Learning of the same task subserved by substantially different mechanisms between patients with body dysmorphic disorder and healthy individuals.

It has remained unclear whether individuals with psychiatric disorders involving altered visual processing employ similar neuronal mechanisms during perceptual learning of a visual task. We investigated this question by training patients with body dysmorphic disorder, a psychiatric disorder characterized by distressing or impairing preoccupation with nonexistent or slight defects in one's physical appearance, and healthy controls on a visual detection task for human faces with low spatial frequency components. Brain activation during task performance was measured with functional magnetic resonance imaging before the beginning and after the end of behavioral training. Both groups of participants improved performance on the trained task to a similar extent. However, neuronal changes in the fusiform face area were substantially different between groups such that activation for low spatial frequency faces in the right fusiform face area increased after training in body dysmorphic disorder patients but decreased in controls. Moreover, functional connectivity between left and right fusiform face area decreased after training in patients but increased in controls. Our results indicate that neuronal mechanisms involved in perceptual learning of a face detection task differ fundamentally between body dysmorphic disorder patients and controls. Such different neuronal mechanisms in body dysmorphic disorder patients might reflect the brain's adaptations to altered functions imposed by the psychiatric disorder.

Neural ensembles in the murine medial prefrontal cortex process distinct information during visual perceptual learning.

BACKGROUND: Perceptual learning refers to an augmentation of an organism's ability to respond to external stimuli, which has been described in most sensory modalities. Visual perceptual learning (VPL) is a manifestation of plasticity in visual information processing that occurs in the adult brain, and can be used to ameliorate the ability of patients with visual defects mainly based on an improvement of detection or discrimination of features in visual tasks. While some brain regions such as the primary visual cortex have been described to participate in VPL, the way more general high-level cognitive brain areas are involved in this process remains unclear. Here, we showed that the medial prefrontal cortex (mPFC) was essential for both the training and maintenance processes of VPL in mouse models. RESULTS: We built a new VPL model in a custom-designed training chamber to enable the utilization of miniScopes when mice freely executed the VPL task. We found that pyramidal neurons in the mPFC participate in both the training process and maintenance of VPL. By recording the calcium activity of mPFC pyramidal neurons while mice freely executed the task, distinct ON and OFF neural ensembles tuned to different behaviors were identified, which might encode different cognitive information. Decoding analysis showed that mouse behaviors could be well predicted using the activity of each ON ensemble. Furthermore, VPL recruited more reward-related components in the mPFC. CONCLUSION: We revealed the neural mechanism underlying vision improvement following VPL and identify distinct ON and OFF neural ensembles in the mPFC that tuned to different information during visual perceptual training. These results uncover an important role of the mPFC in VPL, with more reward-related components being also involved, and pave the way for future clarification of the reward signal coding rules in VPL.

Sleep-Dependent Facilitation of Visual Perceptual Learning Is Consistent with a Learning-Dependent Model.

How sleep leads to offline performance gains in learning remains controversial. A use-dependent model assumes that sleep processing leading to performance gains occurs based on general cortical usage during wakefulness, whereas a learning-dependent model assumes that this processing is specific to learning. Here, we found evidence that supports a learning-dependent model in visual perceptual learning (VPL) in humans (both sexes). First, we measured the strength of spontaneous oscillations during sleep after two training conditions that required the same amount of training or visual cortical usage; one generated VPL (learning condition), while the other did not (interference condition). During a post-training nap, slow-wave activity (SWA) and sigma activity during non-rapid eye movement (NREM) sleep and theta activity during REM sleep were source localized to the early visual areas using retinotopic mapping. Inconsistent with a use-dependent model, only in the learning condition, sigma and theta activity, not SWA, increased in a trained region-specific manner and correlated with performance gains. Second, we investigated the roles of occipital sigma and theta activity during sleep. Occipital sigma activity during NREM sleep was significantly correlated with performance gains in presleep learning; however, occipital theta activity during REM sleep was correlated with presleep learning stabilization, shown as resilience to interference from postsleep learning in a trained region-specific manner. Occipital SWA was not associated with offline performance gains or stabilization. These results demonstrate that sleep processing leading to performance gains is learning dependent in VPL and involves occipital sigma and theta activity during sleep.SIGNIFICANCE STATEMENT The present study shows strong evidence that could help resolve the long-standing controversy surrounding sleep processing that strengthens learning (performance gains). There are two conflicting models. A use-dependent model assumes that sleep processing leading to performance gains occurs because of general cortical usage during wakefulness, whereas a learning-dependent model assumes that processing occurs specifically for learning. Using visual perceptual learning and interference paradigms, we found that processing did not take place after general cortical usage. Moreover, sigma activity during non-rapid eye movement (REM) sleep and theta activity during REM sleep in occipital areas were found to be involved in processing, which is consistent with the learning-dependent model and not the use-dependent model. These results support the learning-dependent model.

