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Qu S, Shi S, Quan Z, Gao Y, Wang M, Wang Y, Pan G, Lai HY, Roe AW, Zhang X. Design and application of a multimodality-compatible 1Tx/6Rx RF coil for monkey brain MRI at 7T. Neuroimage 2023; 276:120185. [PMID: 37244320 DOI: 10.1016/j.neuroimage.2023.120185] [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: 04/11/2023] [Revised: 05/09/2023] [Accepted: 05/22/2023] [Indexed: 05/29/2023] Open
Abstract
OBJECTIVE Blood-oxygen-level-dependent functional MRI allows to investigte neural activities and connectivity. While the non-human primate plays an essential role in neuroscience research, multimodal methods combining functional MRI with other neuroimaging and neuromodulation enable us to understand the brain network at multiple scales. APPROACH In this study, a tight-fitting helmet-shape receive array with a single transmit loop for anesthetized macaque brain MRI at 7T was fabricated with four openings constructed in the coil housing to accommodate multimodal devices, and the coil performance was quantitatively evaluated and compared to a commercial knee coil. In addition, experiments over three macaques with infrared neural stimulation (INS), focused ultrasound stimulation (FUS), and transcranial direct current stimulation (tDCS) were conducted. MAIN RESULTS The RF coil showed higher transmit efficiency, comparable homogeneity, improved SNR and enlarged signal coverage over the macaque brain. Infrared neural stimulation was applied to the amygdala in deep brain region, and activations in stimulation sites and connected sites were detected, with the connectivity consistent with anatomical information. Focused ultrasound stimulation was applied to the left visual cortex, and activations were acquired along the ultrasound traveling path, with all time course curves consistent with pre-designed paradigms. The existence of transcranial direct current stimulation electrodes brought no interference to the RF system, as evidenced through high-resolution MPRAGE structure images. SIGNIFICANCE This pilot study reveals the feasibility for brain investigation at multiple spatiotemporal scales, which may advance our understanding in dynamic brain networks.
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Affiliation(s)
- Shuxian Qu
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Sunhang Shi
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Zhiyan Quan
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Yang Gao
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; College of Electrical Engineering, Zhejiang University, Hangzhou, China
| | - Minmin Wang
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China
| | - Yueming Wang
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China; State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China
| | - Gang Pan
- MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China.
| | - Hsin-Yi Lai
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
| | - Anna Wang Roe
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
| | - Xiaotong Zhang
- The Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China; College of Electrical Engineering, Zhejiang University, Hangzhou, China.
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2
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Tract-specific statistics based on diffusion-weighted probabilistic tractography. Commun Biol 2022; 5:138. [PMID: 35177755 PMCID: PMC8854429 DOI: 10.1038/s42003-022-03073-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 01/24/2022] [Indexed: 11/09/2022] Open
Abstract
Diffusion-weighted neuroimaging approaches provide rich evidence for estimating the structural integrity of white matter in vivo, but typically do not assess white matter integrity for connections between two specific regions of the brain. Here, we present a method for deriving tract-specific diffusion statistics, based upon predefined regions of interest. Our approach derives a population distribution using probabilistic tractography, based on the Nathan Kline Institute (NKI) Enhanced Rockland sample. We determine the most likely geometry of a path between two regions and express this as a spatial distribution. We then estimate the average orientation of streamlines traversing this path, at discrete distances along its trajectory, and the fraction of diffusion directed along this orientation for each participant. The resulting participant-wise metrics (tract-specific anisotropy; TSA) can then be used for statistical analysis on any comparable population. Based on this method, we report both negative and positive associations between age and TSA for two networks derived from published meta-analytic studies (the “default mode” and “what-where” networks), along with more moderate sex differences and age-by-sex interactions. The proposed method can be applied to any arbitrary set of brain regions, to estimate both the spatial trajectory and DWI-based anisotropy specific to those regions. Andrew Reid et al. use publicly available data to present a method for deriving tract-specific statistics based on diffusion-weighted MRI, based upon arbitrarily-defined regions of interest. Their approach enables them to report both negative and positive associations between age and tract-specific anisotropy along with more moderate sex differences and age-by-sex interactions.
