ABSTRACT
Whether the size of the prefrontal cortex (PFC) in humans is disproportionate when compared to other species is a persistent debate in evolutionary neuroscience. This question has left the study of over/under-expansion in other structures relatively unexplored. We therefore sought to address this gap by adapting anatomical areas from the digital atlases of 18 mammalian species, to create a common interspecies classification. Our approach used data-driven analysis based on phylogenetic generalized least squares to evaluate anatomical expansion covering the whole brain. Our main finding suggests a divergence in primate evolution, orienting the stereotypical mammalian cerebral proportion toward a frontal and parietal lobe expansion in catarrhini (primate parvorder comprising old world monkeys, apes, and humans). Cerebral lobe volumes slopes plotted for catarrhini species were ranked as parietalâ¼frontal > temporal > occipital, contrasting with the ranking of other mammalian species (occipital > temporal > frontalâ¼parietal). Frontal and parietal slopes were statistically different in catarrhini when compared to other species through bootstrap analysis. Within the catarrhini's frontal lobe, the prefrontal cortex was the principal driver of frontal expansion. Across all species, expansion of the frontal lobe appeared to be systematically linked to the parietal lobe. Our findings suggest that the human frontal and parietal lobes are not disproportionately enlarged when compared to other catarrhini. Nevertheless, humans remain unique in carrying the most relatively enlarged frontal and parietal lobes in an infraorder exhibiting a disproportionate expansion of these areas.
Subject(s)
Biological Evolution , Catarrhini , Frontal Lobe , Parietal Lobe , Animals , Atlases as Topic , Catarrhini/anatomy & histology , Frontal Lobe/anatomy & histology , Humans , Organ Size , Parietal Lobe/anatomy & histology , PhylogenyABSTRACT
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.
Subject(s)
Glutamic Acid , Magnetic Resonance Imaging , Animals , Brain/diagnostic imaging , Brain/metabolism , Brain Mapping , Glutamic Acid/metabolism , Humans , Magnetic Resonance Imaging/methods , PrimatesABSTRACT
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.
Subject(s)
Atlases as Topic , Brain/diagnostic imaging , Cheirogaleidae , Default Mode Network/diagnostic imaging , Adult , Animals , Attention/physiology , Brain/physiology , Default Mode Network/physiology , Executive Function/physiology , Female , Functional Neuroimaging , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Neural Pathways/diagnostic imaging , Neural Pathways/physiology , RestABSTRACT
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.
Subject(s)
Brain/physiology , Connectome/methods , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Nerve Net/physiology , Animals , Brain/diagnostic imaging , Connectome/standards , Female , Image Processing, Computer-Assisted/standards , Magnetic Resonance Imaging/standards , Male , Mice , Mice, Inbred C57BL , Nerve Net/diagnostic imaging , Reproducibility of ResultsABSTRACT
Non-human primates are a critical species for the identification of key biological mechanisms in normal and pathological aging. One of these primates, the mouse lemur, has been widely studied as a model of cerebral aging or Alzheimer's disease. The amplitude of low-frequency fluctuations of blood oxygenation level-dependent (BOLD) can be measured with functional MRI. Within specific frequency bands (e.g. the 0.01-0.1 Hz), these amplitudes were proposed to indirectly reflect neuronal activity as well as glucose metabolism. Here, we first created whole brain maps of the mean amplitude of low frequency fluctuations (mALFF) in young mouse lemurs (mean ± SD: 2.1 ± 0.8 years). Then, we extracted mALFF in old lemurs (mean ± SD: 8.8 ± 1.1 years) to identify age-related changes. A high level of mALFF was detected in the temporal cortex (Brodmann area 20), somatosensory areas (Brodmann area 5), insula (Brodmann areas 13-6) and the parietal cortex (Brodmann area 7) of healthy young mouse lemurs. Aging was associated with alterations of mALFF in somatosensory areas (Brodmann area 5) and the parietal cortex (Brodmann area 7).
Subject(s)
Alzheimer Disease , Cheirogaleidae , Lemur , Lemuridae , Sensorimotor Cortex , Strepsirhini , Animals , Cheirogaleidae/physiology , Magnetic Resonance Imaging , Brain/pathology , Aging , Alzheimer Disease/pathologyABSTRACT
Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.
Subject(s)
Brain Mapping , Brain , Rats , Animals , Brain Mapping/methods , Consensus , Neuroimaging , Magnetic Resonance Imaging/methodsABSTRACT
The human default mode network (DMN) is engaged at rest and in cognitive states such as self-directed thoughts. Interconnected homologous cortical areas in primates constitute a network considered as the equivalent. Here, based on a cross-species comparison of the DMN between humans and non-hominoid primates (macaques, marmosets, and mouse lemurs), we report major dissimilarities in connectivity profiles. Most importantly, the medial prefrontal cortex (mPFC) of non-hominoid primates is poorly engaged with the posterior cingulate cortex (PCC), though strong correlated activity between the human PCC and the mPFC is a key feature of the human DMN. Instead, a fronto-temporal resting-state network involving the mPFC was detected consistently across non-hominoid primate species. These common functional features shared between non-hominoid primates but not with humans suggest a substantial gap in the organization of the primate's DMN and its associated cognitive functions.
Subject(s)
Brain Mapping , Brain , Animals , Callithrix , Default Mode Network , Magnetic Resonance Imaging , Neural PathwaysABSTRACT
Small-mammal neuroimaging offers incredible opportunities to investigate structural and functional aspects of the brain. Many tools have been developed in the last decade to analyse small animal data, but current softwares are less mature than the available tools that process human brain data. The Python package Sammba-MRI (SmAll-MaMmal BrAin MRI in Python; http://sammba-mri.github.io) allows flexible and efficient use of existing methods and enables fluent scriptable analysis workflows, from raw data conversion to multimodal processing.