Anodal online transcranial direct current stimulation facilitates visual motion perceptual learning.

Visual perceptual learning (VPL) has great potential implications for clinical populations, but adequate improvement often takes weeks to months to obtain; therefore, practical applications of VPL are limited. Strategies that enhance visual performance acquisition make great practical sense. Transcranial direct current stimulation (tDCS) could be beneficial to VPL, but thus far, the results are inconsistent. The current study had two objectives: (1) to investigate the effect of anodal tDCS on VPL and (2) to determine whether the timing sequence of anodal tDCS and training influences VPL. Anodal tDCS was applied on the left human middle temporal (hMT+) during training on a coherent motion discrimination task (online), anodal tDCS was also applied before training (offline) and sham tDCS was applied during training (sham). The coherent thresholds were measured without stimulation before, 2 days after and 1 month after training. All participants trained for five consecutive days. Anodal tDCS resulted in more performance improvement when applied during daily training but not when applied before training. Additionally, neither within-session improvement nor between-session improvement differed among the online, offline and sham tDCS conditions. These findings contribute to the development of efficient stimulation protocols and a deep understanding of the mechanisms underlying the effect of tDCS on VPL.

Current Developments in the Management of Amblyopia with the Use of Perceptual Learning Techniques.

Background and Objectives: Amblyopia is a neurodevelopmental disorder caused by interocular suppression of visual input, affecting visual acuity, stereopsis, contrast sensitivity, and other visual functions. Conventional treatment comprises occlusion of the sound eye. In recent years, novel therapies that deploy perceptual learning (PL) principles have been introduced. The purpose of this study is to assess the latest scientific data on this topic. Materials and Methods: For this purpose, we conducted a literature search for relevant studies published during the previous 4 years (2020-2023). Results: A plethora of visual perceptual learning protocols have been recently developed. Dichoptic video games, contrast rebalanced movies, and online perceptual training platforms are the main formats. Perceptual learning activates neuroplasticity, overcomes interocular suppression, and improves the visual impairments induced by amblyopia. Conclusions: This novel treatment is effective in both children and adults, as well as in patients non-responding to patching.

Testing the efficacy of vision training for presbyopia: alternating-distance training does not facilitate vision improvement compared to fixed-distance training.

PURPOSE: Current evidence demonstrates the effectiveness of vision training for presbyopia. We developed and examined a training program to test the effectiveness of alternating focal distances as a training method. METHODS: We devised a sharpness discrimination task, in which participants judged whether the stimulus was a sine- or square-wave grating, and tested in two training groups and one control group. In the alternating-distance training group (N = 8, age 49-64), participants had to alternate the fixation between a near- and far-screen. In the fixed-distance training group (N=8, age 47-65), participants fixated on the same-distance target for the whole block. Before and after the 20 training sessions, we measured the near- and far-visual acuity (VA) using the Landolt C and Early Treatment Diabetic Retinopathy Study (ETDRS) tasks and contrast sensitivity using the qCSF procedure. The control group (N=8, age 49-65) participated only in the pre- and post-tests. RESULTS: Both training groups showed a significant improvement between the pre- and post-tests in the Landolt C task, and the improvement sizes were not significantly different between the groups. In the ETDRS task, only the fixed-distance training group showed significant improvement, although there was no significant difference between the two groups. Neither group showed improvement in the contrast sensitivity task compared to the control group. CONCLUSION: The novel sharpness discrimination task can be an effective training method for presbyopia to prevent the deterioration of VA; however, contrary to popular belief, the effect of alternating-distance training was comparable to or even weaker than that of fixed-distance training.

Deep Neural Networks for Modeling Visual Perceptual Learning.

