Possum-A Framework for Three-Dimensional Reconstruction of Brain Images from Serial Sections

Imaging of developing human brains with ex vivo PSOCT and dMRI

The human brain undergoes substantial developmental changes in the first five years of life. Particularly in the white matter, myelination of axons occurs near birth and continues at a rapid pace during the first 2 to 3 years. Diffusion MRI (dMRI) has revolutionized our understanding of developmental trajectories in white matter. However, the mm-resolution of in vivo techniques bears significant limitation in revealing the microstructure of the developing brain. Polarization sensitive optical coherence tomography (PSOCT) is a three-dimensional (3D) optical imaging technique that uses polarized light interferometry to target myelinated fiber tracts with micrometer resolution. Previous studies have shown that PSOCT contributes significantly to the elucidation of myelin content and quantification of fiber orientation in adult human brains. In this study, we utilized the PSOCT technique to study developing brains during the first 5 years of life in combination with ex vivo dMRI. The results showed that the optical properties of PSOCT quantitatively reveal the myelination process in young children. The imaging contrast of the optic axis orientation is a sensitive measure of fiber orientations in largely unmyelinated brains as young as 3-months-old. The micrometer resolution of PSOCT provides substantially enriched information about complex fiber networks and complements submillimeter dMRI. This new optical tool offers great potential to reveal the white matter structures in normal neurodevelopment and developmental disorders in unprecedented detail.

Molecular signatures of cortical expansion in the human fetal brain

The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. A growing catalogue of cells in the prenatal brain has revealed remarkable molecular diversity across cortical areas.1,2 Despite this, little is known about how this translates into the patterns of differential cortical expansion observed in humans during the latter stages of gestation. Here we present a new resource, μBrain, to facilitate knowledge translation between molecular and anatomical descriptions of the prenatal developing brain. Built using generative artificial intelligence, μBrain is a three-dimensional cellular-resolution digital atlas combining publicly-available serial sections of the postmortem human brain at 21 weeks gestation3 with bulk tissue microarray data, sampled across 29 cortical regions and 5 transient tissue zones.4 Using μBrain, we evaluate the molecular signatures of preferentially-expanded cortical regions during human gestation, quantified in utero using magnetic resonance imaging (MRI). We find that differences in the rates of expansion across cortical areas during gestation respect anatomical and evolutionary boundaries between cortical types5 and are founded upon extended periods of upper-layer cortical neuron migration that continue beyond mid-gestation. We identify a set of genes that are upregulated from mid-gestation and highly expressed in rapidly expanding neocortex, which are implicated in genetic disorders with cognitive sequelae. Our findings demonstrate a spatial coupling between areal differences in the timing of neurogenesis and rates of expansion across the neocortical sheet during the prenatal epoch. The μBrain atlas is available from: https://garedaba.github.io/micro-brain/ and provides a new tool to comprehensively map early brain development across domains, model systems and resolution scales.

Localization and Registration of 2D Histological Mouse Brain Images in 3D Atlas Space

To accurately explore the anatomical organization of neural circuits in the brain, it is crucial to map the experimental brain data onto a standardized system of coordinates. Studying 2D histological mouse brain slices remains the standard procedure in many laboratories. Mapping these 2D brain slices is challenging; due to deformations, artifacts, and tilted angles introduced during the standard preparation and slicing process. In addition, analysis of experimental mouse brain slices can be highly dependent on the level of expertise of the human operator. Here we propose a computational tool for Accurate Mouse Brain Image Analysis (AMBIA), to map 2D mouse brain slices on the 3D brain model with minimal human intervention. AMBIA has a modular design that comprises a localization module and a registration module. The localization module is a deep learning-based pipeline that localizes a single 2D slice in the 3D Allen Brain Atlas and generates a corresponding atlas plane. The registration module is built upon the Ardent python package that performs deformable 2D registration between the brain slice to its corresponding atlas. By comparing AMBIA's performance in localization and registration to human ratings, we demonstrate that it performs at a human expert level. AMBIA provides an intuitive and highly efficient way for accurate registration of experimental 2D mouse brain images to 3D digital mouse brain atlas. Our tool provides a graphical user interface and it is designed to be used by researchers with minimal programming knowledge.

