MC, Forstmann BU. Variability in subthalamic nucleus targeting for deep brain stimulation with 3 and 7 Tesla magnetic resonance imaging. NEUROIMAGE-CLINICAL 2021; 32:102829. [PMID: 34560531 PMCID: PMC8463907 DOI: 10.1016/j.nicl.2021.102829] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/12/2021] [Accepted: 09/12/2021] [Indexed: 12/13/2022]
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective surgical treatment for Parkinson's disease (PD). Side-effects may, however, be induced when the DBS lead is placed suboptimally. Currently, lower field magnetic resonance imaging (MRI) at 1.5 or 3 Tesla (T) is used for targeting. Ultra-high-field MRI (7 T and above) can obtain superior anatomical information and might therefore be better suited for targeting. This study aims to test whether optimized 7 T imaging protocols result in less variable targeting of the STN for DBS compared to clinically utilized 3 T images. Three DBS-experienced neurosurgeons determined the optimal STN DBS target site on three repetitions of 3 T-T2, 7 T-T2*, 7 T-R2* and 7 T-QSM images for five PD patients. The distance in millimetres between the three repetitive coordinates was used as an index of targeting variability and was compared between field strength, MRI contrast and repetition with a Bayesian ANOVA. Further, the target coordinates were registered to MNI space, and anatomical coordinates were compared between field strength, MRI contrast and repetition using a Bayesian ANOVA. The results indicate that the neurosurgeons are stable in selecting the DBS target site across MRI field strength, MRI contrast and repetitions. The analysis of the coordinates in MNI space however revealed that the actual selected location of the electrode is seemingly more ventral when using the 3 T scan compared to the 7 T scans.
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Affiliation(s)
- Bethany R Isaacs
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands; Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Margot Heijmans
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands.
| | - Mark L Kuijf
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Pieter L Kubben
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Linda Ackermans
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Yasin Temel
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Max C Keuken
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
| | - Birte U Forstmann
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
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18
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Copeland A, Silver E, Korja R, Lehtola SJ, Merisaari H, Saukko E, Sinisalo S, Saunavaara J, Lähdesmäki T, Parkkola R, Nolvi S, Karlsson L, Karlsson H, Tuulari JJ. Infant and Child MRI: A Review of Scanning Procedures. Front Neurosci 2021; 15:666020. [PMID: 34321992 PMCID: PMC8311184 DOI: 10.3389/fnins.2021.666020] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 05/04/2021] [Indexed: 12/13/2022] Open
Abstract
Magnetic resonance imaging (MRI) is a safe method to examine human brain. However, a typical MR scan is very sensitive to motion, and it requires the subject to lie still during the acquisition, which is a major challenge for pediatric scans. Consequently, in a clinical setting, sedation or general anesthesia is often used. In the research setting including healthy subjects anesthetics are not recommended for ethical reasons and potential longer-term harm. Here we review the methods used to prepare a child for an MRI scan, but also on the techniques and tools used during the scanning to enable a successful scan. Additionally, we critically evaluate how studies have reported the scanning procedure and success of scanning. We searched articles based on special subject headings from PubMed and identified 86 studies using brain MRI in healthy subjects between 0 and 6 years of age. Scan preparations expectedly depended on subject's age; infants and young children were scanned asleep after feeding and swaddling and older children were scanned awake. Comparing the efficiency of different procedures was difficult because of the heterogeneous reporting of the used methods and the success rates. Based on this review, we recommend more detailed reporting of scanning procedure to help find out which are the factors affecting the success of scanning. In the long term, this could help the research field to get high quality data, but also the clinical field to reduce the use of anesthetics. Finally, we introduce the protocol used in scanning 2 to 5-week-old infants in the FinnBrain Birth Cohort Study, and tips for calming neonates during the scans.
