Perceptual Learning of Contrast Detection in the Human Lateral Geniculate Nucleus

A Systematic Review and Meta-Analysis of Perceptual Learning and Video Game Training for Adults with Monocular Amblyopia

INTRODUCTION

Amblyopia is a neurodevelopmental disorder characterized by a reduction in best-corrected visual acuity (BCVA). This meta-analysis aimed to analyze the effectiveness of perceptual learning and video game training for adults with amblyopia.

METHODS

Following Cochrane guidelines (PROSPERO CRD42024504502), we conducted a systematic search across multiple databases. Randomized controlled trials (RCTs) on adults with amblyopia receiving behavioral therapies were included. Data on interventions, sample size, and logMAR visual acuity were extracted and analyzed using Review Manager 5.4 and Stata 17.0.

RESULTS

A total of 6439 studies were identified, with 22 meeting the inclusion criteria after screening. The meta-analysis included 422 adult patients with amblyopia across these studies. Quality assessment revealed that 78% of studies had a low risk of bias. The analysis showed a statistically significant standardized mean difference (SMD) of -0.68 in the experimental group compared with controls, indicating an improvement in visual acuity (P < 0.05). Subgroup analyses indicated that perceptual learning and video game training also resulted in visual improvement (P < 0.05). In addition, the results indicated a significant improvement in visual acuity with dichoptic training or monocular training, reaching visual acuity improvement (P < 0.05).

CONCLUSIONS

These findings indicate that targeted visual training facilitates neural plasticity, reduces interocular suppression, and reinforces neural pathways associated with visual processing. While video game-based interventions represent a viable and engaging rehabilitation strategy, a combined approach may be most effective in enhancing monocular and binocular functions. Future research should focus on refining training protocols to enhance both monocular and binocular visual function more effectively.

Monocular Contrast Sensitivity Visual Perceptual Learning Rebalances Adult Amblyopes' Two Eyes

Purpose

This study investigates the effects of monocular contrast sensitivity visual perceptual learning on binocular visual functions of adults with binocular imbalances.

Methods

Sixteen adults with anisometropic amblyopia (mean age, 24.63 ± 3.56 years), 20 adults with myopic anisometropia (mean age, 24.20 ± 1.94 years), and 16 visually normal adults (mean age, 24.88 ± 1.89 years) participated in this study. Each group was evenly divided into training (anisometropic amblyopia, myopic anisometropia, normal training group) and untrained control groups (anisometropic amblyopia controls, myopic anisometropia controls, and normal controls). Training groups underwent 10 days of monocular contrast sensitivity perceptual learning (two-alternative forced-choice contrast detection task at 6 cycles per degree) using the amblyopic or nondominant eye, whereas the control groups received no intervention during the same period. Monocular visual acuity, monocular and binocular contrast sensitivity, and balance point were measured before and after the intervention.

Results

Monocular contrast sensitivity perceptual learning significantly improved both contrast sensitivity and balance point at the trained spatial frequency (6 cycles per degree) in the trained eyes of the anisometropic amblyopia training group and myopic anisometropia training group, with improvements generalizing to nearby untrained spatial frequencies. However, no significant improvements were observed in binocular summation ratios for either group. The normal training group showed modest improvements limited to the trained eye at both trained and neighboring spatial frequencies, without significant binocular or untrained eye benefits.

Conclusions

Monocular contrast sensitivity visual perceptual learning effectively enhances monocular visual performance and positively affects binocular functions across trained and nearby untrained spatial frequencies, indicating its potential clinical usefulness in improving binocular vision among adults with binocular imbalances.

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.

Using EEG microstates to examine whole-brain neuronal networks during offline rest consolidation after visual perceptual learning

Visual perceptual learning (VPL) leads to improvements in visual skills after practice or training in visual perceptual tasks. Evidence suggests that newly formed skills are preferentially consolidated by the brain during offline task-free periods. Additionally, VPL can lead to changes in brain areas associated with higher cognitive functions. Thus, training may result in changes in whole-brain networks during the offline consolidation period. To test this inference, electroencephalography (EEG) microstates were used to explore the dynamic characteristics of the whole-brain network during consolidation periods after training. Forty-five healthy young adults were randomly divided into three groups for training with moderate, easy and difficult intensity. The participants were trained on a coherent motion discrimination task, and the coherence threshold and resting EEG were measured before and after training. The results showed that visual performance improved only in the moderate training group and not in the easy or difficult training groups. Microstate analyses revealed significant decreases in the duration and occurrence rate of microstate C (often associated with the default mode network) during offline consolidation following moderate training. Moreover, the duration of microstate D (often associated with the dorsal attention network) significantly increased. However, moderate training did not change the duration or occurrence rate of microstate B (often associated with the visual network). This study revealed the activity of whole-brain networks in the consolidation period after VPL.

