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

Touch-driven advantages in reaction time but not in performance in a cross-sensory comparison of reinforcement learning

Recent research has highlighted a notable confidence bias in the haptic sense, yet its impact on learning relative to other senses remains unexplored. This online study investigated learning behaviour across visual, auditory, and haptic modalities using a probabilistic selection task on computers and mobile devices, employing dynamic and ecologically valid stimuli to enhance generalisability. We analysed reaction time as an indicator of confidence, alongside learning speed and task accuracy. Our results revealed the fastest reaction times with haptic stimuli, suggesting heightened perceptual confidence, whereas visual stimuli were the slowest, and auditory stimuli were intermediate. Despite these differences, all modalities demonstrated consistent learning speeds and accuracies. These findings support the 'common currency' hypothesis of perceptual confidence, facilitating modality-independent meta-representations for efficient decision-making. Additionally, reaction times were significantly faster on touch-based mobile devices compared to computers, underscoring the metacognitive efficiency of haptic feedback in technology-enhanced environments. The combination of faster reaction time in the haptic modality without sacrificing accuracy and the enhanced efficiency of touch-based interfaces advocates for the integration of haptics in technological designs to boost efficiency while maintaining a high level of precision.

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.

Visual Perceptual Learning of Form-Motion Integration: Exploring the Involved Mechanisms with Transfer Effects and the Equivalent Noise Approach

Background: Visual perceptual learning plays a crucial role in shaping our understanding of how the human brain integrates visual cues to construct coherent perceptual experiences. The visual system is continually challenged to integrate a multitude of visual cues, including form and motion, to create a unified representation of the surrounding visual scene. This process involves both the processing of local signals and their integration into a coherent global percept. Over the past several decades, researchers have explored the mechanisms underlying this integration, focusing on concepts such as internal noise and sampling efficiency, which pertain to local and global processing, respectively. Objectives and Methods: In this study, we investigated the influence of visual perceptual learning on non-directional motion processing using dynamic Glass patterns (GPs) and modified Random-Dot Kinematograms (mRDKs). We also explored the mechanisms of learning transfer to different stimuli and tasks. Specifically, we aimed to assess whether visual perceptual learning based on illusory directional motion, triggered by form and motion cues (dynamic GPs), transfers to stimuli that elicit comparable illusory motion, such as mRDKs. Additionally, we examined whether training on form and motion coherence thresholds improves internal noise filtering and sampling efficiency. Results: Our results revealed significant learning effects on the trained task, enhancing the perception of dynamic GPs. Furthermore, there was a substantial learning transfer to the non-trained stimulus (mRDKs) and partial transfer to a different task. The data also showed differences in coherence thresholds between dynamic GPs and mRDKs, with GPs showing lower coherence thresholds than mRDKs. Finally, an interaction between visual stimulus type and session for sampling efficiency revealed that the effect of training session on participants' performance varied depending on the type of visual stimulus, with dynamic GPs being influenced differently than mRDKs. Conclusion: These findings highlight the complexity of perceptual learning and suggest that the transfer of learning effects may be influenced by the specific characteristics of both the training stimuli and tasks, providing valuable insights for future research in visual processing.

Distinct Neural Plasticity Enhancing Visual Perception

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

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

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

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.

Perspectives on the Combined Use of Electric Brain Stimulation and Perceptual Learning in Vision

A growing body of literature offers exciting perspectives on the use of brain stimulation to boost training-related perceptual improvements in humans. Recent studies suggest that combining visual perceptual learning (VPL) training with concomitant transcranial electric stimulation (tES) leads to learning rate and generalization effects larger than each technique used individually. Both VPL and tES have been used to induce neural plasticity in brain regions involved in visual perception, leading to long-lasting visual function improvements. Despite being more than a century old, only recently have these techniques been combined in the same paradigm to further improve visual performance in humans. Nonetheless, promising evidence in healthy participants and in clinical population suggests that the best could still be yet to come for the combined use of VPL and tES. In the first part of this perspective piece, we briefly discuss the history, the characteristics, the results and the possible mechanisms behind each technique and their combined effect. In the second part, we discuss relevant aspects concerning the use of these techniques and propose a perspective concerning the combined use of electric brain stimulation and perceptual learning in the visual system, closing with some open questions on the topic.

