Rapidly repeated visual stimulation induces long-term potentiation of VEPs and increased content of membrane AMPA and NMDA receptors in the V1 cortex of cats

Studies report that rapidly repeated sensory stimulation can evoke LTP-like improvement of neural response in the sensory cortex. Whether this neural response potentiation is similar to the classic LTP induced by presynaptic electrical stimulation remains unclear. This study examined the effects of repeated high-frequency (9 Hz) versus low-frequency (1 Hz) visual stimulation on visually-evoked field potentials (VEPs) and the membrane protein content of AMPA / NMDA receptors in the primary visual cortex (V1) of cats. The results showed that repeated high-frequency visual stimulation (HFS) caused a long-term improvement in peak-to-peak amplitude of V1-cortical VEPs in response to visual stimuli at HFS-stimulated orientation (SO: 90°) and non-stimulated orientation (NSO: 180°), but the effect exhibited variations depending on stimulus orientation: the amplitude increase of VEPs in response to visual stimuli at SO was larger, reached a maximum earlier and lasted longer than at NSO. By contrast, repeated low-frequency visual stimulation (LFS) had not significantly affected the amplitude of V1-cortical VEPs in response to visual stimuli at both SO and NSO. Furthermore, the membrane protein content of the key subunit GluA1 of AMPA receptors and main subunit NR1 of AMPA receptors in V1 cortex was significantly increased after HFS but not LFS when compared with that of control cats. Taken together, these results indicate that HFS can induce LTP-like improvement of VEPs and an increase in membrane protein of AMPA and NMDA receptors in the V1 cortex of cats, which is similar to but less specific to stimulus orientation than the classic LTP.

Profiles of visual perceptual learning in feature space

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

Category representation in primary visual cortex after visual perceptual learning

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

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09926-8.

Plasticity-stability dynamics during post-training processing of learning

Learning continues beyond the end of training. Post-training learning is supported by changes in plasticity and stability in the brain during both wakefulness and sleep. However, the lack of a unified measure for assessing plasticity and stability dynamics during training and post-training periods has limited our understanding of how these dynamics shape learning. Focusing primarily on procedural learning, we integrate work using behavioral paradigms and a recently developed measure, the excitatory-to-inhibitory (E/I) ratio, to explore the delicate balance between plasticity and stability and its relationship to post-training learning. This reveals plasticity-stability cycles during both wakefulness and sleep that enhance learning and protect it from new learning during post-training processing.

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.

The study of plasticity has always been about gradients

The experimental study of learning and plasticity has always been driven by an implicit question: how can physiological changes be adaptive and improve performance? For example, in Hebbian plasticity only synapses from presynaptic neurons that were active are changed, avoiding useless changes. Similarly, in dopamine-gated learning synapse changes depend on reward or lack thereof and do not change when everything is predictable. Within machine learning we can make the question of which changes are adaptive concrete: performance improves when changes correlate with the gradient of an objective function quantifying performance. This result is general for any system that improves through small changes. As such, physiology has always implicitly been seeking mechanisms that allow the brain to approximate gradients. Coming from this perspective we review the existing literature on plasticity-related mechanisms, and we show how these mechanisms relate to gradient estimation. We argue that gradients are a unifying idea to explain the many facets of neuronal plasticity.

Many Roads Lead to Rome: Differential Learning Processes for the Same Perceptual Improvement

Repeatedly exercising a perceptual ability usually leads to improvement, yet it is unclear whether the mechanisms supporting the same perceptual learning could be flexibly adjusted according to the training settings. Here, we trained adult observers in an orientation-discrimination task at either a single (focused) retinal location or multiple (distributed) retinal locations. We examined the observers' discriminability (N = 52) and bias (N = 20) in orientation perception at the trained and untrained locations. The focused and distributed training enhanced orientation discriminability by the same amount and induced a bias in perceived orientation at the trained locations. Nevertheless, the distributed training promoted location generalization of both practice effects, whereas the focused training resulted in specificity. The two training tactics also differed in long-term retention of the training effects. Our results suggest that, depending on the training settings of the same task, the same discrimination learning could differentially engage location-specific and location-invariant representations of the learned stimulus feature.

