Two-stage model in perceptual learning: toward a unified theory

Distinct Neural Plasticity Enhancing Visual Perception

The developed human brain shows remarkable plasticity following perceptual learning, resulting in improved visual sensitivity. However, such improvements commonly require extensive stimuli exposure. Here we show that efficiently enhancing visual perception with minimal stimuli exposure recruits distinct neural mechanisms relative to standard repetition-based learning. Participants (n = 20, 12 women, 8 men) encoded a visual discrimination task, followed by brief memory reactivations of only five trials each performed on separate days, demonstrating improvements comparable with standard repetition-based learning (n = 20, 12 women, 8 men). Reactivation-induced learning engaged increased bilateral intraparietal sulcus (IPS) activity relative to repetition-based learning. Complementary evidence for differential learning processes was further provided by temporal-parietal resting functional connectivity changes, which correlated with behavioral improvements. The results suggest that efficiently enhancing visual perception with minimal stimuli exposure recruits distinct neural processes, engaging higher-order control and attentional resources while leading to similar perceptual gains. These unique brain mechanisms underlying improved perceptual learning efficiency may have important implications for daily life and in clinical conditions requiring relearning following brain damage.

Unsupervised learning as a computational principle works in visual learning of natural scenes, but not of artificial stimuli

The question of whether we learn exposed visual features remains a subject of controversy. A prevalent computational model suggests that visual features frequently exposed to observers in natural environments are likely to be learned. However, this unsupervised learning model appears to be contradicted by the significant body of experimental results with human participants that indicates visual perceptual learning (VPL) of visible task-irrelevant features does not occur with frequent exposure. Here, we demonstrate a resolution to this controversy with a new finding: Exposure to a dominant global orientation as task-irrelevant leads to VPL of the orientation, particularly when the orientation is derived from natural scene images, whereas VPL did not occur with artificial images even with matched distributions of local orientations and spatial frequencies to natural scene images. Further investigation revealed that this disparity arises from the presence of higher-order statistics derived from natural scene images-global structures such as correlations between different local orientation and spatial frequency channels. Moreover, behavioral and neuroimaging results indicate that the dominant orientation from these higher-order statistics undergoes less attentional suppression than that from artificial images, which may facilitate VPL. Our results contribute to resolving the controversy by affirming the validity of unsupervised learning models for natural scenes but not for artificial stimuli. They challenge the assumption that VPL occurring in everyday life can be predicted by laws governing VPL for conventionally used artificial stimuli.

Transcranial direct current stimulation of the prefrontal and visual cortices diversely affects early and late perceptual learning

BACKGROUND

Research has shown that visual perceptual learning (VPL) is related to modifying neural activity in higher level decision-making regions. However, the causal roles of the prefrontal and visual cortexes in VPL are still unclear. Here, we investigated how anodal transcranial direct current stimulation (tDCS) of the prefrontal and visual cortices modulates VPL in the early and later phases and the role of multiple brain regions.

METHODS

Perceptual learning on the coherent motion direction identification task included early and later stages. After early training, participants needed to continuously train to reach a plateau; once the plateau was reached, participants entered a later stage. Sixty participants were randomly divided into five groups. Regardless of the training at the early and later stages, four groups received multitarget tDCS over the right dorsolateral prefrontal cortex (rDLPFC) and right middle temporal area (rMT), single-target tDCS over the rDLPFC, and single-target tDCS over the rMT or sham stimulation, and one group was stimulated at the ipsilateral brain region (i.e., left MT).

RESULTS

Compared with sham stimulation, multitarget and two single-target tDCS over the rDLPFC or rMT improved posttest performance and accelerated learning during the early period. However, multitarget tDCS and two single-target tDCS led to equivalent benefits for VPL. Additionally, these beneficial effects were absent when anodal tDCS was applied to the ipsilateral brain region. For the later period, the above facilitating effects on VPL induced by multitarget or single-target tDCS disappeared.

CONCLUSIONS

This study suggested the causal role of the prefrontal and visual cortices in visual motion perceptual learning by anodal tDCS but failed to find greater beneficial effects by simultaneously stimulating the prefrontal and visual cortices. Future research should investigate the functional associations between multiple brain regions to further promote VPL.

Table tennis players use superior saccadic eye movements to track moving visual targets

Introduction

Table tennis players perform visually guided visuomotor responses countlessly. The exposure of the visual system to frequent and long-term motion stimulation has been known to improve perceptual motion detection and discrimination abilities as a learning effect specific to that stimulus, so may also improve visuo-oculomotor performance. We hypothesized and verified that table tennis players have good spatial accuracy of saccades to moving targets.

Methods

University table tennis players (TT group) and control participants with no striking-sports experience (Control group) wore a virtual reality headset and performed two ball-tracking tasks to track moving and stationary targets in virtual reality. The ball moved from a predetermined position on the opponent's court toward the participant's court. A total of 54 conditions were examined for the moving targets in combinations of three ball trajectories (familiar parabolic, unfamiliar descent, and unfamiliar horizontal), three courses (left, right, and center), and six speeds.

Results and discussion

All participants primarily used catch-up saccades to track the moving ball. The TT group had lower mean and inter-trial variability in saccade endpoint error compared to the Control group, showing higher spatial accuracy and precision, respectively. It suggests their improvement of the ability to analyze the direction and speed of the ball's movement and predict its trajectory and future destination. The superiority of the spatial accuracy in the TT group was seen in both the right and the left courses for all trajectories but that of precision was for familiar parabolic only. The trajectory dependence of improved saccade precision in the TT group implies the possibility that the motion vision system is trained by the visual stimuli frequently encountered in table tennis. There was no difference between the two groups in the onset time or spatial accuracy of saccades for stationary targets appearing at various positions on the ping-pong table.

Conclusion

Table tennis players can obtain high performance (spatial accuracy and precision) of saccades to track moving targets as a result of motion vision ability improved through a vast amount of visual and visuo-ocular experience in their play.

Perceptual learning in humans: An active, top-down-guided process

Deep neural network (DNN) models of human-like vision are typically built by feeding blank slate DNN visual images as training data. However, the literature on human perception and perceptual learning suggests that developing DNNs that truly model human vision requires a shift in approach in which perception is not treated as a largely bottom-up process, but as an active, top-down-guided process.