Post mortem mapping of connectional anatomy for the validation of diffusion MRI

Diffusion MRI (dMRI) is a unique tool for the study of brain circuitry, as it allows us to image both the macroscopic trajectories and the microstructural properties of axon bundles in vivo. The Human Connectome Project ushered in an era of impressive advances in dMRI acquisition and analysis. As a result of these efforts, the quality of dMRI data that could be acquired in vivo improved substantially, and large collections of such data became widely available. Despite this progress, the main limitation of dMRI remains: it does not image axons directly, but only provides indirect measurements based on the diffusion of water molecules. Thus, it must be validated by methods that allow direct visualization of axons but that can only be performed in post mortem brain tissue. In this review, we discuss methods for validating the various features of connectional anatomy that are extracted from dMRI, both at the macro-scale (trajectories of axon bundles), and at micro-scale (axonal orientations and other microstructural properties). We present a range of validation tools, including anatomic tracer studies, Klingler's dissection, myelin stains, label-free optical imaging techniques, and others. We provide an overview of the basic principles of each technique, its limitations, and what it has taught us so far about the accuracy of different dMRI acquisition and analysis approaches.

Refractive-index matching enhanced polarization sensitive optical coherence tomography quantification in human brain tissue

The importance of polarization-sensitive optical coherence tomography (PS-OCT) has been increasingly recognized in human brain imaging. Despite the recent progress of PS-OCT in revealing white matter architecture and orientation, quantification of fine-scale fiber tracts in the human brain cortex has been a challenging problem, due to a low birefringence in the gray matter. In this study, we investigated the effect of refractive index matching by 2,2'-thiodiethanol (TDE) immersion on the improvement of PS-OCT measurements in ex vivo human brain tissue. We show that we can obtain fiber orientation maps of U-fibers that underlie sulci, as well as cortical fibers in the gray matter, including radial fibers in gyri and distinct layers of fibers exhibiting laminar organization. Further analysis shows that index matching reduces the noise in axis orientation measurements by 56% and 39%, in white and gray matter, respectively. Index matching also enables precise measurements of apparent birefringence, which was underestimated in the white matter by 82% but overestimated in the gray matter by 16% prior to TDE immersion. Mathematical simulations show that the improvements are primarily attributed to the reduction in the tissue scattering coefficient, leading to an enhanced signal-to-noise ratio in deeper tissue regions, which could not be achieved by conventional noise reduction methods.

High-fidelity approximation of grid- and shell-based sampling schemes from undersampled DSI using compressed sensing: Post mortem validation

While many useful microstructural indices, as well as orientation distribution functions, can be obtained from multi-shell dMRI data, there is growing interest in exploring the richer set of microstructural features that can be extracted from the full ensemble average propagator (EAP). The EAP can be readily computed from diffusion spectrum imaging (DSI) data, at the cost of a very lengthy acquisition. Compressed sensing (CS) has been used to make DSI more practical by reducing its acquisition time. CS applied to DSI (CS-DSI) attempts to reconstruct the EAP from significantly undersampled q-space data. We present a post mortem validation study where we evaluate the ability of CS-DSI to approximate not only fully sampled DSI but also multi-shell acquisitions with high fidelity. Human brain samples are imaged with high-resolution DSI at 9.4T and with polarization-sensitive optical coherence tomography (PSOCT). The latter provides direct measurements of axonal orientations at microscopic resolutions, allowing us to evaluate the mesoscopic orientation estimates obtained from diffusion MRI, in terms of their angular error and the presence of spurious peaks. We test two fast, dictionary-based, L2-regularized algorithms for CS-DSI reconstruction. We find that, for a CS acceleration factor of R=3, i.e., an acquisition with 171 gradient directions, one of these methods is able to achieve both low angular error and low number of spurious peaks. With a scan length similar to that of high angular resolution multi-shell acquisition schemes, this CS-DSI approach is able to approximate both fully sampled DSI and multi-shell data with high accuracy. Thus it is suitable for orientation reconstruction and microstructural modeling techniques that require either grid- or shell-based acquisitions. We find that the signal-to-noise ratio (SNR) of the training data used to construct the dictionary can have an impact on the accuracy of CS-DSI, but that there is substantial robustness to loss of SNR in the test data. Finally, we show that, as the CS acceleration factor increases beyond R=3, the accuracy of these reconstruction methods degrade, either in terms of the angular error, or in terms of the number of spurious peaks. Our results provide useful benchmarks for the future development of even more efficient q-space acceleration techniques.

