The UNC-Wisconsin rhesus macaque neurodevelopment database: A structural MRI and DTI database of early postnatal development

Rhesus macaques are commonly used as a translational animal model in neuroimaging and neurodevelopmental research. In this report, we present longitudinal data from both structural and diffusion MRI images generated on a cohort of 34 typically developing monkeys from 2 weeks to 36 months of age. All images have been manually skull stripped and are being made freely available via an online repository for use by the research community

The effect of multiple anesthesia exposures on white matter microstructure in the rhesus macaque during the early postnatal phase

Brain maturation is a complex process driven by myelination, growth of neurons, and the development of their connections during the first years of life. The increase in brain connections is followed by a process of dendritic pruning and loss of synaptic contacts, presumably shaping and sculpting a more efficient network of connections that are continuously remodeled throughout life (Engert & Bonhoeffer, 1999; Lebel, Walker, Leemans, Phillips, & Beaulieu, 2008; Stepanyants, Hof, & Chklovskii, 2002). Although brain maturation has been studied extensively, both at a functional level (behavior) and at a structural and mediating level (cellular physiology), information at the level of neuroanatomical structure and connectivity during the early childhood to pubertal years is not as comprehensive. However, this information is of special interest because it provides insight into a different perspective of the anatomical substrates and captures major changes in brain development. Furthermore, understanding developmental brain changes will ultimately help us to better diagnose neurodevelopmental conditions that first present clearly in adolescence, such as attention deficit hyperactivity disorder, depression, and schizophrenia, and devise targeted therapies for these brain disorders.Bachelor of Scienc

Disentangling the effects of early caregiving experience and heritable factors on brain white matter development in rhesus monkeys

Early social experiences, particularly maternal care, shape behavioral and physiological development in primates. Thus, it is not surprising that adverse caregiving, such as child maltreatment leads to a vast array of poor developmental outcomes, including increased risk for psychopathology across the lifespan. Studies of the underlying neurobiology of this risk have identified structural and functional alterations in cortico-limbic brain circuits that seem particularly sensitive to these early adverse experiences and are associated with anxiety and affective disorders. However, it is not understood how these neurobiological alterations unfold during development as it is very difficult to study these early phases in humans, where the effects of maltreatment experience cannot be disentangled from heritable traits. The current study examined the specific effects of experience (“nurture”)versus heritable factors (“nature”)on the development of brain white matter (WM)tracts with putative roles in socioemotional behavior in primates from birth through the juvenile period. For this we used a randomized crossfostering experimental design in a naturalistic rhesus monkey model of infant maltreatment, where infant monkeys were randomly assigned at birth to either a mother with a history of maltreating her infants, or a competent mother. Using a longitudinal diffusion tensor imaging (DTI)atlas-based tract-profile approach we identified widespread, but also specific, maturational changes on major brain tracts, as well as alterations in a measure of WM integrity (fractional anisotropy, FA)in the middle longitudinal fasciculus (MdLF)and the inferior longitudinal fasciculus (ILF), of maltreated animals, suggesting decreased structural integrity in these tracts due to early adverse experience. Exploratory voxelwise analyses confirmed the tract-based approach, finding additional effects of early adversity, biological mother, social dominance rank, and sex in other WM tracts. These results suggest tract-specific effects of postnatal maternal care experience versus heritable or biological factors on primate WM microstructural development. Further studies are needed to determine the specific behavioral outcomes and biological mechanisms associated with these alterations in WM integrity

Structural development of cortical lobes during the first 6 months of life in infant macaques

This study mapped the developmental trajectories of cortical regions in comparison to overall brain growth in typically developing, socially-housed infant macaques. Volumetric changes of cortical brain regions were examined longitudinally between 2–24 weeks of age (equivalent to the first 2 years in humans) in 21 male rhesus macaques. Growth of the prefrontal, frontal, parietal, occipital, and temporal cortices (visual and auditory) was examined using MRI and age-specific infant macaque brain atlases developed by our group. Results indicate that cortical volumetric development follows a cubic growth curve, but maturational timelines and growth rates are region-specific. Total intracranial volume (ICV) increased significantly during the first 5 months of life, leveling off thereafter. Prefrontal and temporal visual cortices showed fast volume increases during the first 16 weeks, followed by a plateau, and significant growth again between 20–24 weeks. Volume of the frontal and temporal auditory cortices increased substantially between 2–24 weeks. The parietal cortex showed a significant volume increase during the first 4 months, whereas the volume of the occipital lobe increased between 2–12 weeks and plateaued thereafter. These developmental trajectories show similarities to cortical growth in human infants, providing foundational information necessary to build nonhuman primate (NHP) models of human neurodevelopmental disorders