Perceptual learning is robust to manipulations of valence and arousal in childhood and adulthood

Despite clear links between affective processes in many areas of cognition and perception, the influence of affective valence and arousal on low-level perceptual learning have remained largely unexplored. Such influences could have the potential to disrupt or enhance learning that would have long-term consequences for young learners. The current study manipulated 8- to 11-year-old children's and young adults' mood using video clips (to induce a positive mood) or a psychosocial stressor (to induce a negative mood). Each participant then completed one session of a low-level visual learning task (visual texture paradigm). Using novel computational methods, we did not observe evidence for the modulation of visual perceptual learning by manipulations of emotional arousal or valence in either children or adults. The majority of results supported a model of perceptual learning that is overwhelmingly constrained to the task itself and independent from external factors such as variations in learners' affect.

Attention network modulation via tRNS correlates with attention gain

Transcranial random noise stimulation (tRNS) can enhance vision in the healthy and diseased brain. Yet, the impact of multi-day tRNS on large-scale cortical networks is still unknown. We investigated the impact of tRNS coupled with behavioral training on resting-state functional connectivity and attention. We trained human subjects for 4 consecutive days on two attention tasks, while receiving tRNS over the intraparietal sulci, the middle temporal areas, or Sham stimulation. We measured resting-state functional connectivity of nodes of the dorsal and ventral attention network (DVAN) before and after training. We found a strong behavioral improvement and increased connectivity within the DVAN after parietal stimulation only. Crucially, behavioral improvement positively correlated with connectivity measures. We conclude changes in connectivity are a marker for the enduring effect of tRNS upon behavior. Our results suggest that tRNS has strong potential to augment cognitive capacity in healthy individuals and promote recovery in the neurological population.

Perceptual learning as a result of concerted changes in prefrontal and visual cortex

Our perceptual ability remarkably improves with training. Some studies on visual perceptual learning have shown refined neural representation of the trained stimulus in the visual cortex, whereas others have exclusively argued for improved readout and decision-making processes in the frontoparietal cortex. The mixed results have rendered the underlying neural mechanisms puzzling and hotly debated. By simultaneously recording from monkey visual area V4 and ventrolateral prefrontal cortex (PFC) implanted with microelectrode arrays, we dissected learning-induced cortical changes over the course of training the monkeys in a global form detection task. Decoding analysis dissociated two distinct components of neuronal population codes that were progressively and markedly enhanced in both V4 and PFC. One component was closely related to the target stimulus feature and was subject to task-dependent top-down modulation; it emerged earlier in V4 than PFC and its enhancement was specific to the trained configuration of the target stimulus. The other component of the neural code was entirely related to the animal's behavioral choice; it emerged earlier in PFC than V4 and its enhancement completely generalized to an untrained stimulus configuration. These results implicate two concurrent and synergistic learning processes: a perceptual process that is specific to the details of the trained stimulus feature and a cognitive process that is dependent on the total amount of learning experience in the trained task. When combined, these two learning processes were well predictive of the animal's learning behavior.

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.

Behavioural performance improvement in visuomotor learning correlates with functional and microstructural brain changes

A better understanding of practice-induced functional and structural changes in our brains can help us design more effective learning environments that provide better outcomes. Although there is growing evidence from human neuroimaging that experience-dependent brain plasticity is expressed in measurable brain changes that are correlated with behavioural performance, the relationship between behavioural performance and structural or functional brain changes, and particularly the time course of these changes, is not well characterised. To understand the link between neuroplastic changes and behavioural performance, 15 healthy participants in this study followed a systematic eye movement training programme for 30 min daily at home, 5 days a week and for 6 consecutive weeks. Behavioural performance statistics and eye tracking data were captured throughout the training period to evaluate learning outcomes. Imaging data (DTI and fMRI) were collected at baseline, after two and six weeks of continuous training, and four weeks after training ended. Participants showed significant improvements in behavioural performance (faster task completion time, lower fixation number and fixation duration). Spatially overlapping reductions in microstructural diffusivity measures (MD, AD and RD) and functional activation increases (BOLD signal) were observed in two main areas: extrastriate visual cortex (V3d) and the frontal part of the cerebellum/Fastigial Oculomotor Region (FOR), which are both involved in visual processing. An increase of functional activity was also recorded in the right frontal eye field. Behavioural, structural and functional changes were correlated. Microstructural change is a better predictor for long-term behavioural change than functional activation is, whereas the latter is superior in predicting instantaneous performance. Structural and functional measures at week 2 of the training programme also predict performance at week 6 and 10, which suggests that imaging data at an early stage of training may be useful in optimising practice environments or rehabilitative training programmes.

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.