Modulating temporal dynamics of performance across retinotopic locations enhances the generalization of perceptual learning

Human visual perception can be improved through perceptual learning. However, such learning is often specific to stimulus and learning conditions. Here, we explored how temporal dynamics of performance across conditions impact learning generalization. Participants performed a visual task, with the target at retinotopic location A. Then, the target was presented at location B either immediately after location A (same-session performance) or following a 48h consolidation period (different-session performance). Long-term generalization was measured the following week. Following initial training, both groups demonstrated generalization, consistent with previous accounts of fast learning. However, long-term generalization was enhanced in the same-session performance group. Consistently, improvements at locations A and B were correlated only following same-session performance, implying an integrated learning process across locations. The results support a new account of perceptual learning and generalization dynamics, suggesting that the temporal proximity of learning and consolidation of different conditions may integrate correlated learning processes, facilitating generalized learning.

Neural networks underlying visual illusions: An activation likelihood estimation meta-analysis

Visual illusions have long been used to study visual perception and contextual integration. Neuroimaging studies employ illusions to identify the brain regions involved in visual perception and how they interact. We conducted an Activation Likelihood Estimation (ALE) meta-analysis and meta-analytic connectivity modeling on fMRI studies using static and motion illusions to reveal the neural signatures of illusory processing and to investigate the degree to which different areas are commonly recruited in perceptual inference. The resulting networks encompass ventral and dorsal regions, including the inferior and middle occipital cortices bilaterally in both types of illusions. The static and motion illusion networks selectively included the right posterior parietal cortex and the ventral premotor cortex respectively. Overall, these results describe a network of areas crucially involved in perceptual inference relying on feed-back and feed-forward interactions between areas of the ventral and dorsal visual pathways. The same network is proposed to be involved in hallucinogenic symptoms characteristic of schizophrenia and other disorders, with crucial implications in the use of illusions as biomarkers.

Dissociable effects of transcranial direct current stimulation (tDCS) on early and later stages of visual motion perceptual learning

Transcranial direct current stimulation (tDCS) has the potential to benefit visual perceptual learning (VPL). However, previous studies investigated the effect of tDCS on VPL within early sessions, and the influence of tDCS on learning effects at later stages (plateau level) is unclear. Here, participants completed 9 days of training on coherent motion direction identification to reach a plateau (stage 1) and then continued training for 3 days (stage 2). The coherent thresholds were measured before training, after stage 1 and after stage 2. In the first group, anodal tDCS was applied when participants trained over a period of 12 days (stage 1+ stage 2). In the second group, participants completed a 9-day training period without any stimulation to reach a plateau (stage 1); after that, participants completed a 3-day training period while anodal tDCS was administered (stage 2). The third group was treated the same as the second group except that anodal tDCS was replaced by sham tDCS. The results showed that anodal tDCS did not improve posttest performance after the plateau was reached. The comparison of learning curves between the first and third groups showed that anodal tDCS decreased the threshold at the early stage, but it did not improve the plateau level. For the second and third groups, anodal tDCS did not further enhance the plateau level after a continued 3-day training period. These results suggest that anodal tDCS boosts VLP during the early period of training sessions, but it fails to facilitate later learning effects. This study contributed to a deep understanding of the dissociable tDCS effects at distinct temporal stages, which may be due to the dynamic change in brain regions during the time course of VPL.

The phase of plasticity-induced neurochemical changes of high-frequency repetitive transcranial magnetic stimulation are different from visual perceptual learning

Numerous studies have found that repetitive transcranial magnetic stimulation (rTMS) modulates plasticity. rTMS has often been used to change neural networks underlying learning, often under the assumption that the mechanism of rTMS-induced plasticity should be highly similar to that associated with learning. The presence of visual perceptual learning (VPL) reveals the plasticity of early visual systems, which is formed through multiple phases. Hence, we tested how high-frequency (HF) rTMS and VPL modulate the effect of visual plasticity by investigating neurometabolic changes in early visual areas. We employed an excitatory-to-inhibitory (E/I) ratio, which refers to glutamate concentration divided by GABA+ concentration, as an index of the degree of plasticity. We compared neurotransmitter concentration changes after applying HF rTMS to the visual cortex with those after training in a visual task, in otherwise identical procedures. Both the time courses of the E/I ratios and neurotransmitter contributions to the E/I ratio significantly differed between HF rTMS and training conditions. The peak E/I ratio occurred 3.5 h after HF rTMS with decreased GABA+, whereas the peak E/I ratio occurred 0.5 h after visual training with increased glutamate. Furthermore, HF rTMS temporally decreased the thresholds for detecting phosphene and perceiving low-contrast stimuli, indicating increased visual plasticity. These results suggest that plasticity in early visual areas induced by HF rTMS is not as involved in the early phase of development of VPL that occurs during and immediately after training.

Visual Plasticity in Adulthood: Perspectives from Hebbian and Homeostatic Plasticity

The visual system retains profound plastic potential in adulthood. In the current review, we summarize the evidence of preserved plasticity in the adult visual system during visual perceptual learning as well as both monocular and binocular visual deprivation. In each condition, we discuss how such evidence reflects two major cellular mechanisms of plasticity: Hebbian and homeostatic processes. We focus on how these two mechanisms work together to shape plasticity in the visual system. In addition, we discuss how these two mechanisms could be further revealed in future studies investigating cross-modal plasticity in the visual system.

Tactile angle discriminability improvement: Contributions of working memory training and continuous attended sensory input

Perceptual learning is commonly assumed to enhance perception through continuous attended sensory input. However, learning is generalizable to performance in untrained stimuli and tasks. Although previous studies have observed a possible generalization effect across tasks as a result of working memory (WM) training, comparisons of the contributions of WM training and continuous attended sensory input to perceptual learning generalization are still rare. Therefore, we compared which factors contributed most to perceptual generalization and investigated which skills acquired during WM training led to tactile generalization across tasks. Here, a Braille-like dot pattern matching n-back WM task was used as the WM training task, with four workload levels (0, 1, 2, and 3-back levels). A tactile angle discrimination (TAD) task was used as a pre- and posttest to assess improvements in tactile perception. Between tests, four subject groups were randomly assigned to four different workload n-back tasks to consecutively complete three sessions of training. The results showed that tactile n-back WM training could enhance TAD performance, with the 3-back training group having the highest TAD threshold improvement rate. Furthermore, the rate of WM capacity improvement on the 3-back level across training sessions was correlated with the rate of TAD threshold improvement. These findings suggest that continuous attended sensory input and enhanced WM capacity can lead to improvements in TAD ability, and that greater improvements in WM capacity can predict greater improvements in TAD performance.

NEW & NOTEWORTHY Perceptual learning is not always specific to the trained task and stimuli. We demonstrate that both continuous attended sensory input and improved WM capacity can be used to enhance tactile angle discrimination (TAD) ability. Moreover, WM capacity improvement is important in generalizing the training effect to the TAD ability. These findings contribute to understanding the mechanism of perceptual learning generalization across tasks.

