Perceptual learning in Vision Research

Visual perceptual learning is enhanced by training in the illusory far space

Visual objects in the peripersonal space (PPS) are perceived faster than farther ones appearing in the extrapersonal space (EPS). This shows preferential processing for visual stimuli near our body. Such an advantage should favour visual perceptual learning occurring near, as compared with far from observers, but opposite evidence has been recently provided from online testing protocols, showing larger perceptual learning in the far space. Here, we ran two laboratory-based experiments investigating whether visual training in PPS and EPS has different effects. We used the horizontal Ponzo Illusion to create a lateralized depth perspective while participants completed a visual search task in which they reported whether or not a specific target object orientation (e.g., a triangle pointing upwards) was present among distractors. This task was completed before and after a training phase in either the (illusory) near or far space for 1 h. In Experiment 1, the near space was in the left hemispace, whereas in Experiment 2, it was in the right. Results showed that, in both experiments, participants were more accurate after training in the far space, whereas training in the near space led to either improvement in the far space (Experiment 1), or no change (Experiment 2). Moreover, we found a larger visual perceptual learning when stimuli were presented in the left compared with the right hemispace. Differently from visual processing, visual perceptual learning is more effective in the far space. We propose that depth is a key dimension that can be used to improve human visual learning.

What you saw a while ago determines what you see now: Extending awareness priming to implicit behaviors and uncovering its temporal dynamics

Past experiences influence how we perceive and respond to the present. A striking example is awareness priming, in which prior conscious perception enhances visibility and discrimination of subsequent stimuli. In this partially pre-registered study, we address a long-standing debate and broaden the scope of awareness priming by demonstrating its effects on implicit motor responses. Using a large sample size (N = 48) and a novel continuous flash suppression (CFS) paradigm, we show that prior conscious perception not only boosts subjective visibility, objective discrimination accuracy, but also enhances implicit motor responses of subsequently encountered threshold-level stimuli. Exploratory temporal dynamics analyses confirm the transient nature of awareness priming: It peaks rapidly and decays gradually, even when high-visibility trials, which could shape subsequent perception, persist. This temporal profile sets awareness priming apart from other influences of prior experience, such as serial dependence or perceptual learning. We also make a novel observation: Recent conscious experience enhances discrimination accuracy, whereas more distant experiences primarily improve subjective visibility. These findings suggest that prior conscious perception shapes conscious awareness and discrimination accuracy through independent mechanisms, likely mediated by brain areas with differing temporal receptive windows across the cortical hierarchy. By shedding new light on the scope and temporal dynamics of awareness priming, this work advances our understanding of how previous conscious perception shapes current perception and behavior.

Perceptual training of audiovisual simultaneity judgments generalizes across spatial locations

Multisensory processing critically depends on the perceived timing of stimuli in the different sensory modalities. Crossmodal stimuli that fall within rather than outside an individual temporal binding window (TBW) are more likely to be bound into a multisensory percept. A number of studies have shown that a short perceptual training in which participants receive feedback on their responses in an audiovisual simultaneity judgment (SJ) task can substantially decrease the size of the TBW and hence increase crossmodal temporal acuity. Here we tested whether multisensory perceptual learning in the SJ task is specific for the spatial locations at which the audiovisual stimuli are presented during training. Participants received feedback about the correctness of their SJ responses for audiovisual stimuli which were presented in one hemifield only. The TBW was assessed separately for audiovisual stimuli in each hemifield before and one day after the training. In line with previous findings, the size of the TBW was significantly reduced after the training phase. Importantly, an equally strong reduction of TBW size was observed in both the trained and the untrained hemifield. Thus, multisensory temporal learning completely generalized to the untrained hemifield, suggesting that the improvement in crossmodal temporal acuity was mediated by higher, location-invariant processing stages. These findings have implications for the design of multisensory training protocols in applied settings such as clinical interventions by showing that training at multiple spatial locations might not be necessary to achieve robust improvements in crossmodal temporal acuity.

Anterograde interference in multitask perceptual learning

Learning to perform multiple tasks robustly is a crucial facet of human intelligence, yet its mechanisms remain elusive. Here, we formulated four hypotheses concerning task interactions and investigated them by analyzing training sequence effects through a continual learning framework. Forty-nine subjects learned seven tasks sequentially, each of the seven groups following a distinct sequence. Results showed that subjects learning a task later in a sequence exhibited poorer performance in six tasks (Contrast, Vernier, Face, Motion, Auditory, and N-back tasks, except for the Shape task) compared to those who learned this task earlier. Interestingly, sequence position had minimal impact on forgetting. A complementary dual-task experiment corroborated these findings. Through detailed analyses of session and block learning curves, we revealed task-specific anterograde interference, but no retrograde interference. These findings support the integrated reweighting theory and shed light on the meta-plasticity mechanism governing how human brain balances plasticity and stability.

Differential modulation of the cortical alpha rhythm and activation of distinct neural networks during tactile perception training by learners and non-learners

Background

The sensitivity and discrimination capacity of sensory systems can be improved by perceptual training. Most individuals demonstrate tactile perceptual learning, but with marked differences in efficiency. Here, we investigated the neural mechanisms underlying individual differences in tactile learning efficiency at the network level.

Methods

Electroencephalographic (EEG) signals were recorded from 25 neurologically healthy participants at baseline, after one training session (50 trials) on the tactile grating orientation discrimination task (GOT), and again after four sessions of GOT training (200 training trials in total). Participants were then divided into low- and high-learning groups based on the post-training change in GOT threshold (sensitivity). Cortical alpha-band power, which is associated with sensory processing efficiency, was compared between baseline and post-training in low- and high-learning groups. Coherence analysis was also performed between EEG electrode pairs to reveal functional connectivity (FC) networks associated with low and high learning.

Results

In the high-learner group, alpha-band power spectral density (PSD) was significantly stronger post-training at the left central-parietal electrodes. In addition, FC in the alpha band was significantly strengthened within left frontal-parietal regions after training. In the low-learner group, post-training alpha-band PSD was significantly strengthened at the bilateral frontal-central electrodes, while FC in the alpha band did not change significantly compared to baseline.

Conclusion

These results suggest that individual differences in tactile learning may result from the utilization of distinct neural networks.

Personalized Visual Perceptual Learning Digital Therapy for Visual Field Defects Following Stroke: A Randomized Clinical Trial

Importance

Effective treatments for restoring visual field defects (VFDs) in patients with stroke necessitate validation through randomized clinical trials.

Objective

To evaluate the efficacy and safety of a personalized digital therapeutic based on visual perceptual learning for treating poststroke VFDs.

Design, Setting, and Participants

A multicenter randomized clinical trial was conducted from October 19, 2022, to November 8, 2023, at 12 hospitals in South Korea. The study included poststroke outpatients 19 years or older with persistent VFDs (>3 months after stroke) and neuroimaging-confirmed stroke lesions in the visual pathway.

Intervention

The training group underwent personalized visual discrimination tasks (orientation and rotation) using a mobile virtual reality headset 5 days a week for 12 weeks, with 360 trials per day. The control group received no intervention.

