Merged magnetic resonance and light sheet microscopy of the whole mouse brain.

We have developed workflows to align 3D magnetic resonance histology (MRH) of the mouse brain with light sheet microscopy (LSM) and 3D delineations of the same specimen. We start with MRH of the brain in the skull with gradient echo and diffusion tensor imaging (DTI) at 15 µm isotropic resolution which is ~ 1,000 times higher than that of most preclinical MRI. Connectomes are generated with superresolution tract density images of ~5 µm. Brains are cleared, stained for selected proteins, and imaged by LSM at 1.8 µm/pixel. LSM data are registered into the reference MRH space with labels derived from the ABA common coordinate framework. The result is a high-dimensional integrated volume with registration (HiDiver) with alignment precision better than 50 µm. Throughput is sufficiently high that HiDiver is being used in quantitative studies of the impact of gene variants and aging on mouse brain cytoarchitecture and connectomics.

High-resolution diffusion magnetic resonance imaging and spatial-transcriptomic in developing mouse brain.

Brain development is a highly complex process regulated by numerous genes at the molecular and cellular levels. Brain tissue exhibits serial microstructural changes during the development process. High-resolution diffusion magnetic resonance imaging (dMRI) affords a unique opportunity to probe these changes in the developing brain non-destructively. In this study, we acquired multi-shell dMRI datasets at 32 µm isotropic resolution to investigate the tissue microstructure alterations, which we believe to be the highest spatial resolution dMRI datasets obtained for postnatal mouse brains. We adapted the Allen Developing Mouse Brain Atlas (ADMBA) to integrate quantitative MRI metrics and spatial transcriptomics. Diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI) metrics were used to quantify brain development at different postnatal days. We demonstrated that the differential evolutions of fiber orientation distributions contribute to the distinct development patterns in white matter (WM) and gray matter (GM). Furthermore, the genes enriched in the nervous system that regulate brain structure and function were expressed in spatial correlation with age-matched dMRI. This study is the first one providing high-resolution dMRI, including DTI, DKI, and NODDI models, to trace mouse brain microstructural changes in WM and GM during postnatal development. This study also highlighted the genotype-phenotype correlation of spatial transcriptomics and dMRI, which may improve our understanding of brain microstructure changes at the molecular level.

Prenatal heroin exposure alters brain morphology and connectivity in adolescent mice.

The United States is experiencing a dramatic increase in maternal opioid misuse and, consequently, the number of individuals exposed to opioids in utero. Prenatal opioid exposure has both acute and long-lasting effects on health and wellbeing. Effects on the brain, often identified at school age, manifest as cognitive impairment, attention deficit, and reduced scholastic achievement. The neurobiological basis for these effects is poorly understood. Here, we examine how in utero exposure to heroin affects brain development into early adolescence in a mouse model. Pregnant C57BL/6J mice received escalating doses of heroin twice daily on gestational days 4-18. The brains of offspring were assessed on postnatal day 28 using 9.4 T diffusion MRI of postmortem specimens at 36 µm resolution. Whole-brain volumes and the volumes of 166 bilateral regions were compared between heroin-exposed and control offspring. We identified a reduction in whole-brain volume in heroin-exposed offspring and heroin-associated volume changes in 29 regions after standardizing for whole-brain volume. Regions with bilaterally reduced standardized volumes in heroin-exposed offspring relative to controls include the ectorhinal and insular cortices. Regions with bilaterally increased standardized volumes in heroin-exposed offspring relative to controls include the periaqueductal gray, septal region, striatum, and hypothalamus. Leveraging microscopic resolution diffusion tensor imaging and precise regional parcellation, we generated whole-brain structural MRI diffusion connectomes. Using a dimension reduction approach with multivariate analysis of variance to assess group differences in the connectome, we found that in utero heroin exposure altered structure-based connectivity of the left septal region and the region that acts as a hub for limbic regulatory actions. Consistent with clinical evidence, our findings suggest that prenatal opioid exposure may have effects on brain morphology, connectivity, and, consequently, function that persist into adolescence. This work expands our understanding of the risks associated with opioid misuse during pregnancy and identifies biomarkers that may facilitate diagnosis and treatment.