Early stage of radiological expertise modulates resting-state local coherence in the inferior temporal lobe

Background

The visual system and its inherent functions undergo experience-dependent changes through the lifespan, enabling acquisition of new skills. Previous fMRI studies using tasks reported increased specialization in a number of cortical regions subserving visual expertise. Although ample studies focused on representation of long-term visual expertise in the brain, i.e. in terms of year, monthly-based early-stage representation of visual expertise remains unstudied. Given that spontaneous neuronal oscillations actively encode previous experience, we propose brain representations in the resting state is fundamentally important.

Objective

The current study aimed to investigate how monthly-based early-stage visual expertise are represented in the resting state using the expertise model of radiologists.

Methods

In particular, we investigated the altered local clustering pattern of spontaneous brain activity using regional homogeneity (ReHo). A cohort group of radiology interns (n = 22) after one-month training in X-ray department and matched laypersons (n = 22) were recruited after rigorous behavioral assessment.

Results

The results showed higher ReHo in the right hippocampus (HIP) and the right ventral anterior temporal lobe (vATL) (corrected by Alphasim correction, P < 0.05). Moreover, ReHo in the right HIP correlated with the number of cases reviewed during intern radiologists' training (corrected by Alphasim correction, P < 0.05).

Conclusions

In sum, our results demonstrated that the early stage of visual expertise is more concerned with stabilizing visual feature and domain-specific knowledge into long-term memory. The results provided novel evidence regarding how early-stage visual expertise is represented in the resting brain, which help further elaborate how human visual expertise is acquired. We propose that our current study may provide novel ideas for developing new training protocols in medical schools.

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.

Learned low priority of attention after training to suppress color singleton distractor

Allocating attention to significant events, such as a salient object, is effortless. Our brain is effective on this type of processing because doing so is generally beneficial for survival. However, a salient object could also be distracting and ignoring it costs a large amount of cognitive resource. In the present study, we conducted two behavioral experiments to investigate the effect of learned suppression of a salient color. Particularly, we were interested in the effect of learning in a new task context in which the previously suppressed color was task irrelevant. In Experiment 1, we trained the participants for five days with explicit instruction to suppress a color singleton distractor in a visual search task. We measured the effect of training with a dot probe task before and after the training. Colors in the dot probe task only served as the background and were not associated with the position of the target dot. However, we found that attention was involuntarily biased away from the previously suppressed color. In Experiment 2, the color singleton could either be the target or distractor in the visual search task, making the suppression of the color singleton inefficient for task performance. The results showed no training effect in the dot probe task after this manipulation. These findings provided direct evidence for the learned low priority of attention after training to suppress the color singleton distractor.

Visual neuroscience: A shrewd look at perceptual learning

A new study provides insight into the neuronal mechanisms that underlie visual learning in the tree shrew, revealing how improved coding for trained stimuli in visual cortex can negatively affect the perception of other stimuli.

Statistical Learning in Vision

Vision and learning have long been considered to be two areas of research linked only distantly. However, recent developments in vision research have changed the conceptual definition of vision from a signal-evaluating process to a goal-oriented interpreting process, and this shift binds learning, together with the resulting internal representations, intimately to vision. In this review, we consider various types of learning (perceptual, statistical, and rule/abstract) associated with vision in the past decades and argue that they represent differently specialized versions of the fundamental learning process, which must be captured in its entirety when applied to complex visual processes. We show why the generalized version of statistical learning can provide the appropriate setup for such a unified treatment of learning in vision, what computational framework best accommodates this kind of statistical learning, and what plausible neural scheme could feasibly implement this framework. Finally, we list the challenges that the field of statistical learning faces in fulfilling the promise of being the right vehicle for advancing our understanding of vision in its entirety. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A distinct route for efficient learning and generalization in autism