Main Outcome and Measures

The primary outcome was improved visual areas (defined as sensitivity increased by ≥6 decibels [dB] during 12 weeks) assessed using Humphrey visual field tests at baseline and 12 weeks.

Results

Of 93 enrolled stroke outpatients with VFDs, 82 were included in the final analysis (41 in the intervention group and 41 in the control group; median [IQR] age, 52 [42-65] years; 57 male [69.5%]). As primary measures, the training group, with a high adherence rate, showed significantly greater improvement (sensitivity increased by ≥6 dB) in the whole field (median difference, 72 [95% CI, 36-108] degrees squared; P = .003; mean [SD], 194.1 [197.3] vs 82.5 [95.0] degrees squared) and defective hemifield (median difference, 72 [95% CI, 36-108] degrees squared; P = .002; mean [SD], 158.9 [159.0] vs 72.0 [91.4] degrees squared) compared with the control group. As secondary measures, mean (SD) Humphrey visual field test scores improved after 12 weeks in the training group (whole field: 0.72 [1.55] dB; P = .005; defective hemifield: 1.20 [2.08] dB; P < .001) but not in the control group (whole field: 0.03 [1.30] dB; P = .88; defective hemifield: 0.06 [1.85] dB; P = .84).

Conclusions and Relevance

In this randomized clinical trial of a digital therapeutic for chronic poststroke VFDs, the visual perceptual learning-based training demonstrated significant improvements in the whole field and defective hemifield.

Trial Registration

ClinicalTrials.gov Identifier: NCT05525949.

Asymmetric transfer between the learning of the complex stimulus

Introduction

Perceptual learning of complex stimulus (such as faces or houses) are shown to be specific to the stimulus, indicating the plasticity of the human high-level visual cortex. However, limited understanding exists regarding the plasticity of the representation of complex stimuli in visual working memory (VWM) and its specificity.

Methods

To address this question, we adopted a delayed match-to-sample task to train the working memory for faces and houses. Subjects were trained for 6 days with neutral faces, happy faces, sad faces, and houses in Experiments 1, 2, 3, and 4, respectively.

Results

The results revealed that training significantly increased the sensitivity (d') to discriminate the visual representations in VWM in all four experiments. Furthermore, the learning effects of neutral faces were transferable to emotional faces and vice versa. However, the learning effects of emotional faces exhibited limited transfer to untrained emotional faces. More importantly, the transfer of learning effects between faces and houses was asymmetrical, i.e., only the learning effects of faces could transfer to houses, whereas the reverse was not true.

Discussion

These results highlight distinct cognitive processes underlying the training effects for different stimulus categories and provide valuable insights into the mechanisms of VWM improvement.

Tricking our brains to learn and remember; is all learning incidental?

Do we choose what we learn? On the contrary, research suggests that much of learning is incidental. The present article reviews frameworks of incidental statistical and perceptual learning and discusses implications of these frameworks to memory. This research supports the premise that much of what we know is shaped by statistical regularities in the environment, how our attention is directed, and what reinforcement we receive from successes and failures. This incidental learning shapes what we perceive and what we remember. This idea that we don't control when and what we learn, instead we at best trick our brain into states that will lead to desired learning outcomes, has important implications both to individuals and society.

Hierarchical Bayesian augmented Hebbian reweighting model of perceptual learning

The augmented Hebbian reweighting model (AHRM) has proven effective in modeling the collective performance of observers in perceptual learning studies. In this work, we introduce a novel hierarchical Bayesian version of the AHRM (HB-AHRM), which allows us to model the learning curves of individual participants and the entire population within a unified framework. We compare the performance of HB-AHRM with that of a Bayesian inference procedure, which independently estimates posterior distributions of model parameters for each participant without using a hierarchical structure. To address the substantial computational challenges, we propose a method for approximating the likelihood function in the AHRM through feature engineering and linear regression, increasing the speed of the estimation process by a factor of 20,000. This enhancement enables the HB-AHRM to compute the posterior distributions of hyperparameters and model parameters at the population, subject, and test levels, facilitating statistical inferences across these layers. Although developed in the context of a single experiment, the HB-AHRM and its associated methods are broadly applicable to data from various perceptual learning studies, offering predictions of human performance at both individual and population levels. Furthermore, the approximated likelihood approach may prove useful in fitting other stochastic models that lack analytic solutions.

Perceptual learning improves discrimination but does not reduce distortions in appearance

Human perceptual sensitivity often improves with training, a phenomenon known as "perceptual learning." Another important perceptual dimension is appearance, the subjective sense of stimulus magnitude. Are training-induced improvements in sensitivity accompanied by more accurate appearance? Here, we examined this question by measuring both discrimination (sensitivity) and estimation (appearance) responses to near-horizontal motion directions, which are known to be repulsed away from horizontal. Participants performed discrimination and estimation tasks before and after training in either the discrimination or the estimation task or none (control group). Human observers who trained in either discrimination or estimation exhibited improvements in discrimination accuracy, but estimation repulsion did not decrease; instead, it either persisted or increased. Hence, distortions in perception can be exacerbated after perceptual learning. We developed a computational observer model in which perceptual learning arises from increases in the precision of underlying neural representations, which explains this counterintuitive finding. For each observer, the fitted model accounted for discrimination performance, the distribution of estimates, and their changes with training. Our empirical findings and modeling suggest that learning enhances distinctions between categories, a potentially important aspect of real-world perception and perceptual learning.

Brief memory reactivation may not improve visual perception

Visual perceptual learning often requires a substantial number of trials to observe significant learning effects. Previously Amar-Halpert et al. (2017) have shown that brief reactivation (5 trials/day) is sufficient to improve the performance of the texture discrimination task (TDT), yielding comparable improvements to those achieved through full practice (252 trials/day). The finding is important since it would refine our understanding of learning mechanisms and applications. In the current study, we attempted to replicate these experiments using a larger number of observers and an improved experimental design. Using between-group comparison, we did find significant improvements in the reactivation group and the full-practice group as Amar-Halpert et al. (2017) showed. However, these improvements were comparable to those of the no-reactivation group with no exposure to the TDT task over the same period. Importantly, our within-group comparison showed that both the reactivation and no-reactivation groups exhibited additional significant improvements after further practicing the TDT task for an additional three days, demonstrating that the full-practice effect was significantly superior to the effects of brief memory reactivation or simple test-retest. Besides, when refining the constant stimuli method with fewer stimulus levels and more trials per level, we still observed comparable improvements brought by the reactivation and no-reactivation groups. Therefore, our results suggested that brief memory reactivation may not significantly contribute to the improvement of perceptual learning, and traditional perceptual training could still be a necessary and effective approach for substantial improvements.

