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Learning to perform a perceptual decision task is generally achieved through sessions of effortful practice with feedback. Here, we investigated how passive exposure to task-relevant stimuli, which is relatively effortless and does not require feedback, influences active learning. First, we trained mice in a sound-categorization task with various schedules combining passive exposure and active training. Mice that received passive exposure exhibited faster learning, regardless of whether this exposure occurred entirely before active training or was interleaved between active sessions. We next trained neural-network models with different architectures and learning rules to perform the task. Networks that use the statistical properties of stimuli to enhance separability of the data via unsupervised learning during passive exposure provided the best account of the behavioral observations. We further found that, during interleaved schedules, there is an increased alignment between weight updates from passive exposure and active training, such that a few interleaved sessions can be as effective as schedules with long periods of passive exposure before active training, consistent with our behavioral observations. These results provide key insights for the design of efficient training schedules that combine active learning and passive exposure in both natural and artificial systems. 

Most current theories and models of second language speech perception are grounded in the notion that learners acquire speech sound categories in their target language. In this paper, this classic idea in speech perception is revisited, given that clear evidence for formation of such categories is lacking in previous research. To understand the debate on the nature of speech sound representations in a second language, an operational definition of “category” is presented, and the issues of categorical perception and current theories of second language learning are reviewed. Following this, behavioral and neuroimaging evidence for and against acquisition of categorical representations is described. Finally, recommendations for future work are discussed. The paper concludes with a recommendation for integration of behavioral and neuroimaging work and theory in this area.