Adult visual deprivation engages associative, presynaptic plasticity of thalamic input to cortex

Associative plasticity at thalamocortical synapses is thought to be constrained by age in the mammalian cortex. However, here we show for the first time that prolonged visual deprivation induces robust and reversible plasticity at synapses between first order visual thalamus and cortical layer 4 pyramidal neurons. The plasticity is associative and expressed by changes in presynaptic function, thereby amplifying and relaying the change in efferent drive to the visual cortex.

Effect of facial emotion recognition learning transfers across emotions

Introduction

Perceptual learning of facial expression is shown specific to the train expression, indicating separate encoding of the emotional contents in different expressions. However, little is known about the specificity of emotional recognition training with the visual search paradigm and the sensitivity of learning to near-threshold stimuli.

Methods

In the present study, we adopted a visual search paradigm to measure the recognition of facial expressions. In Experiment 1 (Exp1), Experiment 2 (Exp2), and Experiment 3 (Exp3), subjects were trained for 8 days to search for a target expression in an array of faces presented for 950 ms, 350 ms, and 50 ms, respectively. In Experiment 4 (Exp4), we trained subjects to search for a target of a triangle, and tested them with the task of facial expression search. Before and after the training, subjects were tested on the trained and untrained facial expressions which were presented for 950 ms, 650 ms, 350 ms, or 50 ms.

Results

The results showed that training led to large improvements in the recognition of facial emotions only if the faces were presented long enough (Exp1: 85.89%; Exp2: 46.05%). Furthermore, the training effect could transfer to the untrained expression. However, when the faces were presented briefly (Exp3), the training effect was small (6.38%). In Exp4, the results indicated that the training effect could not transfer across categories.

Discussion

Our findings revealed cross-emotion transfer for facial expression recognition training in a visual search task. In addition, learning hardly affects the recognition of near-threshold expressions.

Only cortical prediction error signals are involved in visual learning, despite availability of subcortical prediction error signals

Both the midbrain systems, encompassing the ventral striatum (VS), and the cortical systems, including the dorsal anterior cingulate cortex (dACC), play roles in reinforcing and enhancing learning. However, the specific contributions of signals from these regions in learning remains unclear. To investigate this, we examined how VS and dACC are involved in visual perceptual learning (VPL) through an orientation discrimination task. In the primary experiment, subjects fasted for 5 hours before each of 14 days of training sessions and 3 days of test sessions. Subjects were rewarded with water for accurate trial responses. During the test sessions, BOLD signals were recorded from regions including VS and dACC. Although BOLD signals in both areas were associated with positive and negative RPEs, only those in dACC associated with negative RPE showed a significant correlation with performance improvement. Additionally, no significant correlation was observed between BOLD signals associated with RPEs in VS and dACC. These results suggest that although signals associated with positive and negative RPEs from both midbrain and cortical systems are readily accessible, only RPE signals in the prefrontal system, generated without linking to RPE signals in VS, are utilized for the enhancement of VPL.

Thalamic regulation of ocular dominance plasticity in adult visual cortex

Experience-dependent plasticity in the adult visual system is generally thought of as a cortical process. However, several recent studies have shown that perceptual learning or monocular deprivation can also induce plasticity in the adult dorsolateral geniculate nucleus (dLGN) of the thalamus. How plasticity in the thalamus and cortex interact in the adult visual system is ill-understood. To assess the influence of thalamic plasticity on plasticity in primary visual cortex (V1), we made use of our previous finding that during the critical period ocular dominance (OD) plasticity occurs in dLGN and requires thalamic synaptic inhibition. Using multielectrode recordings we find that this is also true in adult mice, and that in the absence of thalamic inhibition and plasticity, OD plasticity in adult V1 is absent. To study the influence of V1 on thalamic plasticity, we silenced V1 and show that during the critical period, but not in adulthood, the OD shift in dLGN is partially caused by feedback from V1. We conclude that during adulthood the thalamus plays an unexpectedly dominant role in experience-dependent plasticity in V1. Our findings highlight the importance of considering the thalamus as a potential source of plasticity in learning events that are typically thought of as cortical processes.

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.