Fast perceptual learning induces location-specific facilitation and suppression at early stages of visual cortical processing

Tens of minutes of training can significantly improve visual discriminability of human adults, and this fast perceptual learning (PL) effect is usually specific to the trained location, with little transfer to untrained locations. Although location specificity is generally considered as a hallmark of visual PL, it remains unclear whether it involves both facilitation of trained locations and suppression of untrained locations. Here we developed a novel experimental design to investigate the cognitive neural mechanism of location specificity of fast PL. Specifically, we manipulated attentional settings and recorded event-related potentials (ERPs) in both the training and tests. To get reliable location-specific PL effects on early ERPs, we adopted a new approach involving analysis of contralateral-minus-ipsilateral P1 (P1c-i). ERP results showed that tens of minutes of training not only increased the late P1c-i (~100-120 ms) evoked by targets at the trained location, but also decreased the early P1c-i (~75-95 ms) evoked by distractors at the untrained location, both of which were location specific. Moreover, comparison between the pretest and posttest revealed that the suppression effect of early P1c-i preserved even when the untrained location became target location, whereas the facilitation effect of late P1c-i appeared only when the trained location remained actively attended. These findings provide the first evidence that fast PL induces both location-specific facilitation and location-specific suppression at early stages of visual cortical processing. We speculate that while the facilitation effect indicates more efficient allocation of voluntary attention to the trained location induced by fast PL, the suppression effect may reflect learning-associated involuntary suppression of visual processing at the untrained location. Several confounding factors with regard to the early ERP effects of PL are discussed, and some important issues worth further investigation are proposed.

Dissociable components of visual perceptual learning characterized by non-invasive brain stimulation: Stage 1 Registered Report

Visual perceptual learning (VPL), the training-induced improvement in visual tasks, has long been considered the product of neural plasticity at early and local stages of signal processing. However, recent evidence suggests that multiple networks and mechanisms, including stimulus- and task-specific plasticity, concur in generating VPL. Accordingly, early models of VPL, which characterized learning as being local and mostly involving early sensory areas, such as V1, have been updated to embrace these newfound complexities, acknowledging the involvement on parietal (i.e. intra-parietal sulcus) and frontal (i.e. dorsolateral prefrontal cortex) areas, in aspects concerning decision-making, feedback integration and task structure. However, evidence of multiple brain regions differentially involved in different aspects of learning is thus far mostly correlational, emerging from electrophysiological and neuroimaging techniques. To directly address these multiple components of VPL, we propose to use a causal neuromodulation technique, namely transcranial random noise stimulation, to selectively modulate the activity of different brain regions suggested to be involved in various aspects of learning. Specifically, we will target a region in the occipital cortex, which has been associated with stimulus-specific plasticity, and one in the parietal cortex, which has been associated with task-specific plasticity, in a between-subject design. Measures of transfer of learning to untrained stimuli and tasks will be used to evaluate the role of different regions and test for double dissociations between learning effects and stimulated area, shedding lights on learning mechanisms in the visual system. Evidence of dissociable mechanisms of learning can help refine current models of VPL and may help develop more effective visual training and rehabilitation protocols.

Comparing conventional and action video game training in visual perceptual learning

Action video game (AVG) playing has been found to transfer to a variety of laboratory tasks in visual cognition. More recently, it has even been found to transfer to low-level visual "psychophysics tasks. This is unexpected since such low-level tasks have traditionally been found to be largely "immune" to transfer from another task, or even from the same task but a different stimulus attribute, e.g., motion direction. In this study, we set out to directly quantify transfer efficiency from AVG training to motion discrimination. Participants (n = 65) trained for 20 h on either a first-person active shooting video game, or a motion direction discrimination task with random dots. They were tested before, midway, and after training with the same motion task and an orientation discrimination task that had been shown to receive transfer from AVG training, but not from motion training. A subsequent control group (n = 18) was recruited to rule out any test-retest effect, by taking the same tests with the same time intervals, but without training. We found that improvement in motion discrimination performance was comparable between the AVG training and control groups, and less than the motion discrimination training group. We could not replicate the AVG transfer to orientation discrimination, but this was likely due to the fact that our participants were practically at chance for this task at all test points. Our study found no evidence, in either accuracy or reaction time, that AVG training transferred to motion discrimination. Overall, our results suggest that AVG training transferred little to lower-level visual skills, refining understanding of the mechanisms by which AVGs may affect vision. Protocol registration The accepted stage 1 protocol for this study can be found on the Open Science Framework at https://osf.io/zdv9c/?view_only=5b3b0c161dad448d9d1d8b14ce91ab11 . The stage 1 protocol for this Registered Report was accepted in principle on 01/12/22. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/ZDV9C.

Generalization in perceptual learning across stimuli and tasks

Perceptual learning, known to improve visual perception, demonstrates the plasticity of brain processes underlying vision. Early studies, using the backward-masked texture discrimination task (TDT), focused on the lack of generalizing learning to stimulus features, relating learning specificity to the selectivity of the brain networks involved in the visual task. Learning was found to be highly specific to the stimulus features, as expected from the processing selectivity found in early visual areas as well as to the task employed in training, pointing to top-down effects. More recent studies demonstrate the generalization of learning to untrained features under specifically designed training procedures. Here we suggest that transfer of learning takes place when the trained and untrained stimuli and task activate overlapping brain processes. We tested the effect of TDT learning, under conditions with and without visual adaptation, on the contrast detection (CD) of localized Gabor targets, either alone or backward masked (BM). At the TDT peripheral-target location, we found that the transfer of learning between TDT to CD and BM occurs under the TDT adaptation condition, but not under the no-adaptation condition, whereas at the TDT center-target location we found that transfer occurs for both conditions. Our results suggest that learning generalization across experimental conditions depends on overlapping neural processes within brain networks, here dominated by the inhibitory effects involved in adaptation and in spatiotemporal masking. Importantly, increased adaptation during training, due to increased stimulus consistency, enabled the transfer of learning to other tasks limited by sensory adaptation.

Recent Visual Experience Reshapes V4 Neuronal Activity and Improves Perceptual Performance

Recent visual experience heavily influences our visual perception, but how neuronal activity is reshaped to alter and improve perceptual discrimination remains unknown. We recorded from populations of neurons in visual cortical area V4 while two male rhesus macaque monkeys performed a natural image change detection task under different experience conditions. We found that maximizing the recent experience with a particular image led to an improvement in the ability to detect a change in that image. This improvement was associated with decreased neural responses to the image, consistent with neuronal changes previously seen in studies of adaptation and expectation. We found that the magnitude of behavioral improvement was correlated with the magnitude of response suppression. Furthermore, this suppression of activity led to an increase in signal separation, providing evidence that a reduction in activity can improve stimulus encoding. Within populations of neurons, greater recent experience was associated with decreased trial-to-trial shared variability, indicating that a reduction in variability is a key means by which experience influences perception. Taken together, the results of our study contribute to an understanding of how recent visual experience can shape our perception and behavior through modulating activity patterns in the mid-level visual cortex.

