The function of the neocortex is fundamentally determined by its repeating microcircuit motif, but also by its rich, hierarchical, interregional structure with a highly specific laminar architecture. The last decade has seen the emergence of extensive new data sets on anatomy and connectivity at the whole brain scale, providing promising new directions for studies of cortical function that take into account the inseparability of whole-brain and microcircuit architectures. Here, we present a data-driven computational model of the anatomy of non-barrel primary somatosensory cortex of juvenile rat, which integrates whole-brain scale data while providing cellular and subcellular specificity. This multiscale integration was achieved by building the morphologically detailed model of cortical circuitry embedded within a volumetric, digital brain atlas. The model consists of 4.2 million morphologically detailed neurons belonging to 60 different morphological types, placed in the nonbarrel subregions of the Paxinos and Watson atlas. They are connected by 13.2 billion synapses determined by axo-dendritic overlap, comprising local connectivity and long-range connectivity defined by topographic mappings between subregions and laminar axonal projection profiles, both parameterized by whole brain data sets. Additionally, we incorporated core- and matrix-type thalamocortical projection systems, associated with sensory and higher-order extrinsic inputs, respectively. An analysis of the modeled synaptic connectivity revealed a highly nonrandom topology with substantial structural differences but also synergy between local and long-range connectivity. Long-range connections featured a more divergent structure with a comparatively small group of neurons serving as hubs to distribute excitation to far away locations. Taken together with analyses at different spatial granularities, these results support the notion that local and interregional connectivity exist on a spectrum of scales, rather than as separate and distinct networks, as is commonly assumed. Finally, we predicted how the emergence of primary sensory cortical maps is constrained by the anatomy of thalamo-cortical projections. A subvolume of the model comprising 211,712 neurons in the front limb, jaw, and dysgranular zone has been made freely and openly available to the community.

Recent developments in experimental techniques have enabled simultaneous recordings from thousands of neurons, enabling the study of functional cell assemblies. However, determining the patterns of synaptic connectivity giving rise to assemblies remains challenging. To address this, we developed a complementary, simulation-based approach, using a detailed, large-scale cortical network model. Using a combination of established methods we detected functional cell assemblies from the stimulus-evoked spiking activity of 186,665 neurons. We studied how the structure of synaptic connectivity underlies assembly composition, quantifying the effects of thalamic innervation, recurrent connectivity, and the spatial arrangement of synapses on dendrites. We determined that these features reduce up to 30%, 22%, and 10% of the uncertainty of a neuron belonging to an assembly. The detected assemblies were activated in a stimulus-specific sequence and were grouped based on their position in the sequence. We found that the different groups were affected to different degrees by the structural features we considered. Additionally, connectivity was more predictive of assembly membership if its direction aligned with the temporal order of assembly activation, if it originated from strongly interconnected populations, and if synapses clustered on dendritic branches. In summary, reversing Hebb's postulate, we showed how cells that are wired together, fire together, quantifying how connectivity patterns interact to shape the emergence of assemblies. This includes a qualitative aspect of connectivity: not just the amount, but also the local structure matters; from the subcellular level in the form of dendritic clustering to the presence of specific network motifs. This connectivity-based characterization of cell assemblies creates an opportunity to study plasticity at the assembly level, and beyond strictly pairwise interactions.

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BACKGROUND AND PURPOSE The spinal subarachnoid space (SSAS) is vital for neurologic function. Although SSAS alterations are known to occur after spinal cord injury (SCI), there is a lack of high‐resolution imaging studies of the SSAS after SCI in rodents. Therefore, the aim here was to assess changes in the SSAS of rats subjected to graded SCI, using high‐resolution micro‐CT myelography. METHODS Long‐Evans adult rats were subjected to mild or severe spinal cord contusion at T9. Imaging studies of SSAS features were carried out in injured rats at acute (day 1) and subacute (day 15) stages postinjury, as well as in control rats, using high‐resolution micro‐CT myelography with a contrast‐enhanced digital subtraction protocol. We studied a total of 33 rats randomly allocated into five experimental groups. Micro‐CT myelograms were assessed by expert observers using both qualitative and quantitative criteria. RESULTS Qualitative and quantitative analyses showed that SCI induces changes in the SSAS that vary as a function of both injury severity and time elapsed after injury. SSAS blockage was the main alteration detected. Moreover, the method used here allowed fine details to be observed in small animals, such as variations in the preferential pathways for contrast medium flow, neuroimaging nerve root enhancement, and leakage of contrast medium due to tearing of the dural sac. CONCLUSION Micro‐CT myelography provides high‐resolution images of changes in the SSAS after SCI in rats and is a useful tool for further experimental studies involving rat SCI in vivo.

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