Diffusion MRI and anatomic tracing in the same brain reveal common failure modes of tractography

Anatomic tracing is recognized as a critical source of knowledge on brain circuitry that can be used to assess the accuracy of diffusion MRI (dMRI) tractography. However, most prior studies that have performed such assessments have used dMRI and tracer data from different brains and/or have been limited in the scope of dMRI analysis methods allowed by the data. In this work, we perform a quantitative, voxel-wise comparison of dMRI tractography and anatomic tracing data in the same macaque brain. An ex vivo dMRI acquisition with high angular resolution and high maximum b-value allows us to compare a range of q-space sampling, orientation reconstruction, and tractography strategies. The availability of tracing in the same brain allows us to localize the sources of tractography errors and to identify axonal configurations that lead to such errors consistently, across dMRI acquisition and analysis strategies. We find that these common failure modes involve geometries such as branching or turning, which cannot be modeled well by crossing fibers. We also find that the default thresholds that are commonly used in tractography correspond to rather conservative, low-sensitivity operating points. While deterministic tractography tends to have higher sensitivity than probabilistic tractography in that very conservative threshold regime, the latter outperforms the former as the threshold is relaxed to avoid missing true anatomical connections. On the other hand, the q-space sampling scheme and maximum b-value have less of an impact on accuracy. Finally, using scans from a set of additional macaque brains, we show that there is enough inter-individual variability to warrant caution when dMRI and tracer data come from different animals, as is often the case in the tractography validation literature. Taken together, our results provide insights on the limitations of current tractography methods and on the critical role that anatomic tracing can play in identifying potential avenues for improvement.

Precise Mapping of Single Neurons by Calibrated 3D Reconstruction of Brain Slices Reveals Topographic Projection in Mouse Visual Cortex

Recent breakthroughs in neuroanatomical tracing methods have helped unravel complicated neural connectivity in whole-brain tissue at single-cell resolution. However, in most cases, analysis of brain images remains dependent on highly subjective and sample-specific manual processing, preventing precise comparison across sample animals. In the present study, we introduce AMaSiNe, software for automated mapping of single neurons in the standard mouse brain atlas with annotated regions. AMaSiNe automatically calibrates misaligned and deformed slice samples to locate labeled neuronal positions from multiple brain samples into the standardized 3D Allen Mouse Brain Reference Atlas. We exploit the high fidelity and reliability of AMaSiNe to investigate the topographic structures of feedforward projections from the lateral geniculate nucleus to the primary visual area by reconstructing rabies-virus-injected brain slices in 3D space. Our results demonstrate that distinct organization of neural projections can be precisely mapped using AMaSiNe.

A basic MRI anatomy of the rat brain in coronal sections for practical guidance to neuroscientists

Identification of the brain structures in the magnetic resonance imaging (MRI) of the rat is very important for the experimental work of many neuroscientists. Our intention was to recognize most of the structures without overlapping the MRI sections with the histological templates. Three live rats were used for this study who were examined in a micro-MRI apparatus by performing T2-weighted sequences in serial brain sections. Most of the white matter structures were easily identified, e.g. the anterior commissure, corpus callosum with forceps minor and major, cingulum, external and internal capsules, fornix, stria medullaris and terminalis, cranial nerves, mammillothalamic tract, fasciculus retroflexus, medial and lateral lemniscus, posterior commissure, commissures of the superior and inferior colliculi, medial longitudinal fasciculus, and the cerebral peduncle. Large and small gray matter structures were recognized as well, for example, the anterior olfactory structures, nucleus accumbens, caudate putamen, claustrum, bed nucleus of the stria terminalis, pituitary gland, globus pallidus, amygdala, some midline and intralaminar thalamic nuclei, certain hypothalamic nuclei, hippocampal formation, pineal body, periaqueductal gray matter, lateral and medial geniculate bodies, superior and inferior colliculi, and cranial nerves nuclei. All in all, of the total 160 recognized brain structures, 77 were identified without using the corresponding histological atlases. We believe that our labeled MRI pictures could be an important way for quick orientation for evaluating the effects of the experimental work regarding the rat brain.