Foveal neural adaptation to optically induced contrast reduction

Contrast processing is suggested to interact with eye growth and myopia development. A novel contrast-reducing myopia control lens design decreases image contrast and was shown to slow myopia progression. Limited insights exist regarding neural visual processing following adaptation to image contrast reduction. This study investigated foveal neural contrast sensitivity in 29 young adults following a 30-minute adaptation to scattering using a Bangerter occlusion foil 0.8, +0.5-diopter defocus, and a clear lens control condition. Neural contrast sensitivity at its peak sensitivity of 6 cycles per degree was assessed before and after adaptation to the lens conditions, employing a unique interferometric system. Pre-adaptation measurements were averaged from six replicates and post-adaptation measurements by the first and last three of six replicates. The change in neural contrast sensitivity was largest for scattering across the first and last three post-adaptation measurements (+0.05 ± 0.01 logCS and +0.04 ± 0.01 logCS, respectively) compared with control and defocus (all +0.03 ± 0.01 logCS). For scattering, the observed increase of neural contrast sensitivity within the first three measurements differed significantly from the pre-adaptation baseline (p = 0.04) and was significantly higher compared with the control condition (p = 0.04). The sensitivity increases in the control and defocus conditions were not significant (all p > 0.05). As the adaptation effect diminished, no significant differences were found from baseline or between the conditions in the last three measurements (all p > 0.05). When post-adaptation neural contrast sensitivities were clustered into 25-second sequences, a significant effect was observed between the conditions, with only a significant relevant effect between control and scattering at 25 seconds (p = 0.04) and no further significant effects (all p > 0.05). The alteration in neural contrast sensitivity at peak sensitivity was most pronounced following adaptation to the scattering condition compared with defocus and control, suggesting that induced scattering might be considered for myopia control.

Customized Visual Discrimination Digital Therapy According to Visual Field Defects in Chronic Stroke Patients

BACKGROUND AND PURPOSE

Visual perceptual learning (VPL) may improve visual field defects (VFDs) after chronic stroke, but the optimal training duration and location remain unknown. This prospective study aimed to determine the efficacy of 8 weeks of VFD-customized visual discrimination training in improving poststroke VFDs.

METHODS

Prospectively enrolled patients with poststroke VFDs initially received no training for 8 weeks (no-training phase). They subsequently underwent our customized VPL program that included orientation-discrimination tasks in individualized blind fields and central letter-discrimination tasks three times per week for 8 weeks (training phase). We analyzed the luminance detection sensitivity and deviation as measured using Humphrey visual field tests before and after the no-training and training phases. The vision-related quality of life was assessed at baseline and at a 16-week follow-up using the National Eye Institute Visual Function Questionnaire-25 (NEI-VFQ-25).

RESULTS

Changes in mean total deviation (MTD) scores were greater during the training phase than during the no-training phase (defective hemifield, p=0.002; whole field, p=0.004). The MTD scores improved during the training phase (defective hemifield, p=0.004; whole field, p=0.016), but not during the no-training phase (defective hemifield, p=0.178; whole field, p=0.178). The difference between the improved and worsened areas (≥6 dB changes in luminance detection sensitivity) was greater during the training phase than during the no-training phase (p=0.009). The vision-specific social functioning subscore of the NEI-VFQ-25 improved after the 16-week study period (p=0.040).

CONCLUSIONS

Our 8-week VFD-customized visual discrimination training protocol may effectively improve VFDs and vision-specific social functioning in chronic stroke patients.

Hierarchical Bayesian Augmented Hebbian Reweighting Model of Perceptual Learning

The Augmented Hebbian Reweighting Model (AHRM) has been effectively utilized to model the collective performance of observers in various perceptual learning studies. In this work, we have introduced a novel hierarchical Bayesian Augmented Hebbian Reweighting Model (HB-AHRM) to simultaneously model the learning curves of individual participants and the entire population within a single framework. We have compared its performance to that of a Bayesian Inference Procedure (BIP), which independently estimates the posterior distributions of model parameters for each individual subject without employing a hierarchical structure. To cope with the substantial computational demands, we developed an approach to approximate the likelihood function in the AHRM with feature engineering and linear regression, increasing the speed of the estimation procedure by 20,000 times. The HB-AHRM has enabled us to compute the joint posterior distribution of hyperparameters and parameters at the population, observer, and test levels, facilitating statistical inferences across these levels. While we have developed this methodology within the context of a single experiment, the HB-AHRM and the associated modeling techniques can be readily applied to analyze data from various perceptual learning experiments and provide predictions of human performance at both the population and individual levels. The likelihood approximation concept introduced in this study may have broader utility in fitting other stochastic models lacking analytic forms.

Recurrent inhibition refines mental templates to optimize perceptual decisions

Translating sensory inputs to perceptual decisions relies on building internal representations of features critical for solving complex tasks. Yet, we still lack a mechanistic account of how the brain forms these mental templates of task-relevant features to optimize decision-making. Here, we provide evidence for recurrent inhibition: an experience-dependent plasticity mechanism that refines mental templates by enhancing γ-aminobutyric acid (GABA)-mediated (GABAergic) inhibition and recurrent processing in superficial visual cortex layers. We combine ultrahigh-field (7 T) functional magnetic resonance imaging at submillimeter resolution with magnetic resonance spectroscopy to investigate the fine-scale functional and neurochemical plasticity mechanisms for optimized perceptual decisions. We demonstrate that GABAergic inhibition increases following training on a visual (i.e., fine orientation) discrimination task, enhancing the discriminability of orientation representations in superficial visual cortex layers that are known to support recurrent processing. Modeling functional and neurochemical plasticity interactions reveals that recurrent inhibitory processing optimizes brain computations for perpetual decisions and adaptive behavior.

Glaucoma Rehabilitation using ElectricAI Transcranial Stimulation (GREAT)-study protocol for randomized controlled trial using combined perceptual learning and transcranial electrical stimulation for vision enhancement

BACKGROUND

Glaucoma patients with irreversible visual field loss often experience decreased quality of life, impaired mobility, and mental health challenges. Perceptual learning (PL) and transcranial electrical stimulation (tES) have emerged as promising interventions for vision rehabilitation, showing potential in restoring residual visual functions. The Glaucoma Rehabilitation using ElectricAI Transcranial stimulation (GREAT) project aims to investigate whether combining PL and tES is more effective than using either method alone in maximizing the visual function of glaucoma patients. Additionally, the study will assess the impact of these interventions on brain neural activity, blood biomarkers, mobility, mental health, quality of life, and fear of falling.

METHODS

The study employs a three-arm, double-blind, randomized, superiority-controlled design. Participants are randomly allocated in a 1:1:1 ratio to one of three groups receiving: (1) real PL and real tES, (2) real PL and sham tES, and (3) placebo PL and sham tES. Each participant undergoes 10 sessions per block (~ 1 h each), with a total of three blocks. Assessments are conducted at six time points: baseline, interim 1, interim 2, post-intervention, 1-month post-intervention, and 2-month post-intervention. The primary outcome is the mean deviation of the 24-2 visual field measured by the Humphrey visual field analyzer. Secondary outcomes include detection rate in the suprathreshold visual field, balance and gait functions, and electrophysiological and biological responses. This study also investigates changes in neurotransmitter metabolism, biomarkers, self-perceived quality of life, and psychological status before and after the intervention.

DISCUSSION

The GREAT project is the first study to assess the effectiveness of PL and tES in the rehabilitation of glaucoma. Our findings will offer comprehensive assessments of the impact of these treatments on a wide range of brain and vision-related metrics including visual field, neural activity, biomarkers, mobility, mental health, fear of falling, and quality of life.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05874258 . Registered on May 15, 2023.