Training-Induced Changes in Radial-Tangential Anisotropy of Visual Crowding

Purpose

One of the diagnostic features of visual crowding, radial–tangential anisotropy, has been observed both in behavioral experiments as well as in responses of the blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal. As has been shown previously, crowding is stronger for radially arranged flankers, and this tendency is reflected in BOLD signal suppression. In the current study, we examined the effect of practice on the neural correlates of crowding. We expected that training on a crowding task would cause shrinkage of the crowding zone that would be mirrored in corresponding BOLD signal responses.

Methods

Pre- and post-training fMRI images were acquired in 17 healthy volunteers using a 3-tesla MRI scanner. Participants were trained over 4 consecutive days on a crowding task.

Results

Comparison of the pre- and post-training behavioral data indicates a significant shrinkage of the crowding zone as a result of training. Moreover, we observed a pronounced radial–tangential anisotropy in the BOLD signal prior to training; that is, radial flankers induced a larger reduction in the BOLD signal compared to equally spaced tangential flankers. After training, this radial–tangential anisotropy in the BOLD signal was significantly reduced. Specifically, we found significant changes in BOLD responses for the radial flanker configuration.

Conclusions

Our results demonstrate that training-induced changes in the anisotropic shape of the crowding zone are reflected in the BOLD signal in the early visual cortex.

Translational Relevance

Perceptual learning tasks may have the potential to improve visual performance by promoting neural plasticity. Our results could motivate the development of suitable rehabilitation protocols for patients with central vision loss.

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

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

Evaluating the Acute Effect of Stereoscopic Recovery by Dichoptic Stimulation Using Electroencephalogram

Amblyopia is a common developmental disorder in adolescents and children. Stereoscopic loss is a symptom of amblyopia that can seriously affect the quality of patient's life. Recent studies have shown that the push-pull perceptual learning protocol had a positive effect on stereoscopic recovery. In this study, we developed a stereoscopic training method using a polarized visualization system according to the push-pull protocol. Dichoptic stimulation for 36 anisometropic and amblyopic subjects and 33 children with normal visual acuity (VA) has been conducted. Electroencephalogram (EEG) was used to evaluate the neurophysiological changes before, during, and after stimulation. For the anisometropic and amblyopic subjects, the statistical analysis demonstrated significant differences (p < 0.01) in the beta rhythm at the middle temporal and occipital lobes, while the EEG from the normal VA subjects indicated no significant changes when comparing the results before and after training. We concluded that the dichoptic training in our study can activate the middle temporal visual area and visual cortex. The EEG changes can be used to evaluate the training effects. This study also found that the beta band EEG acquired during visual stimulation at the dorsal visual stream can be potentially used for predicting acute training effect. The results facilitated the optimization of the individual training plan.

Progressive Circuit Changes during Learning and Disease

A critical step toward understanding cognition, learning, and brain dysfunction will be identification of the underlying cellular computations that occur in and across discrete brain areas, as well as how they are progressively altered by experience or disease. These computations will be revealed by targeted analyses of the neurons that perform these calculations, defined not only by their firing properties but also by their molecular identity and how they are wired within the local and broad-scale network of the brain. New studies that take advantage of sophisticated genetic tools for cell-type-specific identification and control are revealing how learning and neurological disorders initiate and successively change the properties of defined neural circuits. Understanding the temporal sequence of adaptive or pathological synaptic changes across multiple synapses within a network will shed light into how small-scale neural circuits contribute to higher cognitive functions during learning and disease.

Rapid Plasticity of Higher-Order Thalamocortical Inputs during Sensory Learning

Neocortical circuits are sensitive to experience, showing both anatomical and electrophysiological changes in response to altered sensory input. We examined input- and cell-type-specific changes in thalamo- and intracortical pathways during learning using an automated, home-cage sensory association training (SAT) paradigm coupling multi-whisker stimulation to a water reward. We found that the posterior medial nucleus (POm) but not the ventral posterior medial (VPM) nucleus of the thalamus drives increased cortical activity after 24 h of SAT, when behavioral evidence of learning first emerges. Synaptic strengthening within the POm thalamocortical pathway was first observed at thalamic inputs to L5 and was not generated by sensory stimulation alone. Synaptic changes in L2 were delayed relative to L5, requiring 48 h of SAT to drive synaptic plasticity at thalamic and intracortical inputs onto L2 Pyr neurons. These data identify the POm thalamocortical circuit as a site of rapid synaptic plasticity during learning and suggest a temporal sequence to learning-evoked synaptic changes in the sensory cortex.

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.