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Affiliation(s)
- Anni Copeland
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Eero Silver
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Riikka Korja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychology, University of Turku, Turku, Finland
| | - Satu J. Lehtola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland
| | - Ekaterina Saukko
- Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland
| | - Susanne Sinisalo
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Tuire Lähdesmäki
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Pediatric Neurology, Turku University Hospital, University of Turku, Turku, Finland
| | - Riitta Parkkola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, University of Turku, Turku, Finland
| | - Saara Nolvi
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychology and Speech-Language Pathology, Turku Institute for Advanced Studies, University of Turku, Turku, Finland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku, Turku, Finland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Jetro J. Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
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19
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Schneider TM, Ma J, Wagner P, Behl N, Nagel AM, Ladd ME, Heiland S, Bendszus M, Straub S. Multiparametric MRI for Characterization of the Basal Ganglia and the Midbrain. Front Neurosci 2021; 15:661504. [PMID: 34234639 PMCID: PMC8255625 DOI: 10.3389/fnins.2021.661504] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 05/17/2021] [Indexed: 12/02/2022] Open
Abstract
Objectives To characterize subcortical nuclei by multi-parametric quantitative magnetic resonance imaging. Materials and Methods: The following quantitative multiparametric MR data of five healthy volunteers were acquired on a 7T MRI system: 3D gradient echo (GRE) data for the calculation of quantitative susceptibility maps (QSM), GRE sequences with and without off-resonant magnetic transfer pulse for magnetization transfer ratio (MTR) calculation, a magnetization−prepared 2 rapid acquisition gradient echo sequence for T1 mapping, and (after a coil change) a density-adapted 3D radial pulse sequence for 23Na imaging. First, all data were co-registered to the GRE data, volumes of interest (VOIs) for 21 subcortical structures were drawn manually for each volunteer, and a combined voxel-wise analysis of the four MR contrasts (QSM, MTR, T1, 23Na) in each structure was conducted to assess the quantitative, MR value-based differentiability of structures. Second, a machine learning algorithm based on random forests was trained to automatically classify the groups of multi-parametric voxel values from each VOI according to their association to one of the 21 subcortical structures. Results The analysis of the integrated multimodal visualization of quantitative MR values in each structure yielded a successful classification among nuclei of the ascending reticular activation system (ARAS), the limbic system and the extrapyramidal system, while classification among (epi-)thalamic nuclei was less successful. The machine learning-based approach facilitated quantitative MR value-based structure classification especially in the group of extrapyramidal nuclei and reached an overall accuracy of 85% regarding all selected nuclei. Conclusion Multimodal quantitative MR enabled excellent differentiation of a wide spectrum of subcortical nuclei with reasonable accuracy and may thus enable sensitive detection of disease and nucleus-specific MR-based contrast alterations in the future.
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Affiliation(s)
- Till M Schneider
- Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany
| | - Jackie Ma
- Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany
| | - Patrick Wagner
- Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany
| | - Nicolas Behl
- Division of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Armin M Nagel
- Division of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany.,Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany.,Faculty of Physics and Astronomy and Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany
| | - Sina Straub
- Division of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
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20
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Saban W, Raz G, Grabner RH, Gabay S, Kadosh RC. Primitive visual channels have a causal role in cognitive transfer. Sci Rep 2021; 11:8759. [PMID: 33888804 PMCID: PMC8062541 DOI: 10.1038/s41598-021-88271-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 03/15/2021] [Indexed: 11/08/2022] Open
Abstract
Scientific investigations have long emphasized the cortex's role in cognitive transfer and arithmetic abilities. To date, however, this assumption has not been thoroughly empirically investigated. Here we demonstrated that primitive mechanisms-lower visual channels-have a causal role in cognitive transfer of complex skills such as symbolic arithmetic. We found that exposing only one monocular channel to a visuospatial training resulted in a larger transfer effect in the trained monocular channel compared to the untrained monocular channel. Such cognitive transfer was found for both novel figural-spatial problems (near transfer) and novel subtraction problems (far transfer). Importantly, the benefits of the trained eye were not observed in old problems and in other tasks that did not involve visuospatial abilities (the Stroop task, a multiplication task). These results challenge the exclusive role of the cortex in cognitive transfer and complex arithmetic. In addition, the results suggest a new mechanism for the emergence of cognitive skills, that could be shared across different species.
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Affiliation(s)
- William Saban
- Department of Psychology, IIPDM, University of Haifa, Haifa, Israel.