Visual skill learning is the process of improving responses to surrounding visual stimuli.¹ For individuals with autism spectrum disorders (ASDs), efficient skill learning may be especially valuable due to potential difficulties with sensory processing² and challenges in adjusting flexibly to changing environments.^3,4 Standard skill learning protocols require extensive practice with multiple stimulus repetitions,^5-7 which may be difficult for individuals with ASD and create abnormally specific learning with poor ability to generalize.⁴ Motivated by findings indicating that brief memory reactivations can facilitate skill learning,^8,9 we hypothesized that reactivation learning with few stimulus repetitions will enable efficient learning in individuals with ASD, similar to their learning with standard extensive practice protocols used in previous studies.^4,10,11 We further hypothesized that in contrast to experience-dependent plasticity often resulting in specificity, reactivation-induced learning would enable generalization patterns in ASD. To test our hypotheses, high-functioning adults with ASD underwent brief reactivations of an encoded visual learning task, consisting of only 5 trials each instead of hundreds. Remarkably, individuals with ASD improved their visual discrimination ability in the task substantially, demonstrating successful learning. Furthermore, individuals with ASD generalized learning to an untrained visual location, indicating a unique benefit of reactivation learning mechanisms for ASD individuals. Finally, an additional experiment showed that without memory reactivations ASD subjects did not demonstrate efficient learning and generalization patterns. Taken together, the results provide proof-of-concept evidence supporting a distinct route for efficient visual learning and generalization in ASD, which may be beneficial for skill learning in other sensory and motor domains.

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.

Stimulation of the ventral tegmental area induces visual cortical plasticity at the neuronal level

fMRI studies have shown that pairing a task-irrelevant visual feature with electrical micro-stimulation of the ventral tegmental area (VTA-EM) is sufficient to increase the sensory cortical representation of the paired feature and to improve perceptual performance. However, since fMRI provides an indirect measure of neural activity, the neural response changes underlying the fMRI activations are unknown. Here, we pair a task-irrelevant grating orientation with VTA-EM while attention is directed to a difficult orthogonal task. We examine the changes in neural response properties in macaques by recording spiking activity in the posterior inferior temporal cortex, the locus of fMRI-defined plasticity in previous studies. We observe a relative increase in mean spike rate and preference for the VTA-EM paired orientation compared to an unpaired orientation, which is unrelated to attention. These results demonstrate that VTA-EM-stimulus pairing is sufficient to induce sensory cortical plasticity at the spiking level in nonhuman primates.

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.

Spared perilesional V1 activity underlies training-induced recovery of luminance detection sensitivity in cortically-blind patients

Damage to the primary visual cortex (V1) causes homonymous visual-field loss long considered intractable. Multiple studies now show that perceptual training can restore visual functions in chronic cortically-induced blindness (CB). A popular hypothesis is that training can harness residual visual functions by recruiting intact extrageniculostriate pathways. Training may also induce plastic changes within spared regions of the damaged V1. Here, we link changes in luminance detection sensitivity with retinotopic fMRI activity before and after visual discrimination training in eleven patients with chronic, stroke-induced CB. We show that spared V1 activity representing perimetrically-blind locations prior to training predicts the amount of training-induced recovery of luminance detection sensitivity. Additionally, training results in an enlargement of population receptive fields in perilesional V1, which increases blind-field coverage and may support further recovery with subsequent training. These findings uncover fundamental changes in perilesional V1 cortex underlying training-induced restoration of conscious luminance detection sensitivity in CB.

In humans, stroke damage to V1 causes large visual field defects. Spared V1 activity prior to training predicts the amount of training-induced recovery in luminance detection sensitivity. Moreover, visual training changes population receptive field properties within residual V1 circuits.

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.

Visual association learning induces global network reorganization

It has been proposed that visual learning is accomplished not only by neural plasticity in the visual cortex, but also by complex interactions between bottom-up and top-down processes that may induce global network reorganization. Here, we applied a multivariate analysis to functional connectivity (FC) patterns across the brain to investigate how visual association learning was achieved through large-scale network reorganization. Participants were trained to associate a set of artificial line-drawing objects with English letters. After three consecutive days of training, participants underwent a functional magnetic resonance imaging scan in which they were presented with the trained stimuli, untrained stimuli, and English words. By calculating pairwise FC between 189 nodes of 10 well-established networks across the brain, we found that the visual association learning induced changes in the global FC pattern when viewing the trained stimuli, rendering it more similar to the FC pattern when viewing English words. Critically, the learning-induced global FC pattern differences were mainly driven by the FC related to the high-level networks involved in attention and cognitive control, suggesting the modification of top-down processes during learning. In sum, our study provides one of the first evidence revealing global network reorganization induced by visual learning and sheds new light on the network mechanisms of top-down influences in learning.