Three-dimensional digital image construction of metaxylem vessels in root tips of Zea mays subsp. mexicana from thin transverse sections

PREMISE

Young plant roots share a common architecture: a central vascular cylinder surrounded by enveloping cylinders of ground and dermal tissue produced by an apical promeristem. Roots with closed apical organization can be studied to explore how ontogeny is managed. The analysis of transverse and longitudinal sections has been the most useful approach for this, but suffers from limitations. We developed a new method that utilizes digital photography of transverse sections and three-dimensional (3D) computer virtual reconstructions to overcome the limitations of other techniques.

METHODS

Serial transverse sections of teosinte root tips (Zea mays subsp. mexicana) were used to construct longitudinal images, 3D images, and an animated 3D model. The high-resolution, high-contrast, and low-distortion sectioning method developed previously by the authors enabled high-quality virtual image construction with the aid of a standard laptop computer.

RESULTS

The resulting 3D images allowed greater insight into root tissue ontogeny and organization, especially specific cellular structures such as histogen layers, xylem vessels, pericycle, and meristematic initials.

DISCUSSION

This new method has advantages over confocal laser scanning microscopy and magnetic resonance imaging for visualizing anatomy, and includes a procedure to correct for sectioning distortion. An additional advantage of this method, developed to produce better knowledge about the developmental anatomy of procambium in roots, is its applicability to a wide range of anatomical subjects.

Insight into the fundamental trade-offs of diffusion MRI from polarization-sensitive optical coherence tomography in ex vivo human brain

In the first study comparing high angular resolution diffusion MRI (dMRI) in the human brain to axonal orientation measurements from polarization-sensitive optical coherence tomography (PSOCT), we compare the accuracy of orientation estimates from various dMRI sampling schemes and reconstruction methods. We find that, if the reconstruction approach is chosen carefully, single-shell dMRI data can yield the same accuracy as multi-shell data, and only moderately lower accuracy than a full Cartesian-grid sampling scheme. Our results suggest that current dMRI reconstruction approaches do not benefit substantially from ultra-high b-values or from very large numbers of diffusion-encoding directions. We also show that accuracy remains stable across dMRI voxel sizes of 1 mm or smaller but degrades at 2 mm, particularly in areas of complex white-matter architecture. We also show that, as the spatial resolution is reduced, axonal configurations in a dMRI voxel can no longer be modeled as a small set of distinct axon populations, violating an assumption that is sometimes made by dMRI reconstruction techniques. Our findings have implications for in vivo studies and illustrate the value of PSOCT as a source of ground-truth measurements of white-matter organization that does not suffer from the distortions typical of histological techniques.

Open access resource for cellular-resolution analyses of corticocortical connectivity in the marmoset monkey

Understanding the principles of neuronal connectivity requires tools for efficient quantification and visualization of large datasets. The primate cortex is particularly challenging due to its complex mosaic of areas, which in many cases lack clear boundaries. Here, we introduce a resource that allows exploration of results of 143 retrograde tracer injections in the marmoset neocortex. Data obtained in different animals are registered to a common stereotaxic space using an algorithm guided by expert delineation of histological borders, allowing accurate assignment of connections to areas despite interindividual variability. The resource incorporates tools for analyses relative to cytoarchitectural areas, including statistical properties such as the fraction of labeled neurons and the percentage of supragranular neurons. It also provides purely spatial (parcellation-free) data, based on the stereotaxic coordinates of 2 million labeled neurons. This resource helps bridge the gap between high-density cellular connectivity studies in rodents and imaging-based analyses of human brains.

Understanding principles of neuronal connectivity requires tools for quantification and visualization of large datasets. Here, the authors introduce an online resource encompassing the coordinates of two million neurons labelled by tracer injections in the marmoset cortex, and analysis tools.

In vivo brain imaging with multimodal optical coherence microscopy in a mouse model of thromboembolic photochemical stroke

We used a new multimodal imaging system that combines optical coherence microscopy and brightfield microscopy. Using this in vivo brain monitoring approach and cranial window implantation, we three-dimensionally visualized the vascular network during thrombosis, with high temporal (18 s) and spatial (axial, 2.5    μ m ; lateral, 2.2    μ m ) resolution. We used a modified mouse model of photochemical thromboembolic stroke in order to more accurately parallel human stroke. Specifically, we applied green laser illumination to focally occlude a branch of the middle cerebral artery. Despite the recanalization of the superficial arteries at 24 h after stroke, no blood flow was detected in the small vessels within deeper regions. Moreover, after 24 h of stroke progression, scattering signal enhancement was observed within the stroke region. We also evaluated the infarct extent and shape histologically. In summary, we present a novel approach for real-time mouse brain monitoring and ischemic variability analysis. This multimodal imaging method permits the analysis of thrombosis progression and reperfusion. Additionally and importantly, the system could be used to study the effect of poststroke drug treatments on blood flow in small arteries and capillaries of the brain.