ABSTRACT
In humans, iatrogenic transmission of cerebral amyloid-ß (Aß)-amyloidosis is suspected following inoculation of pituitary-derived hormones or dural grafts presumably contaminated with Aß proteins as well as after cerebral surgeries. Experimentally, intracerebral inoculation of brain homogenate extracts containing misfolded Aß can seed Aß deposition in transgenic mouse models of amyloidosis or in non-human primates. The transmission of cerebral Aß is governed by the host and by the inoculated samples. It is critical to better characterize the propensities of different hosts to develop Aß deposition after contamination by an Aß-positive sample as well as to better assess which biological samples can transmit this lesion. Aß precursor protein (huAPPwt) mice express humanized non-mutated forms of Aß precursor protein and do not spontaneously develop Aß or amyloid deposits. We found that inoculation of Aß-positive brain extracts from Alzheimer patients in these mice leads to a sparse Aß deposition close to the alveus 18 months post-inoculation. However, it does not induce cortical or hippocampal Aß deposition. Secondary inoculation of apparently amyloid deposit-free hippocampal extracts from these huAPPwt mice to APPswe/PS1dE9 mouse models of amyloidosis enhanced Aß deposition in the alveus 9 months post-inoculation. This suggests that Aß seeds issued from human brain samples can persist in furtive forms in brain tissues while maintaining their ability to foster Aß deposition in receptive hosts that overexpress endogenous Aß. This work emphasizes the need for high-level preventive measures, especially in the context of neurosurgery, to prevent the risk of iatrogenic transmission of Aß lesions from samples with sparse amyloid markers.
Subject(s)
Amyloid beta-Peptides/metabolism , Amyloidosis/metabolism , Brain/metabolism , Plaque, Amyloid/metabolism , Tissue Extracts , Alzheimer Disease , Amyloid beta-Peptides/administration & dosage , Amyloid beta-Protein Precursor/genetics , Amyloidosis/pathology , Animals , Brain/pathology , Disease Models, Animal , Hippocampus , Humans , Iatrogenic Disease , Immunohistochemistry , Mice , Mice, Transgenic , Plaque, Amyloid/pathology , Presenilin-1/geneticsABSTRACT
Large-scale research integration is contingent on seamless access to data in standardized formats. Standards enable researchers to understand external experiment structures, pool results, and apply homogeneous preprocessing and analysis workflows. Particularly, they facilitate these features without the need for numerous potentially confounding compatibility add-ons. In small animal magnetic resonance imaging, an overwhelming proportion of data is acquired via the ParaVision software of the Bruker Corporation. The original data structure is predominantly transparent, but fundamentally incompatible with modern pipelines. Additionally, it sources metadata from free-field operator input, which diverges strongly between laboratories and researchers. In this article we present an open-source workflow which automatically converts and reposits data from the ParaVision structure into the widely supported and openly documented Brain Imaging Data Structure (BIDS). Complementing this workflow we also present operator guidelines for appropriate ParaVision data input, and a programmatic walk-through detailing how preexisting scans with uninterpretable metadata records can easily be made compliant after the acquisition.
ABSTRACT
Animal whole-brain functional magnetic resonance imaging (fMRI) provides a non-invasive window into brain activity. A collection of associated methods aims to replicate observations made in humans and to identify the mechanisms underlying the distributed neuronal activity in the healthy and disordered brain. Animal fMRI studies have developed rapidly over the past years, fueled by the development of resting-state fMRI connectivity and genetically encoded neuromodulatory tools. Yet, comparisons between sites remain hampered by lack of standardization. Recently, we highlighted that mouse resting-state functional connectivity converges across centers, although large discrepancies in sensitivity and specificity remained. Here, we explore past and present trends within the animal fMRI community and highlight critical aspects in study design, data acquisition, and post-processing operations, that may affect the results and influence the comparability between studies. We also suggest practices aimed to promote the adoption of standards within the community and improve between-lab reproducibility. The implementation of standardized animal neuroimaging protocols will facilitate animal population imaging efforts as well as meta-analysis and replication studies, the gold standards in evidence-based science.
ABSTRACT
Gadolinium (Gd)-stained MRI is based on Gd contrast agent (CA) administration into the brain parenchyma. The strong signal increase induced by Gd CA can be converted into resolution enhancement to record microscopic MR images. Moreover, inhomogeneous distribution of the Gd CA in the brain improves the contrast between different tissues and provides new contrasts in MR images. Gd-stained MRI detects amyloid plaques, one of the microscopic lesions of Alzheimer's disease (AD), in APPSL/PS1M146L mice or in primates. Numerous transgenic mice with various plaque typologies have been developed to mimic cerebral amyloidosis and comparison of plaque detection between animal models and humans with new imaging methods is a recurrent concern. Here, we investigated detection of amyloid plaques by Gd-stained MRI in five mouse models of amyloidosis (APPSL/PS1M146L, APP/PS1dE9, APP23, APPSwDI, and 3xTg) presenting with compact, diffuse and intracellular plaques as well as in post mortem human-AD brains. The brains were then evaluated by histology to investigate the impact of size, compactness, and iron load of amyloid plaques on their detection by MRI. We show that Gd-stained MRI allows detection of compact amyloid plaques as small as 25 µm, independently of their iron load, in mice as well as in human-AD brains.