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Adam R, Schaeffer DJ, Johnston K, Menon RS, Everling S. Structural alterations in cortical and thalamocortical white matter tracts after recovery from prefrontal cortex lesions in macaques. Neuroimage 2021; 232:117919. [PMID: 33652141 DOI: 10.1016/j.neuroimage.2021.117919] [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: 06/08/2020] [Revised: 02/19/2021] [Accepted: 02/22/2021] [Indexed: 01/04/2023] Open
Abstract
Unilateral damage to the frontoparietal network typically impairs saccade target selection within the contralesional visual hemifield. Severity of deficits and the degree of recovery have been associated with widespread network dysfunction, yet it is not clear how these behavioural and functional brain changes relate with the underlying structural white matter tracts. Here, we investigated whether recovery after unilateral prefrontal cortex (PFC) lesions was associated with changes in white matter microstructure across large-scale frontoparietal cortical and thalamocortical networks. Diffusion-weighted imaging was acquired in four male rhesus macaques at pre-lesion, week 1, and week 8-16 post-lesion when target selection deficits largely recovered. Probabilistic tractography was used to reconstruct cortical frontoparietal fiber tracts, including the superior longitudinal fasciculus (SLF) and transcallosal fibers connecting the PFC or posterior parietal cortex (PPC), as well as thalamocortical fiber tracts connecting the PFC and PPC to thalamic nuclei. We found that the two animals with small PFC lesions showed increased fractional anisotropy in both cortical and thalamocortical fiber tracts when behaviour had recovered. However, we found that fractional anisotropy decreased in cortical frontoparietal tracts after larger PFC lesions yet increased in some thalamocortical tracts at the time of behavioural recovery. These findings indicate that behavioural recovery after small PFC lesions may be supported by both cortical and subcortical areas, whereas larger PFC lesions may have induced widespread structural damage and hindered compensatory remodeling in the cortical frontoparietal network.
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Affiliation(s)
- Ramina Adam
- Graduate Program in Neuroscience, University of Western Ontario, London, Canada; Robarts Research Institute, University of Western Ontario, London, Canada; The Brain and Mind Institute, University of Western Ontario, London, Canada
| | - David J Schaeffer
- Department of Neurobiology, University of Pittsburgh, PA, United States
| | - Kevin Johnston
- The Brain and Mind Institute, University of Western Ontario, London, Canada; Department of Physiology and Pharmacology, University of Western Ontario, London, Canada
| | - Ravi S Menon
- Robarts Research Institute, University of Western Ontario, London, Canada; The Brain and Mind Institute, University of Western Ontario, London, Canada; Department of Medical Biophysics, University of Western Ontario, London, Canada
| | - Stefan Everling
- Graduate Program in Neuroscience, University of Western Ontario, London, Canada; Robarts Research Institute, University of Western Ontario, London, Canada; The Brain and Mind Institute, University of Western Ontario, London, Canada; Department of Physiology and Pharmacology, University of Western Ontario, London, Canada.
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4
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Schaeffer DJ, Liu C, Silva AC, Everling S. Magnetic Resonance Imaging of Marmoset Monkeys. ILAR J 2021; 61:274-285. [PMID: 33631015 PMCID: PMC8918195 DOI: 10.1093/ilar/ilaa029] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 09/22/2020] [Accepted: 10/23/2020] [Indexed: 11/12/2022] Open
Abstract
The use of the common marmoset monkey (Callithrix jacchus) for neuroscientific research has grown markedly in the last decade. Magnetic resonance imaging (MRI) has played a significant role in establishing the extent of comparability of marmoset brain architecture with the human brain and brains of other preclinical species (eg, macaques and rodents). As a non-invasive technique, MRI allows for the flexible acquisition of the same sequences across different species in vivo, including imaging of whole-brain functional topologies not possible with more invasive techniques. Being one of the smallest New World primates, the marmoset may be an ideal nonhuman primate species to study with MRI. As primates, marmosets have an elaborated frontal cortex with features analogous to the human brain, while also having a small enough body size to fit into powerful small-bore MRI systems typically employed for rodent imaging; these systems offer superior signal strength and resolution. Further, marmosets have a rich behavioral repertoire uniquely paired with a lissencephalic cortex (like rodents). This smooth cortical surface lends itself well to MRI and also other invasive methodologies. With the advent of transgenic modification techniques, marmosets have gained significant traction as a powerful complement to canonical mammalian modelling species. Marmosets are poised to make major contributions to preclinical investigations of the pathophysiology of human brain disorders as well as more basic mechanistic explorations of the brain. The goal of this article is to provide an overview of the practical aspects of implementing MRI and fMRI in marmosets (both under anesthesia and fully awake) and discuss the development of resources recently made available for marmoset imaging.