- Department of Psychology, Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.
| | - Gal Raz
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | | | - Shai Gabay
- Department of Psychology, IIPDM, University of Haifa, Haifa, Israel.
| | - Roi Cohen Kadosh
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
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21
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Alkemade A, Forstmann BU. Imaging of the human subthalamic nucleus. HANDBOOK OF CLINICAL NEUROLOGY 2021; 180:403-416. [PMID: 34225944 DOI: 10.1016/b978-0-12-820107-7.00025-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The human subthalamic nucleus (STN) is a small lens shaped iron rich nucleus, which has gained substantial interest as a target for deep brain stimulation surgery for a variety of movement disorders. The internal anatomy of the human STN has not been fully elucidated, and an intensive debate, discussing the level of overlap between putative limbic, associative, and motor zones within the STN is still ongoing. In this chapter, we have summarized anatomical information obtained using different neuroimaging modalities focusing on the anatomy of the STN. Additionally, we have highlighted a number of major challenges faced when using magnetic resonance imaging (MRI) approaches for the visualization of small iron rich deep brain structures such as the STN. In vivo MRI and postmortem microscopy efforts provide valuable complementary information on the internal structure of the STN, although the results are not always fully aligned. Finally, we provide an outlook on future efforts that could contribute to the development of an integrative research approach that will help with the reconciliation of seemingly divergent results across research approaches.
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Affiliation(s)
- Anneke Alkemade
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
| | - Birte U Forstmann
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
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22
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Isaacs BR, Mulder MJ, Groot JM, van Berendonk N, Lute N, Bazin PL, Forstmann BU, Alkemade A. 3 versus 7 Tesla magnetic resonance imaging for parcellations of subcortical brain structures in clinical settings. PLoS One 2020; 15:e0236208. [PMID: 33232325 PMCID: PMC7685480 DOI: 10.1371/journal.pone.0236208] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 11/06/2020] [Indexed: 12/14/2022] Open
Abstract
7 Tesla (7T) magnetic resonance imaging holds great promise for improved visualization of the human brain for clinical purposes. To assess whether 7T is superior regarding localization procedures of small brain structures, we compared manual parcellations of the red nucleus, subthalamic nucleus, substantia nigra, globus pallidus interna and externa. These parcellations were created on a commonly used clinical anisotropic clinical 3T with an optimized isotropic (o)3T and standard 7T scan. The clinical 3T MRI scans did not allow delineation of an anatomically plausible structure due to its limited spatial resolution. o3T and 7T parcellations were directly compared. We found that 7T outperformed the o3T MRI as reflected by higher Dice scores, which were used as a measurement of interrater agreement for manual parcellations on quantitative susceptibility maps. This increase in agreement was associated with higher contrast to noise ratios for smaller structures, but not for the larger globus pallidus segments. Additionally, control-analyses were performed to account for potential biases in manual parcellations by assessing semi-automatic parcellations. These results showed a higher consistency for structure volumes for 7T compared to optimized 3T which illustrates the importance of the use of isotropic voxels for 3D visualization of the surgical target area. Together these results indicate that 7T outperforms c3T as well as o3T given the constraints of a clinical setting.
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Affiliation(s)
- Bethany R. Isaacs
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Department of Experimental Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Martijn J. Mulder
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Psychology and Social Sciences, University of Utrecht, Utrecht, The Netherlands
| | - Josephine M. Groot
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Nikita van Berendonk
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Nicky Lute
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Clinical Neuropsychology, Vrije University, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Max Planck Institute for Human, Cognitive and Brain Sciences, Leipzig, Germany
| | - Birte U. Forstmann
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Anneke Alkemade
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
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23
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Isaacs BR, Keuken MC, Alkemade A, Temel Y, Bazin PL, Forstmann BU. Methodological Considerations for Neuroimaging in Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson's Disease Patients. J Clin Med 2020; 9:E3124. [PMID: 32992558 PMCID: PMC7600568 DOI: 10.3390/jcm9103124] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 09/17/2020] [Accepted: 09/25/2020] [Indexed: 12/17/2022] Open
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus is a neurosurgical intervention for Parkinson's disease patients who no longer appropriately respond to drug treatments. A small fraction of patients will fail to respond to DBS, develop psychiatric and cognitive side-effects, or incur surgery-related complications such as infections and hemorrhagic events. In these cases, DBS may require recalibration, reimplantation, or removal. These negative responses to treatment can partly be attributed to suboptimal pre-operative planning procedures via direct targeting through low-field and low-resolution magnetic resonance imaging (MRI). One solution for increasing the success and efficacy of DBS is to optimize preoperative planning procedures via sophisticated neuroimaging techniques such as high-resolution MRI and higher field strengths to improve visualization of DBS targets and vasculature. We discuss targeting approaches, MRI acquisition, parameters, and post-acquisition analyses. Additionally, we highlight a number of approaches including the use of ultra-high field (UHF) MRI to overcome limitations of standard settings. There is a trade-off between spatial resolution, motion artifacts, and acquisition time, which could potentially be dissolved through the use of UHF-MRI. Image registration, correction, and post-processing techniques may require combined expertise of traditional radiologists, clinicians, and fundamental researchers. The optimization of pre-operative planning with MRI can therefore be best achieved through direct collaboration between researchers and clinicians.