Teaching Neuroscience: Reviving Neuroanatomy, Notes on the 2022 Society for Neuroscience Professional Development Workshop on Teaching.

Students often find neuroanatomy a daunting exercise of rote memorization in a dead language. This workshop was designed to enliven the teaching of neuroanatomy. We recast the topic by extending it to the cellular and sub-cellular levels, animating it by learning to build a brain, and infusing the topic with the lively arts. Due to COVID's interference with the usual schedule of Society for Neuroscience (SfN) events, the 2021 Professional Development Workshop on Teaching was held as a webinar on April 12, 2022 with a follow-up question and answer session on June 7. In this workshop, not only were innovative teaching methods presented, but also the very definition of neuroanatomy was pushed to the limits-even reaching into the molecular and subcellular level. The presenters provided means of engaging students that were no cost, low cost, or well within the reach of most academic institutions. Judging by the attendance, this webinar was quite successful in its goals. Our speakers presented exciting and varied approaches to teaching neuroanatomy. Kaitlyn Casimo presented how the vast resources of the Allen Institute could be employed. Marc Nahmani described how open data resources could be utilized in creating a Course-Based Undergraduate Research Experience (CURE) on neural microanatomy. Erika Fanselow presented novel ways to overcome one of students' big hurdles in grasping neuroanatomy: understanding 3-D relationships. Len White described a creative approach in teaching neuroanatomy by incorporating the humanities, particularly art and literature. This article presents synopses of the presentations, which are written by the four presenters. Additionally, prompted by questions from the viewers, we have constructed a table of our favorite resources. A video of the original presentations as well as links to the subsequent Q & A sessions is available at https://neuronline.sfn.org/training/teaching-neuroscience-reviving-neuroanatomy/.

A multicontrast MR atlas of the Wistar rat brain.

We describe a multi-contrast, multi-dimensional atlas of the Wistar rat acquired at microscopic spatial resolution using magnetic resonance histology (MRH). Diffusion weighted images, and associated scalar images were acquired of a single specimen with a fully sampled Fourier reconstruction, 61 angles and b=3000 s/mm2 yielding 50 um isotropic spatial resolution. The higher angular sampling allows use of the GQI algorithm improving the angular invariance of the scalar images and yielding an orientation distribution function to assist in delineating subtle boundaries where there are crossing fibers  and track density images providing insight into local fiber architecture.  A multigradient echo image of the same specimen was acquired at 25 um isotropic spatial resolution. A quantitative susceptibility map enhances fiber architecture relative to the magnitude images.  An accompanying multi-specimen atlas (n=6) was acquired with compressed sensing with the same diffusion protocol as used for the single specimen atlas.  An average was created using diffeomorphic mapping. Scalar volumes from the diffusion data, a T2* weighted volume, a quantitative susceptibility map, and a track density volume, all registered to the same space provide multiple contrasts to assist in anatomic delineation. The new template  provides significantly increased contrast in the scalar DTI images when compared to previous atlases. A compact interactive viewer based on 3D Slicer is provided to facilitate comparison among the contrasts in the multiple volumes. The single volume and average atlas with multiple 3D volumes provide an improved template for anatomic interrogation of the Wistar rat brain. The improved contrast to noise in the scalar DTI images and the addition of other volumes (eg. QA,QSM,TDI ) will facilitate automated label registration for MR histology and preclinical imaging.

A high-resolution interactive atlas of the human brainstem using magnetic resonance imaging.

Conventional atlases of the human brainstem are limited by the inflexible, sparsely-sampled, two-dimensional nature of histology, or the low spatial resolution of conventional magnetic resonance imaging (MRI). Postmortem high-resolution MRI circumvents the challenges associated with both modalities. A single human brainstem specimen extending from the rostral diencephalon through the caudal medulla was prepared for imaging after the brain was removed from a 65-year-old male within 24 h of death. The specimen was formalin-fixed for two weeks, then rehydrated and placed in a custom-made MRI compatible tube and immersed in liquid fluorocarbon. MRI was performed in a 7-Tesla scanner with 120 unique diffusion directions. Acquisition time for anatomic and diffusion images were 14 h and 208 h, respectively. Segmentation was performed manually. Deterministic fiber tractography was done using strategically chosen regions of interest and avoidance, with manual editing using expert knowledge of human neuroanatomy. Anatomic and diffusion images were rendered with isotropic resolutions of 50 µm and 200 µm, respectively. Ninety different structures were segmented and labeled, and 11 different fiber bundles were rendered with tractography. The complete atlas is available online for interactive use at https://www.civmvoxport.vm.duke.edu/voxbase/login.php?return_url=%2Fvoxbase%2F. This atlas presents multiple contrasting datasets and selected tract reconstruction with unprecedented resolution for MR imaging of the human brainstem. There are immediate applications in neuroanatomical education, with the potential to serve future applications for neuroanatomical research and enhanced neurosurgical planning through "safe" zones of entry into the human brainstem.