Macromolecular tissue volume mapping of lateral geniculate nucleus subdivisions in living human brains

The lateral geniculate nucleus (LGN) is a key thalamic nucleus in the visual system, which has an important function in relaying retinal visual input to the visual cortex. The human LGN is composed mainly of magnocellular (M) and parvocellular (P) subdivisions, each of which has different stimulus selectivity in neural response properties. Previous studies have discussed the potential relationship between LGN subdivisions and visual disorders based on psychophysical data on specific types of visual stimuli. However, these relationships remain speculative because non-invasive measurements of these subdivisions are difficult due to the small size of the LGN. Here we propose a method to identify these subdivisions by combining two structural MR measures: high-resolution proton-density weighted images and macromolecular tissue volume (MTV) maps. We defined the M and P subdivisions based on MTV fraction data and tested the validity of the definition by (1) comparing the data with that from human histological studies, (2) comparing the data with functional magnetic resonance imaging measurements on stimulus selectivity, and (3) analyzing the test-retest reliability. The findings demonstrated that the spatial organization of the M and P subdivisions was consistent across subjects and in line with LGN subdivisions observed in human histological data. Moreover, the difference in stimulus selectivity between the subdivisions identified using MTV was consistent with previous physiology literature. The definition of the subdivisions based on MTV was shown to be robust over measurements taken on different days. These results suggest that MTV mapping is a promising approach for evaluating the tissue properties of LGN subdivisions in living humans. This method potentially will enable neuroscientific and clinical hypotheses about the human LGN subdivisions to be tested.

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.

Calibrating Vision: Concepts and Questions

The idea that visual coding and perception are shaped by experience and adjust to changes in the environment or the observer is universally recognized as a cornerstone of visual processing, yet the functions and processes mediating these calibrations remain in many ways poorly understood. In this article we review a number of facets and issues surrounding the general notion of calibration, with a focus on plasticity within the encoding and representational stages of visual processing. These include how many types of calibrations there are - and how we decide; how plasticity for encoding is intertwined with other principles of sensory coding; how it is instantiated at the level of the dynamic networks mediating vision; how it varies with development or between individuals; and the factors that may limit the form or degree of the adjustments. Our goal is to give a small glimpse of an enormous and fundamental dimension of vision, and to point to some of the unresolved questions in our understanding of how and why ongoing calibrations are a pervasive and essential element of vision.

Enhancement of visual perception by combining transcranial electrical stimulation and visual perceptual training

The visual system remains highly malleable even after its maturity or impairment. Our visual function can be enhanced through many ways, such as transcranial electrical stimulation (tES) and visual perceptual learning (VPL). TES can change visual function rapidly, but its modulation effect is short-lived and unstable. By contrast, VPL can lead to a substantial and long-lasting improvement in visual function, but extensive training is typically required. Theoretically, visual function could be further improved in a shorter time frame by combining tES and VPL than by solely using tES or VPL. Vision enhancement by combining these two methods concurrently is both theoretically and practically significant. In this review, we firstly introduced the basic concept and possible mechanisms of VPL and tES; then we reviewed the current research progress of visual enhancement using the combination of two methods in both general and clinical population; finally, we discussed the limitations and future directions in this field. Our review provides a guide for future research and application of vision enhancement and restoration by combining VPL and tES.

Training with optic flow stimuli promotes recovery in cortical blindness

BACKGROUND

Cortical blindness is a form of severe vision loss that is caused by damage to the primary visual cortex (V1) or its afferents. This condition has devastating effects on quality of life and independence. While there are few treatments currently available, accumulating evidence shows that certain visual functions can be restored with appropriate perceptual training: Stimulus sensitivity can be increased within portions of the blind visual field. However, this increased sensitivity often remains highly specific to the trained stimulus, limiting the overall improvement in visual function.

OBJECTIVE

Recent advances in the field of perceptual learning show that such specificity can be overcome with training paradigms that leverage the properties of higher-level visual cortical structures, which have greater capacity to generalize across stimulus positions and features. This targeting can be accomplished by using more complex training stimuli that elicit robust responses in these visual structures.

METHODS

We trained cortically blind subjects with a complex optic flow motion stimulus that was presented in a location of their blind field. Participants were instructed to train with the stimulus at home for approximately 30 minutes per day. Once performance plateaued, the stimulus was moved deeper into the blind field. A battery of pre- and post-training measures, with careful eye tracking, was performed to quantify the improvements.

RESULTS

We show that 1) optic flow motion discrimination can be relearned in cortically blind fields; 2) training with an optic flow stimulus can lead to improvements that transfer to different tasks and untrained locations; and 3) such training leads to a significant expansion of the visual field. The observed expansion of the visual field was present even when eye movements were carefully controlled. Finally, we show that regular training is critical for improved visual function, as sporadic training reduced the benefits of training, even when the total numbers of training sessions were equated.