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Affiliation(s)
- Bethany R. Isaacs
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
- Department of Experimental Neurosurgery, Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands;
| | - Max C. Keuken
- Municipality of Amsterdam, Services & Data, Cluster Social, 1000 AE Amsterdam, The Netherlands;
| | - Anneke Alkemade
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
| | - Yasin Temel
- Department of Experimental Neurosurgery, Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands;
| | - Pierre-Louis Bazin
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
- Max Planck Institute for Human Cognitive and Brain Sciences, D-04103 Leipzig, Germany
| | - Birte U. Forstmann
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
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24
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Novel imaging techniques to study postmortem human fetal anatomy: a systematic review on microfocus-CT and ultra-high-field MRI. Eur Radiol 2019; 30:2280-2292. [PMID: 31834508 PMCID: PMC7062658 DOI: 10.1007/s00330-019-06543-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 10/10/2019] [Accepted: 10/23/2019] [Indexed: 01/07/2023]
Abstract
Background MRI and CT have been extensively used to study fetal anatomy for research and diagnostic purposes, enabling minimally invasive autopsy and giving insight in human fetal development. Novel (contrast-enhanced) microfocus CT (micro-CT) and ultra-high-field (≥ 7.0 T) MRI (UHF-MRI) techniques now enable micron-level resolution that combats the disadvantages of low-field MRI and conventional CT. Thereby, they might be suitable to study fetal anatomy in high detail and, in time, contribute to the postmortem diagnosis of fetal conditions. Objectives (1) To systematically examine the usability of micro-CT and UHF-MRI to study postmortem human fetal anatomy, and (2) to analyze factors that govern success at each step of the specimen preparation and imaging. Method MEDLINE and EMBASE were systematically searched to identify publications on fetal imaging by micro-CT or UHF-MRI. Scanning protocols were summarized and best practices concerning specimen preparation and imaging were enumerated. Results Thirty-two publications reporting on micro-CT and UHF-MRI were included. The majority of the publications focused on imaging organs separately and seven publications focused on whole body imaging, demonstrating the possibility of visualization of small anatomical structures with a resolution well below 100 μm. When imaging soft tissues by micro-CT, the fetus should be stained by immersion in Lugol’s staining solution. Conclusion Micro-CT and UHF-MRI are both excellent imaging techniques to provide detailed images of gross anatomy of human fetuses. The present study offers an overview of the current best practices when using micro-CT and/or UHF-MRI to study fetal anatomy for clinical and research purposes. Key Points • Micro-CT and UHF-MRI can both be used to study postmortem human fetal anatomy for clinical and research purposes. • Micro-CT enables high-resolution imaging of fetal specimens in relatively short scanning time. However, tissue staining using a contrast solution is necessary to enable soft-tissue visualization. • UHF-MRI enables high-resolution imaging of fetal specimens, without the necessity of prior staining, but with the drawback of long scanning time. Electronic supplementary material The online version of this article (10.1007/s00330-019-06543-8) contains supplementary material, which is available to authorized users.