Motor Learning Improves the Stability of Large-Scale Brain Connectivity Pattern

Repeated practice is fundamental to the acquisition of skills, which is typically accompanied by increasing reliability of neural representations that manifested as more stable activation patterns for the trained stimuli. However, large-scale neural pattern induced by learning has been rarely studied. Here, we investigated whether global connectivity patterns became more reliable as a result of motor learning using a novel analysis of the multivariate pattern of functional connectivity (MVPC). Human participants were trained with a finger-tapping motor task for five consecutive days and went through Functional magnetic resonance imaging (fMRI) scanning before and after training. We found that motor learning increased the whole-brain MVPC stability of the primary motor cortex (M1) when participants performed the trained sequence, while no similar effects were observed for the untrained sequence. Moreover, the increase of MVPC stability correlated with participants’ improvement in behavioral performance. These findings suggested that the acquisition of motor skills was supported by the increased connectivity pattern stability between the M1 and the rest of the brain. In summary, our study not only suggests global neural pattern stabilization as a neural signature for effective learning but also advocates applying the MVPC analysis to reveal mechanisms of distributed network reorganization supporting various types of learning.

Plasticity in perception: insights from color vision deficiencies

Inherited color vision deficiencies typically result from a loss or alteration of the visual photopigments absorbing light and thus impact the very first step of seeing. There is growing interest in how subsequent steps in the visual pathway might be calibrated to compensate for the altered receptor signals, with the possibility that color coding and color percepts might be less severely impacted than the receptor differences predict. These compensatory adjustments provide important insights into general questions about sensory plasticity and the sensory and cognitive processes underlying how we experience color.

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

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

Improved fidelity of orientation perception: a learning effect dissociable from enhanced discriminability

Visual perception can be influenced by stimulus context, selective attention, and prior experience. Many previous studies have shown complex interactions among these influencing factors, but it remains unclear whether context-induced illusions could be reduced by perceptual training and whether such a change in perceptual fidelity is linked to improved perceptual discriminability. To address this question, we introduced a context-induced tilt illusion into an orientation discrimination training paradigm. This resulted in parallel and long-term improvements in the discriminability and fidelity of orientation perception. The improved discriminability was specific to the task-relevant target stimulus but nonspecific to the task-irrelevant context. By contrast, the improved perceptual fidelity was specific to the task-irrelevant contextual stimulus that induced the illusion, but not specific to the task-relevant target stimulus or task performed on one of its features. These results indicate two dissociable learning effects associated with the same training procedure. Such a dissociation was further supported by the observation that the sizes of the two learning effects were uncorrelated across the subjects. Our findings suggest two parallel learning processes: a task-dependent process giving rise to enhanced discriminability for the task-relevant stimulus attribute, and a context-dependent process leading to improved perceptual fidelity for the attended stimuli.

Fear-Related Signals in the Primary Visual Cortex

Neuronal responses in the primary visual cortex (V1) are driven by simple stimuli, but these stimulus-evoked responses can be markedly modulated by non-sensory factors, such as attention and reward [1], and shaped by perceptual training [2]. In real-life situations, neutral visual stimuli can become emotionally tagged by experience, resulting in altered perceptual abilities to detect and discriminate these stimuli [3-5]. Human imaging [4] and electroencephalography (EEG) studies [6-9] have shown that visual fear learning (the acquisition of aversive emotion associated with a visual stimulus) affects the activities in visual cortical areas as early as in V1. However, it remains elusive as to whether the fear-related activities seen in the early visual cortex have to do with feedback influences from other cortical areas; it is also unclear whether and how the response properties of V1 cells are modified during the fear learning. In the current study, we addressed these issues by recording from V1 of awake monkeys implanted with an array of microelectrodes. We found that responses of V1 neurons were rapidly modified when a given orientation of grating stimulus was repeatedly associated with an aversive stimulus. The output visual signals from V1 cells conveyed, from their response outset, fear-related signals that were specific to the fear-associated grating orientation and visual-field location. The specific fear signals were independent of neurons' orientation preferences and were present even though the fear-associated stimuli were rendered invisible. Our findings suggest a bottom-up mechanism that allows for proactive labeling of visual inputs that are predictive of imminent danger.