Pretraining alpha rhythm enhancement by neurofeedback facilitates short-term perceptual learning and improves visual acuity by facilitated consolidation

Introduction

Learning through perceptual training using the Gabor patch (GP) has attracted attention as a new vision restoration technique for myopia and age-related deterioration of visual acuity (VA). However, the task itself is monotonous and painful and requires numerous training sessions and some time before being effective, which has been a challenge for its widespread application. One effective means of facilitating perceptual learning is the empowerment of EEG alpha rhythm in the sensory cortex before neurofeedback (NF) training; however, there is a lack of evidence for VA.

Methods

We investigated whether four 30-min sessions of GP training, conducted over 2 weeks with/without EEG NF to increase alpha power (NF and control group, respectively), can improve vision in myopic subjects. Contrast sensitivity (CS) and VA were measured before and after each GP training.

Results

The NF group showed an improvement in CS at the fourth training session, not observed in the control group. In addition, VA improved only in the NF group at the third and fourth training sessions, this appears as a consolidation effect (maintenance of the previous training effect). Participants who produced stronger alpha power during the third training session showed greater VA recovery during the fourth training session.

Discussion

These results indicate that enhanced pretraining alpha empowerment strengthens the subsequent consolidation of perceptual learning and that even a short period of GP training can have a positive effect on VA recovery. This simple protocol may facilitate use of a training method to easily recover vision.

Transfer of visual perceptual learning over a task-irrelevant feature through feature-invariant representations: Behavioral experiments and model simulations

A large body of literature has examined specificity and transfer of perceptual learning, suggesting a complex picture. Here, we distinguish between transfer over variations in a "task-relevant" feature (e.g., transfer of a learned orientation task to a different reference orientation) and transfer over a "task-irrelevant" feature (e.g., transfer of a learned orientation task to a different retinal location or different spatial frequency), and we focus on the mechanism for the latter. Experimentally, we assessed whether learning a judgment of one feature (such as orientation) using one value of an irrelevant feature (e.g., spatial frequency) transfers to another value of the irrelevant feature. Experiment 1 examined whether learning in eight-alternative orientation identification with one or multiple spatial frequencies transfers to stimuli at five different spatial frequencies. Experiment 2 paralleled Experiment 1, examining whether learning in eight-alternative spatial-frequency identification at one or multiple orientations transfers to stimuli with five different orientations. Training the orientation task with a single spatial frequency transferred widely to all other spatial frequencies, with a tendency to specificity when training with the highest spatial frequency. Training the spatial frequency task fully transferred across all orientations. Computationally, we extended the identification integrated reweighting theory (I-IRT) to account for the transfer data (Dosher, Liu, & Lu, 2023; Liu, Dosher, & Lu, 2023). Just as location-invariant representations in the original IRT explain transfer over retinal locations, incorporating feature-invariant representations effectively accounted for the observed transfer. Taken together, we suggest that feature-invariant representations can account for transfer of learning over a "task-irrelevant" feature.

Visual perceptual learning is effective in the illusory far but not in the near space

Visual shape discrimination is faster for objects close to the body, in the peripersonal space (PPS), compared with objects far from the body. Visual processing enhancement in PPS occurs also when perceived depth is based on 2D pictorial cues. This advantage has been observed from relatively low-level (detection, size, orientation) to high-level visual features (face processing). While multisensory association also displays proximal advantages, whether PPS influences visual perceptual learning remains unclear. Here, we investigated whether perceptual learning effects vary according to the distance of visual stimuli (near or far) from the observer, illusorily induced by leveraging the Ponzo illusion. Participants performed a visual search task in which they reported whether a specific target object orientation (e.g., triangle pointing downward) was present among distractors. Performance was assessed before and after practicing the visual search task (30 minutes/day for 5 days) at either the close (near group) or far (far group) distance. Results showed that participants that performed the training in the near space did not improve. By contrast, participants that performed the training in the far space showed an improvement in the visual search task in both the far and near spaces. We suggest that such improvement following the far training is due to a greater deployment of attention in the far space, which could make the learning more effective and generalize across spaces.

Efficacy of perceptual learning in low vision: A systematic review and meta-analysis

BACKGROUND

Visual perceptual learning (PL) shows promise for enhancing visual functions in individuals with visual impairment.

OBJECTIVE

This systematic review aimed to evaluate the effectiveness of PL in improving visual function.

STUDY ELIGIBILITY

Eligible studies were those examining the efficacy of PL in individuals with low vision.

STUDY APPRAISAL AND SYNTHESIS METHODS

The review protocol was registered with the international Prospective Register of Systematic Reviews (ID CRD42022327545) and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Screened studies were synthesized using random-effects meta-analysis and narrative synthesis following Synthesis Without Meta-analysis guidelines. The quality of the evidence was assessed using the Cochrane risk-of-bias tool and the JBI Critical Appraisal Tool for Quasi-Experimental studies.

RESULTS

Fifty studies were included, covering various visual impairments and employing different PL interventions. Most studies had low risk of bias. Meta-analysis showed significant improvement in visual search for individuals with cortical blindness (Hedges' g = 0.71; 95% confidence interval, 0.48 to 0.93; p=0.002); all other analyses did not show significant improvements-reading in central vision loss and cortical blindness, and visual field in peripheral vision loss and cortical blindness. However, the narrative synthesis provided evidence showing effectiveness, particularly in individuals with central vision loss and cortical blindness, demonstrating positive effects on reading, contrast sensitivity, visual field, and motion perception.

LIMITATIONS

Variations in study design, PL protocols, outcome measures, and measurement methods introduced heterogeneity, limiting the analysis.

CONCLUSIONS

The efficacy of PL in vision rehabilitation remains uncertain. Although meta-analysis results were mostly inconclusive, the narrative synthesis indicated improved visual functions following PL, consistent with individual study findings.

IMPLICATIONS OF KEY FINDINGS

Future research should optimize intervention parameters, explore long-term effects, and assess generalizability across diverse populations and visual impairment etiologies. Larger randomized controlled trials using standardized outcome measures are needed to advance the field.

Study on the relationship between fixation characteristics and hit rate in psychological procedure training of free throw

BACKGROUND

Free throw is an important means of scoring in basketball games. With the improvement of basketball competition level and the enhancement of confrontation degree, the number of free throws in the game gradually increases, so the score of free throw will have an important impact on the result of the game. The purpose of this study is to explore the relationship between visual attention characteristics and hit rate of basketball players in free throw psychological procedure training, so as to provide scientific basis for basketball teaching and training.

METHODS

Forty players with similar free throw abilities were randomly assigned to the experimental group (10 males, 10 females) and control group (10 males, 10 females). The experimental group was free throw psychological procedure training, while the control group was trained with routine training, Eye movement indices (number of fixations, fixation duration, and pupil dilation) and the free throw hit rate and analyzed before and after the experiment. Group differences were examined using t-tests, while paired sample t-tests were conducted to compare pre- and post-test results within each group. The training time and training times of the two groups were the same.

RESULTS

There were significant differences in fixation duration, number of fixations, pupil diameter and free throw hit rate between pre-test and post-test in the experimental group (P < 0.05). Post-test, there were significant differences in number of fixations, fixation duration, pupil diameter and free throw hit rate between the two groups (P < 0.05). There was a significant positive correlation between number of fixations and free throw hit rate in top (P < 0.01), and there was a significant positive correlation between fixation duration and hit rate in front (P < 0.01).