Cytoarchitecture of the mouse brain by high resolution diffusion magnetic resonance imaging.

MRI has been widely used to probe the neuroanatomy of the mouse brain, directly correlating MRI findings to histology is still challenging due to the limited spatial resolution and various image contrasts derived from water relaxation or diffusion properties. Magnetic resonance histology has the potential to become an indispensable research tool to mitigate such challenges. In the present study, we acquired high spatial resolution MRI datasets, including diffusion MRI (dMRI) at 25 â€‹µm isotropic resolution and quantitative susceptibility mapping (QSM) at 21.5 â€‹µm isotropic resolution to validate with conventional mouse brain histology. Diffusion weighted images (DWIs) show better delineation of cortical layers and glomeruli in the olfactory bulb than fractional anisotropy (FA) maps. However, among all the image contrasts, including quantitative susceptibility mapping (QSM), T1/T2∗ images and DTI metrics, FA maps highlight unique laminar architecture in sub-regions of the hippocampus, including the strata of the dentate gyrus and CA fields of the hippocampus. The mean diffusivity (MD) and axial diffusivity (AD) yield higher correlation with DAPI (0.62 and 0.71) and NeuN (0.78 and 0.74) than with NF-160 (-0.34 and -0.49). The correlations between FA and DAPI, NeuN, and NF-160 are 0.31, -0.01, and -0.49, respectively. Our findings demonstrate that MRI at microscopic resolution deliver a three-dimensional, non-invasive and non-destructive platform for characterization of fine structural detail in both gray matter and white matter of the mouse brain.

Predictors of attitudes and performance in U.S. Army recruiters: Does personality matter?

Given the interpersonal nature of recruiting and the validity of personality assessments for predicting performance in a broad range of civilian and military jobs, personality traits are likely to predict the performance of recruiters in the Army as well. However, much of the research on the characteristics of successful recruiters has been conducted in civilian samples and has not examined the effects of recruiters' personality on their job-related attitudes and behaviors. Although some research has examined the prediction of recruiter performance in a military context, more research is needed to identify profiles of personality traits that will help recruiters to be successful on the job. We explored this relationship in a sample of experienced recruiters with at least six months of service in a recruiting duty assignment. Results indicated that composites of personality traits were substantial predictors of recruiter performance and attitudes. The implications of these results for the selection and assessment of recruiters in the U.S. Army will be discussed.

Examining personality for the selection and classification of soldiers: Validity and differential validity across jobs.

A number of past studies have demonstrated that personality traits are modest predictors of workplace attitudes and behaviors and can provide incremental validity over cognitive ability. However, less is known about the utility of personality for job classification. In addition, concerns about the effects of faking on personality measures still remain. In this study, we examined the validity of a forced choice personality measure administered under operational conditions to explore the use of personality traits in high-stakes settings. In addition, we also examined the potential use of personality for classification into military occupational specialties (MOS). We explored these issues in a large sample of Soldiers from five different MOS to examine the prediction of performance during initial military training (IMT). Results indicated that composites of personality traits were valid predictors of performance and attrition and that these composites may be useful for classifying individuals into different military occupations. The implications of these results for Soldier selection and classification are discussed.

Forever young: Neoteny, neurogenesis and a critique of critical periods in olfaction.