Analysis of Perceptual Expertise in Radiology - Current Knowledge and a New Perspective

Radiologists rely principally on visual inspection to detect, describe, and classify findings in medical images. As most interpretive errors in radiology are perceptual in nature, understanding the path to radiologic expertise during image analysis is essential to educate future generations of radiologists. We review the perceptual tasks and challenges in radiologic diagnosis, discuss models of radiologic image perception, consider the application of perceptual learning methods in medical training, and suggest a new approach to understanding perceptional expertise. Specific principled enhancements to educational practices in radiology promise to deepen perceptual expertise among radiologists with the goal of improving training and reducing medical error.

Boosting Learning Efficacy with Noninvasive Brain Stimulation in Intact and Brain-Damaged Humans

Numerous behavioral studies have shown that visual function can improve with training, although perceptual refinements generally require weeks to months of training to attain. This, along with questions about long-term retention of learning, limits practical and clinical applications of many such paradigms. Here, we show for the first time in female and male human participants that just 10 d of visual training coupled with transcranial random noise stimulation (tRNS) over visual areas causes dramatic improvements in visual motion perception. Relative to control conditions and anodal stimulation, tRNS-enhanced learning was at least twice as fast, and, crucially, it persisted for 6 months after the end of training and stimulation. Notably, tRNS also boosted learning in patients with chronic cortical blindness, leading to recovery of motion processing in the blind field after just 10 d of training, a period too short to elicit enhancements with training alone. In sum, our results reveal a remarkable enhancement of the capacity for long-lasting plastic and restorative changes when a neuromodulatory intervention is coupled with visual training.SIGNIFICANCE STATEMENT Our work demonstrates that visual training coupled with brain stimulation can dramatically reduce the training period from months to weeks, and lead to fast improvement in neurotypical subjects and chronic cortically blind patients, indicating the potential of our procedure to help restore damaged visual abilities for currently untreatable visual dysfunctions. Together, these results indicate the critical role of early visual areas in perceptual learning and reveal its capacity for long-lasting plastic changes promoted by neuromodulatory intervention.

Category-Induced Transfer of Visual Perceptual Learning

Visual perceptual learning (VPL) refers to a long-term enhancement of visual task performance as a result of visual experience [1-6]. VPL is generally specific for the trained visual feature, meaning that training on a feature leads to performance enhancement only on the feature and those in its close vicinity. In the meantime, visual perception is often categorical [7-10]. This may partially be because the ecological importance of a stimulus is usually determined by the category to which the stimulus belongs (e.g., snake, lightning, and fish) [11]. Thus, it would be advantageous to an observer if encountering or working on a feature from a category increases sensitivity to features under the same category. However, studies of VPL have used uncategorized features. Here, we found a category-induced transfer of VPL, where VPL of an orientation transferred to untrained orientations within the same category as the trained orientation, but not orientations from the different category. Furthermore, we found that, although category learning transferred to other locations in the visual field, the category-induced transfer of VPL occurred only when visual stimuli for the category learning and those for VPL training were presented at the same location. These results altogether suggest that feature specificity in VPL is greatly influenced by cognitive processing, such as categorization in a top-down fashion. In an environment where features are categorically organized, VPL may be more generalized across features under the same category. Such generalization implies that VPL is of more ecological significance than has been thought.