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25
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Maruyama S, Fukunaga M, Fautz HP, Heidemann R, Sadato N. Comparison of 3T and 7T MRI for the visualization of globus pallidus sub-segments. Sci Rep 2019; 9:18357. [PMID: 31797993 PMCID: PMC6892946 DOI: 10.1038/s41598-019-54880-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 11/20/2019] [Indexed: 12/17/2022] Open
Abstract
The success of deep brain stimulation (DBS) targeting the internal globus pallidus (GPi) depends on the accuracy of electrode localization inside the GPi. In this study, we sought to compare visualization of the medial medullary lamina (MML) and accessory medullary lamina (AML) between proton density-weighted (PDW) and T2-weighted (T2W) sequences on 3T and 7T MRI scanners. Eleven healthy participants (five men and six women; age, 19–28 years; mean, 21.5) and one 61-year-old man were scanned using two-dimensional turbo spin-echo PDW and T2W sequences on 3T and 7T MRI scanners with a 32-channel receiver head coil and a single-channel transmission coil. Profiles of signal intensity were obtained from the pixel values of straight lines over the GP regions crossing the MML and AML. Contrast ratios (CRs) for GPe/MML, GPie/MML, GPie/AML, and GPii/AML were calculated. Qualitatively, 7T visualized both the MML and AML, whereas 3T visualized the MML less clearly and hardly depicted the AML. The T2W sequence at 7T yielded significantly higher CRs for GPie/MML, GPie/AML, and GPii/AML than the PDW sequence at 7T or 3T. The T2W sequence at 7T allows visualization of the internal structures of GPi segments with high signal intensity and contrast.
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Affiliation(s)
- Shuki Maruyama
- Department of System Neuroscience, Division of Cerebral Integration, National Institute for Physiological Sciences (NIPS), 38 Nishigonaka, Myodaiji, Okazaki, Aichi, 444-8585, Japan.,Department of Physiological Sciences, School of Life Science, SOKENDAI (The Graduate University for Advanced Studies), Shonan Village, Hayama, Kanagawa, 240-0193, Japan
| | - Masaki Fukunaga
- Department of System Neuroscience, Division of Cerebral Integration, National Institute for Physiological Sciences (NIPS), 38 Nishigonaka, Myodaiji, Okazaki, Aichi, 444-8585, Japan.,Department of Physiological Sciences, School of Life Science, SOKENDAI (The Graduate University for Advanced Studies), Shonan Village, Hayama, Kanagawa, 240-0193, Japan
| | - Hans-Peter Fautz
- Siemens Healthineers, Allee am Roethelheimpark 2, 91052, Erlangen, Germany
| | - Robin Heidemann
- Siemens Healthineers, Allee am Roethelheimpark 2, 91052, Erlangen, Germany
| | - Norihiro Sadato
- Department of System Neuroscience, Division of Cerebral Integration, National Institute for Physiological Sciences (NIPS), 38 Nishigonaka, Myodaiji, Okazaki, Aichi, 444-8585, Japan. .,Department of Physiological Sciences, School of Life Science, SOKENDAI (The Graduate University for Advanced Studies), Shonan Village, Hayama, Kanagawa, 240-0193, Japan.
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26
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Isaacs BR, Trutti AC, Pelzer E, Tittgemeyer M, Temel Y, Forstmann BU, Keuken MC. Cortico-basal white matter alterations occurring in Parkinson's disease. PLoS One 2019; 14:e0214343. [PMID: 31425517 PMCID: PMC6699705 DOI: 10.1371/journal.pone.0214343] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 07/17/2019] [Indexed: 01/01/2023] Open
Abstract
Magnetic resonance imaging studies typically use standard anatomical atlases for identification and analyses of (patho-)physiological effects on specific brain areas; these atlases often fail to incorporate neuroanatomical alterations that may occur with both age and disease. The present study utilizes Parkinson's disease and age-specific anatomical atlases of the subthalamic nucleus for diffusion tractography, assessing tracts that run between the subthalamic nucleus and a-priori defined cortical areas known to be affected by Parkinson's disease. The results show that the strength of white matter fiber tracts appear to remain structurally unaffected by disease. Contrary to that, Fractional Anisotropy values were shown to decrease in Parkinson's disease patients for connections between the subthalamic nucleus and the pars opercularis of the inferior frontal gyrus, anterior cingulate cortex, the dorsolateral prefrontal cortex and the pre-supplementary motor, collectively involved in preparatory motor control, decision making and task monitoring. While the biological underpinnings of fractional anisotropy alterations remain elusive, they may nonetheless be used as an index of Parkinson's disease. Moreover, we find that failing to account for structural changes occurring in the subthalamic nucleus with age and disease reduce the accuracy and influence the results of tractography, highlighting the importance of using appropriate atlases for tractography.
