Novelty detection is a key capability for practical machine learning in the real world, where
models operate in non-stationary conditions and are repeatedly exposed to new, unseen …

Feedback plays an interesting role in perceptual learning. The complex pattern of empirical
results concerning the role of feedback in perceptual learning rules out both a pure …

In recent years, the idea that the prediction of sensory input is one of the major
computational goals of the nervous system led to the development of several large-scale …

Although much recent work in perceptual learning (PL) has focused on basic sensory
discriminations, recent analyses suggest that PL in a variety of tasks depends on processes …

Sleep promotes adaptation of behavior and underlying neural plasticity in comparison to
active wakefulness. However, the contribution of its two main characteristics, sleep-specific …

The functional form of performance improvements has been extensively studied in speeded
cognitive and motor tasks; in such tasks, reductions in response times have been …

Highlights•Methods and results of Perceptual (PL) and Statistical Learning (SL) are
converging.•A Hierarchical Bayesian framework can unify the treatment of PL and SL.•We …

We present a review of recent studies of perceptual learning conducted with nonhuman
animals. The focus of this research has been to elucidate the mechanisms by which mere …

Though practice can lead to improved performance in many domains, it is currently unknown
how practice affects the deployment of selective attention to filter distracting information. We …

Traditional models of insect vision have assumed that insects are only capable of low-level
analysis of local cues and are incapable of global, holistic perception. However, recent …