Purkinje cells (PCs) primarily project to cerebellar nuclei but also directly innervate the brainstem. Some PC-brainstem projections have been described previously, but most have not been thoroughly characterized. Here, we use a PC-specific cre line to anatomically and electrophysiologically characterize PC projections to the brainstem. PC synapses are surprisingly widespread, with the highest densities found in the vestibular and parabrachial nuclei. However, there are pronounced regional differences in synaptic densities within both the vestibular and parabrachial nuclei. Large optogenetically evoked PC-IPSCs are preferentially observed in subregions with the highest densities of putative PC boutons, suggesting that PCs selectively influence these areas and the behaviors they regulate. Unexpectedly, the pontine central gray and nearby subnuclei also contained a low density of putative PC boutons, and large PC-IPSCs are observed in a small fraction of cells. We combined electrophysiological recordings with immunohistochemistry to assess the molecular identities of two potential PC targets: PC synapses onto mesencephalic trigeminal neurons were not observed even though these cells are in close proximity to PC boutons; PC synapses onto locus coeruleus neurons are exceedingly rare or absent, even though previous studies concluded that PCs are a major input to these neurons. The availability of a highly selective cre line for PCs allowed us to study functional synapses, while avoiding complications that can accompany the use of viral approaches. We conclude that PCs directly innervate numerous brainstem nuclei, and in many nuclei they strongly inhibit a small fraction of cells. This suggests that PCs selectively target cell types with specific behavioral roles in the brainstem.

Investigators conducting behavioral experiments often need precise control over the timing of the delivery of stimuli to subjects and to collect precise times of subsequent behavioral responses. Furthermore, investigators want fine-tuned control over how various multi-modal cues are presented. behaviorMate takes an ‘Intranet of Things’ approach, using a networked system of hardware and software components for achieving these goals. The system outputs a file with integrated timestamp–event pairs that investigators can then format and process using their own analysis pipelines. We present an overview of the electronic components and GUI application that make up behaviorMate as well as mechanical designs for compatible experimental rigs to provide the reader with the ability to set up their own system. A wide variety of paradigms are supported, including goal-oriented learning, random foraging, and context switching. We demonstrate behaviorMate’s utility and reliability with a range of use cases from several published studies and benchmark tests. Finally, we present experimental validation demonstrating different modalities of hippocampal place field studies. Both treadmill with burlap belt and virtual reality with running wheel paradigms were performed to confirm the efficacy and flexibility of the approach. Previous solutions rely on proprietary systems that may have large upfront costs or present frameworks that require customized software to be developed. behaviorMate uses open-source software and a flexible configuration system to mitigate both concerns. behaviorMate has a proven record for head-fixed imaging experiments and could be easily adopted for task control in a variety of experimental situations.