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Affiliation(s)
- Bethany. R. Isaacs
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
- Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Anne. C. Trutti
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
- Cognitive Psychology, University of Leiden, Leiden, the Netherlands
| | - Esther Pelzer
- Translational Neurocircuitry, Max Planck Institute for Metabolism Research, Cologne, Germany
- Department of Neurology, University Clinics, Cologne, Germany
| | - Marc Tittgemeyer
- Translational Neurocircuitry, Max Planck Institute for Metabolism Research, Cologne, Germany
- Department of Neurology, University Clinics, Cologne, Germany
| | - Yasin Temel
- Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Birte. U. Forstmann
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
| | - Max. C. Keuken
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
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27
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Neuroimaging Technological Advancements for Targeting in Functional Neurosurgery. Curr Neurol Neurosci Rep 2019; 19:42. [DOI: 10.1007/s11910-019-0961-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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28
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Mulder MJ, Keuken MC, Bazin PL, Alkemade A, Forstmann BU. Size and shape matter: The impact of voxel geometry on the identification of small nuclei. PLoS One 2019; 14:e0215382. [PMID: 30978242 PMCID: PMC6461289 DOI: 10.1371/journal.pone.0215382] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 04/01/2019] [Indexed: 12/28/2022] Open
Abstract
How, and to what extent do size and shape of a voxel measured with magnetic resonance imaging (MRI) affect the ability to visualize small brain nuclei? Despite general consensus that voxel geometry affects volumetric properties of regions of interest, particularly those of small brain nuclei, no quantitative data on the influence of voxel size and shape on labeling accuracy is available. Using simulations, we investigated the selective influence of voxel geometry by reconstructing simulated ellipsoid structures with voxels varying in shape and size. For each reconstructed ellipsoid, we calculated differences in volume and similarity between the labeled volume and the predefined dimensions of the ellipsoid. Probability functions were derived from one or two individual raters and a simulated ground truth for reference. As expected, larger voxels (i.e., coarser resolution) and increasing anisotropy results in increased deviations of both volume and shape measures, which is of particular relevance for small brain structures. Our findings clearly illustrate the anatomical inaccuracies introduced by the application of large and/or anisotropic voxels. To ensure deviations occur within the acceptable range (Dice coefficient scores; DCS > 0.75, corresponding to < 57% volume deviation), the volume of isotropic voxels should not exceed 5% of the total volume of the region of interest. When high accuracy is required (DCS > 0.90, corresponding to a < 19% volume deviation), the volumes of isotropic voxels should not exceed 0.08%, of the total volume. Finally, when large anisotropic factors (>3) are used, and the ellipsoid is orthogonal to the slice axes, having its long axis in the imaging plane, the voxel volume should not exceed 0.005% of the total volume. This allows sufficient compensation of anisotropy effects, in order to reach accuracy in the acceptable range (DCS > 0.75, corresponding to >57% volume deviation).
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Affiliation(s)
- Martijn J Mulder
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands.,Experimental Psychology, Utrecht University, Utrecht, the Netherlands
| | - Max C Keuken
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands.,Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Anneke Alkemade
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
| | - Birte U Forstmann
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
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29
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Quantifying the contrast of the human locus coeruleus in vivo at 7 Tesla MRI. PLoS One 2019; 14:e0209842. [PMID: 30726221 PMCID: PMC6364884 DOI: 10.1371/journal.pone.0209842] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Accepted: 12/12/2018] [Indexed: 12/31/2022] Open
Abstract
The locus coeruleus is a small brainstem nucleus which contains neuromelanin cells and is involved in a number of cognitive functions such as attention, arousal and stress, as well as several neurological and psychiatric disorders. Locus coeruleus imaging in vivo is generally performed using a T1-weighted turbo spin echo MRI sequence at 3 Tesla (T). However, imaging at high magnetic field strength can increase the signal-to-noise ratio and offers the possibility of imaging at higher spatial resolution. Therefore, in the present study we explored the possibility of visualizing the locus coeruleus at 7T. To this end, twelve healthy volunteers participated in three scanning sessions: two with 3T MRI and one with 7T MRI. The volumes of the first 3T session were used to segment the locus coeruleus, whereas the volumes of the second 3T and the 7T session were used to quantify the contrast of the locus coeruleus with several reference regions across eight different structural sequences. The results indicate that several of the 7T sequences provide detectable contrast between the locus coeruleus and surrounding tissue. Of the tested sequences, a T1-weighted sequence with spectral presaturation inversion recovery (SPIR) seems the most promising method for visualizing the locus coeruleus at ultra-high field MRI. While there is insufficient evidence to prefer the 7T SPIR sequence over the 3T TSE sequence, the isotropic voxels at 7T are an important advantage when visualizing small structures such as the locus coeruleus.