CONCLUSIONS

The psychological procedure training can improve the visual information search strategy and information processing ability of free throw, and significantly improve the free throw hit rate. There was a positive correlation between the front fixation time and the free throw hit rate, and there was a positive correlation between the top number of fixations and the free throw hit rate.

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.

Enabling identification of component processes in perceptual learning with nonparametric hierarchical Bayesian modeling

Perceptual learning is a multifaceted process, encompassing general learning, between-session forgetting or consolidation, and within-session fast relearning and deterioration. The learning curve constructed from threshold estimates in blocks or sessions, based on tens or hundreds of trials, may obscure component processes; high temporal resolution is necessary. We developed two nonparametric inference procedures: a Bayesian inference procedure (BIP) to estimate the posterior distribution of contrast threshold in each learning block for each learner independently and a hierarchical Bayesian model (HBM) that computes the joint posterior distribution of contrast threshold across all learning blocks at the population, subject, and test levels via the covariance of contrast thresholds across blocks. We applied the procedures to the data from two studies that investigated the interaction between feedback and training accuracy in Gabor orientation identification over 1920 trials across six sessions and estimated learning curve with block sizes L = 10, 20, 40, 80, 160, and 320 trials. The HBM generated significantly better fits to the data, smaller standard deviations, and more precise estimates, compared to the BIP across all block sizes. In addition, the HBM generated unbiased estimates, whereas the BIP only generated unbiased estimates with large block sizes but exhibited increased bias with small block sizes. With L = 10, 20, and 40, we were able to consistently identify general learning, between-session forgetting, and rapid relearning and adaptation within sessions. The nonparametric HBM provides a general framework for fine-grained assessment of the learning curve and enables identification of component processes in perceptual learning.

Feature variability determines specificity and transfer in multiorientation feature detection learning

Historically, in many perceptual learning experiments, only a single stimulus is practiced, and learning is often specific to the trained feature. Our prior work has demonstrated that multi-stimulus learning (e.g., training-plus-exposure procedure) has the potential to achieve generalization. Here, we investigated two important characteristics of multi-stimulus learning, namely, roving and feature variability, and their impacts on multi-stimulus learning and generalization. We adopted a feature detection task in which an oddly oriented target bar differed by 16° from the background bars. The stimulus onset asynchrony threshold between the target and the mask was measured with a staircase procedure. Observers were trained with four target orientation search stimuli, either with a 5° deviation (30°-35°-40°-45°) or with a 45° deviation (30°-75°-120°-165°), and the four reference stimuli were presented in a roving manner. The transfer of learning to the swapped target-background orientations was evaluated after training. We found that multi-stimulus training with a 5° deviation resulted in significant learning improvement, but learning failed to transfer to the swapped target-background orientations. In contrast, training with a 45° deviation slowed learning but produced a significant generalization to swapped orientations. Furthermore, a modified training-plus-exposure procedure, in which observers were trained with four orientation search stimuli with a 5° deviation and simultaneously passively exposed to orientations with high feature variability (45° deviation), led to significant orientation learning generalization. Learning transfer also occurred when the four orientation search stimuli with a 5° deviation were presented in separate blocks. These results help us to specify the condition under which multistimuli learning produces generalization, which holds potential for real-world applications of perceptual learning, such as vision rehabilitation and expert training.

Profiles of visual perceptual learning in feature space

Visual perceptual learning (VPL), experience-induced gains in discriminating visual features, has been studied extensively and intensively for many years, its profile in feature space, however, remains unclear. Here, human subjects were trained to perform either a simple low-level feature (grating orientation) or a complex high-level object (face view) discrimination task over a long-time course. During, immediately after, and one month after training, all results showed that in feature space VPL in grating orientation discrimination was a center-surround profile; VPL in face view discrimination, however, was a monotonic gradient profile. Importantly, these two profiles can be emerged by a deep convolutional neural network with a modified AlexNet consisted of 7 and 12 layers, respectively. Altogether, our study reveals for the first time a feature hierarchy-dependent profile of VPL in feature space, placing a necessary constraint on our understanding of the neural computation of VPL.

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.

Exposure to temporal variability promotes subsequent adaptation to new temporal regularities

Noise is intuitively thought to interfere with perceptual learning; However, human and machine learning studies suggest that, in certain contexts, variability may reduce overfitting and improve generalizability. Whereas previous studies have examined the effects of variability in learned stimuli or tasks, it is hitherto unknown what are the effects of variability in the temporal environment. Here, we examined this question in two groups of adult participants (N = 40) presented with visual targets at either random or fixed temporal routines and then tested on the same type of targets at a new nearly-fixed temporal routine. Findings reveal that participants of the random group performed better and adapted quicker following a change in the timing routine, relative to participants of the fixed group. Corroborated with eye-tracking and computational modeling, these findings suggest that prior exposure to temporal variability promotes the formation of new temporal expectations and enhances generalizability in a dynamic environment. We conclude that noise plays an important role in promoting perceptual learning in the temporal domain: rather than interfering with the formation of temporal expectations, noise enhances them. This counterintuitive effect is hypothesized to be achieved through eliminating overfitting and promoting generalizability.

tRNS boosts visual perceptual learning in participants with bilateral macular degeneration

Perceptual learning (PL) has shown promise in enhancing residual visual functions in patients with age-related macular degeneration (MD), however it requires prolonged training and evidence of generalization to untrained visual functions is limited. Recent studies suggest that combining transcranial random noise stimulation (tRNS) with perceptual learning produces faster and larger visual improvements in participants with normal vision. Thus, this approach might hold the key to improve PL effects in MD. To test this, we trained two groups of MD participants on a contrast detection task with (n = 5) or without (n = 7) concomitant occipital tRNS. The training consisted of a lateral masking paradigm in which the participant had to detect a central low contrast Gabor target. Transfer tasks, including contrast sensitivity, near and far visual acuity, and visual crowding, were measured at pre-, mid and post-tests. Combining tRNS and perceptual learning led to greater improvements in the trained task, evidenced by a larger increment in contrast sensitivity and reduced inhibition at the shortest target to flankers' distance. The overall amount of transfer was similar between the two groups. These results suggest that coupling tRNS and perceptual learning has promising potential applications as a clinical rehabilitation strategy to improve vision in MD patients.

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.

Neural mechanisms of face familiarity and learning in the human amygdala and hippocampus

Recognizing familiar faces and learning new faces play an important role in social cognition. However, the underlying neural computational mechanisms remain unclear. Here, we record from single neurons in the human amygdala and hippocampus and find a greater neuronal representational distance between pairs of familiar faces than unfamiliar faces, suggesting that neural representations for familiar faces are more distinct. Representational distance increases with exposures to the same identity, suggesting that neural face representations are sharpened with learning and familiarization. Furthermore, representational distance is positively correlated with visual dissimilarity between faces, and exposure to visually similar faces increases representational distance, thus sharpening neural representations. Finally, we construct a computational model that demonstrates an increase in the representational distance of artificial units with training. Together, our results suggest that the neuronal population geometry, quantified by the representational distance, encodes face familiarity, similarity, and learning, forming the basis of face recognition and memory.

