Internal models are nowadays customarily used in different domains of science and engineering to describe how living organisms or artificial computational units embed their acquired knowledge about recurring events taking place in the surrounding environment. This article reviews the internal model principle in control theory, bioengineering, and neuroscience, illustrating the fundamental concepts and theoretical developments of the few last decades of research.

Processing bodies (p-bodies) are a prototypical phase-separated RNA-containing granule. Their abundance is highly dynamic and has been linked to translation. Yet, the molecular mechanisms responsible for coordinate control of the two processes are unclear. Here, we uncover key roles for eEF2 kinase (eEF2K) in the control of ribosome availability and p-body abundance. eEF2K acts on a sole known substrate, eEF2, to inhibit translation. We find that the eEF2K agonist nelfinavir abolishes p-bodies in sensory neurons and impairs translation. To probe the latter, we used cryo-electron microscopy. Nelfinavir stabilizes vacant 80S ribosomes. They contain SERBP1 in place of mRNA and eEF2 in the acceptor site. Phosphorylated eEF2 associates with inactive ribosomes that resist splitting in vitro. Collectively, the data suggest that eEF2K defines a population of inactive ribosomes resistant to recycling and protected from degradation. Thus, eEF2K activity is central to both p-body abundance and ribosome availability in sensory neurons.

Sculpting a flat patch of membrane into an endocytic vesicle requires curvature generation on the cell surface, which is the primary function of the endocytosis machinery. Using super-resolved live cell fluorescence imaging, we demonstrate that curvature generation by individual clathrin-coated pits can be detected in real time within cultured cells and tissues of developing organisms. Our analyses demonstrate that the footprint of clathrin coats increases monotonically during the formation of pits at different levels of plasma membrane tension. These findings are only compatible with models that predict curvature generation at the early stages of endocytic clathrin pit formation. We also found that CALM adaptors associated with clathrin plaques form clusters, whereas AP2 distribution is more homogenous. Considering the curvature sensing and driving roles of CALM, we propose that CALM clusters may increase the strain on clathrin lattices locally, eventually giving rise to rupture and subsequent pit completion at the edges of plaques.

Animal behavior is shaped both by evolution and by individual experience. Parallel brain pathways encode innate and learned valences of cues, but the way in which they are integrated during action-selection is not well understood. We used electron microscopy to comprehensively map with synaptic resolution all neurons downstream of all Mushroom Body output neurons (encoding learned valences) and characterized their patterns of interaction with Lateral Horn neurons (encoding innate valences) in larva. The connectome revealed multiple types that receive convergent Mushroom Body and Lateral Horn inputs. A subset of these receives excitatory input from positive-valence MB and LH pathways and inhibitory input from negative-valence MB pathways. We confirmed functional connectivity from LH and MB pathways and behavioral roles of two of these neurons. These neurons encode integrated odor value and bidirectionally regulate turning. Based on this we speculate that learning could potentially skew the balance of excitation and inhibition onto these neurons and thereby modulate turning. Together, our study provides insights into the circuits that integrate learned and innate valences to modify behavior.

Parvalbumin and somatostatin inhibitory interneurons gate information flow in discrete cortical areas that compute sensory and cognitive functions. Despite the considerable differences between areas, individual interneuron subtypes are genetically invariant and are thought to form canonical circuits regardless of which area they are embedded in. Here, we investigate whether this is achieved through selective and systematic variations in their afferent connectivity during development. To this end, we examined the development of their inputs within distinct cortical areas. We find that interneuron afferents show little evidence of being globally stereotyped. Rather, each subtype displays characteristic regional connectivity and distinct developmental dynamics by which this connectivity is achieved. Moreover, afferents dynamically regulated during development are disrupted by early sensory deprivation and in a model of fragile X syndrome. These data provide a comprehensive map of interneuron afferents across cortical areas and reveal the logic by which these circuits are established during development.

A group leader decided that his lab would share the fluorescent dyes they create, for free and without authorship requirements. Nearly 12,000 aliquots later, he reveals what has happened since.

In the central nervous system (CNS), functional tasks are often allocated to distinct compartments. This is also evident in the Drosophila CNS where synapses and dendrites are clustered in distinct neuropil regions. The neuropil is separated from neuronal cell bodies by ensheathing glia, which as we show using dye injection experiments, contribute to the formation of an internal diffusion barrier. We find that ensheathing glia are polarized with a basolateral plasma membrane rich in phosphatidylinositol-(3,4,5)-triphosphate (PIP) and the Na/K-ATPase Nervana2 (Nrv2) that abuts an extracellular matrix formed at neuropil-cortex interface. The apical plasma membrane is facing the neuropil and is rich in phosphatidylinositol-(4,5)-bisphosphate (PIP) that is supported by a sub-membranous ß-Spectrin cytoskeleton. ß-spectrin mutant larvae affect ensheathing glial cell polarity with delocalized PIP and Nrv2 and exhibit an abnormal locomotion which is similarly shown by ensheathing glia ablated larvae. Thus, polarized glia compartmentalizes the brain and is essential for proper nervous system function.

Light sheet fluorescence microscopy (LSFM) uses a thin sheet of light to excite only fluorophores within the focal volume. Light sheet microscopes (LSMs) have a true optical sectioning capability and, hence, provide axial resolution, restrict photobleaching and phototoxicity to a fraction of the sample and use cameras to record tens to thousands of images per second. LSMs are used for in-depth analyses of large, optically cleared samples and long-term three-dimensional (3D) observations of live biological specimens at high spatio-temporal resolution. The independently operated illumination and detection trains and the canonical implementations, selective/single plane illumination microscope (SPIM) and digital scanned laser microscope (DSLM), are the basis for many LSM designs. In this Primer, we discuss various applications of LSFM for imaging multicellular specimens, developing vertebrate and invertebrate embryos, brain and heart function, 3D cell culture models, single cells, tissue sections, plants, organismic interaction and entire cleared brains. Further, we describe the combination of LSFM with other imaging approaches to allow for super-resolution or increased penetration depth and the use of sophisticated spatio-temporal manipulations to allow for observations along multiple directions. Finally, we anticipate developments of the field in the near future.

Understanding the structure and operation of any nervous system has been a subject of research for well over a century. A near-term opportunity in this quest is to understand the brain of a model species, the fruit fly Drosophila melanogaster. This is an enticing target given its relatively small size (roughly 200,000 neurons), coupled with the behavioral richness that this brain supports, and the wide variety of techniques now available to study both brain and behavior. It is clear that within a few years we will possess a connectome for D. melanogaster: an electron-microscopy-level description of all neurons and their chemical synaptic connections. Given what we will soon have, what we already know and the research that is currently underway, what more do we need to know to enable us to understand the fly's brain? Here, we itemize the data we will need to obtain, collate and organize in order to build an integrated model of the brain of D. melanogaster.