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The neotenous, or delayed, development of primate neurons, particularly human ones, is thought to underlie primate-specific abilities like cognition. We tested whether synaptic development follows suit—would synapses, in absolute time, develop slower in longer-lived, highly cognitive species like non-human primates than in shorter-lived species with less human-like cognitive abilities, e.g., the mouse? Instead, we find that excitatory and inhibitory synapses in the male Mus musculus (mouse) and Rhesus macaque (primate) cortex form at similar rates, at similar times after birth. Primate excitatory and inhibitory synapses and mouse excitatory synapses also prune in such an isochronic fashion. Mouse inhibitory synapses are the lone exception, which are not pruned and instead continuously added throughout life. The monotony of synaptic development clocks across species with disparate lifespans, experiences, and cognitive abilities argues that such programs are likely orchestrated by genetic events rather than experience. How synapse development correlates with lifespan is unknown. Here, the authors show isochronic synapse development in mouse and primate despite disparate lifespans. As a result, synapse accumulation and reduction finishes in neonatal primates but spans nearly the entire life of the mouse.

Neurons in the thalamic reticular nucleus (TRN) are a primary source of inhibition to the dorsal thalamus and, as they are innervated in part by the cortex, are a means of corticothalamic regulation. Previously, cortical inputs to the TRN were thought to originate solely from layer 6 (L6), but we recently reported the presence of putative synaptic terminals from layer 5 (L5) neurons in multiple cortical areas in the TRN [J. A. Prasad, B. J. Carroll, S. M. Sherman, J. Neurosci. 40, 5785−5796 (2020)]. Here, we demonstrate with electron microscopy that L5 terminals from multiple cortical regions make bona fide synapses in the TRN. We further use light microscopy to localize these synapses relative to recently described TRN subdivisions and show that L5 terminals target the edges of the somatosensory TRN, where neurons reciprocally connect to higher-order thalamus, and that L5 terminals are scarce in the core of the TRN, where neurons reciprocally connect to first-order thalamus. In contrast, L6 terminals densely innervate both edge and core subregions and are smaller than those from L5. These data suggest that a sparse but potent input from L5 neurons of multiple cortical regions to the TRN may yield transreticular inhibition targeted to higherorder thalamus.

Myelin is a defining feature of the vertebrate nervous system. Variability in the thickness of the myelin envelope is a structural feature affecting the conduction of neuronal signals. Conversely, the distribution of myelinated tracts along the length of axons has been assumed to be uniform. Here, we traced high-throughput electron microscopy reconstructions of single axons of pyramidal neurons in the mouse neocortex and built high-resolution maps of myelination. We find that individual neurons have distinct longitudinal distribution of myelin. Neurons in the superficial layers displayed the most diversified profiles, including a new pattern where myelinated segments are interspersed with long, unmyelinated tracts. Our data indicate that the profile of longitudinal distribution of myelin is an integral feature of neuronal identity and may have evolved as a strategy to modulate long-distance communication in the neocortex.

Higher order thalamic neurons receive driving inputs from cortical layer 5 and project back to the cortex, reflecting a transthalamic route for corticocortical communication. To determine whether or not individual neurons integrate signals from different cortical populations, we combined electron microscopy “connectomics” in mice with genetic labeling to disambiguate layer 5 synapses from somato-sensory and motor cortices to the higher order thalamic posterior medial nucleus. A significant convergence of these inputs was found on 19 of 33 reconstructed thalamic cells, and as a population, the layer 5 synapses were larger and located more proximally on dendrites than were unlabeled synapses. Thus, many or most of these thalamic neurons do not simply relay afferent information but instead integrate signals as disparate in this case as those emanating from sensory and motor cortices. These findings add further depth and complexity to the role of the higher order thalamus in overall cortical functioning.

Mammalian neurons operate at length scales spanning six orders of magnitude; they project millimeters to centimeters across brain regions, are composed of micrometer-scale-diameter myelinated axons, and ultimately form nanometer scale synapses. Capturing these anatomical features across that breadth of scale has required imaging samples with multiple independent imaging modalities. Translating between the different modalities, however, requires imaging the same brain with each. Here, we imaged the same postmortem mouse brain over five orders of spatial resolution using MRI, whole brain micrometer-scale synchrotron x-ray tomography (μCT), and large volume automated serial electron microscopy. Using this pipeline, we can track individual myelinated axons previously relegated to axon bundles in diffusion tensor MRI or arbitrarily trace neurons and their processes brain-wide and identify individual synapses on them. This pipeline provides both an unprecedented look across a single brain's multi-scaled organization as well as a vehicle for studying the brain's multi-scale pathologies.

