The time course and specificity of perceptual deterioration

Repeated within-day testing on a texture discrimination task leads to retinotopically specific decreases in performance. Although perceptual learning has been shown to be highly specific to the retinotopic location and characteristics of the trained stimulus, the specificity of perceptual deterioration has not been studied. We investigated the similarities between learning and deterioration by examining whether deterioration transfers to new distractor or target orientations or to the untrained eye. Participants performed a texture discrimination task in three one-hour sessions. We tested the specificity of deterioration in the final session by switching either the orientation of the background or the target elements by 90 degrees. We found that performance deteriorated steadily both within and across the first two sessions and was specific to the target but not the distractor orientation. In a separate experiment, we found that deterioration transferred to the untrained eye. Changes in performance were independent of reported sleepiness and awareness of stimulus changes, arguing against the possibility that perceptual deterioration is due to general fatigue. Rather, we hypothesize that perceptual deterioration may be caused by changes in the ability for attention to selectively enhance the responses of relatively low-level orientation-selective sensory neurons, possibly within the primary visual cortex. Further, the differences in specificity profiles between learning and deterioration suggest separate underlying mechanisms that occur within the same cortical area.     

Neural systems underlying learning and representation of global motion

We demonstrate performance-related changes in cortical and cerebellar activity. The largest learning-dependent changes were observed in the anterior lateral cerebellum, where the extent and intensity of activation correlated inversely with psychophysical performance. After learning had occurred (a few minutes), the cerebellar activation almost disappeared; however, it was restored when the subjects were presented with a novel, untrained direction of motion for which psychophysical performance also reverted to chance level. Similar reductions in the extent and intensity of brain activations in relation to learning occurred in the superior colliculus, anterior cingulate, and parts of the extrastriate cortex. The motion direction-sensitive middle temporal visual complex was a notable exception, where there was an expansion of the cortical territory activated by the trained stimulus. Together, these results indicate that the learning and representation of visual motion discrimination are mediated by different, but probably interacting, neuronal subsystems.     

Arc expression and neuroplasticity in primary auditory cortex during initial learning are inversely related to neural activity

Models of learning-dependent sensory cortex plasticity require local activity and reinforcement. An alternative proposes that neural activity involved in anticipation of a sensory stimulus, or the preparatory set, can direct plasticity so that changes could occur in regions of sensory cortex lacking activity. To test the necessity of target-induced activity for initial sensory learning, we trained rats to detect a low-frequency sound. After learning, Arc expression and physiologically measured neuroplasticity were strong in a high-frequency auditory cortex region with very weak target-induced activity in control animals. After 14 sessions, Arc and neuroplasticity were aligned with target-induced activity. The temporal and topographic correspondence between Arc and neuroplasticity suggests Arc may be intrinsic to the neuroplasticity underlying perceptual learning. Furthermore, not all neuroplasticity could be explained by activity-dependent models but can be explained if the neural activity involved in the preparatory set directs plasticity.     

Interocular transfer in perceptual learning of a pop-out discrimination task.

The specificity of the improvement in perceptual learning is often used to localize the neuronal changes underlying this type of adult plasticity. We investigated a visual texture discrimination task previously reported to be accomplished preattentively and for which learning-related changes were inferred to occur at a very early level of the visual processing stream. The stimulus was a matrix of lines from which a target popped out, due to an orientation difference between the three target lines and the background lines. The task was to report the global orientation of the target and was performed monocularly. The subjects' performance improved dramatically with training over the course of 2-3 weeks, after which we tested the specificity of the improvement for the eye trained. In all subjects tested, there was complete interocular transfer of the learning effect. The neuronal correlate of this learning are therefore most likely localized in a visual area where input from the two eyes has come together.     

