behaviorMate: An Intranet of Things Approach for Adaptable Control of Behavioral and Navigation-Based Experiments.
John C BowlerGeorge ZakkaHyun Choong YongWenke LiBovey RaoZhenrui LiaoJames B PriestleyAttila LosonczyPublished in: bioRxiv : the preprint server for biology (2023)
Investigators conducting behavioral experiments often need precise control over the timing of stimulus delivery and logging of behavioral response times. Furthermore, investigators may want fine-tuned control over how various multimodal cues are presented. behaviorMate is a cost-effective, integrated system of hardware and software components for achieving these goals without requiring the user to write any code. Straightforward setup and ease of use facilitate the reproducibility of complex behavioral tasks. Following each session recording, behaviorMate outputs a file with integrated timestamp-event pairs the investigator can format and process using their own analysis pipeline. This time-stamped behavior data is especially useful when aligned with other data streams such as 2-photon calcium imaging or electrophysiological recordings. We present an overview of the electronic components and application that comprise 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 behavioral 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 of the behaviorMate system in multimodal hippocampal place field studies.