Standardized automated training of rhesus monkeys for neuroscience research in their housing environment

Abstract

Teaching nonhuman primates the complex cognitive behavioral tasks that are central to cognitive neuroscience research is an essential and challenging endeavor. It is crucial for the scientific success that the animals learn to interpret the often complex task rules and reliably and enduringly act accordingly. To achieve consistent behavior and comparable learning histories across animals, it is desirable to standardize training protocols. Automatizing the training can significantly reduce the time invested by the person training the animal. In addition, self-paced training schedules with individualized learning speeds based on automatic updating of task conditions could enhance the animals' motivation and welfare. We developed a training paradigm for across-task unsupervised training (AUT) of successively more complex cognitive tasks to be administered through a stand-alone housing-based system optimized for rhesus monkeys in neuroscience research settings (Calapai A, Berger M, Niessing M, Heisig K, Brockhausen R, Treue S, Gail A. Behav Res Methods 5: 1-11, 2016). The AUT revealed interindividual differences in long-term learning progress between animals, helping to characterize learning personalities, and commonalities, helping to identify easier and more difficult learning steps in the training protocol. Our results demonstrate that 1) rhesus monkeys stay engaged with the AUT over months despite access to water and food outside the experimental sessions but with lower numbers of interaction compared with conventional fluid-controlled training; 2) with unsupervised training across sessions and task levels, rhesus monkeys can learn tasks of sufficient complexity for state-of-the-art cognitive neuroscience in their housing environment; and 3) AUT learning progress is primarily determined by the number of interactions with the system rather than the mere exposure time. NEW & NOTEWORTHY We demonstrate that highly structured training of behavioral tasks, as used in neuroscience research, can be achieved in an unsupervised fashion over many sessions and task difficulties in a monkey housing environment. Employing a predefined training strategy allows for an observer-independent comparison of learning between animals and of training approaches. We believe that self-paced standardized training can be utilized for pretraining and animal selection and can contribute to animal welfare in a neuroscience research environment.

Keywords: 3R; animal welfare; automated training; cognitive training; environmental enrichment.