From the Cover: Learning sculpts the spontaneous activity of the resting human brain

The brain is not a passive sensory-motor analyzer driven by environmental stimuli, but actively maintains ongoing representations that may be involved in the coding of expected sensory stimuli, prospective motor responses, and prior experience. Spontaneous cortical activity has been proposed to play an important part in maintaining these ongoing, internal representations, although its functional role is not well understood. One spontaneous signal being intensely investigated in the human brain is the interregional temporal correlation of the blood-oxygen level-dependent (BOLD) signal recorded at rest by functional MRI (functional connectivity-by-MRI, fcMRI, or BOLD connectivity). This signal is intrinsic and coherent within a number of distributed networks whose topography closely resembles that of functional networks recruited during tasks. While it is apparent that fcMRI networks reflect anatomical connectivity, it is less clear whether they have any dynamic functional importance. Here, we demonstrate that visual perceptual learning, an example of adult neural plasticity, modifies the resting covariance structure of spontaneous activity between networks engaged by the task. Specifically, after intense training on a shape-identification task constrained to one visual quadrant, resting BOLD functional connectivity and directed mutual interaction between trained visual cortex and frontal-parietal areas involved in the control of spatial attention were significantly modified. Critically, these changes correlated with the degree of perceptual learning. We conclude that functional connectivity serves a dynamic role in brain function, supporting the consolidation of previous experience.     

Direction of motion discrimination after early lesions of striate cortex (V1) of the macaque monkey

Previous studies have established that humans and monkeys with damage to striate cortex are able to detect and localize bright targets within the resultant scotoma. Electrophysiological evidence in monkeys suggests that residual vision also might include sensitivity to direction of visual motion. We tested whether macaque monkeys with longstanding lesions of striate cortex (V1), sustained in infancy, could discriminate visual stimuli on the basis of direction of motion. Three monkeys with unilateral striate cortex lesions sustained in infancy were tested 2-5 years postlesion on a direction of motion discrimination task. Each monkey was trained to make saccadic eye movements to a field of moving dots or to withhold such eye movements, depending on the direction of motion in a coherent random dot display. With smaller motion displays, monkeys were unable to detect or discriminate motion within the scotoma, although they could discriminate moving from static stimuli. Yet, each monkey was able to discriminate direction of motion when the motion stimulus was larger, but still confined to the scotoma. The results demonstrate that the recovery after infant damage to striate cortex includes some sensitivity to direction of visual motion.     

Where practice makes perfect in texture discrimination: evidence for primary visual cortex plasticity.

In terms of functional anatomy, where does learning occur when, for a basic visual discrimination task, performance improves with practice (perceptual learning)? We report remarkable long-term learning in a simple texture discrimination task where learning is specific for retinal input. This learning is (i) local (in a retinotopic sense), (ii) orientation specific but asymmetric (it is specific for background but not for target-element orientation), and (iii) strongly monocular (there is little interocular transfer of learning). Our results suggest that learning involves experience-dependent changes at a level of the visual system where monocularity and the retinotopic organization of the visual input are still retained and where different orientations are processed separately. These results can be interpreted in terms of local plasticity induced by retinal input in early visual processing in human adults, presumably at the level of orientation-gradient sensitive cells in primary visual cortex.     

Correspondence of presaccadic activity in the monkey primary visual cortex with saccadic eye movements

We continuously scan the visual world via rapid or saccadic eye movements. Such eye movements are guided by visual information, and thus the oculomotor structures that determine when and where to look need visual information to control the eye movements. To know whether visual areas contain activity that may contribute to the control of eye movements, we recorded neural responses in the visual cortex of monkeys engaged in a delayed figure-ground detection task and analyzed the activity during the period of oculomotor preparation. We show that approximately 100 ms before the onset of visually and memory-guided saccades neural activity in V1 becomes stronger where the strongest presaccadic responses are found at the location of the saccade target. In addition, in memory-guided saccades the strength of presaccadic activity shows a correlation with the onset of the saccade. These findings indicate that the primary visual cortex contains saccade-related responses and participates in visually guided oculomotor behavior.     

Individual variability in functional connectivity predicts performance of a perceptual task

People differ in their ability to perform novel perceptual tasks, both during initial exposure and in the rate of improvement with practice. It is also known that regions of the brain recruited by particular tasks change their activity during learning. Here we investigate neural signals predictive of individual variability in performance. We used resting-state functional MRI to assess functional connectivity before training on a novel visual discrimination task. Subsequent task performance was related to functional connectivity measures within portions of visual cortex and between visual cortex and prefrontal association areas. Our results indicate that individual differences in performing novel perceptual tasks can be related to individual differences in spontaneous cortical activity.     

Attentional control of early perceptual learning.

