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Glutamate is the amino acid with the highest cerebral concentration. It plays a central role in brain metabolism. It is also the principal excitatory neurotransmitter in the brain and is involved in multiple cognitive functions. Alterations of the glutamatergic system may contribute to the pathophysiology of many neurological disorders. For example, changes of glutamate availability are reported in rodents and humans during Alzheimer's and Huntington's diseases, epilepsy as well as during aging. Most studies evaluating cerebral glutamate have used invasive or spectroscopy approaches focusing on specific brain areas. Chemical Exchange Saturation Transfer imaging of glutamate (gluCEST) is a recently developed imaging technique that can be used to study relative changes in glutamate distribution in the entire brain with higher sensitivity and at higher resolution than previous techniques. It thus has strong potential clinical applications to assess glutamate changes in the brain. High field is a key condition to perform gluCEST images with a meaningful signal to noise ratio. Thus, even if some studies started to evaluate gluCEST in humans, most studies focused on rodent models that can be imaged at high magnetic field. In particular, systematic characterization of gluCEST contrast distribution throughout the whole brain has never been performed in humans or non-human primates. Here, we characterized for the first time the distribution of the gluCEST contrast in the whole brain and in large-scale networks of mouse lemur primates at 11.7 Tesla. Because of its small size, this primate can be imaged in high magnetic field systems. It is widely studied as a model of cerebral aging or Alzheimer's disease. We observed high gluCEST contrast in cerebral regions such as the nucleus accumbens, septum, basal forebrain, cortical areas 24 and 25. Age-related alterations of this biomarker were detected in the nucleus accumbens, septum, basal forebrain, globus pallidus, hypophysis, cortical areas 24, 21, 6 and in olfactory bulbs. An age-related gluCEST contrast decrease was also detected in specific neuronal networks, such as fronto-temporal and evaluative limbic networks. These results outline regional differences of gluCEST contrast and strengthen its potential to provide new biomarkers of cerebral function in primates., Competing Interests: Declaration of Competing Interest The authors do not have financial and non-financial competing interests in relation to the work described., (Copyright © 2022. Published by Elsevier Inc.)

Measures of resting-state functional connectivity allow the description of neuronal networks in humans and provide a window on brain function in normal and pathological conditions. Characterizing neuronal networks in animals is complementary to studies in humans to understand how evolution has modelled network architecture. The mouse lemur (Microcebus murinus) is one of the smallest and more phylogenetically distant primates as compared to humans. Characterizing the functional organization of its brain is critical for scientists studying this primate as well as to add a link for comparative animal studies. Here, we created the first functional atlas of mouse lemur brain and describe for the first time its cerebral networks. They were classified as two primary cortical networks (somato-motor and visual), two high-level cortical networks (fronto-parietal and fronto-temporal) and two limbic networks (sensory-limbic and evaluative-limbic). Comparison of mouse lemur and human networks revealed similarities between mouse lemur high-level cortical networks and human networks as the dorsal attentional (DAN), executive control (ECN), and default-mode networks (DMN). These networks were however not homologous, possibly reflecting differential organization of high-level networks. Finally, cerebral hubs were evaluated. They were grouped along an antero-posterior axis in lemurs while they were split into parietal and frontal clusters in humans., (Copyright © 2020. Published by Elsevier Inc.)

