The role of external reinforcement is an issue of much debate and uncertainty in perceptual learning research. Although it is commonly acknowledged that external reinforcement, such as performance feedback, can aid in perceptual learning (M. H. Herzog & M. Fahle, 1997), there are many examples in which it is not required (K. Ball & R. Sekuler, 1987; M. Fahle, S. Edelman, & T. Poggio, 1995; A. Karni & D. Sagi, 1991; S. P. McKee & G. Westheimer, 1978; L. P. Shiu & H. Pashler, 1992). Additionally, learning without external reinforcement can occur even for stimuli that are irrelevant to the subject's task (A. R. Seitz & T. Watanabe, 2003). It has been thus hypothesized that internal reinforcement can serve a similar role as external reinforcement in learning (M. H. Herzog & M. Fahle, 1998; A. Seitz & T. Watanabe, 2005). This idea suggests that perceptual learning should occur in the absence of external reinforcement provided that easy exemplars are utilized as a basis for the subject to generate internal reinforcement. Here, we report results from two studies that show that this is not always the case. In the first study, subjects participated in two sessions of a motion direction discrimination task with low-contrast dots moving in directions separated by 90 degrees. In the second study, subjects participated in 12 orientation-discrimination sessions using oriented bars (oriented either 70 degrees or 110 degrees) that were masked by spatial noise. Trials of different signal levels (yielding psychometric functions ranging from chance to ceiling) were randomly interleaved. In both studies, subjects experiencing external reinforcement showed significant learning, whereas subjects receiving no external reinforcement failed to show learning. We conclude that while internal reinforcement is an important learning signal, the presence of easy exemplars is not sufficient to generate reinforcement signals.

Critical flicker fusion thresholds (CFFT) describe when quick amplitude modulations of a light source become undetectable as the frequency of the modulation increases. The threshold at which CFF occurs has been shown to remain constant under repeated testing. Additionally, CFF thresholds are correlated with various measures of intelligence, and have been regarded by clinicians as a general measure of cortical processing capacity. For these reasons, CFF is used as a cognitive indicator in drug studies, as a measure of fatigue, and has been suggested as a diagnostic measure for various brain diseases. Here we report that CFFT increases dramatically in subjects who are trained with a motion-direction learning procedure. Control tasks demonstrate that CFFT changes are tightly coupled with improvements in discriminating the direction of motion stimuli, and are likely related to plasticity in low-level visual areas that are specialized to process motion signals. This plasticity is long-lasting and is retained for at least one year after training. Combined, these results show that CFFT relates to a specialized sensory process and bring into question that CFFT is a measure of high-level, or general, processes.

Perceptual learning is an improvement in one's sensory abilities after training and is thought to help us to better adapt to the sensory environment. Here, we show that perceptual learning also can lead to misperceptions, such that subjects actually perceive stimuli when none are physically presented. After learning, subjects not only showed enhanced performance when tested with the motion direction of the trained stimulus but also often reported seeing dots moving in the trained direction when no stimulus was displayed. We further show that these misperceptions are not attributable to a response bias. These results show that there are costs as well as benefits to perceptual learning and that performance enhancements for a specific feature also can be accompanied by misperceptions of the visual environment.motion ͉ plasticity vision ͉ learning ͉ psychophysics A central issue in neuroscience is how the adult brain selectively adapts to important environmental changes. Although the brain needs to adapt to new environments, its architecture must protect itself from modification from the continual bombardment of undesirable information. How the brain solves this so-called stability-plasticity dilemma (1, 2) in its sensory areas is largely unresolved.Plasticity in the early sensory systems has traditionally been thought to occur only during early development and then to be hard-wired in adults (3). This view has been substantiated by studies of critical period development in which gross plasticity of early sensory areas only occurs for a brief period after birth (4, 5). These data were used to support the hypothesis that as opposed to higher-level perceptual stages, the low-level sensory stages need to consistently process primitive sensory features, such as in vision orientation, spatial frequency, and local motion. The stabilization of sensory systems after birth is important because plasticity in sensory areas would alter the input to higher-level processing areas and fundamentally affect our perceptions as well as the comparison between new perceptions and learned templates.Recently, the view that once sensory systems are stabilized they never change has been challenged by studies of perceptual learning (6-11), which show that even in adults, perceptual abilities can be sharpened with repeated exposure or training. For example, experts such as radiologists develop with training refined abilities to distinguish subtle patterns of tumors in images that show no pattern to the untrained eye (12). Psychophysical studies of visual plasticity have demonstrated that detection or discrimination thresholds can be reduced and usually show a high degree of specificity with respect to the orientation (9, 13, 14), direction (15, 16), retinotopic location (9, 13, 17), and ocularity (13) of the trained visual stimuli. The specificity of perceptual learning has been regarded as a manifestation of plasticity in sensory cortical processes including very low-level stages of processing (18-21), although this does not exclude the invo...