Sensorimotor integration is a field rich in theory backed by a large body of psychophysical evidence. Relating the underlying neural circuitry to these theories has, however, been more challenging. With a wide array of complex behaviors coordinated by their small brains, insects provide powerful model systems to study key features of sensorimotor integration at a mechanistic level. Insect neural circuits perform both hard-wired and learned sensorimotor transformations. They modulate their neural processing based on both internal variables, such as the animal’s behavioral state, and external ones, such as the time of day. Here we present some studies using insect model systems that have produced insights, at the level of individual neurons, about sensorimotor integration and the various ways in which it can be modified by context.

The neural underpinnings of sensorimotor integration are best studied in the context of well-characterized behavior. A rich trove of Drosophila behavioral genetics research offers a variety of well-studied behaviors and candidate brain regions that can form the bases of such studies. The development of tools to perform in vivo physiology from the Drosophila brain has made it possible to monitor activity in defined neurons in response to sensory stimuli. More recently still, it has become possible to perform recordings from identified neurons in the brain of head-fixed flies during walking or flight behaviors. In this chapter, we discuss how experiments that simultaneously monitor behavior and physiology in Drosophila can be combined with other techniques to produce testable models of sensorimotor circuit function.

Cognition encompasses a range of higher-order mental processes, such as attention, working memory, and model-based decision-making. These processes are thought to involve the dynamic interaction of multiple central brain regions. A mechanistic understanding of such computations requires not only monitoring and manipulating specific neural populations during behavior, but also knowing the connectivity of the underlying circuitry. These goals are experimentally challenging in mammals, but are feasible in numerically simpler insect brains. In Drosophila melanogaster in particular, genetic tools enable precisely targeted physiology and optogenetics in actively behaving animals. In this article we discuss how these advantages are increasingly being leveraged to study abstract neural representations and sensorimotor computations that may be relevant for cognition in both insects and mammals.

Cortical neurons exhibit temporally irregular spiking patterns and heterogeneous firing rates. These features arise in model circuits operating in a 'fluctuation-driven regime', in which fluctuations in membrane potentials emerge from the network dynamics. However, it is still debated whether the cortex operates in such a regime. We evaluated the fluctuation-driven hypothesis by analyzing spiking and sub-threshold membrane potentials of neurons in the frontal cortex of mice performing a decision-making task. We showed that while standard fluctuation-driven models successfully account for spiking statistics, they fall short in capturing the heterogeneity in sub-threshold activity. This limitation is an inevitable outcome of bombarding single-compartment neurons with a large number of pre-synaptic inputs, thereby clamping the voltage of all neurons to more or less the same average voltage. To address this, we effectively incorporated dendritic morphology into the standard models. Inclusion of dendritic morphology in the neuronal models increased neuronal selectivity and reduced error trials, suggesting a functional role for dendrites during decision-making. Our work suggests that, during decision-making, cortical neurons in high-order cortical areas operate in a fluctuation-driven regime.

The atomic structure of the infectious, protease-resistant, β-sheet-rich and fibrillar mammalian prion remains unknown. Through the cryo-EM method MicroED, we reveal the sub-ångström-resolution structure of a protofibril formed by a wild-type segment from the β2-α2 loop of the bank vole prion protein. The structure of this protofibril reveals a stabilizing network of hydrogen bonds that link polar zippers within a sheet, producing motifs we have named 'polar clasps'.

Protein kinase A (PKA) plays multiple roles in neurons. The localization and specificity of PKA are largely controlled by A-kinase anchoring proteins (AKAPs). However, the dynamics of PKA in neurons and the roles of specific AKAPs are poorly understood. We imaged the distribution of type II PKA in hippocampal and cortical layer 2/3 pyramidal neurons in vitro and in vivo. PKA was concentrated in dendritic shafts compared to the soma, axons, and dendritic spines. This spatial distribution was imposed by the microtubule-binding protein MAP2, indicating that MAP2 is the dominant AKAP in neurons. Following cAMP elevation, catalytic subunits dissociated from the MAP2-tethered regulatory subunits and rapidly became enriched in nearby spines. The spatial gradient of type II PKA between dendritic shafts and spines was critical for the regulation of synaptic strength and long-term potentiation. Therefore, the localization and activity-dependent translocation of type II PKA are important determinants of PKA function.