Training peripheral vision to read: Using stimulus exposure and identity priming

Reading in the periphery can be improved with perceptual learning. A conventional training paradigm involves repeated practice on a character-based task (e.g., recognizing random letters/words). While the training is effective, the hours of strenuous effort required from the trainees makes it difficult to implement the training in low-vision patients. Here, we developed a training paradigm utilizing stimulus exposure and identity priming to minimize training effort and improve training accessibility while maintaining the active engagement of observers through a stimulus visibility task. Twenty-one normally sighted young adults were randomly assigned to three groups: a control group, a with-repetition training group, and a without-repetition training group. All observers received a pre-test and a post-test scheduled 1 week apart. Each test consisted of measurements of reading speed, visual-span profile, the spatial extent of crowding, and isolated-letter profiles at 10° eccentricity in the lower visual field. Training consists of five daily sessions (a total of 7,150 trials) of viewing trigram stimuli (strings of three letters) with identity priming (prior knowledge of target letter identity). The with-repetition group was given the option to replay each stimulus (averaged 0.4 times). In comparison to the control group, both training groups showed significant improvements in all four performance measures. Stimulus replay did not yield a measurable benefit on learning. Learning transferred to various untrained tasks and conditions, such as the reading task and untrained letter size. Reduction in crowding was the main basis of the training-related improvement in reading. We also found that the learning can be partially retained for a minimum of 3 months and that complete retention is attainable with additional monthly training. Our findings suggest that conventional training task that requires recognizing random letters or words is dispensable for improving peripheral reading. Utilizing stimulus exposure and identity priming accompanied by a stimulus visibility task, our novel training procedure offers effective intervention, simple implementation, capability for remote and self-administration, and an easy translation into low-vision reading rehabilitation.

Assessing the functions underlying learning using by-trial and by-participant models: Evidence from two visual perceptual learning paradigms

Inferred mechanisms of learning, such as those involved in improvements resulting from perceptual training, are reliant on (and reflect) the functional forms that models of learning take. However, previous investigations of the functional forms of perceptual learning have been limited in ways that are incompatible with the known mechanisms of learning. For instance, previous work has overwhelmingly aggregated learning data across learning participants, learning trials, or both. Here we approach the study of the functional form of perceptual learning on the by-person and by-trial levels at which the mechanisms of learning are expected to act. Each participant completed one of two visual perceptual learning tasks over the course of two days, with the first 75% of task performance using a single reference stimulus (i.e., "training") and the last 25% using an orthogonal reference stimulus (to test generalization). Five learning functions, coming from either the exponential or the power family, were fit to each participant's data. The exponential family was uniformly supported by Bayesian Information Criteria (BIC) model comparisons. The simplest exponential function was the best fit to learning on a texture oddball detection task, while a Weibull (augmented exponential) function tended to be the best fit to learning on a dot-motion discrimination task. The support for the exponential family corroborated previous by-person investigations of the functional form of learning, while the novel evidence supporting the Weibull learning model has implications for both the analysis and the mechanistic bases of the learning.

Reward Rapidly Enhances Visual Perception

Rewards exert a deep influence on our cognition and behavior. Here, we used a paradigm in which reward information was provided at either encoding or retrieval of a brief, masked stimulus to show that reward can also rapidly modulate perceptual encoding of visual information. Experiment 1 (n = 30 adults) showed that participants' response accuracy was enhanced when a to-be-encoded grating signaled high reward relative to low reward, but only when the grating was presented very briefly and participants reported that they were not consciously aware of it. Experiment 2 (n = 29 adults) showed that there was no difference in participants' response accuracy when reward information was instead provided at the stage of retrieval, ruling out an explanation of the reward-modulation effect in terms of differences in motivated retrieval. Taken together, our findings provide behavioral evidence consistent with a rapid reward modulation of visual perception, which may not require consciousness.

Stereoscopic Visual Perceptual Learning in Seniors

BACKGROUND

We showed that seniors can improve their stereoscopic ability (stereoacuity) and corresponding reaction time with repetitive training and, furthermore, that these improvements through training are still present even after a longer period of time without training.

METHODS

Eleven seniors (average age: 85.90 years) trained twice a week for six weeks with dynamic stereoscopic perception training using a vision training apparatus (c-Digital Vision Trainer®). Stereoscopic training was performed in 12 training session (n = 3072) of visual tasks. The task was to identify and select one of four figures (stereoscopic stimuli) that was of a different disparity using a controller. The tests included a dynamic training (showing rotating balls) and a static test (showing plates without movement). Before and after training, the stereoacuity and the corresponding reaction times were identified with the static stereotest in order to determine the individual training success. The changes in respect to reaction time of stereoscopic stimuli with decreasing disparity were calculated.

RESULTS

After 6 weeks of training, reaction time improved in the median from 936 arcsec to 511 arcsec. Stereoscopic vision improved from 138 arcsec to 69 arcsec, which is an improvement of two levels of difficulty. After 6 months without training, the improvement, achieved by training, remained stable.

CONCLUSIONS

In older people, visual training leads to a significant, long-lasting improvement in stereoscopic vision and the corresponding reaction time in seniors. This indicates cortical plasticity even in old age.

Contrast adaptation improves spatial integration

The effects of contrast adaptation and contrast area summation (spatial integration) were investigated using a contrast discrimination task. The task consisted of a target of variable size, and a pedestal with a fixed base contrast. Discrimination performance was examined for a condition in which the pedestal size was fixed, equal to the largest target size, and for a condition in which the pedestal size matched the target size and thus varied with it. Repeated performance of the task produced rapid within-session improvements for both conditions. For stimuli with a matching size of target and pedestal, the performance improved only for the larger targets, indicating the development of spatial integration, which was initially absent for these stimuli. However, the improvements were mostly temporary, and were not fully retained between subsequent daily sessions. The temporary nature of the sensitivity gains implies that they resulted, at least in part, from rapid adaptation to the stimulus contrast. We suggest that adaptation decorrelates and thus reduces the spatial noise generated by a high-contrast pedestal, leading to improved spatial integration (area summation) and better contrast sensitivity. A decorrelation model successfully predicted our experimental results.