CONCLUSIONS

These findings are consistent with the hypothesis that complex training stimuli can improve outcomes in cortical blindness, provided that patients adhere to a regular training regimen. Nevertheless, such interventions remain limited in their ability to restore functional vision.

Loss and enhancement of layer-selective signals in geniculostriate and corticotectal pathways of adult human amblyopia

How abnormal visual experiences early in life influence human subcortical pathways is poorly understood. Using high-resolution fMRI and pathway-selective visual stimuli, we investigate the influence of amblyopia on response properties and the effective connectivity of subcortical visual pathways of the adult human brain. Compared to the normal and fellow eyes, stimuli presented to the amblyopic eye show selectively reduced response in the parvocellular layers of the lateral geniculate nucleus and weaker effective connectivity to V1. Compared to the normal eye, the response of the amblyopic eye to chromatic stimulus decreases in the superficial layers of the superior colliculus, while response of the fellow eye robustly increases in the deep SC with stronger connectivity from the visual cortex. Therefore, amblyopia leads to selective parvocellular alterations of the geniculostriate and corticotectal pathways. These findings provide the neural basis for amblyopic deficits in visual acuity, ocular motor control, and attention.

Role of Structural, Metabolic, and Functional MRI in Monitoring Visual System Impairment and Recovery

The visual system, consisting of the eyes and the visual pathways of the brain, receives and interprets light from the environment so that we can perceive the world around us. A wide variety of disorders can affect human vision, ranging from ocular to neurologic to systemic in nature. While other noninvasive imaging techniques such as optical coherence tomography and ultrasound can image particular sections of the visual system, magnetic resonance imaging (MRI) offers high resolution without depth limitations. MRI also gives superior soft-tissue contrast throughout the entire pathway compared to computed tomography. By leveraging different imaging sequences, MRI is uniquely capable of unveiling the intricate processes of ocular anatomy, tissue physiology, and neurological function in the human visual system from the microscopic to macroscopic levels. In this review we discuss how structural, metabolic, and functional MRI can be used in the clinical assessment of normal and pathologic states in the anatomic structures of the visual system, including the eyes, optic nerves, optic chiasm, optic tracts, visual brain nuclei, optic radiations, and visual cortical areas. We detail a selection of recent clinical applications of MRI at each position along the visual pathways, including the evaluation of pathology, plasticity, and the potential for restoration, as well as its limitations and key areas of ongoing exploration. Our discussion of the current and future developments in MR ocular and neuroimaging highlights its potential impact on our ability to understand visual function in new detail and to improve our protection and treatment of anatomic structures that are integral to this fundamental sensory system. LEVEL OF EVIDENCE 3:   TECHNICAL EFFICACY STAGE 3:  .

Feature-based attention enables robust, long-lasting location transfer in human perceptual learning

Visual perceptual learning (VPL) is typically specific to the trained location and feature. However, the degree of specificity depends upon particular training protocols. Manipulating covert spatial attention during training facilitates learning transfer to other locations. Here we investigated whether feature-based attention (FBA), which enhances the representation of particular features throughout the visual field, facilitates VPL transfer, and how long such an effect would last. To do so, we implemented a novel task in which observers discriminated a stimulus orientation relative to two reference angles presented simultaneously before each block. We found that training with FBA enabled remarkable location transfer, reminiscent of its global effect across the visual field, but preserved orientation specificity in VPL. Critically, both the perceptual improvement and location transfer persisted after 1 year. Our results reveal robust, long-lasting benefits induced by FBA in VPL, and have translational implications for improving generalization of training protocols in visual rehabilitation.

Sensory-Induced Human LTP-Like Synaptic Plasticity - Using Visual Evoked Potentials to Explore the Relation Between LTP-Like Synaptic Plasticity and Visual Perceptual Learning

Objective

Stimulus-selective response modulation (SRM) of sensory evoked potentials represents a well-established non-invasive index of long-term potentiation-like (LTP-like) synaptic plasticity in the human sensory cortices. Although our understanding of the mechanisms underlying stimulus-SRM has increased over the past two decades, it remains unclear how this form of LTP-like synaptic plasticity is related to other basic learning mechanisms, such as perceptual learning. The aim of the current study was twofold; firstly, we aimed to corroborate former stimulus-SRM studies, demonstrating modulation of visual evoked potential (VEP) components following high-frequency visual stimulation. Secondly, we aimed to investigate the association between the magnitudes of LTP-like plasticity and visual perceptual learning (VPL).