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The gray mouse lemur (Microcebus murinus) is a small prosimian of growing interest for studies of primate biology and evolution, and notably as a model organism of brain aging. As brain atlases are essential tools for brain investigation, the objective of the current work was to create the first 3D digital atlas of the mouse lemur brain. For this, a template image was constructed from in vivo magnetic resonance imaging (MRI) data of 34 animals. This template was then manually segmented into 40 cortical, 74 subcortical and 6 cerebro-spinal fluid (CSF) regions. Additionally, we generated probability maps of gray matter, white matter and CSF. The template, manual segmentation and probability maps, as well as imaging tools used to create and manipulate the template, can all be freely downloaded. The atlas was first used to automatically assess regional age-associated cerebral atrophy in a cohort of mouse lemurs previously studied by voxel based morphometry (VBM). Results based on the atlas were in good agreement with the VBM ones, showing age-associated atrophy in the same brain regions such as the insular, parietal or occipital cortices as well as the thalamus or hypothalamus. The atlas was also used as a tool for comparative neuroanatomy. To begin with, we compared measurements of brain regions in our MRI data with histology-based measures from a reference article largely used in previous comparative neuroanatomy studies. We found large discrepancies between our MRI-based data and those of the reference histology-based article. Next, regional brain volumes were compared amongst the mouse lemur and several other mammalian species where high quality volumetric MRI brain atlases were available, including rodents (mouse, rat) and primates (marmoset, macaque, and human). Unlike those based on histological atlases, measures from MRI atlases indicated similar cortical to cerebral volume indices in all primates, including in mouse lemurs, and lower values in mice. On the other hand, white matter to cerebral volume index increased from rodents to small primates (mouse lemurs and marmosets) to macaque, reaching their highest values in humans., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Amyloid plaques are one of the major microscopic lesions that characterize Alzheimer's disease. Current approaches to detect amyloid plaques by using magnetic resonance imaging (MRI) contrast agents require invasive procedures to penetrate the blood-brain barrier (BBB) and to deliver the contrast agent into the vicinity of amyloid plaques. Here we have developed a new protocol (US-Gd-staining) that enables the detection of amyloid plaques in the brain of an APP/PS1 transgenic mouse model of amyloidosis after intra-venous injection of a non-targeted, clinically approved MRI contrast agent (Gd-DOTA, Dotarem®) by transiently opening the BBB with unfocused ultrasound (1 MHz) and clinically approved microbubbles (Sonovue®, Bracco). This US-Gd-staining protocol can detect amyloid plaques with a short imaging time (32 min) and high in-plane resolution (29 μm). The sensitivity and resolution obtained is at least equal to that provided by MRI protocols using intra-cerebro-ventricular injection of contrast agents, a reference method used to penetrate the BBB. To our knowledge this is the first study to demonstrate the ability of MR imaging to detect amyloid plaques by using a peripheral intra-venous injection of a clinically approved NMR contrast agent., (Copyright © 2013. Published by Elsevier Inc.)

Biomarkers and technologies similar to those used in humans are essential for the follow-up of Alzheimer's disease (AD) animal models, particularly for the clarification of mechanisms and the screening and validation of new candidate treatments. In humans, changes in brain metabolism can be detected by 1-deoxy-2-[(18)F] fluoro-D-glucose PET (FDG-PET) and assessed in a user-independent manner with dedicated software, such as Statistical Parametric Mapping (SPM). FDG-PET can be carried out in small animals, but its resolution is low as compared to the size of rodent brain structures. In mouse models of AD, changes in cerebral glucose utilization are usually detected by [(14)C]-2-deoxyglucose (2DG) autoradiography, but this requires prior manual outlining of regions of interest (ROI) on selected sections. Here, we evaluate the feasibility of applying the SPM method to 3D autoradiographic data sets mapping brain metabolic activity in a transgenic mouse model of AD. We report the preliminary results obtained with 4 APP/PS1 (64+/-1 weeks) and 3 PS1 (65+/-2 weeks) mice. We also describe new procedures for the acquisition and use of "blockface" photographs and provide the first demonstration of their value for the 3D reconstruction and spatial normalization of post mortem mouse brain volumes. Despite this limited sample size, our results appear to be meaningful, consistent, and more comprehensive than findings from previously published studies based on conventional ROI-based methods. The establishment of statistical significance at the voxel level, rather than with a user-defined ROI, makes it possible to detect more reliably subtle differences in geometrically complex regions, such as the hippocampus. Our approach is generic and could be easily applied to other biomarkers and extended to other species and applications., (Copyright 2010 Elsevier Inc. All rights reserved.)