Perceptual learning is any relatively permanent change of perception (usually improvement as measured by changes in perceptual thresholds or brain physiology) as a result of experience. The specification “relatively permanent” distinguishes perceptual learning from sensitization (and habituation) as well as from priming, which denote more transient changes in perception. In contrast to classical conditioning, perceptual learning involves individual stimuli rather than the association of two or more stimuli, and is not restricted to one specific response, as in operant conditioning. Perceptual learning clearly is of the implicit or procedural type: it does not lead to conscious insights that can be (easily) communicated, as is the case in declarative, or factual learning. The brain circuits storing facts and events (episodes) seem to at least partially differ from those analyzing the outer world. Hence, in amnesic syndromes, scenes may be analyzed without subsequent memory (e.g., after lesions of the hippocampal formation). Perceptual learning, on the other hand, seems to change the very cortical circuits solving the perceptual task trained. In this review, I will present results suggesting that perceptual learning is (a) very specific for elementary attributes of the stimulus, such as its orientation, and (b) able to change signal processing even on the level of primary sensory cortices that were considered as “hard wired” in adults in the not too distant past.
The perceptual task employed to test perceptual learning in most of the experiments reported here is vernier acuity, a type of visual hyperacuity (Wülfing,
1892; Westheimer,
1976). In these hyperacuity tasks, even untrained observers can attain thresholds around 10 arcsec. (These are thresholds calculated according to the conventional definition, while the appropriately calculated thresholds are a factor of 2 higher, cf. Harris & Fahle,
1995). These thresholds are at least slightly below the spacing of foveal photoreceptors, and through training, they can improve by up to a factor of 5 (i.e., to 2 arcsec in especially gifted and trained observers).
Obviously, performance in these tasks is not determined primarily by the optics of the eye nor by the photoreceptor spacing, though both factors are important because they ensure that the requirements of the sampling theorem for complete, high-resolution reconstruction of the original stimulus are met (cf., Barlow,
1981; Crick, Marr, & Poggio,
1981). Performance is instead limited by the signal-to-noise ratio of the information reaching the cortex and by the precision and selectivity of cortical processing. Hyperacuity is a good choice to study learning processes in visual perception because it is a very sensitive measure based on cortical processing. Moreover, hyperacuity is not some freak ability of over-trained laboratory observers but can be achieved even without specific training, and simultaneously at many positions in the visual field (Fahle,
1991).