Methods

42 healthy adults participated in the study. EEG data was recorded during a standard high-frequency stimulus-SRM paradigm. Amplitude values were measured from the peaks of visual components C1, P1, and N1. Embedded in the same experimental session, the VPL task required the participants to discriminate between a masked checkerboard pattern and a visual “noise” stimulus before, during and after the stimulus-SRM probes.

Results

We demonstrated significant amplitude modulations of VEPs components C1 and N1 from baseline to both post-stimulation probes. In the VPL task, we observed a significant change in the average threshold levels from the first to the second round. No significant association between the magnitudes of LTP-like plasticity and performance on the VPL task was evident.

Conclusion

To the extent of our knowledge, this study is the first to examine the relationship between the visual stimulus-RM phenomenon and VPL in humans. In accordance with previous studies, we demonstrated robust amplitude modulations of the C1 and N1 components of the VEP waveform. However, we did not observe any significant correlations between modulation magnitude of VEP components and VPL task performance, suggesting that these phenomena rely on separate learning mechanisms implemented by different neural mechanisms.

Visual perceptual learning generalizes to untrained effectors

Visual perceptual learning (VPL) is an improvement in visual function following training. Although the practical utility of VPL was once thought to be limited by its specificity to the precise stimuli used during training, more recent work has shown that such specificity can be overcome with appropriate training protocols. In contrast, relatively little is known about the extent to which VPL exhibits motor specificity. Previous studies have yielded mixed results. In this work, we have examined the effector specificity of VPL by training observers on a motion discrimination task that maintains the same visual stimulus (drifting grating) and task structure, but that requires different effectors to indicate the response (saccade vs. button press). We find that, in these conditions, VPL transfers fully between a manual and an oculomotor response. These results are consistent with the idea that VPL entails the learning of a decision rule that can generalize across effectors.

Awake suppression after brief exposure to a familiar stimulus

Newly learned information undergoes a process of awake reactivation shortly after the learning offset and we recently demonstrated that this effect can be observed as early as area V1. However, reactivating all experiences can be wasteful and unnecessary, especially for familiar stimuli. Therefore, here we tested whether awake reactivation occurs differentially for new and familiar stimuli. Subjects completed a brief visual task on a stimulus that was either novel or highly familiar due to extensive prior training on it. Replicating our previous results, we found that awake reactivation occurred in V1 for the novel stimulus. On the other hand, brief exposure to the familiar stimulus led to 'awake suppression' such that neural activity patterns immediately after exposure to the familiar stimulus diverged from the patterns associated with that stimulus. Further, awake reactivation was observed selectively in V1, whereas awake suppression had similar strength across areas V1-V3. These results are consistent with the presence of a competition between local awake reactivation and top-down awake suppression, with suppression becoming dominant for familiar stimuli.

Multi-Stage Cortical Plasticity Induced by Visual Contrast Learning

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

Recurrent Processing Drives Perceptual Plasticity

Learning and experience are critical for translating ambiguous sensory information from our environments to perceptual decisions. Yet evidence on how training molds the adult human brain remains controversial, as fMRI at standard resolution does not allow us to discern the finer scale mechanisms that underlie sensory plasticity. Here, we combine ultra-high-field (7T) functional imaging at sub-millimeter resolution with orientation discrimination training to interrogate experience-dependent plasticity across cortical depths that are known to support dissociable brain computations. We demonstrate that learning alters orientation-specific representations in superficial rather than middle or deeper V1 layers, consistent with recurrent plasticity mechanisms via horizontal connections. Further, learning increases feedforward rather than feedback layer-to-layer connectivity in occipito-parietal regions, suggesting that sensory plasticity gates perceptual decisions. Our findings reveal finer scale plasticity mechanisms that re-weight sensory signals to inform improved decisions, bridging the gap between micro- and macro-circuits of experience-dependent plasticity.

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Discrimination training alters orientation representations in superficial V1 layers

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Orientation-specific V1 plasticity is independent of task context

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Discrimination training alters orientation representations in middle IPS layers

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Learning enhances feedforward connectivity from visual to parietal cortex

General learning ability in perceptual learning

Developing expertise in any field usually requires acquisition of a wide range of skills. Most current studies on perceptual learning have focused on a single task and concluded that learning is quite specific to the trained task, and the ubiquitous individual differences reflect random fluctuations across subjects. Whether there exists a general learning ability that determines individual learning performance across multiple tasks remains largely unknown. In a large-scale perceptual learning study with a wide range of training tasks, we found that initial performance, task, and individual differences all contributed significantly to the learning rates across the tasks. Most importantly, we were able to extract both a task-specific but subject-invariant component of learning, that accounted for 38.6% of the variance, and a subject-specific but task-invariant perceptual learning ability, that accounted for 36.8% of the variance. The existence of a general perceptual learning ability across multiple tasks suggests that individual differences in perceptual learning are not "noise"; rather, they reflect the variability of learning ability across individuals. These results could have important implications for selecting potential trainees in occupations that require perceptual expertise and designing better training protocols to improve the efficiency of clinical rehabilitation.

