To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

Dendritic spines’ electrical function?: Dendritic spines are small protrusions that cover the dendrites of most neurons in the brain. Their electrical properties are still controversially discussed. Cornejo et al . used an array of techniques to investigate the degree of voltage attenuation by dendritic spine necks in pyramidal neurons of the mouse neocortex. Spines not only synchronously depolarized in response to backpropagating action potentials, but local and transient depolarization also occurred. Isolated depolarization in individual spines reflected localized synaptic activation. A significant voltage gradient between dendritic spine and dendrite indicated that spines may constitute elementary electric compartments. The spine neck resistance is thus not negligible and may substantially contribute to the regulation of synaptic efficacy in the central nervous system. —PRS

Computational modeling of signal propagation in neurons is critical to our understanding of basic principles underlying brain organization and activity. Exploring these models is used to address basic neuroscience questions as well as to gain insights for clinical applications. The seminal Hodgkin Huxley model is a common theoretical framework to study brain activity. It was mainly used to investigate the electrochemical and physical properties of neurons. The influence of neuronal structure on activity patterns was explored, however, the rich dynamics observed in neurons with different morphologies is not yet fully understood. Here, we study signal propagation in fundamental building blocks of neuronal branching trees, unbranched and branched axons. We show how these simple axonal elements can code information on spike trains, and how asymmetric responses can emerge in axonal branching points. This asymmetric phenomenon has been observed experimentally but until now lacked theoretical characterization. Together, our results suggest that axonal morphological parameters are instrumental in activity modulation and information coding. The insights gained from this work lay the ground for better understanding the interplay between function and form in real-world complex systems. It may also supply theoretical basis for the development of novel therapeutic approaches to damaged nervous systems.

The propagation of action potentials along axons is traditionally considered reliable due to the high safety factor for axonal spike transmission. However, numerical simulations suggest that high-frequency spikes could fail to invade distal axonal branches. To explore this experimentally in vivo, we used an axonal-targeted calcium indicator to image action potentials at axonal terminal branches in the superficial layers of mouse somatosensory cortical neurons. We activated axons with an extracellular electrode, varying stimulation frequencies, and analyzed the images to computationally extract axonal morphologies and associated calcium responses. We found that axonal boutons have higher calcium accumulations than their axonal shafts, as was reported in vitro. However, contrary to previous in vitro results, our data reveal spike failures at high spike frequencies in a significant subset of branches as a function of branching geometry. These findings suggest that axonal morphologies could contribute to signal processing in the cortex.