Deviance sensitivity is the specific response to a surprising stimulus, one that violates expectations set by the past stimulation stream. In audition, deviance sensitivity is often conflated with stimulus-specific adaptation (SSA), the decrease in responses to a common stimulus that only partially generalizes to other, rare stimuli. SSA is usually measured using oddball sequences, where a common (standard) tone and a rare (deviant) tone are randomly intermixed. However, the larger responses to a tone when deviant does not necessarily represent deviance sensitivity. Deviance sensitivity is commonly tested using a control sequence in which many different tones serve as the standard, eliminating the expectations set by the standard ('deviant among many standards'). When the response to a tone when deviant (against a single standard) is larger than the responses to the same tone in the control sequence, it is concluded that true deviance sensitivity occurs. In primary auditory cortex of anesthetized rats, responses to deviants and to the same tones in the control condition are comparable in size. We recorded local field potentials and multiunit activity from the auditory cortex of awake, freely moving rats, implanted with 32-channel drivable microelectrode arrays and using telemetry. We observed highly significant SSA in the awake state. Moreover, the responses to a tone when deviant were significantly larger than the responses to the same tone in the control condition. These results establish the presence of true deviance sensitivity in primary auditory cortex in awake rats.

Detecting rare and surprising events is a useful strategy for sensory -systems. In the human auditory system, deviance detection is indexed by an important component of the auditory event-related potentials, the mismatch negativity (MMN). Responses of single neurons in the inferior colliculus, medial geniculate body, and auditory cortex of mammals (cats, rats, and mice) show responses that share some properties with MMN: they are evoked by rare events, are preattentive (in as much as they occur in anesthetized animals), and, at least at the level of primary auditory cortex, cannot be accounted for by simple fatigue of the incoming sensory information. Here we extend these results to deviations beyond tone frequency. Recording in rat primary auditory cortex and using oddball sequences consisting of two frozen tokens of broadband noise samples, we found differences between the responses to the same token when used as the common and when used as the deviant, showing an exquisite sensitivity to the small differences between two spectro-temporally similar sounds. Similarly, differential adaptation can be demonstrated when using two word-like stimuli that have been derived from human speech but adapted to the rat auditory system. Thus, differential adaptation to common and rare sounds is present also with sounds whose complexity mirrors that of natural environments.

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.

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.