Stimulus variability and task relevance modulate binding-learning

Classical theories of attention posit that integration of features into object representation (or feature binding) requires engagement of focused attention. Studies challenging this idea have demonstrated that feature binding can happen outside of the focus of attention for familiar objects, as well as for arbitrary color-orientation conjunctions. Detection performance for arbitrary feature conjunction improves with training, suggesting a potential role of perceptual learning mechanisms in the integration of features, a process called "binding-learning". In the present study, we investigate whether stimulus variability and task relevance, two critical determinants of visual perceptual learning, also modulate binding-learning. Transfer of learning in a visual search task to a pre-exposed color-orientation conjunction was assessed under conditions of varying stimulus variability and task relevance. We found transfer of learning for the pre-exposed feature conjunctions that were trained with high variability (Experiment 1). Transfer of learning was not observed when the conjunction was rendered task-irrelevant during training due to pop-out targets (Experiment 2). Our findings show that feature binding is determined by principles of perceptual learning, and they support the idea that functions traditionally attributed to goal-driven attention can be grounded in the learning of the statistical structure of the environment.

Individual difference predictors of learning and generalization in perceptual learning

Given appropriate training, human observers typically demonstrate clear improvements in performance on perceptual tasks. However, the benefits of training frequently fail to generalize to other tasks, even those that appear similar to the trained task. A great deal of research has focused on the training task characteristics that influence the extent to which learning generalizes. However, less is known about what might predict the considerable individual variations in performance. As such, we conducted an individual differences study to identify basic cognitive abilities and/or dispositional traits that predict an individual's ability to learn and/or generalize learning in tasks of perceptual learning. We first showed that the rate of learning and the asymptotic level of performance that is achieved in two different perceptual learning tasks (motion direction and odd-ball texture detection) are correlated across individuals, as is the degree of immediate generalization that is observed and the rate at which a generalization task is learned. This indicates that there are indeed consistent individual differences in perceptual learning abilities. We then showed that several basic cognitive abilities and dispositional traits are associated with an individual's ability to learn (e.g., simple reaction time; sensitivity to punishment) and/or generalize learning (e.g., cognitive flexibility; openness to experience) in perceptual learning tasks. We suggest that the observed individual difference relationships may provide possible targets for future intervention studies meant to increase perceptual learning and generalization.

Multi-Stage Cortical Plasticity Induced by Visual Contrast Learning

Perceptual learning, the improved sensitivity via repetitive practice, is a universal phenomenon in vision and its neural mechanisms remain controversial. A central question is which stage of processing is changed after training. To answer this question, we measured the contrast response functions and electroencephalography (EEG) before and after ten daily sessions of contrast detection training. Behavioral results showed that training substantially improved visual acuity and contrast sensitivity. The learning effect was significant at the trained condition and partially transferred to control conditions. Event-related potential (ERP) results showed that training reduced the latency in both early and late ERPs at the trained condition. Specifically, contrast-gain-related changes were observed in the latency of P1, N1-P2 complex, and N2, which reflects neural changes across the early, middle, and high-level sensory stages. Meanwhile, response-gain-related changes were found in the latency of N2, which indicates stimulus-independent effect in higher-level stages. In sum, our findings indicate that learning leads to changes across different processing stages and the extent of learning and transfer may depend on the specific stage of information processing.

Speech in noise perception improved by training fine auditory discrimination: far and applicable transfer of perceptual learning

A longstanding focus of perceptual learning research is learning specificity, the difficulty for learning to transfer to tasks and situations beyond the training setting. Previous studies have focused on promoting transfer across stimuli, such as from one sound frequency to another. Here we examined whether learning could transfer across tasks, particularly from fine discrimination of sound features to speech perception in noise, one of the most frequently encountered perceptual challenges in real life. Separate groups of normal-hearing listeners were trained on auditory interaural level difference (ILD) discrimination, interaural time difference (ITD) discrimination, and fundamental frequency (F₀) discrimination with non-speech stimuli delivered through headphones. While ITD training led to no improvement, both ILD and F₀ training produced learning as well as transfer to speech-in-noise perception when noise differed from speech in the trained feature. These training benefits did not require similarity of task or stimuli between training and application settings, construing far and wide transfer. Thus, notwithstanding task specificity among basic perceptual skills such as discrimination of different sound features, auditory learning appears readily transferable between these skills and their “upstream” tasks utilizing them, providing an effective approach to improving performance in challenging situations or challenged populations.

Role of endogenous and exogenous attention in task-relevant visual perceptual learning

The present study examined the role of exogenous and endogenous attention in task relevant visual perceptual learning (TR-VPL). VPL performance was assessed by examining the learning to a trained stimulus feature and transfer of learning to an untrained stimulus feature. To assess the differential role of attention in VPL, two types of attentional cues were manipulated; exogenous and endogenous. In order to assess the effectiveness of the attentional cue, the two types of attentional cues were further divided into three cue-validity conditions. Participants were trained, on a novel task, to detect the presence of a complex gabor patch embedded in fixed Gaussian contrast noise while contrast thresholds were varied. The results showed initial differences were found prior to training, and so the magnitude of learning was assessed. Exogenous and endogenous attention were both found to facilitate learning and feature transfer when investigating pre-test and post-test thresholds. However, examination of training data indicate attentional differences; with endogenous attention showing consistently lower contrast thresholds as compared to exogenous attention suggesting greater impact of training with endogenous attention. We conclude that several factors, including the use of stimuli that resulted in rapid learning, may have contributed to the generalization of learning found in the present study.

Early Visual Cortex Stimulation Modifies Well-Consolidated Perceptual Gains

Perception thresholds can improve through repeated practice with visual tasks. Can an already acquired and well-consolidated perceptual skill be noninvasively neuromodulated, unfolding the neural mechanisms involved? Here, leveraging the susceptibility of reactivated memories ranging from synaptic to systems levels across learning and memory domains and animal models, we used noninvasive brain stimulation to neuromodulate well-consolidated reactivated visual perceptual learning and reveal the underlying neural mechanisms. Subjects first encoded and consolidated the visual skill memory by performing daily practice sessions with the task. On a separate day, the consolidated visual memory was briefly reactivated, followed by low-frequency, inhibitory 1 Hz repetitive transcranial magnetic stimulation over early visual cortex, which was individually localized using functional magnetic resonance imaging. Poststimulation perceptual thresholds were measured on the final session. The results show modulation of perceptual thresholds following early visual cortex stimulation, relative to control stimulation. Consistently, resting state functional connectivity between trained and untrained parts of early visual cortex prior to training predicted the magnitude of perceptual threshold modulation. Together, these results indicate that even previously consolidated human perceptual memories are susceptible to neuromodulation, involving early visual cortical processing. Moreover, the opportunity to noninvasively neuromodulate reactivated perceptual learning may have important clinical implications.