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Affiliation(s)
- David J Schaeffer
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - CiRong Liu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Afonso C Silva
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Stefan Everling
- Department of Physiology and Pharmacology, Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
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5
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Yacoub E, Grier MD, Auerbach EJ, Lagore RL, Harel N, Adriany G, Zilverstand A, Hayden BY, Heilbronner SR, Uğurbil K, Zimmermann J. Ultra-high field (10.5 T) resting state fMRI in the macaque. Neuroimage 2020; 223:117349. [PMID: 32898683 PMCID: PMC7745777 DOI: 10.1016/j.neuroimage.2020.117349] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 08/20/2020] [Accepted: 08/31/2020] [Indexed: 01/02/2023] Open
Abstract
Resting state functional connectivity refers to the temporal correlations between spontaneous hemodynamic signals obtained using functional magnetic resonance imaging. This technique has demonstrated that the structure and dynamics of identifiable networks are altered in psychiatric and neurological disease states. Thus, resting state network organizations can be used as a diagnostic, or prognostic recovery indicator. However, much about the physiological basis of this technique is unknown. Thus, providing a translational bridge to an optimal animal model, the macaque, in which invasive circuit manipulations are possible, is of utmost importance. Current approaches to resting state measurements in macaques face unique challenges associated with signal-to-noise, the need for contrast agents limiting translatability, and within-subject designs. These limitations can, in principle, be overcome through ultra-high magnetic fields. However, imaging at magnetic fields above 7T has yet to be adapted for fMRI in macaques. Here, we demonstrate that the combination of high channel count transmitter and receiver arrays, optimized pulse sequences, and careful anesthesia regimens, allows for detailed single-subject resting state analysis at high resolutions using a 10.5 Tesla scanner. In this study, we uncover thirty spatially detailed resting state components that are highly robust across individual macaques and closely resemble the quality and findings of connectomes from large human datasets. This detailed map of the rsfMRI 'macaque connectome' will be the basis for future neurobiological circuit manipulation work, providing valuable biological insights into human connectomics.
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Affiliation(s)
- Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Mark D Grier
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States
| | - Edward J Auerbach
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Russell L Lagore
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Department of Neurosurgery, University of Minnesota, Minneapolis, MN 55455, United States
| | - Gregor Adriany
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Anna Zilverstand
- Department of Psychiatry, University of Minnesota, Minneapolis, MN 55455, United States
| | - Benjamin Y Hayden
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States; Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Sarah R Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Kamil Uğurbil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States; Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, United States.
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6
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Schröder R, Kasparbauer AM, Meyhöfer I, Steffens M, Trautner P, Ettinger U. Functional connectivity during smooth pursuit eye movements. J Neurophysiol 2020; 124:1839-1856. [PMID: 32997563 DOI: 10.1152/jn.00317.2020] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Smooth pursuit eye movements (SPEM) hold the image of a slowly moving stimulus on the fovea. The neural system underlying SPEM primarily includes visual, parietal, and frontal areas. In the present study, we investigated how these areas are functionally coupled and how these couplings are influenced by target motion frequency. To this end, healthy participants (n = 57) were instructed to follow a sinusoidal target stimulus moving horizontally at two different frequencies (0.2 Hz, 0.4 Hz). Eye movements and blood oxygen level-dependent (BOLD) activity were recorded simultaneously. Functional connectivity of the key areas of the SPEM network was investigated with a psychophysiological interaction (PPI) approach. How activity in five eye movement-related seed regions (lateral geniculate nucleus, V1, V5, posterior parietal cortex, frontal eye fields) relates to activity in other parts of the brain during SPEM was analyzed. The behavioral results showed clear deterioration of SPEM performance at higher target frequency. BOLD activity during SPEM versus fixation occurred in a geniculo-occipito-parieto-frontal network, replicating previous findings. PPI analysis yielded widespread, partially overlapping networks. In particular, frontal eye fields and posterior parietal cortex showed task-dependent connectivity to large parts of the entire cortex, whereas other seed regions demonstrated more regionally focused connectivity. Higher target frequency was associated with stronger activations in visual areas but had no effect on functional connectivity. In summary, the results confirm and extend previous knowledge regarding the neural mechanisms underlying SPEM and provide a valuable basis for further investigations such as in patients with SPEM impairments and known alterations in brain connectivity.NEW & NOTEWORTHY This study provides a comprehensive investigation of blood oxygen level-dependent (BOLD) functional connectivity during smooth pursuit eye movements. Results from a large sample of healthy participants suggest that key oculomotor regions interact closely with each other but also with regions not primarily associated with eye movements. Understanding functional connectivity during smooth pursuit is important, given its potential role as an endophenotype of psychoses.