Dissociating electrophysiological correlates of contextual and perceptual learning in a visual search task

Perceptual learning and contextual learning are two types of implicit visual learning that can co-occur in the same tasks. For example, to find an animal in the woods, you need to know where to look in the environment (contextual learning) and you must be able to discriminate its features (perceptual learning). However, contextual and perceptual learning are typically studied using distinct experimental paradigms, and little is known regarding their comparative neural mechanisms. In this study, we investigated contextual and perceptual learning in 12 healthy adult humans as they performed the same visual search task, and we examined psychophysical and electrophysiological (event-related potentials) measures of learning. Participants were trained to look for a visual stimulus, a small line with a specific orientation, presented among distractors. We found better performance for the trained target orientation as compared to an untrained control orientation, reflecting specificity of perceptual learning for the orientation of trained elements. This orientation specificity effect was associated with changes in the C1 component. We also found better performance for repeated spatial configurations as compared to novel ones, reflecting contextual learning. This context-specific effect was associated with the N2pc component. Taken together, these results suggest that contextual and perceptual learning are distinct visual learning phenomena that have different behavioral and electrophysiological characteristics.

Robust functional mapping of layer-selective responses in human lateral geniculate nucleus with high-resolution 7T fMRI

The lateral geniculate nucleus (LGN) of the thalamus is the major subcortical relay of retinal input to the visual cortex. It plays important roles in visual perception and cognition and is closely related with several eye diseases and brain disorders. Primate LGNs mainly consist of six layers of monocular neurons with distinct cell types and functions. The non-invasive measure of layer-selective activities of the human LGN would have broad scientific and clinical implications. Using high-resolution functional magnetic resonance imaging (fMRI) at 7 Tesla (T) and carefully designed visual stimuli, we achieved robust functional mapping of eye-specific and also magnocellular/parvocellular-specific laminar patterns of the human LGN. These laminar patterns were highly reproducible with different pulse sequences scanned on separate days, between different subjects, and were in remarkable consistency with the simulation from high-resolution histology of the human LGNs. These findings clearly demonstrate that 7T fMRI can robustly resolve layer-specific responses of the human LGN. This paves the way for future investigation of the critical roles of the LGN in human visual perception and cognition, as well as the neural mechanisms of many developmental and neurodegenerative diseases.

Reversal of Age-Related Changes in Cortical Sound-Azimuth Selectivity with Training

The compromised abilities to understand speech and localize sounds are two hallmark deficits in aged individuals. Earlier studies have shown that age-related deficits in cortical neural timing, which is clearly associated with speech perception, can be partially reversed with auditory training. However, whether training can reverse aged-related cortical changes in the domain of spatial processing has never been studied. In this study, we examined cortical spatial processing in ~21-month-old rats that were trained on a sound-azimuth discrimination task. We found that animals that experienced 1 month of training displayed sharper cortical sound-azimuth tuning when compared to the age-matched untrained controls. This training-induced remodeling in spatial tuning was paralleled by increases of cortical parvalbumin-labeled inhibitory interneurons. However, no measurable changes in cortical spatial processing were recorded in age-matched animals that were passively exposed to training sounds with no task demands. These results that demonstrate the effects of training on cortical spatial domain processing in the rodent model further support the notion that age-related changes in central neural process are, due to their plastic nature, reversible. Moreover, the results offer the encouraging possibility that behavioral training might be used to attenuate declines in auditory perception, which are commonly observed in older individuals.

Objective Assessment of the Effect of Optical Treatment on Magnocellular and Parvocellular-biased Visual Response in Anisometropic Amblyopia

Purpose

Optical treatment can improve visual function in anisometropic amblyopia, but there is no electrophysiological evidence, and the underlying change in visual pathway remains unknown. Our aims were to characterize the functional loss in magnocellular and parvocellular visual pathways in anisometropic amblyopia at baseline and to investigate the effect of optical treatment on the 2 visual pathways.