Supervised Learning Occurs in Visual Perceptual Learning of Complex Natural Images

There have been long-standing debates regarding whether supervised or unsupervised learning mechanisms are involved in visual perceptual learning (VPL) [1-14]. However, these debates have been based on the effects of simple feedback only about response accuracy in detection or discrimination tasks of low-level visual features such as orientation [15-22]. Here, we examined whether the content of response feedback plays a critical role for the acquisition and long-term retention of VPL of complex natural images. We trained three groups of human subjects (n = 72 in total) to better detect "grouped microcalcifications" or "architectural distortion" lesions (referred to as calcification and distortion in the following) in mammograms either with no trial-by-trial feedback, partial trial-by-trial feedback (response correctness only), or detailed trial-by-trial feedback (response correctness and target location). Distortion lesions consist of more complex visual structures than calcification lesions [23-26]. We found that partial feedback is necessary for VPL of calcifications, whereas detailed feedback is required for VPL of distortions. Furthermore, detailed feedback during training is necessary for VPL of distortion and calcification lesions to be retained for 6 months. These results show that although supervised learning is heavily involved in VPL of complex natural images, the extent of supervision for VPL varies across different types of complex natural images. Such differential requirements for VPL to improve the detectability of lesions in mammograms are potentially informative for the professional training of radiologists.

Visual-oculomotor interactions facilitate consolidation of perceptual learning

Visual skill learning is commonly considered a manifestation of brain plasticity. Following encoding, consolidation of the skill may result in between-session performance gains. A great volume of studies have demonstrated that during the offline consolidation interval, the skill is susceptible to external inputs that modify the preformed representation of the memory, affecting future performance. However, while basic visual perceptual learning is thought to be mediated by sensory brain regions or their higher-order readout pathways, the possibility of visual-oculomotor interactions affecting the consolidation interval and reshaping visual learning remains uncharted. Motivated by findings mapping connections between oculomotor behavior and visual performance, we examined whether visual consolidation can be facilitated by visual-oculomotor interactions. To this aim, we paired reactivation of an oculomotor memory with consolidation of a typical visual texture discrimination task. Importantly, the oculomotor memory was encoded by learning of the pure motor component of the movement, removing visual cues. When brief reactivation of the oculomotor memory preceded the visual task, visual gains were substantially enhanced compared with those achieved by visual practice per se and were strongly related to the magnitude of oculomotor gains, suggesting that the brain utilizes oculomotor memory to enhance basic visual perception.

Tactile angle discriminability improvement: roles of training time intervals and different types of training tasks

Perceptual learning, which is not limited to sensory modalities such as vision and touch, emerges within a training session and between training sessions and is accompanied by the remodeling of neural connections in the cortex. However, limited knowledge exists regarding perceptual learning between training sessions. Although tactile studies have paid attention to between-session learning effects, there have been few studies asking fundamental questions regarding whether the time interval between training sessions affects tactile perceptual learning and generalization across tactile tasks. We investigated the effects of different training time intervals on the consecutive performance of a tactile angle discrimination (AD) task and a tactile orientation discrimination (OD) task training on tactile angle discriminability. The results indicated that in the short-interval training group, AD task performance significantly improved in the early stage of learning and nearly plateaued in the later stage, whereas in the long-interval training group, significant improvement was delayed and then also nearly plateaued in the later stage; additionally, improved OD task performance resulted in improved AD task performance. These findings suggest that training time interval affects the early stage of learning but not the later stage and that generalization occurs between different types of tactile tasks.

NEW & NOTEWORTHY Perceptual learning, which constitutes important foundations of complicated cognitive processes, is learning better perception skills. We demonstrate that training time interval can affect the early stage of learning but not the later stage. Moreover, a tactile orientation discrimination training task can also improve tactile angle discrimination performance. These findings may expand the characteristics of between-session learning and help understand the mechanism of the generalization across tactile tasks.

A common probabilistic framework for perceptual and statistical learning

System-level learning of sensory information is traditionally divided into two domains: perceptual learning that focuses on acquiring knowledge suitable for fine discrimination between similar sensory inputs, and statistical learning that explores the mechanisms that develop complex representations of unfamiliar sensory experiences. The two domains have been typically treated in complete separation both in terms of the underlying computational mechanisms and the brain areas and processes implementing those computations. However, a number of recent findings in both domains call in question this strict separation. We interpret classical and more recent results in the general framework of probabilistic computation, provide a unifying view of how various aspects of the two domains are interlinked, and suggest how the probabilistic approach can also alleviate the problem of dealing with widely different types of neural correlates of learning. Finally, we outline several directions along which our proposed approach fosters new types of experiments that can promote investigations of natural learning in humans and other species.

Augmented Reality as a Tool for Studying Visual Plasticity: 2009 to 2018

Augmented reality (AR) has developed rapidly since its conception less than 30 years ago and is now a hot topic for both consumers and scientists. Although much attention has been paid to its application in industry, medicine, education, and entertainment, the use of AR in psychological research has been less noted. In this article, we survey recent progress in basic research that uses AR to explore the plasticity of the adult visual system. We focus on a particular application of AR called altered reality, which has been used to shed new light on mechanisms of long-term contrast adaptation and ocular-dominance plasticity. The results suggest that AR could also be a useful tool for the treatment of visual disorders.

Asymmetric perceptual confounds between canonical lightings and materials

To better understand the interactions between material perception and light perception, we further developed our material probe MatMix 1.0 into MixIM 1.0, which allows optical mixing of canonical lighting modes. We selected three canonical lighting modes (ambient, focus, and brilliance) and created scenes to represent the three illuminations. Together with four canonical material modes (matte, velvety, specular, glittery), this resulted in 12 basis images (the "bird set"). These images were optically mixed in our probing method. Three experiments were conducted with different groups of observers. In Experiment 1, observers were instructed to manipulate MixIM 1.0 and match optically mixed lighting modes while discounting the materials. In Experiment 2, observers were shown a pair of stimuli and instructed to simultaneously judge whether the materials and lightings were the same or different in a four-category discrimination task. In Experiment 3, observers performed both the matching and discrimination tasks in which only the ambient and focus light were implemented. Overall, the matching and discrimination results were comparable as (a) robust asymmetric perceptual confounds were found and confirmed in both types of tasks, (b) performances were consistent and all above chance levels, and (c) observers had higher sensitivities to our canonical materials than to our canonical lightings. The latter result may be explained in terms of a generic insensitivity for naturally occurring variations in light conditions. Our findings suggest that midlevel image features are more robust across different materials than across different lightings and, thus, more diagnostic for materials than for lightings, causing the asymmetric perceptual confounds.

