Behavior consists of the interaction between an organism and its environment, and is controlled by the brain. However, while brain activity varies at fast, sub-seconds time scales, behavioral measures tend to be temporally coarse, often limited just to the success or failure in a trial. The large gap between the temporal resolutions at which brain and behavior are observed likely impedes our understanding of the neural mechanisms underlying behavior. To overcome this problem, we developed the RIFF: an interactive arena for rats that has multiple feeding areas, multiple sound sources, and high-resolution tracking of behavior, with concomitant wireless electrophysiological recordings. The RIFF can be flexibly programmed to create arbitrarily complex tasks that the rats have to solve. It records unrestrained rat behavior together with neuronal data from chronically implanted electrodes. We present here a detailed description of the RIFF. We illustrate its power with results from two exemplary tasks. Rats learned within two days a complex task that required timed movement, and developed anticipatory behavior. Rats found solution strategies that differed between animals but were stable within each animal. We report auditory responses in and around primary auditory cortex as well as in the posterior insular cortex, but show that often the same neurons were also sensitive to non-auditory parameters such as rat location and body orientation. These parameters are crucial for state assessment and the selection of future actions. Our findings show that the complex, unrestrained behavior of rats can be studied in a controlled environment, enabling novel insights into the cognitive capabilities and learning mechanisms of rats. This combination of electrophysiology and detailed behavioral observation opens the way to a better understanding of how the brain controls behavior.

The primary data are the impulse responses that were recorded in an echoic environment, using a set of twelve loudspeakers and a microphone. They were used as a part of an acoustic calibration process of large environments, as presented by Kazakov and Nelken (DOI: 10.1016/j.jneumeth.2018.08.025; Kazakov and Nelken, 2018). The impulse responses can be also used to localize the microphone in 3D (multi-lateration). The required audio files and the MATLAB code allows a complete reproduction of the experiment.

Background:The sound fed to a loudspeaker may significantly differ from that reaching the ear of the listener. The transformation from one to the other consists of spectral distortions with strong dependence on the relative locations of the speaker and the listener as well as on the geometry of the environment. With the increased importance of research in awake, freely-moving animals in large arenas, it becomes important to understand how animal location influences the corresponding spectral distortions.New Method: We describe a full calibration pipeline that includes spatial sampling and estimation of the spectral distortions. We estimated the impulse responses of the environment using Golay complementary sequences.Using those sequences, we also describe an acoustic 3D localization method for freely moving animals.Results: In our arena, the impulse responses are dominated by a small number of strong reflections. We use this understanding to provide guidelines for designing the geometry of the environment as well as the presented sounds, in order to provide more uniform sound levels throughout the environment. Our 3D localization method achieves a 1 cm precision through the utilization of sound cues only.Comparison with Existing Methods: To our knowledge, this is the first description of a large-scale acoustic calibration pipeline with acoustic localization for neuroscience studies.Conclusions: Principled sampling of large arena allows for better design and control of the acoustic information provided to freely-moving animals.

Background Behavior consists of the interaction between an organism and its environment, and is controlled by the brain. Brain activity varies at sub-second time scales, but behavioral measures are usually coarse (often consisting of only binary trial outcomes). Results To overcome this mismatch, we developed the Rat Interactive Foraging Facility (RIFF): a programmable interactive arena for freely moving rats with multiple feeding areas, multiple sound sources, high-resolution behavioral tracking, and simultaneous electrophysiological recordings. The paper provides detailed information about the construction of the RIFF and the software used to control it. To illustrate the flexibility of the RIFF, we describe two complex tasks implemented in the RIFF, a foraging task and a sound localization task. Rats quickly learned to obtain rewards in both tasks. Neurons in the auditory cortex as well as neurons in the auditory field in the posterior insula had sound-driven activity during behavior. Remarkably, neurons in both structures also showed sensitivity to non-auditory parameters such as location in the arena and head-to-body angle. Conclusions The RIFF provides insights into the cognitive capabilities and learning mechanisms of rats and opens the way to a better understanding of how brains control behavior. The ability to do so depends crucially on the combination of wireless electrophysiology and detailed behavioral documentation available in the RIFF.