Methods

Using isolated-check visual-evoked potential, we measured the magnocellular- and parvocellular-biased contrast response functions in 15 normal controls (20.13 ± 3.93 years; mean ± standard deviation), 16 patients with anisometropic amblyopia (18.00 ± 6.04 years) who were fully refractive corrected before and 29 (19.41 ± 7.41 years) who had never been corrected. Twelve previously uncorrected amblyopes received optical treatment for more than 2 months and finished the follow-up measurement.

Results

Both the magnocellular- and parvocellular-biased contrast response functions in the amblyopic eye exhibited significantly reduced response and weaker contrast gains. We also found that the uncorrected amblyopes showed a more severe response reduction in magnocellular-biased, but not parvocellular-biased condition when compared with those corrected, with a weaker initial contrast gain and lower maximal response. After optical treatment, 12 uncorrected amblyopes demonstrated improved visual acuity of the amblyopic eye and a significant response gain to magnocellular-biased but not parvocellular-biased stimuli.

Conclusions

We demonstrated deficits to both magnocellular- and parvocellular-biased stimuli in subjects with anisometropic amblyopia. Optical treatment could produce neurophysiological changes in visual pathways even in older children and adults, which may be mediated through the magnocellular pathway.

Patching and Suppression in Amblyopia: One Mechanism or Two?

Purpose

To determine if benefits from occlusion therapy are due to decreased suppression from the fellow eye in children with amblyopia.

Methods

Ten newly diagnosed amblyopes (7.2 ± 1.4 years old), two with strabismus and eight with anisometropia, participated. Patients were first given a 2-month period of refractive adaptation, followed by occlusion therapy (i.e., patching their fellow eye with an opaque patch for 4 h/day). Visual acuity of the amblyopic eye and interocular suppression were measured before and after 0.5, 1, 2, 4, and 6 months of occlusion therapy. We quantified interocular suppression with a binocular phase combination task.

Results

Visual acuity (in logMAR) improved from 0.50 ± 0.22 (mean ± SD) to 0.33 ± 0.20 for patients who finished a short-term (2 months) occlusion (A1–A10), from 0.53 ± 0.20 to 0.32 ± 0.22 for patients who finished a medium-term (4 months) occlusion (A1–A9), and from 0.48 ± 0.19 to 0.22 ± 0.10 for patients who finished a long-term (6 months) occlusion (A1–A8). Although their visual acuity significantly improved, their degree of suppression, which was abnormal in all cases, did not change consistently. This was true in all durations of occlusion therapy.

Conclusion

Reduced suppression from the fixing eye might not be result from occlusion therapy.

A common probabilistic framework for perceptual and statistical learning

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

Distinguishing Hemodynamics from Function in the Human LGN Using a Temporal Response Model

We developed a temporal population receptive field model to differentiate the neural and hemodynamic response functions (HRF) in the human lateral geniculate nucleus (LGN). The HRF in the human LGN is dominated by the richly vascularized hilum, a structure that serves as a point of entry for blood vessels entering the LGN and supplying the substrates of central vision. The location of the hilum along the ventral surface of the LGN and the resulting gradient in the amplitude of the HRF across the extent of the LGN have made it difficult to segment the human LGN into its more interesting magnocellular and parvocellular regions that represent two distinct visual processing streams. Here, we show that an intrinsic clustering of the LGN responses to a variety of visual inputs reveals the hilum, and further, that this clustering is dominated by the amplitude of the HRF. We introduced a temporal population receptive field model that includes separate sustained and transient temporal impulse response functions that vary on a much short timescale than the HRF. When we account for the HRF amplitude, we demonstrate that this temporal response model is able to functionally segregate the residual responses according to their temporal properties.

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

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

Lateral geniculate nucleus volumetry at 3T and 7T: Four different optimized magnetic-resonance-imaging sequences evaluated against a 7T reference acquisition

PURPOSE

The lateral geniculate nucleus (LGN) is an essential nucleus of the visual pathway, occupying a small volume (60-160 mm³) among the other thalamic nuclei. The reported LGN volumes vary greatly across studies due to technical limitations and due to methodological differences of volume assessment. Yet, structural and anatomical alterations in ophthalmologic and neurodegenerative pathologies can only be revealed by a precise and reliable LGN representation. To improve LGN volume assessment, we first implemented a reference acquisition for LGN volume determination with optimized Contrast to Noise Ratio (CNR) and high spatial resolution. Next, we compared CNR efficiency and rating reliability of 3D Magnetization Prepared Rapid Gradient Echo (MPRAGE) images using white matter nulled (WMn) and grey matter nulled (GMn) sequences and its subtraction (WMn-GMn) relative to the clinical standard Proton Density Turbo Spin Echo (PD 2D TSE) and the reference acquisition. We hypothesized that 3D MPRAGE should provide a higher CNR and volume determination accuracy than the currently used 2D sequences.