Diffusion Tensor Imaging–Based Characterization of Brain Neurodevelopment in Primates

Primate neuroimaging provides a critical opportunity for understanding neurodevelopment. Yet the lack of a normative description has limited the direct comparison with changes in humans. This paper presents for the first time a cross-sectional diffusion tensor imaging (DTI) study characterizing primate brain neurodevelopment between 1 and 6 years of age on 25 healthy undisturbed rhesus monkeys (14 male, 11 female). A comprehensive analysis including region-of-interest, voxel-wise, and fiber tract–based approach demonstrated significant changes of DTI properties over time. Changes in fractional anisotropy (FA), mean diffusivity, axial diffusivity (AD), and radial diffusivity (RD) exhibited a heterogeneous pattern across different regions as well as along fiber tracts. Most of these patterns are similar to those from human studies yet a few followed unique patterns. Overall, we observed substantial increase in FA and AD and a decrease in RD for white matter (WM) along with similar yet smaller changes in gray matter (GM). We further observed an overall posterior-to-anterior trend in DTI property changes over time and strong correlations between WM and GM development. These DTI trends provide crucial insights into underlying age-related biological maturation, including myelination, axonal density changes, fiber tract reorganization, and synaptic pruning processes

Bringing Anatomical Information into Neuronal Network Models

For constructing neuronal network models computational neuroscientists have access to wide-ranging anatomical data that nevertheless tend to cover only a fraction of the parameters to be determined. Finding and interpreting the most relevant data, estimating missing values, and combining the data and estimates from various sources into a coherent whole is a daunting task. With this chapter we aim to provide guidance to modelers by describing the main types of anatomical data that may be useful for informing neuronal network models. We further discuss aspects of the underlying experimental techniques relevant to the interpretation of the data, list particularly comprehensive data sets, and describe methods for filling in the gaps in the experimental data. Such methods of `predictive connectomics' estimate connectivity where the data are lacking based on statistical relationships with known quantities. It is instructive, and in certain cases necessary, to use organizational principles that link the plethora of data within a unifying framework where regularities of brain structure can be exploited to inform computational models. In addition, we touch upon the most prominent features of brain organization that are likely to influence predicted neuronal network dynamics, with a focus on the mammalian cerebral cortex. Given the still existing need for modelers to navigate a complex data landscape full of holes and stumbling blocks, it is vital that the field of neuroanatomy is moving toward increasingly systematic data collection, representation, and publication

Voxel-wise comparisons of cellular microstructure and diffusion-MRI in mouse hippocampus using 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND)

A key challenge in medical imaging is determining a precise correspondence between image properties and tissue microstructure. This comparison is hindered by disparate scales and resolutions between medical imaging and histology. We present a new technique, 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND), for registering medical images with 3D histology to overcome these limitations. Ex vivo 120 × 120 × 200 μm resolution diffusion-MRI (dMRI) data was acquired at 7 T from adult C57Bl/6 mouse hippocampus. Tissue was then optically cleared using CLARITY and stained with cellular markers and confocal microscopy used to produce high-resolution images of the 3D-tissue microstructure. For each sample, a dense array of hippocampal landmarks was used to drive registration between upsampled dMRI data and the corresponding confocal images. The cell population in each MRI voxel was determined within hippocampal subregions and compared to MRI-derived metrics. 3D-BOND provided robust voxel-wise, cellular correlates of dMRI data. CA1 pyramidal and dentate gyrus granular layers had significantly different mean diffusivity (p > 0.001), which was related to microstructural features. Overall, mean and radial diffusivity correlated with cell and axon density and fractional anisotropy with astrocyte density, while apparent fibre density correlated negatively with axon density. Astrocytes, axons and blood vessels correlated to tensor orientation