An active texture-based digital atlas enables automated mapping of structures and markers across brains

Brain atlases enable the mapping of labeled cells and projections from different brains onto a standard coordinate system. We address two issues in the construction and use of atlases. First, expert neuroanatomists ascertain the fine-scale pattern of brain tissue, the 'texture' formed by cellular organization, to define cytoarchitectural borders. We automate the processes of localizing landmark structures and alignment of brains to a reference atlas using machine learning and training data derived from expert annotations. Second, we construct an atlas that is active; that is, augmented with each use. We show that the alignment of new brains to a reference atlas can continuously refine the coordinate system and associated variance. We apply this approach to the adult murine brainstem and achieve a precise alignment of projections in cytoarchitecturally ill-defined regions across brains from different animals.

Mapping Histological Slice Sequences to the Allen Mouse Brain Atlas Without 3D Reconstruction

Histological brain slices are widely used in neuroscience to study the anatomical organization of neural circuits. Systematic and accurate comparisons of anatomical data from multiple brains, especially from different studies, can benefit tremendously from registering histological slices onto a common reference atlas. Most existing methods rely on an initial reconstruction of the volume before registering it to a reference atlas. Because these slices are prone to distortions during the sectioning process and often sectioned with non-standard angles, reconstruction is challenging and often inaccurate. Here we describe a framework that maps each slice to its corresponding plane in the Allen Mouse Brain Atlas (2015) to build a plane-wise mapping and then perform 2D nonrigid registration to build a pixel-wise mapping. We use the L2 norm of the histogram of oriented gradients difference of two patches as the similarity metric for both steps and a Markov random field formulation that incorporates tissue coherency to compute the nonrigid registration. To fix significantly distorted regions that are misshaped or much smaller than the control grids, we train a context-aggregation network to segment and warp them to their corresponding regions with thin plate spline. We have shown that our method generates results comparable to an expert neuroscientist and is significantly better than reconstruction-first approaches. Code and sample dataset are available at sites.google.com/view/brain-mapping.

Navigating the Murine Brain: Toward Best Practices for Determining and Documenting Neuroanatomical Locations in Experimental Studies

In experimental neuroscientific research, anatomical location is a key attribute of experimental observations and critical for interpretation of results, replication of findings, and comparison of data across studies. With steadily rising numbers of publications reporting basic experimental results, there is an increasing need for integration and synthesis of data. Since comparison of data relies on consistently defined anatomical locations, it is a major concern that practices and precision in the reporting of location of observations from different types of experimental studies seem to vary considerably. To elucidate and possibly meet this challenge, we have evaluated and compared current practices for interpreting and documenting the anatomical location of measurements acquired from murine brains with different experimental methods. Our observations show substantial differences in approach, interpretation and reproducibility of anatomical locations among reports of different categories of experimental research, and strongly indicate that ambiguous reports of anatomical location can be attributed to missing descriptions. Based on these findings, we suggest a set of minimum requirements for documentation of anatomical location in experimental murine brain research. We furthermore demonstrate how these requirements have been applied in the EU Human Brain Project to optimize workflows for integration of heterogeneous data in common reference atlases. We propose broad adoption of some straightforward steps for improving the precision of location metadata and thereby facilitating interpretation, reuse and integration of data.