The critical period concept has been one of the most transcendent in science, education, and society forming the basis of our fixation on 'quality' of childhood experiences. The neural basis of this process has been revealed in developmental studies of visual, auditory and somatosensory maps and their enduring modification through manipulations of experience early in life. Olfaction, too, possesses a number of phenomena that share key characteristics with classical critical periods like sensitive temporal windows and experience dependence. In this review, we analyze the candidate critical period-like phenomena in olfaction and find them disanalogous to classical critical periods in other sensory systems in several important ways. This leads us to speculate as to why olfaction may be alone among exteroceptive systems in lacking classical critical periods and how life-long neurogenesis of olfactory sensory neurons and bulbar interneurons-a neotenic vestige-- relates to the structure and function of the mammalian olfactory system.

Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex.

The architecture of iso-orientation domains in the primary visual cortex (V1) of placental carnivores and primates apparently follows species invariant quantitative laws. Dynamical optimization models assuming that neurons coordinate their stimulus preferences throughout cortical circuits linking millions of cells specifically predict these invariants. This might indicate that V1's intrinsic connectome and its functional architecture adhere to a single optimization principle with high precision and robustness. To validate this hypothesis, it is critical to closely examine the quantitative predictions of alternative candidate theories. Random feedforward wiring within the retino-cortical pathway represents a conceptually appealing alternative to dynamical circuit optimization because random dimension-expanding projections are believed to generically exhibit computationally favorable properties for stimulus representations. Here, we ask whether the quantitative invariants of V1 architecture can be explained as a generic emergent property of random wiring. We generalize and examine the stochastic wiring model proposed by Ringach and coworkers, in which iso-orientation domains in the visual cortex arise through random feedforward connections between semi-regular mosaics of retinal ganglion cells (RGCs) and visual cortical neurons. We derive closed-form expressions for cortical receptive fields and domain layouts predicted by the model for perfectly hexagonal RGC mosaics. Including spatial disorder in the RGC positions considerably changes the domain layout properties as a function of disorder parameters such as position scatter and its correlations across the retina. However, independent of parameter choice, we find that the model predictions substantially deviate from the layout laws of iso-orientation domains observed experimentally. Considering random wiring with the currently most realistic model of RGC mosaic layouts, a pairwise interacting point process, the predicted layouts remain distinct from experimental observations and resemble Gaussian random fields. We conclude that V1 layout invariants are specific quantitative signatures of visual cortical optimization, which cannot be explained by generic random feedforward-wiring models.

Segmentation of the canine corpus callosum using diffusion-tensor imaging tractography.

OBJECTIVE: We set out to determine functional white matter (WM) connections passing through the canine corpus callosum; these WM connections would be useful for subsequent studies of canine brains that serve as models for human WM pathway disease. Based on prior studies, we anticipated that the anterior corpus callosum would send projections to the anterior cerebral cortex whereas progressively posterior segments would send projections to more posterior cortex. MATERIALS AND METHODS: A postmortem canine brain was imaged using a 7-T MRI system producing 100-µm-isotropic-resolution diffusion-tensor imaging analyzed by tractography. Using regions of interest (ROIs) within cortical locations, which were confirmed by a Nissl stain that identified distinct cortical architecture, we successfully identified six important WM pathways. We also compared fractional anisotropy (FA), apparent diffusion coefficient (ADC), radial diffusivity, and axial diffusivity in tracts passing through the genu and splenium. RESULTS: Callosal fibers were organized on the basis of cortical destination (e.g., fibers from the genu project to the frontal cortex). Histologic results identified the motor cortex on the basis of cytoarchitectonic criteria that allowed placement of ROIs to discriminate between frontal and parietal lobes. We also identified cytoarchitecture typical of the orbital frontal, anterior frontal, and occipital regions and placed ROIs accordingly. FA, ADC, radial diffusivity, and axial diffusivity values were all higher in posterior corpus callosum fiber tracts. CONCLUSION: Using six cortical ROIs, we identified six major WM tracts that reflect major functional divisions of the cerebral hemispheres, and we derived quantitative values that can be used for study of canine models of human WM pathologic states.

Experience with moving visual stimuli drives the early development of cortical direction selectivity.