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Affiliation(s)
| | | | - Inga Meyhöfer
- Department of Psychology, University of Bonn, Bonn, Germany
| | - Maria Steffens
- Department of Psychology, University of Bonn, Bonn, Germany
| | - Peter Trautner
- Institute for Experimental Epileptology and Cognition Research, University of Bonn, Bonn, Germany.,Core Facility MRI, Bonn Technology Campus, University of Bonn, Bonn, Germany
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7
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Grier MD, Zimmermann J, Heilbronner SR. Estimating Brain Connectivity With Diffusion-Weighted Magnetic Resonance Imaging: Promise and Peril. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2020; 5:846-854. [PMID: 32513555 PMCID: PMC7483308 DOI: 10.1016/j.bpsc.2020.04.009] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 03/20/2020] [Accepted: 04/18/2020] [Indexed: 01/22/2023]
Abstract
Diffusion-weighted magnetic resonance imaging (dMRI) is a popular tool for noninvasively assessing properties of white matter in the brain. Among other uses, dMRI data can be used to produce estimates of anatomical connectivity on the basis of tractography. However, direct comparisons of anatomical connectivity as estimated through invasive neural tract-tracing experiments and dMRI-derived connectivity have shown only a moderate relationship in nonhuman primate (particularly macaque) studies. Tractography is plagued by known problems associated with resolution, crossing fibers, and curving fibers, among others. These problems lead to deficits in both sensitivity and specificity, which trade off with each other in multiple datasets. Although not yet examined quantitatively, there is reason to believe that some large white matter bundles, those with more topographic organization, may produce more accurate results than others. Moving forward, sophisticated analytical approaches and anatomical constraints may improve tractography accuracy. However, broadly speaking, dMRI-derived estimates of brain connectivity should be approached with caution.
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Affiliation(s)
- Mark D Grier
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota; Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
| | - Sarah R Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, Minnesota.
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8
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Yang J, Li Q. Manganese-Enhanced Magnetic Resonance Imaging: Application in Central Nervous System Diseases. Front Neurol 2020; 11:143. [PMID: 32161572 PMCID: PMC7052353 DOI: 10.3389/fneur.2020.00143] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 02/07/2020] [Indexed: 12/12/2022] Open
Abstract
Manganese-enhanced magnetic resonance imaging (MEMRI) relies on the strong paramagnetism of Mn2+. Mn2+ is a calcium ion analog and can enter excitable cells through voltage-gated calcium channels. Mn2+ can be transported along the axons of neurons via microtubule-based fast axonal transport. Based on these properties, MEMRI is used to describe neuroanatomical structures, monitor neural activity, and evaluate axonal transport rates. The application of MEMRI in preclinical animal models of central nervous system (CNS) diseases can provide more information for the study of disease mechanisms. In this article, we provide a brief review of MEMRI use in CNS diseases ranging from neurodegenerative diseases to brain injury and spinal cord injury.