Perceptual Learning Based on the Lateral Masking Paradigm in Anisometropic Amblyopia With or Without a Patching History

Purpose

Perceptual learning (PL) has shown promising performance in restoring visual function in adolescent amblyopes. We retrospectively compared the effect of a well-accepted PL paradigm on patients with anisometropic amblyopia with or without a patching therapy history (patching therapy [PT] group versus no patching therapy [NPT] group).

Methods

Eighteen PT and 13 NPT patients with anisometropic amblyopia underwent monocular PL for 3 months. During training, patients practiced a Gabor detection task following the lateral masking paradigm by applying a temporal two-alternative forced choice procedure with the amblyopic eye. Monocular contrast sensitivity functions (CSF), visual acuity, interocular differences in visual function metrics, and stereoacuity were compared before and after training.

Results

PL improved the visual acuity of the amblyopia eyes by 0.5 lines on average in the PT group and 1.5 lines in the NPT group. A significant reduction in the interocular difference in visual acuity was observed in the NPT group (P < 0.01) but not in the PT group (P = 0.05). Regarding CSF metrics, the area under the log CSF and cutoff in the amblyopic eyes of the NPT groups increased after training (P < 0.05). In addition, the interocular differences of the CSF metrics (P < 0.05) in the NPT group were significantly reduced. However, in the PT group, all the CSF metrics were unchanged after training. A total of 27 of 31 patients in both groups had no measurable stereopsis pretraining, and recovery after training was not significant.

Conclusions

PL based on a lateral masking training paradigm improved visual function in anisometropic amblyopia. Patients without a patching history achieved greater benefits.

Translational Relevance

PL based on a lateral masking training paradigm could be a new treatment for amblyopia.

Improving iconic memory through contrast detection training with HOA-corrected vision

Iconic memory and short-term memory are not only crucial for perception and cognition, but also of great importance to mental health. Here, we first showed that both types of memory could be improved by improving limiting processes in visual processing through perceptual learning. Normal adults were trained in a contrast detection task for ten days, with their higher-order aberrations (HOA) corrected in real-time. We found that the training improved not only their contrast sensitivity function (CSF), but also their iconic memory and baseline information maintenance for short-term memory, and the relationship between memory and CSF improvements could be well-predicted by an observer model. These results suggest that training the limiting component of a cognitive task with visual perceptual learning could improve visual cognition. They may also provide an empirical foundation for new therapies to treat people with poor sensory memory.

Estimating the Trial-by-Trial Learning Curve in Perceptual Learning with Hierarchical Bayesian Modeling

The learning curve serves as a crucial metric for assessing human performance in perceptual learning. It may encompass various component processes, including general learning, between-session forgetting or consolidation, and within-session rapid relearning and adaptation or deterioration. Typically, empirical learning curves are constructed by aggregating tens or hundreds of trials of data in blocks or sessions. Here, we devised three inference procedures for estimating the trial-by-trial learning curve based on the multi-component functional form identified in Zhao et al. (submitted): general learning, between-session forgetting, and within-session rapid relearning and adaptation. These procedures include a Bayesian inference procedure (BIP) estimating the posterior distribution of parameters for each learner independently, and two hierarchical Bayesian models (HBMv and HBMc) computing the joint posterior distribution of parameters and hyperparameters at the population, subject, and test levels. The HBMv and HBMc incorporate variance and covariance hyperparameters, respectively, between and within subjects. We applied these procedures to data from two studies investigating the interaction between feedback and training accuracy in Gabor orientation identification across about 2000 trials spanning six sessions (Liu et al., 2010, 2012) and estimated the trial-by-trial learning curves at both the subject and population levels. The HBMc generated best fits to the data and the smallest half width of 68.2% credible interval of the learning curves compared to the BIP and HBMv. The parametric HBMc with the multi-component functional form provides a general framework for trial-by-trial analysis of the component processes in perceptual learning and for predicting the learning curve in unmeasured time points.

Against cortical reorganisation

Neurological insults, such as congenital blindness, deafness, amputation, and stroke, often result in surprising and impressive behavioural changes. Cortical reorganisation, which refers to preserved brain tissue taking on a new functional role, is often invoked to account for these behavioural changes. Here, we revisit many of the classical animal and patient cortical remapping studies that spawned this notion of reorganisation. We highlight empirical, methodological, and conceptual problems that call this notion into doubt. We argue that appeal to the idea of reorganisation is attributable in part to the way that cortical maps are empirically derived. Specifically, cortical maps are often defined based on oversimplified assumptions of 'winner-takes-all', which in turn leads to an erroneous interpretation of what it means when these maps appear to change. Conceptually, remapping is interpreted as a circuit receiving novel input and processing it in a way unrelated to its original function. This implies that neurons are either pluripotent enough to change what they are tuned to or that a circuit can change what it computes. Instead of reorganisation, we argue that remapping is more likely to occur due to potentiation of pre-existing architecture that already has the requisite representational and computational capacity pre-injury. This architecture can be facilitated via Hebbian and homeostatic plasticity mechanisms. Crucially, our revised framework proposes that opportunities for functional change are constrained throughout the lifespan by the underlying structural 'blueprint'. At no period, including early in development, does the cortex offer structural opportunities for functional pluripotency. We conclude that reorganisation as a distinct form of cortical plasticity, ubiquitously evoked with words such as 'take-over'' and 'rewiring', does not exist.

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.

Perceptual learning across saccades: Feature but not location specific

Perceptual learning is the ability to enhance perception through practice. The hallmark of perceptual learning is its specificity for the trained location and stimulus features, such as orientation. For example, training in discriminating a grating's orientation improves performance only at the trained location but not in other untrained locations. Perceptual learning has mostly been studied using stimuli presented briefly while observers maintained gaze at one location. However, in everyday life, stimuli are actively explored through eye movements, which results in successive projections of the same stimulus at different retinal locations. Here, we studied perceptual learning of orientation discrimination across saccades. Observers were trained to saccade to a peripheral grating and to discriminate its orientation change that occurred during the saccade. The results showed that training led to transsaccadic perceptual learning (TPL) and performance improvements which did not generalize to an untrained orientation. Remarkably, however, for the trained orientation, we found a complete transfer of TPL to the untrained location in the opposite hemifield suggesting high flexibility of reference frame encoding in TPL. Three control experiments in which participants were trained without saccades did not show such transfer, confirming that the location transfer was contingent upon eye movements. Moreover, performance at the trained location, but not at the untrained location, was also improved in an untrained fixation task. Our results suggest that TPL has both, a location-specific component that occurs before the eye movement and a saccade-related component that involves location generalization.