The performance of adult humans in simple visual tasks improves dramatically with practice. This improvement is highly specific to basic attributes of the trained stimulus, suggesting that the underlying changes occur at low-level processing stages in the brain, where different orientations and spatial frequencies are handled by separate channels. We asked whether these practice effects are determined solely by activity in stimulus-driven mechanisms or whether high-level attentional mechanisms, which are linked to the perceptual task, might control the learning process. We found that practicing one task did not improve performance in an alternative task, even though both tasks used exactly the same visual stimuli but depended on different stimulus attributes (either orientation of local elements or global shape). Moreover, even when the experiment was designed so that the same responses were associated with the same stimuli (although subjects were instructed to attend to the attribute underlying one task), learning did not transfer from one task to the other. These results suggest that specific high-level attentional mechanisms, controlling changes at early visual processing levels, are essential in perceptual learning.     

Perceptual learning modifies the functional specializations of visual cortical areas

Training can improve performance of perceptual tasks. This phenomenon, known as perceptual learning, is strongest for the trained task and stimulus, leading to a widely accepted assumption that the associated neuronal plasticity is restricted to brain circuits that mediate performance of the trained task. Nevertheless, learning does transfer to other tasks and stimuli, implying the presence of more widespread plasticity. Here, we trained human subjects to discriminate the direction of coherent motion stimuli. The behavioral learning effect substantially transferred to noisy motion stimuli. We used transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms underlying the transfer of learning. The TMS experiment revealed dissociable, causal contributions of V3A (one of the visual areas in the extrastriate visual cortex) and MT+ (middle temporal/medial superior temporal cortex) to coherent and noisy motion processing. Surprisingly, the contribution of MT+ to noisy motion processing was replaced by V3A after perceptual training. The fMRI experiment complemented and corroborated the TMS finding. Multivariate pattern analysis showed that, before training, among visual cortical areas, coherent and noisy motion was decoded most accurately in V3A and MT+, respectively. After training, both kinds of motion were decoded most accurately in V3A. Our findings demonstrate that the effects of perceptual learning extend far beyond the retuning of specific neural populations for the trained stimuli. Learning could dramatically modify the inherent functional specializations of visual cortical areas and dynamically reweight their contributions to perceptual decisions based on their representational qualities. These neural changes might serve as the neural substrate for the transfer of perceptual learning.Perceptual learning, an enduring improvement in the performance of a sensory task resulting from practice, has been widely used as a model to study experience-dependent cortical plasticity in adults (1). However, at present, there is no consensus on the nature of the neural mechanisms underlying this type of learning. Perceptual learning is often specific to the physical properties of the trained stimulus, leading to the hypothesis that the underlying neural changes occur in sensory coding areas (2). Electrophysiological and brain imaging studies have shown that visual perceptual learning alters neural response properties in primary visual cortex (3, 4) and extrastriate areas including V4 (5) and MT+ (middle temporal/medial superior temporal cortex) (6), as well as object selective areas in the inferior temporal cortex (7, 8). An alternative hypothesis proposes that perceptual learning is mediated by downstream cortical areas that are responsible for attentional allocation and/or decision-making, such as the intraparietal sulcus (IPS) and anterior cingulate cortex (9, 10).Learning is most beneficial when it enables generalized improvements in performance with other tasks and stimuli. Although specificity is one of the hallmarks of perceptual learning, transfer of learning to untrained stimuli and tasks does occur, to a greater or lesser extent (2). For example, visual perceptual learning of an orientation task involving clear displays (a Gabor patch) also improved performance of an orientation task involving noisy displays (a Gabor patch embedded in a random-noise mask) (11). Transfer of perceptual learning to untrained tasks indicates that neuronal plasticity accompanying perceptual learning is not restricted to brain circuits that mediate performance of the trained task, and perceptual training may lead to more widespread and profound plasticity than we previously believed. However, this issue has rarely been investigated. Almost all studies concerned with the neural basis of perceptual learning have used the same task and stimuli for training and testing. One exception is a study conducted by Chowdhury and DeAngelis (12). It is known that learning of fine depth discrimination in a clear display can transfer to coarse depth discrimination in a noisy display (13). Chowdhury and DeAngelis (12) examined the effect of fine depth discrimination training on the causal contribution of macaque MT to coarse depth discrimination. MT activity was essential for coarse depth discrimination before training. However, after training, inactivation of MT had no effect on coarse depth discrimination. This result is striking, but the neural substrate of learning transfer was not revealed.Here, we performed a transcranial magnetic stimulation (TMS) experiment and a functional magnetic resonance imaging (fMRI) experiment, seeking to identify the neural mechanisms involved in the transfer of learning from coherent motion (i.e., a motion stimulus containing 100% signal) to a task involving noisy motion (i.e., a motion stimulus containing only 40% signal and 60% noise:40% coherent motion). By testing with stimuli other than the trained stimulus, we uncovered much more profound functional changes in the brain than expected. Before training, V3A and MT+ were the dominant areas for the processing of coherent and noisy motion, respectively. Learning modified their inherent functional specializations, whereby V3A superseded MT+ as the dominant area for the processing of noisy motion after training. This change in functional specialization involving key areas within the cortical motion processing network served as the neural substrate for the transfer of motion perceptual learning.     