The onset of vision occurs when neural circuits in the visual cortex are immature, lacking both the full complement of connections and the response selectivity that defines functional maturity. Direction-selective responses are particularly vulnerable to the effects of early visual deprivation, but it remains unclear how stimulus-driven neural activity guides the emergence of cortical direction selectivity. Here we report observations from a motion training protocol that allowed us to monitor the impact of experience on the development of direction-selective responses in visually naive ferrets. Using intrinsic signal imaging techniques, we found that training with a single axis of motion induced the rapid emergence of direction columns that were confined to cortical regions preferentially activated by the training stimulus. Using two-photon calcium imaging techniques, we found that single neurons in visually naive animals exhibited weak directional biases and lacked the strong local coherence in the spatial organization of direction preference that was evident in mature animals. Training with a moving stimulus, but not with a flashed stimulus, strengthened the direction-selective responses of individual neurons and preferentially reversed the direction biases of neurons that deviated from their neighbours. Both effects contributed to an increase in local coherence. We conclude that early experience with moving visual stimuli drives the rapid emergence of direction-selective responses in the visual cortex.

An Open Resource: MR and light sheet microscopy stereotaxic atlas of the mouse brain.

We have combined MR histology and light sheet microscopy (LSM) of five postmortem C57BL/6J mouse brains in a stereotaxic space based on micro-CT yielding a multimodal 3D atlas with the highest spatial and contrast resolution yet reported. Brains were imaged in situ with multi gradient echo (mGRE) and diffusion tensor imaging (DTI) at 15 µm resolution (∼ 2.4 million times that of clinical MRI). Scalar images derived from the average DTI and mGRE provide unprecedented contrast in 14 complementary 3D volumes, each highlighting distinct histologic features. The same tissues scanned with LSM and registered into the stereotaxic space provide 17 different molecular cell type stains. The common coordinate framework labels (CCFv3) complete the multimodal atlas. The atlas has been used to correct distortions in the Allen Brain Atlas and harmonize it with Franklin Paxinos. It provides a unique resource for stereotaxic labeling of mouse brain images from many sources.

Initial neighborhood biases and the quality of motion stimulation jointly influence the rapid emergence of direction preference in visual cortex.

Visual experience plays a critical role in the development of direction-selective responses in ferret visual cortex. In visually naive animals, presentation of a bidirectional "training" stimulus induces rapid increases in the direction-selective responses of single neurons that can be predicted by small but significant direction biases that are present in neighboring neurons at the onset of stimulation. In this study we used in vivo two-photon imaging of calcium signals to further explore the contribution of visual experience to the emergence of direction- selective responses in ferret visual cortex. The first set of experiments was designed to determine whether visual experience is required for the development of the initial neighborhood bias. In animals that were dark-reared until the time of eye opening, we found that individual neurons exhibited weak direction-selective responses accompanied by a reduced but statistically significant neighborhood bias, indicating that both features arise without the need for visual experience. The second set of experiments used a unidirectional training stimulus to assess the relative roles of the neighborhood bias and visual experience in determining the direction preference that cortical neurons acquire during direction training. We found that neurons became more responsive to the trained direction even when they were located in regions of the cortex with an initial neighborhood bias for the direction opposite the training stimulus. Together, these results suggest an adaptive developmental strategy for the elaboration of direction-selective responses, one in which experience-independent mechanisms provide a symmetry-breaking seed for the instructive effects of visual experience.

A rapid workflow for neuron counting in combined light sheet microscopy and magnetic resonance histology.

Information on regional variation in cell numbers and densities in the CNS provides critical insight into structure, function, and the progression of CNS diseases. However, variability can be real or a consequence of methods that do not account for technical biases, including morphologic deformations, errors in the application of cell type labels and boundaries of regions, errors of counting rules and sampling sites. We address these issues in a mouse model by introducing a workflow that consists of the following steps: 1. Magnetic resonance histology (MRH) to establish the size, shape, and regional morphology of the mouse brain in situ. 2. Light-sheet microscopy (LSM) to selectively label neurons or other cells in the entire brain without sectioning artifacts. 3. Register LSM volumes to MRH volumes to correct for dissection errors and both global and regional deformations. 4. Implement stereological protocols for automated sampling and counting of cells in 3D LSM volumes. This workflow can analyze the cell densities of one brain region in less than 1 min and is highly replicable in cortical and subcortical gray matter regions and structures throughout the brain. This method demonstrates the advantage of not requiring an extensive amount of training data, achieving a F1 score of approximately 0.9 with just 20 training nuclei. We report deformation-corrected neuron (NeuN) counts and neuronal density in 13 representative regions in 5 C57BL/6J cases and 2 BXD strains. The data represent the variability among specimens for the same brain region and across regions within the specimen. Neuronal densities estimated with our workflow are within the range of values in previous classical stereological studies. We demonstrate the application of our workflow to a mouse model of aging. This workflow improves the accuracy of neuron counting and the assessment of neuronal density on a region-by-region basis, with broad applications for studies of how genetics, environment, and development across the lifespan impact cell numbers in the CNS.