Perceptual learning of task-irrelevant features depends on the sensory context

The brain has evolved to extract behaviourally meaningful information from the environment. For example, it has been shown that visual perceptual learning (VPL) can occur for task-irrelevant stimulus features when those features are consistently paired with internal or external reinforcement signals. It is, however, unclear whether or not task-irrelevant VPL is influenced by stimulus features that are unrelated to reinforcement in a given sensory context. To address this question, we exposed participants to task-irrelevant and subliminal coherent motion stimuli in the background while they performed a central character identification task. A specific motion direction was consistently paired with the task-targets, while two other directions occurred only with distractors and, thus, were unrelated to reinforcement. We found that the magnitude of VPL of the target-paired direction was significantly greater when the distractor-paired directions were close to the target-paired direction, compared to when they were farther. Thus, even very weak signals that are both subliminal and unrelated to reinforcement are processed and exert an influence on VPL. This finding suggests that the outcome of VPL depends on the sensory context in which learning takes place and calls for a refinement of VPL theories to incorporate exposure-based influences on learning.

Feature-Specific Awake Reactivation in Human V1 after Visual Training

Brain activity patterns exhibited during task performance have been shown to spontaneously reemerge in the following restful awake state. Such "awake reactivation" has been observed across higher-order cortex for complex images or associations. However, it is still unclear whether the reactivation extends to primary sensory areas that encode simple stimulus features. To address this question, we trained human subjects from both sexes on a particular visual feature (Gabor orientation) and tested whether this feature will be reactivated immediately after training. We found robust reactivation in human V1 that lasted for at least 8 min after training offset. This effect was not present in higher retinotopic areas, such as V2, V3, V3A, or V4v. Further analyses suggested that the amount of awake reactivation was related to the amount of performance improvement on the visual task. These results demonstrate that awake reactivation extends beyond higher-order areas and also occurs in early sensory cortex.SIGNIFICANCE STATEMENT How do we acquire new memories and skills? New information is known to be consolidated during offline periods of rest. Recent studies suggest that a critical process during this period of consolidation is the spontaneous reactivation of previously experienced patterns of neural activity. However, research in humans has mostly examined such reactivation processes in higher-order cortex. Here we show that awake reactivation occurs even in the primary visual cortex V1 and that this reactivation is related to the amount of behavioral learning. These results pinpoint awake reactivation as a process that likely occurs across the entire human brain and could play an integral role in memory consolidation.

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

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

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.

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

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

Neural mechanisms of motion perceptual learning in noise

Practice improves our perceptual ability. However, the neural mechanisms underlying this experience-dependent plasticity in adult brain remain unclear. Here, we studied the long-term neural correlates of motion perceptual learning. Subjects' behavioral performance and BOLD signals were tracked before, immediately after, and 2 weeks after practicing a motion direction discrimination task in noise over six daily sessions. Parallel to the specificity and persistency of the behavioral learning effect, we found that training sharpened the cortical tuning in MT, and enhanced the connectivity strength from MT to the intraparietal sulcus (IPS, a motion decision-making area). In addition, the decoding accuracy for the trained motion direction was improved in IPS 2 weeks after training. The dual changes in the sensory and the high-level cortical areas suggest that learning refines the neural representation of the trained stimulus and facilitates the information transmission in the decision process. Our findings are consistent with the functional specialization in the visual cortex, and provide empirical evidence to the reweighting theory of perceptual learning at a large spatial scale. Hum Brain Mapp 38:6029-6042, 2017. © 2017 Wiley Periodicals, Inc.

Perceptual Learning of Contrast Detection in the Human Lateral Geniculate Nucleus

The brain is continuously modified by perceptual experience throughout life. Perceptual learning, which refers to the long-term performance improvement resulting from practice, has been widely used as a paradigm to study experience-dependent brain plasticity in adults [1, 2]. In the visual system, adult plasticity is largely believed to be restricted to the cortex, with subcortical structures losing their capacity for change after a critical period of development [3, 4]. Although various cortical mechanisms have been shown to mediate visual perceptual learning [5-12], there has been no reported investigation of perceptual learning in subcortical nuclei. Here, human subjects were trained on a contrast detection task for 30 days, leading to a significant contrast sensitivity improvement that was specific to the trained eye and the trained visual hemifield. Training also resulted in an eye- and hemifield-specific fMRI signal increase to low-contrast patterns in the magnocellular layers of the lateral geniculate nucleus (LGN), even when subjects did not pay attention to the patterns. Such an increase was absent in the parvocellular layers of the LGN and visual cortical areas. Furthermore, the behavioral benefit significantly correlated with the neural enhancement. These findings suggest that LGN signals can be amplified by training to detect faint patterns. Neural plasticity induced by perceptual learning in human adults might not be confined to the cortical level but might occur as early as at the thalamic level.