Understanding visual perceptual learning (VPL) has become increasingly more challenging as new phenomena are discovered with novel stimuli and training paradigms. Although existing models aid our knowledge of critical aspects of VPL, the connections shown by these models between behavioral learning and plasticity across different brain areas are typically superficial. Most models explain VPL as readout from simple perceptual representations to decision areas and are not easily adaptable to explain new findings. Here, we show that a well -known instance of deep neural network (DNN), whereas not designed specifically for VPL, provides a computational model of VPL with enough complexity to be studied at many levels of analyses. After learning a Gabor orientation discrimination task, the DNN model reproduced key behavioral results, including increasing specificity with higher task precision, and also suggested that learning precise discriminations could transfer asymmetrically to coarse discriminations when the stimulus conditions varied. Consistent with the behavioral findings, the distribution of plasticity moved toward lower layers when task precision increased and this distribution was also modulated by tasks with different stimulus types. Furthermore, learning in the network units demonstrated close resemblance to extant electrophysiological recordings in monkey visual areas. Altogether, the DNN fulfilled predictions of existing theories regarding specificity and plasticity and reproduced findings of tuning changes in neurons of the primate visual areas. Although the comparisons were mostly qualitative, the DNN provides a new method of studying VPL, can serve as a test bed for theories, and assists in generating predictions for physiological investigations.SIGNIFICANCE STATEMENT Visual perceptual learning (VPL) has been found to cause changes at multiple stages of the visual hierarchy. We found that training a deep neural network (DNN) on an orientation discrimination task produced behavioral and physiological patterns similar to those found in human and monkey experiments. Unlike existing VPL models, the DNN was pre-trained on natural images to reach high performance in object recognition, but was not designed specifically for VPL; however, it fulfilled predictions of existing theories regarding specificity and plasticity and reproduced findings of tuning changes in neurons of the primate visual areas. When used with care, this unbiased and deep-hierarchical model can provide new ways of studying VPL from behavior to physiology.

Increase in MST activity correlates with visual motion learning: A functional MRI study of perceptual learning.

Repeated practice of a specific task can improve visual performance, but the neural mechanisms underlying this improvement in performance are not yet well understood. Here we trained healthy participants on a visual motion task daily for 5 days in one visual hemifield. Before and after training, we used functional magnetic resonance imaging (fMRI) to measure the change in neural activity. We also imaged a control group of participants on two occasions who did not receive any task training. While in the MRI scanner, all participants completed the motion task in the trained and untrained visual hemifields separately. Following training, participants improved their ability to discriminate motion direction in the trained hemifield and, to a lesser extent, in the untrained hemifield. The amount of task learning correlated positively with the change in activity in the medial superior temporal (MST) area. MST is the anterior portion of the human motion complex (hMT+). MST changes were localized to the hemisphere contralateral to the region of the visual field, where perceptual training was delivered. Visual areas V2 and V3a showed an increase in activity between the first and second scan in the training group, but this was not correlated with performance. The contralateral anterior hippocampus and bilateral dorsolateral prefrontal cortex (DLPFC) and frontal pole showed changes in neural activity that also correlated with the amount of task learning. These findings emphasize the importance of MST in perceptual learning of a visual motion task. Hum Brain Mapp 39:145-156, 2018. © 2017 Wiley Periodicals, Inc.

Preliminary evidence for a role of the personality trait in visual perceptual learning.

Recent research has shown that reinforcement can facilitate visual perceptual learning (VPL), but no study has examined the relations between individual differences in reinforcement sensitivity and VPL. This study tested the hypothesis that when monetary incentive was involved, the personality traits of harm avoidance and reward dependence (HA and RD, two measures of reinforcement sensitivity) would be linked to VPL performance. We trained two groups of subjects with a visual motion direction discrimination task for six days. The experimental group received monetary incentive feedback, whereas the control group received non-monetary feedback. As expected, the score of HA was negatively correlated with VPL for the experimental group, but not for the control group. RD was not a significant predictor. These results were discussed in terms of the role of non-perceptual factors such as reinforcement, personality, higher cognition, and motivation in VPL.

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.

Evaluation of visual plasticity in patients with refractive amblyopia treated using a visual perceptual learning system.

BACKGROUND: Amblyopia is a neurological deficit in binocular vision that affects 3% of the population and is the result of disruptions in early visual development. OBJECTIVE: In this study, we used a visual perceptual learning system for the short-term treatment of children with ametropic amblyopia and evaluated the clinical efficacy of this system in terms of visual plasticity. METHODS: We conducted a retrospective analysis of the clinical data of 114 children (228 eyes) with refractive amblyopia, who were aged 6.51 ± 1.51 years. Prior to the treatment, we evaluated all children with amblyopia using the visual information processing test. We determined the type of amblyopic defect according to the type of amblyopia, corrected visual acuity, and advanced visual function test results. Based on the type of defect, each child with amblyopia was given short-term visual perception training for 10 days. Finally, we compared the results of visual acuity and visual information processing tests before and after the treatment. RESULTS: The best-corrected visual acuity of patients was better after 10 days of visual training than that before training (P< 0.05). The perceptual eye position after training improved with statistically significant differences in horizontal and vertical perceptual eye position (both P< 0.05) compared to that before training. The number of amblyopic children without suppression in both eyes was 81 cases (71.1%) after training which was higher than that (65 cases, or 57.0%) before training, with a statistically significant difference (P< 0.05). Binocular fine stereopsis and dynamic stereopsis improved after training with a statistically significant difference (both P< 0.05). CONCLUSION: In this study, it was found that patients with amblyopia showed visual plasticity. Moreover, continuous visual perceptual learning improved the best-corrected visual acuity and recovered stereopsis in children with refractive amblyopia.