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30
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Caan MWA, Bazin PL, Marques JP, de Hollander G, Dumoulin SO, van der Zwaag W. MP2RAGEME: T 1 , T 2 * , and QSM mapping in one sequence at 7 tesla. Hum Brain Mapp 2018; 40:1786-1798. [PMID: 30549128 PMCID: PMC6590660 DOI: 10.1002/hbm.24490] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Revised: 11/21/2018] [Accepted: 11/28/2018] [Indexed: 12/19/2022] Open
Abstract
Quantitative magnetic resonance imaging generates images of meaningful physical or chemical variables measured in physical units that allow quantitative comparisons between tissue regions and among subjects scanned at the same or different sites. Here, we show that we can acquire quantitative T1, T2*, and quantitative susceptibility mapping (QSM) information in a single acquisition, using a multi‐echo (ME) extension of the second gradient‐echo image of the MP2RAGE sequence. This combination is called MP2RAGE ME, or MP2RAGEME. The simultaneous acquisition results in large time savings, perfectly coregistered data, and minimal image quality differences compared to separately acquired data. Following a correction for residual transmit B1+‐sensitivity, quantitative T1, T2*, and QSM values were in excellent agreement with those obtained from separately acquired, also B1+‐corrected, MP2RAGE data and ME gradient echo data. The quantitative values from reference regions of interests were also in very good correspondence with literature values. From the MP2RAGEME data, we further derived a multiparametric cortical parcellation, as well as a combined arterial and venous map. In sum, our MP2RAGEME sequence has the benefit in large time savings, perfectly coregistered data and minor image quality differences.
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Affiliation(s)
- Matthan W A Caan
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands.,Amsterdam UMC, University of Amsterdam, Biomedical Engineering and Physics, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands.,Social Brain Laboratory, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - José P Marques
- Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Gilles de Hollander
- Experimental and Applied Psychology, VU University, Amsterdam, The Netherlands
| | - Serge O Dumoulin
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands.,Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands.,Experimental and Applied Psychology, VU University, Amsterdam, The Netherlands
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31
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Keuken MC, van Maanen L, Boswijk M, Forstmann BU, Steyvers M. Large scale structure-function mappings of the human subcortex. Sci Rep 2018; 8:15854. [PMID: 30367080 PMCID: PMC6203787 DOI: 10.1038/s41598-018-33796-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Accepted: 10/07/2018] [Indexed: 12/02/2022] Open
Abstract
Currently little is known about structure-function mappings in the human subcortex. Here we present a large-scale automated meta-analysis on the literature to understand the structure-function mapping in the human subcortex. The results provide converging evidence into unique large scale structure-function mappings of the human subcortex based on their functional and anatomical similarity.
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Affiliation(s)
- Max C Keuken
- University of Amsterdam, Integrative Model-based Cognitive Neuroscience research unit, Amsterdam, The Netherlands.,University of Leiden, Cognitive Psychology, Leiden, The Netherlands
| | - Leendert van Maanen
- University of Amsterdam, Integrative Model-based Cognitive Neuroscience research unit, Amsterdam, The Netherlands.,University of Amsterdam, Department of Psychological Methods, Amsterdam, The Netherlands
| | - Michiel Boswijk
- University of Amsterdam, Integrative Model-based Cognitive Neuroscience research unit, Amsterdam, The Netherlands
| | - Birte U Forstmann
- University of Amsterdam, Integrative Model-based Cognitive Neuroscience research unit, Amsterdam, The Netherlands.
| | - Mark Steyvers
- Department of Cognitive Sciences, University of California, Irvine, USA
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