Perceptual learning while preparing saccades

Traditional perceptual learning protocols rely almost exclusively on long periods of uninterrupted fixation. Taking a first step towards understanding perceptual learning in natural vision, we had observers report the orientation of a briefly flashed stimulus (clockwise or counterclockwise from a reference orientation) presented strictly during saccade preparation at a location offset from the saccade target. For each observer, the saccade direction, stimulus location, and orientation remained the same throughout training. Subsequently, we assessed performance during fixation in three transfer sessions, either at the trained or at an untrained location, and either using an untrained (Experiment 1) or the trained (Experiment 2) stimulus orientation. We modeled the evolution of contrast thresholds (i.e., the stimulus contrast necessary to discriminate its orientation correctly 75% of the time) as an exponential learning curve, and quantified departures from this curve in transfer sessions using two new, complementary measures of transfer costs (i.e., performance decrements after the transition into the Transfer phase). We observed robust perceptual learning and associated transfer costs for untrained locations and orientations. We also assessed if spatial transfer costs were reduced for the remapped location of the pre-saccadic stimulus-the location the stimulus would have had (but never had) after the saccade. Although the pattern of results at that location differed somewhat from that at the control location, we found no clear evidence for perceptual learning at remapped locations. Using novel, model-based ways to assess learning and transfer costs, our results show that location and feature specificity, hallmarks of perceptual learning, subsist if the target stimulus is presented strictly during saccade preparation throughout training.

Bottom-up saliency and top-down learning in the primary visual cortex of monkeys

Early sensory cortex is better known for representing sensory inputs but less for the effect of its responses on behavior. Here we explore the behavioral correlates of neuronal responses in primary visual cortex (V1) in a task to detect a uniquely oriented bar-the orientation singleton-in a background of uniformly oriented bars. This singleton is salient or inconspicuous when the orientation contrast between the singleton and background bars is sufficiently large or small, respectively. Using implanted microelectrodes, we measured V1 activities while monkeys were trained to quickly saccade to the singleton. A neuron's responses to the singleton within its receptive field had an early and a late component, both increased with the orientation contrast. The early component started from the outset of neuronal responses; it remained unchanged before and after training on the singleton detection. The late component started ∼40 ms after the early one; it emerged and evolved with practicing the detection task. Training increased the behavioral accuracy and speed of singleton detection and increased the amount of information in the late response component about a singleton's presence or absence. Furthermore, for a given singleton, faster detection performance was associated with higher V1 responses; training increased this behavioral-neural correlate in the early V1 responses but decreased it in the late V1 responses. Therefore, V1's early responses are directly linked with behavior and represent the bottom-up saliency signals. Learning strengthens this link, likely serving as the basis for making the detection task more reflexive and less top-down driven.

Retained capacity for perceptual learning of degraded speech in primary progressive aphasia and Alzheimer's disease

Background

Processing of degraded speech is a promising model for understanding communication under challenging listening conditions, core auditory deficits and residual capacity for perceptual learning and cerebral plasticity in major dementias.

Methods

We compared the processing of sine-wave-degraded speech in 26 patients with primary progressive aphasia (non-fluent, semantic, and logopenic variants), 10 patients with typical Alzheimer’s disease and 17 healthy control subjects. Participants were required to identify sine-wave words that were more predictable (three-digit numbers) or less predictable (place names). The change in identification performance within each session indexed perceptual learning. Neuroanatomical associations of degraded speech processing were assessed using voxel-based morphometry.

Results

Patients with non-fluent and logopenic progressive aphasia and typical Alzheimer’s disease showed impaired identification of sine-wave numbers, whereas all syndromic groups showed impaired identification of sine-wave place names. A significant overall identification advantage for numbers over place names was shown by patients with typical Alzheimer’s disease, patients with semantic progressive aphasia and healthy control participants. All syndromic groups showed spontaneous perceptual learning effects for sine-wave numbers. For the combined patient cohort, grey matter correlates were identified across a distributed left hemisphere network extending beyond classical speech-processing cortices.

Conclusions

These findings demonstrate resilience of auditory perceptual learning capacity across dementia syndromes, despite variably impaired perceptual decoding of degraded speech and reduced predictive integration of semantic knowledge. This work has implications for the neurobiology of dynamic sensory processing and plasticity in neurodegenerative diseases and for development of novel biomarkers and therapeutic interventions.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0399-2) contains supplementary material, which is available to authorized users.