Decision-making processes in perceptual learning depend on effectors.

Visual perceptual learning is traditionally thought to arise in visual cortex. However, typical perceptual learning tasks also involve systematic mapping of visual information onto motor actions. Because the motor system contains both effector-specific and effector-unspecific representations, the question arises whether visual perceptual learning is effector-specific itself, or not. Here, we study this question in an orientation discrimination task. Subjects learn to indicate their choices either with joystick movements or with manual reaches. After training, we challenge them to perform the same task with eye movements. We dissect the decision-making process using the drift diffusion model. We find that learning effects on the rate of evidence accumulation depend on effectors, albeit not fully. This suggests that during perceptual learning, visual information is mapped onto effector-specific integrators. Overlap of the populations of neurons encoding motor plans for these effectors may explain partial generalization. Taken together, visual perceptual learning is not limited to visual cortex, but also affects sensorimotor mapping at the interface of visual processing and decision making.

Digital therapeutics using virtual reality-based visual perceptual learning for visual field defects in stroke: A double-blind randomized trial.

INTRODUCTION: Visual field defects (VFDs) represent a debilitating poststroke complication, characterized by unseen parts of the visual field. Visual perceptual learning (VPL), involving repetitive visual training in blind visual fields, may effectively restore visual field sensitivity in cortical blindness. This current multicenter, double-blind, randomized, controlled clinical trial investigated the efficacy and safety of VPL-based digital therapeutics (Nunap Vision [NV]) for treating poststroke VFDs. METHODS: Stroke outpatients with VFDs (>6 months after stroke onset) were randomized into NV (defective field training) or Nunap Vision-Control (NV-C, central field training) groups. Both interventions provided visual perceptual training, consisting of orientation, rotation, and depth discrimination, through a virtual reality head-mounted display device 5 days a week for 12 weeks. The two groups received VFD assessments using Humphrey visual field (HVF) tests at baseline and 12-week follow-up. The final analysis included those completed the study (NV, n = 40; NV-C, n = 35). Efficacy measures included improved visual area (sensitivity ≥6 dB) and changes in the HVF scores during the 12-week period. RESULTS: With a high compliance rate, NV and NV-C training improved the visual areas in the defective hemifield (>72 degrees2) and the whole field (>108 degrees2), which are clinically meaningful improvements despite no significant between-group differences. According to within-group analyses, mean total deviation scores in the defective hemifield improved after NV training (p = .03) but not after NV-C training (p = .12). CONCLUSIONS: The current trial suggests that VPL-based digital therapeutics may induce clinically meaningful visual improvements in patients with poststroke VFDs. Yet, between-group differences in therapeutic efficacy were not found as NV-C training exhibited unexpected improvement comparable to NV training, possibly due to learning transfer effects.

Category representation in primary visual cortex after visual perceptual learning.

The visual perceptual learning (VPL) leads to long-term enhancement of visual task performance. The subjects are often trained to link different visual stimuli to several options, such as the widely used two-alternative forced choice (2AFC) task, which involves an implicit categorical decision. The enhancement of performance has been related to the specific changes of neural activities, but few studies investigate the effects of categorical responding on the changes of neural activities. Here we investigated whether the neural activities would exhibit the categorical characteristics if the subjects are requested to respond visual stimuli in a categorical manner during VPL. We analyzed the neural activities of two monkeys in a contour detection VPL. We found that the neural activities in primary visual cortex (V1) converge to one pattern if the contour can be detected by monkey and another pattern if the contour cannot be detected, exhibiting a kind of category learning that the neural representations of detectable contour become less selective for number of bars forming contour and diverge from the representations of undetectable contour. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09926-8.

Variability in training unlocks generalization in visual perceptual learning through invariant representations.