A rapid workflow for neuron counting in combined light sheet microscopy and magnetic resonance histology.

Information on regional variation in cell numbers and densities in the CNS provides critical insight into structure, function, and the progression of CNS diseases. However, variability can be real or can be a consequence of methods that do not account for technical biases, including morphologic deformations, errors in the application of cell type labels and boundaries of regions, errors of counting rules and sampling sites. We address these issues of by introducing a workflow that consists of the following steps: 1. Magnetic resonance histology (MRH) to establish the size, shape, and regional morphology of the mouse brain in situ. 2. Light-sheet microscopy (LSM) to selectively label all neurons or other cells in the entire brain without sectioning artifacts. 3. Register LSM volumes to MRH volumes to correct for dissection errors and morphological deformations. 4. Implement novel protocol for automated sampling and counting of cells in 3D LSM volumes. This workflow can analyze the cells density of one brain region in less than 1 min and is highly replicable to cortical and subcortical gray matter regions and structures throughout the brain. We report deformation-corrected neuron (NeuN) counts and neuronal density in 13 representative regions in 5 C57B6/6J and 2 BXD strains. The data represent the variability among cases for the same brain region and across regions within case. Our data are consistent with previous studies. We demonstrate the application of our workflow to a mouse model of aging. This workflow improves the accuracy of neuron counting and the assessment of neuronal density on a region-by-region basis, with broad applications in how genetics, environment, and development across the lifespan impact brain structure.

Vision and cortical map development.

Functional maps arise in developing visual cortex as response selectivities become organized into columnar patterns of population activity. Recent studies of developing orientation and direction maps indicate that both are sensitive to visual experience, but not to the same degree or duration. Direction maps have a greater dependence on early vision, while orientation maps remain sensitive to experience for a longer period of cortical maturation. There is also a darker side to experience: abnormal vision through closed lids produces severe impairments in neuronal selectivity, rendering these maps nearly undetectable. Thus, the rules that govern their formation and the construction of the underlying neural circuits are modulated-for better or worse-by early vision. Direction maps, and possibly maps of other properties that are dependent upon precise conjunctions of spatial and temporal signals, are most susceptible to the potential benefits and maladaptive consequences of early sensory experience.

Gaussian process methods for estimating cortical maps.

A striking feature of cortical organization is that the encoding of many stimulus features, for example orientation or direction selectivity, is arranged into topographic maps. Functional imaging methods such as optical imaging of intrinsic signals, voltage sensitive dye imaging or functional magnetic resonance imaging are important tools for studying the structure of cortical maps. As functional imaging measurements are usually noisy, statistical processing of the data is necessary to extract maps from the imaging data. We here present a probabilistic model of functional imaging data based on Gaussian processes. In comparison to conventional approaches, our model yields superior estimates of cortical maps from smaller amounts of data. In addition, we obtain quantitative uncertainty estimates, i.e. error bars on properties of the estimated map. We use our probabilistic model to study the coding properties of the map and the role of noise-correlations by decoding the stimulus from single trials of an imaging experiment.

Mapping multiple features in the population response of visual cortex.

Stimulus features such as edge orientation, motion direction and spatial frequency are thought to be encoded in the primary visual cortex by overlapping feature maps arranged so that the location of neurons activated by a particular combination of stimulus features can be predicted from the intersections of these maps. This view is based on the use of grating stimuli, which limit the range of stimulus combinations that can be examined. We used optical imaging of intrinsic signals in ferrets to assess patterns of population activity evoked by the motion of a texture (a field of iso-oriented bars). Here we show that the same neural population can be activated by multiple combinations of orientation, length, motion axis and speed. Rather than reflecting the intersection of multiple maps, our results indicate that population activity in primary visual cortex is better described as a single map of spatiotemporal energy.