Visual perceptual learning modulates decision network in the human brain: The evidence from psychophysics, modeling, and functional magnetic resonance imaging

Perceptual learning refers to improved perceptual performance after intensive training and was initially suggested to reflect long-term plasticity in early visual cortex. Recent behavioral and neurophysiological evidence further suggested that the plasticity in brain regions related to decision making could also contribute to the observed training effects. However, how perceptual learning modulates the responses of decision-related regions in the human brain remains largely unknown. In the present study, we combined psychophysics and functional magnetic resonance imaging (fMRI), and adopted a model-based approach to investigate this issue. We trained participants on a motion direction discrimination task and fitted their behavioral data using the linear ballistic accumulator model. The results from model fitting showed that behavioral improvement could be well explained by a specific improvement in sensory information accumulation. A critical model parameter, the drift rate of the information accumulation, was correlated with the fMRI responses derived from three spatial independent components: ventral premotor cortex (PMv), supplementary eye field (SEF), and the fronto-parietal network, including intraparietal sulcus (IPS) and frontal eye field (FEF). In this decision network, we found that the behavioral training effects were accompanied by signal enhancement specific to trained direction in PMv and FEF. Further, we also found direction-specific signal reduction in sensory areas (V3A and MT+), as well as the strengthened effective connectivity from V3A to PMv and from IPS to FEF. These findings provide evidence for the learning-induced decision refinement after perceptual learning and the brain regions that are involved in this process.

"Approximate number system" training: A perceptual learning approach

Recent research suggests that humans perceive quantity using a non-symbolic "number sense." This sense is then thought to provide a foundation for understanding symbolic numbers in formal education. Given this link, there has been interest in the extent to which the approximate number system (ANS) can be improved via dedicated training, as this could provide a route to improving performance in symbolic mathematics. However, current evidence regarding the trainability of the ANS comes largely from studies that have used short training durations, leaving open the question of whether improvements occur over a longer time span. To address this limitation, we utilized a perceptual learning approach to investigate the extent to which long-term (8,000+ trials) training modifies the ANS. Consistent with the general methodological approach common in the domain of perceptual learning (where learning specificity is commonly observed), we also examined whether ANS training generalizes to: (a) untrained locations in the visual field; (b) an enumeration task; (c) a higher-level ratio comparison task; and (d) arithmetic ability. In contrast to previous short-term training studies showing that ANS learning quickly asymptotes, our long-term training approach revealed that performance continued to improve even after thousands of trials. We further found that the training generalized to untrained visual locations. At post-test there was non-significant evidence for generalization to a low-level enumeration task, but not to our high-level tasks, including ratio comparison, multi-object tracking, and arithmetic performance. These results demonstrate the potential utility of long-term psychophysical training, but also suggest that ANS training alone (even long-duration training) may be insufficient to modify higher-level math skills.

High reward enhances perceptual learning

Studies of perceptual learning have revealed a great deal of plasticity in adult humans. In this study, we systematically investigated the effects and mechanisms of several forms (trial-by-trial, block, and session rewards) and levels (no, low, high, subliminal) of monetary reward on the rate, magnitude, and generalizability of perceptual learning. We found that high monetary reward can greatly promote the rate and boost the magnitude of learning and enhance performance in untrained spatial frequencies and eye without changing interocular, interlocation, and interdirection transfer indices. High reward per se made unique contributions to the enhanced learning through improved internal noise reduction. Furthermore, the effects of high reward on perceptual learning occurred in a range of perceptual tasks. The results may have major implications for the understanding of the nature of the learning rule in perceptual learning and for the use of reward to enhance perceptual learning in practical applications.

Visual perceptual training reconfigures post-task resting-state functional connectivity with a feature-representation region

The neural mechanisms underlying visual perceptual learning (VPL) have typically been studied by examining changes in task-related brain activation after training. However, the relationship between post-task "offline" processes and VPL remains unclear. The present study examined this question by obtaining resting-state functional magnetic resonance imaging (fMRI) scans of human brains before and after a task-fMRI session involving visual perceptual training. During the task-fMRI session, participants performed a motion coherence discrimination task in which they judged the direction of moving dots with a coherence level that varied between trials (20, 40, and 80%). We found that stimulus-induced activation increased with motion coherence in the middle temporal cortex (MT+), a feature-specific region representing visual motion. On the other hand, stimulus-induced activation decreased with motion coherence in the dorsal anterior cingulate cortex (dACC) and bilateral insula, regions involved in decision making under perceptual ambiguity. Moreover, by comparing pre-task and post-task rest periods, we revealed that resting-state functional connectivity (rs-FC) with the MT+ was significantly increased after training in widespread cortical regions including the bilateral sensorimotor and temporal cortices. In contrast, rs-FC with the MT+ was significantly decreased in subcortical regions including the thalamus and putamen. Importantly, the training-induced change in rs-FC was observed only with the MT+, but not with the dACC or insula. Thus, our findings suggest that perceptual training induces plastic changes in offline functional connectivity specifically in brain regions representing the trained visual feature, emphasising the distinct roles of feature-representation regions and decision-related regions in VPL.

Visual learning with reduced adaptation is eccentricity-specific

Visual learning is known to be specific to the trained target location, showing little transfer to untrained locations. Recently, learning was shown to transfer across equal-eccentricity retinal-locations when sensory adaptation due to repetitive stimulation was minimized. It was suggested that learning transfers to previously untrained locations when the learned representation is location invariant, with sensory adaptation introducing location-dependent representations, thus preventing transfer. Spatial invariance may also fail when the trained and tested locations are at different distance from the center of gaze (different retinal eccentricities), due to differences in the corresponding low-level cortical representations (e.g. allocated cortical area decreases with eccentricity). Thus, if learning improves performance by better classifying target-dependent early visual representations, generalization is predicted to fail when locations of different retinal eccentricities are trained and tested in the absence sensory adaptation. Here, using the texture discrimination task, we show specificity of learning across different retinal eccentricities (4-8°) using reduced adaptation training. The existence of generalization across equal-eccentricity locations but not across different eccentricities demonstrates that learning accesses visual representations preceding location independent representations, with specificity of learning explained by inhomogeneous sensory representation.

