Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Reinforcement-guided decision making is the ability to choose between competing courses of action based on the relative value of the benefits and their consequences. This process is integral to the normal human behavior and has been shown to be disrupted by neurological and psychiatric disorders such as addiction, schizophrenia, and depression. Rodents have long been used to uncover the neurobiology of human cognition. To this end, several behavioral tasks have been developed; however, most are non-automated and are labor-intensive. The recent development of the open-source microcontroller has enabled researchers to automate operant-based tasks for assessing a variety of cognitive tasks, standardizing the stimulus presentation, improving the data recording and consequently, improving the research output. Here, we describe an automated delay-based reinforcement-guided decision-making task, using an operant T-maze controlled by custom-written software programs. Using these decision-making tasks, we show the changes in the local field potential activities in the anterior cingulate cortex of a rat whilst it performs a delay-based cost-and-benefit decision-making task.