MATERIALS AND METHODS

In 31 healthy subjects, we obtained at 3 and 7 T the following MR sequences: PD-TSE, MPRAGE with white/grey matter signal nulled (WMn/GMn), and a motion-corrected segmented MPRAGE sequence with a resolution of 0.4 × 0.4 × 0.4 mm³ (reference acquisition). To increase CNR, GMn were subtracted from WMn (WMn-GMn). Four investigators manually segmented the LGN independently.

RESULTS

The reference acquisition provided a very sharp depiction of the LGN and an estimated mean LGN volume of 124 ± 3.3 mm³. WMn-GMn had the highest CNR and gave the most reproducible LGN volume estimations between field strengths. Even with the highest CNR efficiency, PD-TSE gave inconsistent LGN volumes with the weakest reference acquisition correlation. The LGN WM rim induced a significant difference between LGN volumes estimated from WMn and GMn. WMn and GMn LGN volume estimations explained most of the reference acquisition volumes' variance. For all sequences, the volume rating reliability were good. On the other hand, the best CNR rating reliability, LGN volume and CNR correlations with the reference acquisition were obtained with GMn at 7 T.

CONCLUSION

WMn and GMn MPRAGE allow reliable LGN volume determination at both field strengths. The precise location and identification of the LGN (volume) can help to optimize neuroanatomical and neurophysiological studies, which involve the LGN structure. Our optimized imaging protocol may be used for clinical applications aiming at small nuclei volumetric and CNR quantification.

Perceptual learning of fine contrast discrimination changes neuronal tuning and population coding in macaque V4

Perceptual learning, the improvement in perceptual abilities with training, is thought to be mediated by an alteration of neuronal tuning. It remains poorly understood how tuning properties change as training progresses, whether improved stimulus tuning directly links to increased behavioural readout of sensory information, or how population coding mechanisms change with training. Here, we recorded continuously from multiple neuronal clusters in area V4 while macaque monkeys learned a fine contrast categorization task. Training increased neuronal coding abilities by shifting the steepest point of contrast response functions towards the categorization boundary. Population coding accuracy of difficult discriminations resulted largely from an increased information coding of individual channels, particularly for those channels that in early learning had larger ability for easy discriminations, but comparatively small encoding abilities for difficult discriminations. Population coding was also enhanced by specific changes in correlations. Neuronal activity became more indicative of upcoming choices with training.

Perceptual learning, the improvement in perceptual abilities with training, is thought to involve changes in neuronal 'tuning'. Here, the authors show that perceptual learning works by making neurons increasingly sensitive to task-relevant differences in stimuli, and by improving population coding mechanisms.

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.

Towards a whole brain model of Perceptual Learning

A hallmark of modern Perceptual Learning (PL) is the extent to which learning is specific to the trained stimuli. Such specificity to orientation, spatial location and even eye of training has been used as psychophysical evidence of the neural basis of learning. This argument that specificity of PL implies regionalization of brain plasticity implicitly assumes that examination of a singular locus of PL is an appropriate approach to understand learning. However, recent research shows that learning effects once thought to be specific depend on subtleties of the training paradigm and that within even a simple training procedure there are multiple aspects of the task and stimuli that are learned simultaneously. Here, we suggest that learning on any task involves a broad network of brain regions undergoing changes in representations, read-out weights, decision rules, attention and feedback processes as well as oculomotor changes. However, importantly, the distribution of learning across the neural system depends upon the details of the training procedure and the characterstics of the individual being trained. We propose that to advance our understanding of PL, the field must move towards understanding how distributed brain processes jointly contribute to behavioral learning effects.

Structural and Functional Connectivity Changes Beyond Visual Cortex in a Later Phase of Visual Perceptual Learning

The neural mechanisms of visual perceptual learning (VPL) remain unclear. Previously we found that activation in the primary visual cortex (V1) increased in the early encoding phase of training, but returned to baseline levels in the later retention phase. To examine neural changes during the retention phase, we measured structural and functional connectivity changes using MRI. After weeks of training on a texture discrimination task, the fractional anisotropy of the inferior longitudinal fasciculus, a major tract connecting visual and anterior areas, was increased, as well as the functional connectivity between V1 and anterior regions mediated by the ILF. These changes were strongly correlated with behavioral performance improvements. These results suggest a two-phase model of VPL in which localized functional changes in V1 in the encoding phase of training are followed by changes in both structural and functional connectivity in ventral visual processing, perhaps leading to the long-term stabilization of VPL.