The Japan Monkey Centre Primates Brain Imaging Repository for comparative neuroscience: an archive of digital records including records for endangered species

Advances in magnetic resonance imaging (MRI) and computational analysis technology have enabled comparisons among various primate brains in a three-dimensional electronic format. Results from comparative studies provide information about common features across primates and species-specific features of neuroanatomy. Investigation of various species of non-human primates is important for understanding such features, but the majority of comparative MRI studies have been based on experimental primates, such as common marmoset, macaques, and chimpanzee. A major obstacle has been the lack of a database that includes non-experimental primates’ brain MRIs. To facilitate scientific discoveries in the field of comparative neuroanatomy and brain evolution, we launched a collaborative project to develop an open-resource repository of non-human primate brain images obtained using ex vivo MRI. As an initial open resource, here we release a collection of structural MRI and diffusion tensor images obtained from 12 species: pygmy marmoset, owl monkey, white-fronted capuchin, crab-eating macaque, Japanese macaque, bonnet macaque, toque macaque, Sykes’ monkey, red-tailed monkey, Schmidt’s guenon, de Brazza’s guenon, and lar gibbon. Sixteen postmortem brain samples from the 12 species, stored in the Japan Monkey Centre (JMC), were scanned using a 9.4-T MRI scanner and made available through the JMC collaborative research program (http://www.j-monkey.jp/BIR/index_e.html). The expected significant contributions of the JMC Primates Brain Imaging Repository include (1) resources for comparative neuroscience research, (2) preservation of various primate brains, including those of endangered species, in a permanent digital form, (3) resources with higher resolution for identifying neuroanatomical features, compared to previous MRI atlases, (4) resources for optimizing methods of scanning large fixed brains, and (5) references for veterinary neuroradiology. User-initiated research projects beyond these contributions are also anticipated

Evolutionary Trajectories of Cognitive Abilities and of their Putative Neuroanatomical and Allometric Correlates: Testing Novel Hypotheses of Cognitive Evolution and Cognitive Integration with Phylogenetic Comparative Methods

The study of primate intelligence, and specifically of general intelligence, has progressed rapidly in the last two decades, however several issues remain unexplored. While neuroanatomical volume measures (NVMs) such as brain size, neocortex size, and absolute or relative size of other brain regions have been frequently framed as substrates for general intelligence, such claims are largely based on simple correlative analyses. Furthermore, while factor analytical techniques have identified a general factor among cognitive abilities when using datasets of species’ mean performances, there have been no examinations of whether the common factor is predictably more strongly present in some primate lineages than in others, and whether relations among brain regions are similarly stronger in some primate lineages than in others. Here, such issues in the comparative literature on primate intelligence are addressed in a new set of studies that present two main novel contributions to the scientific understanding of primate intelligence: First, the evolutionary patterns of the history of changes in general intelligence in primates is examined and compared to those behind the history of changes in brain size and the size of brain regions most commonly used in comparative cognition studies. Studying evolutionary patterns behind a trait permits examining how conserved it is across evolutionary time, how fast it has evolved, and the degree to which it has evolved in a particular direction (i.e., if natural selection regimes have been consistent). Phylogenetic comparative methods employed on datasets of primate species reveal that general intelligence has evolved at a faster pace than NVMs and it has evolved more consistently towards a selection optimum. In contrast to the overall emphasis given in the literature to brain size and neocortex ratio as substrates for intelligence, the NVM with results that most strongly approached the patterns identified for general intelligence is residual cerebellar size (relative to body size). Secondly, a hypothesis is advanced that species higher on general intelligence exhibit a stronger manifold (i.e., higher factor loadings) as general intelligence has previously been empirically associated with ecological generalism, rather than with specialism. As such, cognitive specialization and independence among abilities should be a hallmark of species that have not evolved strong general intelligence. The Continuous Parameter Estimation Model (CPEM) is used in a dataset of cognitive abilities in primate species, and largely confirms the hypothesis forwarded. However, when the same analytical approach is replicated using data on sizes of brain regions, it is found that brain size fails to predict or coevolve with factor loadings of brain regions. Similarly, telencephalon size (a brain structure that holds several of the regions theoretically proposed to serve as substrates for intelligence) fails to predict the strength of factor loadings of telencephalic regions. This set of studies supports the notion that the comparability between the evolution of general intelligence and the evolution of volumes of neuroanatomical structures is more limited than previously thought. Alternative substrates for general intelligence are discussed

The immediate early gene Egr3 Is required for hippocampal induction of Bdnf by electroconvulsive stimulation