Stimulus and location specificity are long considered hallmarks of visual perceptual learning. This renders visual perceptual learning distinct from other forms of learning, where generalization can be more easily attained, and therefore unsuitable for practical applications, where generalization is key. Based on the hypotheses derived from the structure of the visual system, we test here whether stimulus variability can unlock generalization in perceptual learning. We train subjects in orientation discrimination, while we vary the amount of variability in a task-irrelevant feature, spatial frequency. We find that, independently of task difficulty, this manipulation enables generalization of learning to new stimuli and locations, while not negatively affecting the overall amount of learning on the task. We then use deep neural networks to investigate how variability unlocks generalization. We find that networks develop invariance to the task-irrelevant feature when trained with variable inputs. The degree of learned invariance strongly predicts generalization. A reliance on invariant representations can explain variability-induced generalization in visual perceptual learning. This suggests new targets for understanding the neural basis of perceptual learning in the higher-order visual cortex and presents an easy-to-implement modification of common training paradigms that may benefit practical applications.

Dyadic visual perceptual learning on orientation discrimination.

The belief that learning can be modulated by social context is mainly supported by high-level value-based learning studies. However, whether social context can even modulate low-level learning such as visual perceptual learning (VPL) is still unknown. Unlike traditional VPL studies in which participants were trained singly, here, we developed a novel dyadic VPL paradigm in which paired participants were trained with the same orientation discrimination task and could monitor each other's performance. We found that the social context (i.e., dyadic training) led to a greater behavioral performance improvement and a faster learning rate compared with the single training. Interestingly, the facilitating effects could be modulated by the performance difference between paired participants. Functional magnetic resonance imaging (fMRI) results showed that, compared with the single training, social cognition areas including bilateral parietal cortex and dorsolateral prefrontal cortex displayed a different activity pattern and enhanced functional connectivities to early visual cortex (EVC) during the dyadic training. Furthermore, the dyadic training resulted in more refined orientation representation in primary visual cortex (V1), which was closely associated with the greater behavioral performance improvement. Taken together, we demonstrate that the social context, learning with a partner, can remarkably augment the plasticity of low-level visual information process by means of reshaping the neural activities in EVC and social cognition areas, as well as their functional interplays.

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.

Posttraining anodal tDCS improves early consolidation of visual perceptual learning.

OBJECTIVE: We aimed to investigate the transcranial direct current stimulation (tDCS)-induced facilitation of early consolidation over a period of extended training sessions and explored the effect of tDCS on visual perceptual learning (VPL) improvement during online learning and offline consolidation. METHODS: In the current double-blind sham-controlled study, twenty-four healthy participants were trained on coherent motion direction identification for 5 consecutive sessions. Performance was assessed at the pre- and posttests. Anodal or sham tDCS of the left human middle temporal region (hMT+) was applied immediately after the completion of daily training (termed early consolidation). RESULTS: The magnitude of improvement between anodal and sham tDCS was marginally significant, supporting the beneficial effect of anodal tDCS on VPL by stimulating early consolidation. Additionally, anodal tDCS induced a larger improvement between the first two training sessions than sham tDCS. No effect of anodal tDCS was found on the within-session improvement. CONCLUSIONS: The above results indicated that anodal tDCS facilitates offline consolidation during the early period of the whole training series, not online learning. The possible neural mechanisms and limitations (sample size and persistent effects) were discussed. SIGNIFICANCE: Our findings support the use of the combination of tDCS and behavioral training in facilitating visual rehabilitation and contribute to a deeper understanding of learning processes by neuromodulation procedures.

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.

Efficient learning in children with rapid GABA boosting during and after training.

It is generally thought that children learn more efficiently than adults. One way to accomplish this is to have learning rapidly stabilized such that it is not interfered with by subsequent learning. Although γ-aminobutyric acid (GABA) plays an important role in stabilization, it has been reported that GABAergic inhibitory processing is not fully matured yet in children compared with adults. Does this finding indicate that more efficient learning in children is not due to more rapid stabilization? Here, we measured the concentration of GABA in early visual cortical areas in a time-resolved fashion before, during, and after visual perceptual learning (VPL) within subjects using functional MRS (fMRS) and then compared the concentrations between children (8 to 11 years old) and adults (18 to 35 years old). We found that children exhibited a rapid boost of GABA during visual training that persisted after training ended, whereas the concentration of GABA in adults remained unchanged. Moreover, behavioral experiments showed that children exhibited rapid development of resilience to retrograde interference, which indicates that children stabilize VPL much faster than adults. These results together suggest that inhibitory processing in children's brains is more dynamic and adapts more quickly to stabilize learning than in adults, making learning more efficient in children.