Feature reliability determines specificity and transfer of perceptual learning in orientation search

Training can modify the visual system to produce a substantial improvement on perceptual tasks and therefore has applications for treating visual deficits. Visual perceptual learning (VPL) is often specific to the trained feature, which gives insight into processes underlying brain plasticity, but limits VPL’s effectiveness in rehabilitation. Under what circumstances VPL transfers to untrained stimuli is poorly understood. Here we report a qualitatively new phenomenon: intrinsic variation in the representation of features determines the transfer of VPL. Orientations around cardinal are represented more reliably than orientations around oblique in V1, which has been linked to behavioral consequences such as visual search asymmetries. We studied VPL for visual search of near-cardinal or oblique targets among distractors of the other orientation while controlling for other display and task attributes, including task precision, task difficulty, and stimulus exposure. Learning was the same in all training conditions; however, transfer depended on the orientation of the target, with full transfer of learning from near-cardinal to oblique targets but not the reverse. To evaluate the idea that representational reliability was the key difference between the orientations in determining VPL transfer, we created a model that combined orientation-dependent reliability, improvement of reliability with learning, and an optimal search strategy. Modeling suggested that not only search asymmetries but also the asymmetric transfer of VPL depended on preexisting differences between the reliability of near-cardinal and oblique representations. Transfer asymmetries in model behavior also depended on having different learning rates for targets and distractors, such that greater learning for low-reliability distractors facilitated transfer. These findings suggest that training on sensory features with intrinsically low reliability may maximize the generalizability of learning in complex visual environments.

Training can modify the visual system to produce improvements on perceptual tasks (visual perceptual learning), which is associated with adult brain plasticity. Visual perceptual learning has important clinical applications: it improves the vision of adults with visual deficits, e.g. amblyopia and cortical blindness, and even presbyopia (aging eye). A critical issue in visual perceptual learning is its specificity to the trained stimulus. Specificity gives insight into the processes underling experience-dependent plasticity but can be an obstacle in the development of efficient rehabilitation protocols. Under what circumstances visual perceptual learning transfers to untrained stimuli is poorly understood. Here we report a qualitatively new phenomenon: specificity in visual search depends on intrinsic variations in the reliability of feature representations; e.g., vertically oriented lines are represented in V1 with greater reliability than tilted lines. Our data and computational model suggest that training on sensory features with intrinsically low reliability can maximize the generalizability of learning, particularly in complex natural environments in which task performance is limited by low-reliability features. Our study has possible implications for the development of efficient clinical applications of perceptual learning.

Overlearning hyperstabilizes a skill by rapidly making neurochemical processing inhibitory-dominant

Overlearning refers to the continued training of a skill after performance improvement has plateaued. Whether overlearning is beneficial is a question in our daily lives that has never been clearly answered. Here, we report a new important role: Overlearning abruptly changes neurochemical processing to hyper-stabilize and protect trained perceptual learning from subsequent new learning. Usually, learning immediately after training is so unstable that it can be disrupted by subsequent new learning, unless waiting for passive stabilization, which takes hours. However, overlearning so rapidly and strongly stabilizes the learning state that it not only becomes resilient against, but disrupts, subsequent new learning. Such hyper-stabilization is associated with an abrupt shift from glutamate-dominant excitatory to gamma-aminobutyric-acid-dominant inhibitory processing in early visual areas. Hyper-stabilization contrasts with passive and slower stabilization, which is associated with a mere reduction of an excitatory dominance to baseline levels. Utilizing hyper-stabilization may lead to efficient learning paradigms.

Motion direction discrimination training reduces perceived motion repulsion

Participants often exaggerate the perceived angular separation between two simultaneously presented motion stimuli, which is referred to as motion repulsion. The overestimation helps participants differentiate between the two superimposed motion directions, yet it causes the impairment of direction perception. Since direction perception can be refined through perceptual training, we here attempted to investigate whether the training of a direction discrimination task changes the amount of motion repulsion. Our results showed a direction-specific learning effect, which was accompanied by a reduced amount of motion repulsion both for the trained and the untrained directions. The reduction of the motion repulsion disappeared when the participants were trained on a luminance discrimination task (control experiment 1) or a speed discrimination task (control experiment 2), ruling out any possible interpretation in terms of adaptation or training-induced attentional bias. Furthermore, training with a direction discrimination task along a direction 150° away from both directions in the transparent stimulus (control experiment 3) also had little effect on the amount of motion repulsion, ruling out the contribution of task learning. The changed motion repulsion observed in the main experiment was consistent with the prediction of the recurrent model of perceptual learning. Therefore, our findings demonstrate that training in direction discrimination can benefit the precise direction perception of the transparent stimulus and provide new evidence for the recurrent model of perceptual learning.

A dissociation between consolidated perceptual learning and sensory adaptation in vision

Perceptual learning refers to improvement in perception thresholds with practice, however, extended training sessions show reduced performance during training, interfering with learning. These effects were taken to indicate a tight link between sensory adaptation and learning. Here we show a dissociation between adaptation and consolidated learning. Participants trained with a texture discrimination task, in which visual processing time is limited by a temporal target-to-mask window defined as the Stimulus-Onset-Asynchrony (SOA). An initial training phase, previously shown to produce efficient learning, was followed by training structures with varying numbers of SOAs. Largest interference with learning was found in structures containing the largest SOA density, when SOA was gradually decreased. When SOAs were largely kept unchanged, learning was effective. All training structures yielded the same within-session performance reduction, as expected from sensory adaptation. The results point to a dissociation between within-day effects, which depend on the number of trials per se regardless of their temporal structure, and consolidation effects observed on the following day, which were mediated by the temporal structure of practice. These results add a new dimension to consolidation in perceptual learning, suggesting that the degree of its effectiveness depends on variations in temporal properties of the visual stimuli.

Rapid and long-lasting learning of feature binding

How are features integrated (bound) into objects and how can this process be facilitated? Here we investigated the role of rapid perceptual learning in feature binding and its long-lasting effects. By isolating thecontributions of individual features from their conjunctionsbetween training and test displays, we demonstrate for the first time that training can rapidly and substantially improve feature binding. Observers trained on a conjunction search task consisting of a rapid display with one target-conjunction, then tested with a new target-conjunction. Features were the same between training and test displays. Learning transferred to the new target when its conjunction was presented as a distractor, but not when only its component features were presented in different conjunction distractors during training. Training improvement lasted for up to 16months, but, in all conditions, it was specific to the trained target. Our findings suggest that with short training observers' ability to bind two specific features into an object is improved, and that this learning effect can last for over a year. Moreover, our findings show that while the short-term learning effect reflects activation of presented items and their binding, long-term consolidation is task specific.

Neuroimaging Evidence for 2 Types of Plasticity in Association with Visual Perceptual Learning

Visual perceptual learning (VPL) is long-term performance improvement as a result of perceptual experience. It is unclear whether VPL is associated with refinement in representations of the trained feature (feature-based plasticity), improvement in processing of the trained task (task-based plasticity), or both. Here, we provide empirical evidence that VPL of motion detection is associated with both types of plasticity which occur predominantly in different brain areas. Before and after training on a motion detection task, subjects' neural responses to the trained motion stimuli were measured using functional magnetic resonance imaging. In V3A, significant response changes after training were observed specifically to the trained motion stimulus but independently of whether subjects performed the trained task. This suggests that the response changes in V3A represent feature-based plasticity in VPL of motion detection. In V1 and the intraparietal sulcus, significant response changes were found only when subjects performed the trained task on the trained motion stimulus. This suggests that the response changes in these areas reflect task-based plasticity. These results collectively suggest that VPL of motion detection is associated with the 2 types of plasticity, which occur in different areas and therefore have separate mechanisms at least to some degree.

Efficient reinforcement learning of a reservoir network model of parametric working memory achieved with a cluster population winner-take-all readout mechanism

The brain often has to make decisions based on information stored in working memory, but the neural circuitry underlying working memory is not fully understood. Many theoretical efforts have been focused on modeling the persistent delay period activity in the prefrontal areas that is believed to represent working memory. Recent experiments reveal that the delay period activity in the prefrontal cortex is neither static nor homogeneous as previously assumed. Models based on reservoir networks have been proposed to model such a dynamical activity pattern. The connections between neurons within a reservoir are random and do not require explicit tuning. Information storage does not depend on the stable states of the network. However, it is not clear how the encoded information can be retrieved for decision making with a biologically realistic algorithm. We therefore built a reservoir-based neural network to model the neuronal responses of the prefrontal cortex in a somatosensory delayed discrimination task. We first illustrate that the neurons in the reservoir exhibit a heterogeneous and dynamical delay period activity observed in previous experiments. Then we show that a cluster population circuit decodes the information from the reservoir with a winner-take-all mechanism and contributes to the decision making. Finally, we show that the model achieves a good performance rapidly by shaping only the readout with reinforcement learning. Our model reproduces important features of previous behavior and neurophysiology data. We illustrate for the first time how task-specific information stored in a reservoir network can be retrieved with a biologically plausible reinforcement learning training scheme.

Real-Time Strategy Video Game Experience and Visual Perceptual Learning

Visual perceptual learning (VPL) is defined as long-term improvement in performance on a visual-perception task after visual experiences or training. Early studies have found that VPL is highly specific for the trained feature and location, suggesting that VPL is associated with changes in the early visual cortex. However, the generality of visual skills enhancement attributable to action video-game experience suggests that VPL can result from improvement in higher cognitive skills. If so, experience in real-time strategy (RTS) video-game play, which may heavily involve cognitive skills, may also facilitate VPL. To test this hypothesis, we compared VPL between RTS video-game players (VGPs) and non-VGPs (NVGPs) and elucidated underlying structural and functional neural mechanisms. Healthy young human subjects underwent six training sessions on a texture discrimination task. Diffusion-tensor and functional magnetic resonance imaging were performed before and after training. VGPs performed better than NVGPs in the early phase of training. White-matter connectivity between the right external capsule and visual cortex and neuronal activity in the right inferior frontal gyrus (IFG) and anterior cingulate cortex (ACC) were greater in VGPs than NVGPs and were significantly correlated with RTS video-game experience. In both VGPs and NVGPs, there was task-related neuronal activity in the right IFG, ACC, and striatum, which was strengthened after training. These results indicate that RTS video-game experience, associated with changes in higher-order cognitive functions and connectivity between visual and cognitive areas, facilitates VPL in early phases of training. The results support the hypothesis that VPL can occur without involvement of only visual areas. Significance statement: Although early studies found that visual perceptual learning (VPL) is associated with involvement of the visual cortex, generality of visual skills enhancement by action video-game experience suggests that higher-order cognition may be involved in VPL. If so, real-time strategy (RTS) video-game experience may facilitate VPL as a result of heavy involvement of cognitive skills. Here, we compared VPL between RTS video-game players (VGPs) and non-VGPs (NVGPs) and investigated the underlying neural mechanisms. VGPs showed better performance in the early phase of training on the texture discrimination task and greater level of neuronal activity in cognitive areas and structural connectivity between visual and cognitive areas than NVGPs. These results support the hypothesis that VPL can occur beyond the visual cortex.

Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information

When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity.

Hydration status moderates the effects of drinking water on children's cognitive performance

Changes in hydration status throughout the day may affect cognitive performance with implications for learning success in the classroom. Our study tested the hypothesis that the benefit of drinking water on working memory and attention depends upon children's hydration status and renal response to water intake. Fifty-two children aged 9-12 years old were tested under two experimental conditions. The treatment session (Water session) consisted of a standard breakfast with 200 ml water, a baseline test, consumption of 750 ml of water over a period of two hours and subsequently retested. No water was provided after breakfast during the control session. Changes in hydration were assessed via urine samples. Cognitive testing consisted of digit span, pair cancellation, and delayed match to sample tasks. Children who exhibited smaller decreases in urine osmolality following water intake performed significantly better on the water day compared to the control day on a digit-span task and pair-cancellation task. Children who exhibited larger decreases in urine osmolality following water intake performed better on the control day compared to the water day on the digit-span task and pair-cancellation task. These results suggest that focusing on adequate hydration over time may be key for cognitive enhancement.

Sensory recalibration integrates information from the immediate and the cumulative past

Vision usually provides the most accurate and reliable information about the location of objects in our environment, and thus serves as a reference for recalibrating auditory spatial maps. Recent studies have shown that recalibration does not require accumulated evidence of cross-modal mismatch to be triggered, but occurs as soon as after one single exposure. Here we tested whether instantaneous recalibration and recalibration based on accumulated evidence represent the same underlying learning mechanism or involve distinct neural systems. Participants had to localize two sounds, a low- and a high-frequency tone, which were paired with opposite directions of audiovisual spatial mismatch (leftward vs. rightward). In accordance with the cumulative stimulus history, localization in unimodal auditory trials was shifted in opposite directions for the two sound frequencies. On a trial-by-trial basis, however, frequency-specific recalibration was reduced when preceded by an audiovisual stimulus with a different sound frequency and direction of spatial mismatch. Thus, the immediate past invoked an instantaneous frequency-invariant recalibration, while the cumulative past invoked changes in frequency-specific spatial maps. These findings suggest that distinct recalibration mechanisms operating at different timescales jointly determine sound localization behavior.