Early growth response 3 (Egr3) is an immediate early gene (IEG) that is regulated downstream of a cascade of genes associated with risk for psychiatric disorders, and dysfunction of Egr3 itself has been implicated in schizophrenia, bipolar disorder, and depression. As an activity-dependent transcription factor, EGR3 is poised to regulate the neuronal expression of target genes in response to environmental events. In the current study, we sought to identify a downstream target of EGR3 with the goal of further elucidating genes in this biological pathway relevant for psychiatric illness risk. We used electroconvulsive stimulation (ECS) to induce high-level expression of IEGs in the brain, and conducted expression microarray to identify genes differentially regulated in the hippocampus of Egr3-deficient (-/-) mice compared to their wildtype (WT) littermates. Our results replicated previous work showing that ECS induces high-level expression of the brain-derived neurotrophic factor (Bdnf) in the hippocampus of WT mice. However, we found that this induction is absent in Egr3-/- mice. Quantitative real-time PCR (qRT-PCR) validated the microarray results (performed in males) and replicated the findings in two separate cohorts of female mice. Follow-up studies of activity-dependent Bdnf exons demonstrated that ECS-induced expression of both exons IV and VI requires Egr3. In situ hybridization demonstrated high-level cellular expression of Bdnf in the hippocampal dentate gyrus following ECS in WT, but not Egr3-/-, mice. Bdnf promoter analysis revealed eight putative EGR3 binding sites in the Bdnf promoter, suggesting a mechanism through which EGR3 may directly regulate Bdnf gene expression. These findings do not appear to result from a defect in the development of hippocampal neurons in Egr3-/- mice, as cell counts in tissue sections stained with anti-NeuN antibodies, a neuron-specific marker, did not differ between Egr3-/- and WT mice. In addition, Sholl analysis and counts of dendritic spines in golgi-stained hippocampal sections revealed no difference in dendritic morphology or synaptic spine density in Egr3-/-, compared to WT, mice. These findings indicate that Egr3 is required for ECS-induced expression of Bdnf in the hippocampus and suggest that Bdnf may be a downstream gene in our previously identified biologically pathway for psychiatric illness susceptibility.US National Institute of Mental Health [R01MH097803, R21MH113154]; Natural Sciences and Engineering Research Council of CanadaOpen access journal.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The Japan Monkey Centre Primates Brain Imaging Repository of high-resolution postmortem magnetic resonance imaging: the second phase of the archive of digital records

超高磁場MRIで見る霊長類「全脳」神経回路の多様性 --分野横断型の霊長類脳標本画像リポジトリ：ヒト脳と精神・神経疾患の理解を加速する国際研究基盤--. 京都大学プレスリリース. 2023-05-22.A comparison of neuroanatomical features of the brain between humans and our evolutionary relatives, nonhuman primates, is key to understanding the human brain system and the neural basis of mental and neurological disorders. Although most comparative MRI studies of human and nonhuman primate brains have been based on brains of primates that had been used as subjects in experiments, it is essential to investigate various species of nonhuman primates in order to elucidate and interpret the diversity of neuroanatomy features among humans and nonhuman primates. To develop a research platform for this purpose, it is necessary to harmonize the scientific contributions of studies with the standards of animal ethics, animal welfare, and the conservation of brain information for long-term continuation of the field. In previous research, we first developed a gated data-repository of anatomical images obtained using 9.4-T ex vivo MRI of postmortem brain samples from 12 nonhuman primate species, and which are stored at the Japan Monkey Centre. In the present study, as a second phase, we released a collection of T2-weighted images and diffusion tensor images obtained in nine species: white-throated capuchin, Bolivian squirrel monkey, stump-tailed macaque, Tibet monkey, Sykes’ monkey, Assamese macaque, pig-tailed macaque, crested macaque, and chimpanzee. Our image repository should facilitate scientific discoveries in the field of comparative neuroscience. This repository can also promote animal ethics and animal welfare in experiments with nonhuman primate models by optimizing methods for in vivo and ex vivo MRI scanning of brains and supporting veterinary neuroradiological education. In addition, the repository is expected to contribute to conservation, preserving information about the brains of various primates, including endangered species, in a permanent digital form

Correlations among Brain Gray Matter Volumes, Age, Gender, and Hemisphere in Healthy Individuals

To determine the relationship between age and gray matter structure and how interactions between gender and hemisphere impact this relationship, we examined correlations between global or regional gray matter volume and age, including interactions of gender and hemisphere, using a general linear model with voxel-based and region-of-interest analyses. Brain magnetic resonance images were collected from 1460 healthy individuals aged 20–69 years; the images were linearly normalized and segmented and restored to native space for analysis of global gray matter volume. Linearly normalized images were then non-linearly normalized and smoothed for analysis of regional gray matter volume. Analysis of global gray matter volume revealed a significant negative correlation between gray matter ratio (gray matter volume divided by intracranial volume) and age in both genders, and a significant interaction effect of age × gender on the gray matter ratio. In analyzing regional gray matter volume, the gray matter volume of all regions showed significant main effects of age, and most regions, with the exception of several including the inferior parietal lobule, showed a significant age × gender interaction. Additionally, the inferior temporal gyrus showed a significant age × gender × hemisphere interaction. No regional volumes showed significant age × hemisphere interactions. Our study may contribute to clarifying the mechanism(s) of normal brain aging in each brain region

The nonhuman primate neuroimaging and neuroanatomy project

Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function, connectivity, and their variability across individuals using high-quality non-invasive data from many subjects. Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, ‘ground truth’ validation of connectivity using invasive tracers is not feasible in humans. Studies using nonhuman primates (NHPs) enable comparisons between invasive and non-invasive measures, including exploration of how “functional connectivity” from fMRI and “tractographic connectivity” from diffusion MRI compare with long-distance connections measured using tract tracing. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior