Summary Practice improves discrimination of many basic visual features, such as contrast, orientation, positional offset, etc. [1–7]. Perceptual learning of many of these tasks is found to be retinal location specific, in that learning transfers little to an untrained retinal location [1, 6–8]. In most perceptual learning models, this location specificity is interpreted as a pointer to a retinotopic early visual cortical locus of learning [1, 6–11]. Alternatively, an untested hypothesis is that learning could occur in a central site, but it consists of two separate aspects: learning to discriminate a specific stimulus feature (“feature learning”), and learning to deal with stimulus non-specific factors like local noise at the stimulus location (“location learning”) [12]. Therefore, learning is not transferable to a new location that has never been location-trained. To test this hypothesis we developed a novel double-training paradigm that employed conventional feature training (e.g., contrast) at one location, and additional training with an irrelevant feature/task (e.g. orientation) at a second location, either simultaneously or at a different time. Our results showed that this additional location training enabled a complete transfer of feature learning (e.g., contrast) to the second location. This finding challenges location specificity and its inferred cortical retinotopy as central concepts to many perceptual learning models, and suggests perceptual learning involves higher non-retinotopic brain areas that enable location transfer.

Visual perceptual learning models, as constrained by orientation and location specificities, propose that learning either reflects changes in V1 neuronal tuning or reweighting specific V1 inputs in either the visual cortex or higher areas. Here we demonstrate that, with a training-plus-exposure procedure, in which observers are trained at one orientation and either simultaneously or subsequently passively exposed to a second transfer orientation, perceptual learning can completely transfer to the second orientation in tasks known to be orientation-specific. However, transfer fails if exposure precedes the training. These results challenge the existing specific perceptual learning models by suggesting a more general perceptual learning process. We propose a rule-based learning model to explain perceptual learning and its specificity and transfer. In this model, a decision unit in high-level brain areas learns the rules of reweighting the V1 inputs through training. However, these rules cannot be applied to a new orientation/location because the decision unit cannot functionally connect to the new V1 inputs that are unattended or even suppressed after training at a different orientation/location, which leads to specificity. Repeated orientation exposure or location training reactivates these inputs to establish the functional connections and enable the transfer of learning.

Unlike most visual tasks, contrast discrimination has been reported to be unchanged by practice (Dorais & Sagi, 1997; Adini, Sagi, & Tsodyks, 2002), unless practice is undertaken in the presence of flankers (context-enabled learning, Adini et al., 2002). Here we show that under experimental conditions nearly identical to those in the no-flanker practice experiment of Adini et al. (2002), practice significantly improved contrast discrimination. Moreover, in a separate experiment, we found that practice without flankers can improve contrast discrimination to a level only reached with flankers in Adini et al. (2002), but further practice with flankers produces no further improvement of contrast discrimination. These results call into question whether the "context-enabled learning" proposed by Adini et al. (2002) is different from regular contrast learning without flankers. In separate experiments, we found that contrast learning is tuned to spatial frequency, orientation, retinal location, and, unexpectedly, contrast. We also replicated Sagi, Adini, Tsodyks, and Wilkonsky's (2003) more recent finding that no regular contrast learning occurs if reference contrasts are randomly interleaved (contrast roving), and further demonstrated that flankers have no effect on contrast learning under contrast roving, another piece of evidence equating "context-enabled learning" to regular contrast learning. The contrast specificity of learning and the lack of learning under contrast roving provide new evidence in favor of a multiple contrast-selective channels model of contrast discrimination, and against saturating transducer models and multiplicative noise models.

Perceptual learning of orientation discrimination is reported to be precisely specific to the trained retinal location. This specificity is often taken as evidence for localizing the site of orientation learning to retinotopic cortical areas V1/V2. However, the extant physiological evidence for training improved orientation turning in V1/V2 neurons is controversial and weak. Here we demonstrate substantial transfer of orientation learning across retinal locations, either from the fovea to the periphery or amongst peripheral locations. Most importantly, we found that a brief pretest at a peripheral location before foveal training enabled complete transfer of learning, so that additional practice at that peripheral location resulted in no further improvement. These results indicate that location specificity in orientation learning depends on the particular training procedures, and is not necessarily a genuine property of orientation learning. We suggest that non-retinotopic high brain areas may be responsible for orientation learning, consistent with the extant neurophysiological data.