Rigid and non-rigid registration of polarized light imaging data for 3D reconstruction of the temporal lobe of the human brain at micrometer resolution

To understand the spatial organization as well as long- and short-range connections of the human brain at microscopic resolution, 3D reconstruction of histological sections is important. We approach this challenge by reconstructing series of unstained histological sections of multi-scale (1.3μm and 64μm) and multi-modal 3D polarized light imaging (3D-PLI) data. Since spatial coherence is lost during the sectioning procedure, image registration is the major step in 3D reconstruction. We propose a non-rigid registration method which comprises of a novel multi-modal similarity metric and an improved regularization scheme to cope with deformations inevitably introduced during the sectioning procedure, as well as a rigid registration approach using a robust similarity metric for improved initial alignment. We also introduce a multi-scale feature-based localization and registration approach for mapping of 1.3μm sections to 64μm sections and a scale-adaptive method that can handle challenging sections with large semi-global deformations due to tissue splits. We have applied our registration method to 126 consecutive sections of the temporal lobe of the human brain with 64μm and 1.3μm resolution. Each step of the registration method was quantitatively evaluated using 10 different sections and manually determined ground truth, and a quantitative comparison with previous methods was performed. Visual assessment of the reconstructed volumes and comparison with reference volumes confirmed the high quality of the registration result.

Data integration through brain atlasing: Human Brain Project tools and strategies

The Human Brain Project (HBP), an EU Flagship Initiative, is currently building an infrastructure that will allow integration of large amounts of heterogeneous neuroscience data. The ultimate goal of the project is to develop a unified multi-level understanding of the brain and its diseases, and beyond this to emulate the computational capabilities of the brain. Reference atlases of the brain are one of the key components in this infrastructure. Based on a new generation of three-dimensional (3D) reference atlases, new solutions for analyzing and integrating brain data are being developed. HBP will build services for spatial query and analysis of brain data comparable to current online services for geospatial data. The services will provide interactive access to a wide range of data types that have information about anatomical location tied to them. The 3D volumetric nature of the brain, however, introduces a new level of complexity that requires a range of tools for making use of and interacting with the atlases. With such new tools, neuroscience research groups will be able to connect their data to atlas space, share their data through online data systems, and search and find other relevant data through the same systems. This new approach partly replaces earlier attempts to organize research data based only on a set of semantic terminologies describing the brain and its subdivisions.

A three-dimensional stereotaxic atlas of the gray short-tailed opossum (Monodelphis domestica) brain

The gray short-tailed opossum (Monodelphis domestica) is a small marsupial gaining recognition as a laboratory animal in biomedical research. Despite numerous studies on opossum neuroanatomy, a consistent and comprehensive neuroanatomical reference for this species is still missing. Here we present the first three-dimensional, multimodal atlas of the Monodelphis opossum brain. It is based on four complementary imaging modalities: high resolution ex vivo magnetic resonance images, micro-computed tomography scans of the cranium, images of the face of the cutting block, and series of sections stained with the Nissl method and for myelinated fibers. Individual imaging modalities were reconstructed into a three-dimensional form and then registered to the MR image by means of affine and deformable registration routines. Based on a superimposition of the 3D images, 113 anatomical structures were demarcated and the volumes of individual regions were measured. The stereotaxic coordinate system was defined using a set of cranial landmarks: interaural line, bregma, and lambda, which allows for easy expression of any location within the brain with respect to the skull. The atlas is released under the Creative Commons license and available through various digital atlasing web services.

Towards a comprehensive atlas of cortical connections in a primate brain: Mapping tracer injection studies of the common marmoset into a reference digital template

The marmoset is an emerging animal model for large‐scale attempts to understand primate brain connectivity, but achieving this aim requires the development and validation of procedures for normalization and integration of results from many neuroanatomical experiments. Here we describe a computational pipeline for coregistration of retrograde tracing data on connections of cortical areas into a 3D marmoset brain template, generated from Nissl‐stained sections. The procedure results in a series of spatial transformations that are applied to the coordinates of labeled neurons in the different cases, bringing them into common stereotaxic space. We applied this procedure to 17 injections, placed in the frontal lobe of nine marmosets as part of earlier studies. Visualizations of cortical patterns of connections revealed by these injections are supplied as Supplementary Materials. Comparison between the results of the automated and human‐based processing of these cases reveals that the centers of injection sites can be reconstructed, on average, to within 0.6 mm of coordinates estimated by an experienced neuroanatomist. Moreover, cell counts obtained in different areas by the automated approach are highly correlated (r = 0.83) with those obtained by an expert, who examined in detail histological sections for each individual. The present procedure enables comparison and visualization of large datasets, which in turn opens the way for integration and analysis of results from many animals. Its versatility, including applicability to archival materials, may reduce the number of additional experiments required to produce the first detailed cortical connectome of a primate brain. J. Comp. Neurol. 524:2161–2181, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.