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Affiliation(s)
- Jun Yang
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital & Cancer Center, Kunming, China
| | - Qinqing Li
- Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital & Cancer Center, Kunming, China
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9
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Snyder AZ, Bauer AQ. Mapping Structure-Function Relationships in the Brain. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2019; 4:510-521. [PMID: 30528965 PMCID: PMC6488459 DOI: 10.1016/j.bpsc.2018.10.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Revised: 10/17/2018] [Accepted: 10/17/2018] [Indexed: 01/06/2023]
Abstract
Mapping the structural and functional connectivity of the brain is a major focus of systems neuroscience research and will help to identify causally important changes in neural circuitry responsible for behavioral dysfunction. Several methods for examining brain activity in humans have been extended to rodent and monkey models in which molecular and genetic manipulations exist for linking to human disease. In this review, which is part of a special issue focused on bridging brain connectivity information across species and spatiotemporal scales, we address mapping brain activity and neural connectivity in rodents using optogenetics in conjunction with either functional magnetic resonance imaging or optical intrinsic signal imaging. We chose to focus on these techniques because they are capable of reporting spontaneous or evoked hemodynamic activity most closely linked to human neuroimaging studies. We discuss the capabilities and limitations of blood-based imaging methods, usage of optogenetic techniques to map neural systems in rodent models, and other powerful mapping techniques for examining neural connectivity over different spatial and temporal scales. We also discuss implementing strategies for mapping brain connectivity in humans with both basic and clinical applications, and conclude with how cross-species mapping studies can be utilized to influence preclinical imaging studies and clinical practices alike.
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Affiliation(s)
- Abraham Z Snyder
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Adam Q Bauer
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri.
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10
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Deng W, Faiq MA, Liu C, Adi V, Chan KC. Applications of Manganese-Enhanced Magnetic Resonance Imaging in Ophthalmology and Visual Neuroscience. Front Neural Circuits 2019; 13:35. [PMID: 31156399 PMCID: PMC6530364 DOI: 10.3389/fncir.2019.00035] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2019] [Accepted: 04/26/2019] [Indexed: 12/21/2022] Open
Abstract
Understanding the mechanisms of vision in health and disease requires knowledge of the anatomy and physiology of the eye and the neural pathways relevant to visual perception. As such, development of imaging techniques for the visual system is crucial for unveiling the neural basis of visual function or impairment. Magnetic resonance imaging (MRI) offers non-invasive probing of the structure and function of the neural circuits without depth limitation, and can help identify abnormalities in brain tissues in vivo. Among the advanced MRI techniques, manganese-enhanced MRI (MEMRI) involves the use of active manganese contrast agents that positively enhance brain tissue signals in T1-weighted imaging with respect to the levels of connectivity and activity. Depending on the routes of administration, accumulation of manganese ions in the eye and the visual pathways can be attributed to systemic distribution or their local transport across axons in an anterograde fashion, entering the neurons through voltage-gated calcium channels. The use of the paramagnetic manganese contrast in MRI has a wide range of applications in the visual system from imaging neurodevelopment to assessing and monitoring neurodegeneration, neuroplasticity, neuroprotection, and neuroregeneration. In this review, we present four major domains of scientific inquiry where MEMRI can be put to imperative use — deciphering neuroarchitecture, tracing neuronal tracts, detecting neuronal activity, and identifying or differentiating glial activity. We deliberate upon each category studies that have successfully employed MEMRI to examine the visual system, including the delivery protocols, spatiotemporal characteristics, and biophysical interpretation. Based on this literature, we have identified some critical challenges in the field in terms of toxicity, and sensitivity and specificity of manganese enhancement. We also discuss the pitfalls and alternatives of MEMRI which will provide new avenues to explore in the future.
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Affiliation(s)
- Wenyu Deng
- NYU Langone Eye Center, Department of Ophthalmology, NYU School of Medicine, NYU Langone Health, New York University, New York, NY, United States
| | - Muneeb A Faiq
- NYU Langone Eye Center, Department of Ophthalmology, NYU School of Medicine, NYU Langone Health, New York University, New York, NY, United States
| | - Crystal Liu
- NYU Langone Eye Center, Department of Ophthalmology, NYU School of Medicine, NYU Langone Health, New York University, New York, NY, United States
| | - Vishnu Adi
- NYU Langone Eye Center, Department of Ophthalmology, NYU School of Medicine, NYU Langone Health, New York University, New York, NY, United States
| | - Kevin C Chan
- NYU Langone Eye Center, Department of Ophthalmology, NYU School of Medicine, NYU Langone Health, New York University, New York, NY, United States.,Department of Radiology, NYU School of Medicine, NYU Langone Health, New York University, New York, NY, United States.,Center for Neural Science, Faculty of Arts and Science, New York University, New York, NY, United States
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