Visual perceptual learning modulates microsaccade rate and directionality

Microsaccades, incessant "fixational eye movements" (< 1°), are an important window into cognitive functions. Yet, its role in visual perceptual learning (VPL)-improvements in visual discrimination due to practice-remains practically unexplored. Here we investigated whether and how microsaccades change in VPL. Human observers performed a Landolt acuity task for 5 consecutive days and were assigned to the Neutral or Attention group. On each trial, two peripheral Landolt squares were presented briefly along a diagonal. Observers reported the gap side of the target stimulus. Training improved acuity and modified the microsaccade rate; with training, the rate decreased during the fixation period but increased during the response cue. Furthermore, microsaccade direction during the response cue was biased toward the target location, and training enhanced and sped up this bias. Finally, the microsaccade rate during a task-free fixation period correlated with observers' initial acuity threshold, indicating that the fewer the microsaccades during fixation the better the individual visual acuity. All these results, which were similar for both the Neutral and Attention groups and at both trained and untrained locations, suggest that microsaccades could serve as a physiological marker reflecting functional dynamics in human perceptual learning.

Cortical excitability in human somatosensory and visual cortex: implications for plasticity and learning - a minireview

The balance of excitation and inhibition plays a key role in plasticity and learning. A frequently used, reliable approach to assess intracortical inhibition relies on measuring paired-pulse behavior. Moreover, recent developments of magnetic resonance spectroscopy allows measuring GABA and glutamate concentrations. We give an overview about approaches employed to obtain information about excitatory states in human participants and discuss their putative relation. We summarize paired-pulse techniques and basic findings characterizing paired-pulse suppression in somatosensory (SI) and (VI) visual areas. Paired-pulse suppression describes the effect of paired sensory stimulation at short interstimulus intervals where the cortical response to the second stimulus is significantly suppressed. Simultaneous assessments of paired-pulse suppression in SI and VI indicated that cortical excitability is not a global phenomenon, but instead reflects the properties of local sensory processing. We review studies using non-invasive brain stimulation and perceptual learning experiments that assessed both perceptual changes and accompanying changes of cortical excitability in parallel. Independent of the nature of the excitation/inhibition marker used these data imply a close relationship between altered excitability and altered performance. These results suggest a framework where increased or decreased excitability is linked with improved or impaired perceptual performance. Recent findings have expanded the potential role of cortical excitability by demonstrating that inhibition markers such as GABA concentrations, paired-pulse suppression or alpha power predict to a substantial degree subsequent perceptual learning outcome. This opens the door for a targeted intervention where subsequent plasticity and learning processes are enhanced by altering prior baseline states of excitability.

The impact of training on the inner-outer asymmetry in crowding

Inner-outer asymmetry, where the outer flanker induces stronger crowding than the inner flanker, is a hallmark property of visual crowding. It is unclear the contribution of inner-outer asymmetry to the pattern of crowding errors (biased predominantly toward the flanker identities) and the role of training on crowding errors. In a typical radial crowding display, 20 observers were asked to report the orientation of a target Gabor (7.5° eccentricity) flanked by either an inner or outer Gabor along the horizontal meridian. The results showed that outer flanker conditions induced stronger crowding, accompanied by assimilative errors to the outer flanker for similar target/flanker elements. In contrast, the inner flanker condition exhibited weaker crowding, with no significant patterns of crowding errors. A population coding model showed that the flanker weights in the outer flanker condition were significantly higher than those in the inner flanker condition. Nine observers continued to train the outer flanker condition for four sessions. Training reduced inner-outer asymmetry and reduced flanker weights to the outer flanker. The learning effects were retained over 4 to 6 months. Individual differences in the appearance of crowding errors, the strength of inner-outer asymmetry, and the training effects were evident. Nevertheless, our findings indicate that different crowding mechanisms may be responsible for the asymmetric crowding effects induced by inner and outer flankers, with the outer flankers dominating the appearance more than the inner ones. Training reduces inner-outer asymmetry by reducing target/flanker confusion, and learning is persistent over months, suggesting that perceptual learning has the potential to improve visual performance by promoting neural plasticity.

Humans display interindividual differences in the latent mechanisms underlying fear generalization behaviour

Human generalization research aims to understand the processes underlying the transfer of prior experiences to new contexts. Generalization research predominantly relies on descriptive statistics, assumes a single generalization mechanism, interprets generalization from mono-source data, and disregards individual differences. Unfortunately, such an approach fails to disentangle various mechanisms underlying generalization behaviour and can readily result in biased conclusions regarding generalization tendencies. Therefore, we combined a computational model with multi-source data to mechanistically investigate human generalization behaviour. By simultaneously modelling learning, perceptual and generalization data at the individual level, we revealed meaningful variations in how different mechanisms contribute to generalization behaviour. The current research suggests the need for revising the theoretical and analytic foundations in the field to shift the attention away from forecasting group-level generalization behaviour and toward understanding how such phenomena emerge at the individual level. This raises the question for future research whether a mechanism-specific differential diagnosis may be beneficial for generalization-related psychiatric disorders.

Pathway and directional specificity of Hebbian plasticity in the cortical visual motion processing network

Cortico-cortical paired associative stimulation (ccPAS), which repeatedly pairs single-pulse transcranial magnetic stimulation (TMS) over two distant brain regions, is thought to modulate synaptic plasticity. We explored its spatial selectivity (pathway and direction specificity) and its nature (oscillatory signature and perceptual consequences) when applied along the ascending (Forward) and descending (Backward) motion discrimination pathway. We found unspecific connectivity increases in bottom-up inputs in the low gamma band, probably reflecting visual task exposure. A clear distinction in information transfer occurred in the re-entrant alpha signals, which were only modulated by Backward-ccPAS, and predictive of visual improvements in healthy participants. These results suggest a causal involvement of the re-entrant MT-to-V1 low-frequency inputs in motion discrimination and integration in healthy participants. Modulating re-entrant input activity could provide single-subject prediction scenarios for visual recovery. Visual recovery might indeed partly rely on these residual inputs projecting to spared V1 neurons.

Initial motor skill performance predicts future performance, but not learning

People show vast variability in skill performance and learning. What determines a person's individual performance and learning ability? In this study we explored the possibility to predict participants' future performance and learning, based on their behavior during initial skill acquisition. We recruited a large online multi-session sample of participants performing a sequential tapping skill learning task. We used machine learning to predict future performance and learning from raw data acquired during initial skill acquisition, and from engineered features calculated from the raw data. Strong correlations were observed between initial and final performance, and individual learning was not predicted. While canonical experimental tasks developed and selected to detect average effects may constrain insights regarding individual variability, development of novel tasks may shed light on the underlying mechanism of individual skill learning, relevant for real-life scenarios.

Are sleep disturbances a cause or consequence of autism spectrum disorder?

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by core symptoms such as atypical social communication, stereotyped behaviors, and restricted interests. One of the comorbid symptoms of individuals with ASD is sleep disturbance. There are two major hypotheses regarding the neural mechanism underlying ASD, i.e., the excitation/inhibition (E/I) imbalance and the altered neuroplasticity hypotheses. However, the pathology of ASD remains unclear due to inconsistent research results. This paper argues that sleep is a confounding factor, thus, must be considered when examining the pathology of ASD because sleep plays an important role in modulating the E/I balance and neuroplasticity in the human brain. Investigation of the E/I balance and neuroplasticity during sleep might enhance our understanding of the neural mechanisms of ASD. It may also lead to the development of neurobiologically informed interventions to supplement existing psychosocial therapies.