A1 neural basis of frequency discrimination learning

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DESCRIPTION (provided by applicant): This application outlines a direct study of the mechanisms of auditory learning. Animals are capable of making new associations between positive reinforcers, the sensory context that preceded them, and the motor acts that cause them. The proposed studies will use multiple microelectrode implant technology to record simultaneously from a large number of neurons in auditory cortex throughout a period in which an animal acquires a new association. The specific intent will be to observe how the auditory cortex representation of the sensory context is altered by the learning. The monkeys will be trained to discriminate short sound tones. As they begin to perform the task to receive rewards, their brain learning machinery is engaged and causes unavoidable changes in how sounds are represented. Data will be collected in parallel, in terms of the animal's perceptual capabilities and the response properties of neurons in auditory fields within and outside the behavioral tasks. The use of implants in neural systems has advanced much in the last decade; this study will apply that technology to study learning. In the first phase of training, animals will respond to short tones that are just higher in frequency than fixed comparison tones. Preliminary studies have shown that if the target stimulus comes from a fixed range, the representation of that frequency range grows and intensifies. After this initial phase, the animals will perform the same frequency discrimination task using randomized frequencies for comparison and target tone pips. A control experiment will replicate the trials of the first phase of training in naive animals that are only passive listeners. These studies should contribute to defining the plastic properties of cortical fields as dynamic learning neural networks. Such networks are most easily understood in terms of their initial sets of connections and their learning rules. This study will isolate and test different hypotheses for learning rules, and will lead to a greater understanding of the adaptive role of the cerebral cortex in general, both in instrumental learning and in classical conditioning.