•Tractography underestimates long-range connectivity relative to tracers.•Tractography modular and hub-node structure is biased by geometry.•Consideration of geometry is crucial for validation of new tractography approaches. Diffusion MRI tractography is the only noninvasive method to measure the structural connectome in humans. However, recent validation studies have revealed limitations of modern tractography approaches, which lead to significant mistracking caused in part by local uncertainties in fiber orientations that accumulate to produce larger errors for longer streamlines. Characterizing the role of this length bias in tractography is complicated by the true underlying contribution of spatial embedding to brain topology. In this work, we compare graphs constructed with ex vivo tractography data in mice and neural tracer data from the Allen Mouse Brain Connectivity Atlas to random geometric surrogate graphs which preserve the low-order distance effects from each modality in order to quantify the role of geometry in various network properties. We find that geometry plays a substantially larger role in determining the topology of graphs produced by tractography than graphs produced by tracers. Tractography underestimates weights at long distances compared to neural tracers, which leads tractography to place network hubs close to the geometric center of the brain, as do corresponding tractography-derived random geometric surrogates, while tracer graphs place hubs further into peripheral areas of the cortex. We also explore the role of spatial embedding in modular structure, network efficiency and other topological measures in both modalities. Throughout, we compare the use of two different tractography streamline node assignment strategies and find that the overall differences between tractography approaches are small relative to the differences between tractography- and tracer-derived graphs. These analyses help quantify geometric biases inherent to tractography and promote the use of geometric benchmarking in future tractography validation efforts.

Synchrotron-based X-ray tomography offers the potential for rapid large-scale reconstructions of the interiors of materials and biological tissue at fine resolution. However, for radiation sensitive samples, there remain fundamental trade-offs between damaging samples during longer acquisition times and reducing signals with shorter acquisition times. We present a deep convolutional neural network (CNN) method that increases the acquired X-ray tomographic signal by at least a factor of 10 during low-dose fast acquisition by improving the quality of recorded projections. Short-exposure-time projections enhanced with CNNs show signal-to-noise ratios similar to long-exposure-time projections. They also show lower noise and more structural information than low-dose short-exposure acquisitions post-processed by other techniques. We evaluated this approach using simulated samples and further validated it with experimental data from radiation sensitive mouse brains acquired in a tomographic setting with transmission X-ray microscopy. We demonstrate that automated algorithms can reliably trace brain structures in low-dose datasets enhanced with CNN. This method can be applied to other tomographic or scanning based X-ray imaging techniques and has great potential for studying faster dynamics in specimens

Conventional heavy metal poststaining methods on thin sections lend contrast but often cause contamination. To avoid this problem, we tested several en bloc staining techniques to contrast tissue in serial sections mounted on solid substrates for examination by field emission scanning electron microscopy (FESEM). Because FESEM section imaging requires that specimens have higher contrast and greater electrical conductivity than transmission electron microscopy (TEM) samples, our technique uses osmium impregnation (OTO) to make the samples conductive while heavily staining membranes for segmentation studies. Combining this step with other classic heavy metal en bloc stains, including uranyl acetate (UA), lead aspartate, copper sulfate and lead citrate, produced clean, highly contrasted TEM and scanning electron microscopy (SEM) samples of insect, fish and mammalian nervous systems. This protocol takes 7–15 d to prepare resin-embedded tissue, cut sections and produce serial section images.

The structural dynamics of synapses probably has a crucial role in the development and plasticity of the nervous system. In the mammalian brain, the vast majority of excitatory axo-dendritic synapses occur on dendritic specializations called ‘spines’. However, little is known about their long-term changes in the intact developing or adult animal. To address this question we developed a transcranial two-photon imaging technique to follow identified spines of layer-5 pyramidal neurons in the primary visual cortex of living transgenic mice expressing yellow fluorescent protein. Here we show that filopodia-like dendritic protrusions, extending and retracting over hours, are abundant in young animals but virtually absent from the adult. In young mice, within the ‘critical period’ for visual cortex development, ∼73% of spines remain stable over a one-month interval; most changes are associated with spine elimination. In contrast, in adult mice, the overwhelming majority of spines (∼96%) remain stable over the same interval with a half-life greater than 13 months. These results indicate that spines, initially plastic during development, become remarkably stable in the adult, providing a potential structural basis for long-term information storage.

Lipid membranes are key to the nanoscale compartmentalization of biological systems, but fluorescent visualization of them in intact tissues, with nanoscale precision, is challenging to do with high labeling density. Here, we report ultrastructural membrane expansion microscopy (umExM), which combines an innovative membrane label and optimized expansion microscopy protocol, to support dense labeling of membranes in tissues for nanoscale visualization. We validate the high signal-to-background ratio, and uniformity and continuity, of umExM membrane labeling in brain slices, which supports the imaging of membranes and proteins at a resolution of ~60 nm on a confocal microscope. We demonstrate the utility of umExM for the segmentation and tracing of neuronal processes, such as axons, in mouse brain tissue. Combining umExM with optical fluctuation imaging, or iterating the expansion process, yields ~35 nm resolution imaging, pointing towards the potential for electron microscopy resolution visualization of brain membranes on ordinary light microscopes. Lipid membranes are hard to visualise in tissues with nanoscale precision. The authors report ultrastructural membrane expansion microscopy (umExM), a tool that enables dense membrane labelling for nanoscale imaging of cellular membranes using a standard confocal microscope.