Neuronal representations of stimulus associations develop in the temporal lobe during learning

Visual stimuli that are frequently seen together become associated in long-term memory, such that the sight of one stimulus readily brings to mind the thought or image of the other. It has been hypothesized that acquisition of such long-term associative memories proceeds via the strengthening of connections between neurons representing the associated stimuli, such that a neuron initially responding only to one stimulus of an associated pair eventually comes to respond to both. Consistent with this hypothesis, studies have demonstrated that individual neurons in the primate inferior temporal cortex tend to exhibit similar responses to pairs of visual stimuli that have become behaviorally associated. In the present study, we investigated the role of these areas in the formation of conditional visual associations by monitoring the responses of individual neurons during the learning of new stimulus pairs. We found that many neurons in both area TE and perirhinal cortex came to elicit more similar neuronal responses to paired stimuli as learning proceeded. Moreover, these neuronal response changes were learning-dependent and proceeded with an average time course that paralleled learning. This experience-dependent plasticity of sensory representations in the cerebral cortex may underlie the learning of associations between objects.     

Spatial attention affects brain activity in human primary visual cortex

Functional MRI was used to test whether instructing subjects to attend to one or another location in a visual scene would affect neural activity in human primary visual cortex. Stimuli were moving gratings restricted to a pair of peripheral, circular apertures, positioned to the right and to the left of a central fixation point. Subjects were trained to perform a motion discrimination task, attending (without moving their eyes) at any moment to one of the two stimulus apertures. Functional MRI responses were recorded while subjects were cued to alternate their attention between the two apertures. Primary visual cortex responses in each hemisphere modulated with the alternation of the cue; responses were greater when the subject attended to the stimuli in the contralateral hemifield. The attentional modulation of the brain activity was about 25% of that evoked by alternating the stimulus with a uniform field.     

Increase of the RNA-binding protein HuD and posttranscriptional up-regulation of the GAP-43 gene during spatial memory

Neuronal ELAV-like proteins (HuB, HuC, and HuD) are highly conserved RNA-binding proteins able to selectively associate with the 3' UTR of a subset of target mRNAs and increase their cytoplasmic stability and rate of translation. We previously demonstrated the involvement of these proteins in learning, reporting that they undergo a sustained up-regulation in the hippocampus of mice trained in a spatial discrimination task. Here, we extend this finding, showing that a similar up-regulation occurs in the hippocampus of rats trained in another spatial learning paradigm, the Morris water maze. HuD, a strictly neuron-specific ELAV-like protein, is shown to increase after learning, with a preferential binding to the cytoskeletal fraction. HuD up-regulation is associated with an enhancement of GAP-43 mRNA and protein levels, with an apparently increased HuD colocalization with the GAP-43 mRNA and an increased association of neuronal ELAV-like proteins with the GAP-43 mRNA. These learning-dependent biochemical events appear to be spatiotemporally controlled, because they do not occur in another brain region involved in learning, the retrosplenial cortex, and at the level of protein expression they show extinction 1 month after training despite memory retention. By contrast, HuD mRNA levels still remain increased after 1 month in the CA1 region. This persistence may have implications for long-term memory recall.     

INAUGURAL ARTICLE by a Recently Elected Academy Member:A monocular contribution to stimulus rivalry

When corresponding areas of the two eyes view dissimilar images, stable perception gives way to visual competition wherein perceptual awareness alternates between those images. Moreover, a given image can remain visually dominant for several seconds at a time even when the competing images are swapped between the eyes multiple times each second. This perceptual stability across eye swaps has led to the widespread belief that this unique form of visual competition, dubbed stimulus rivalry, is governed by eye-independent neural processes at a purely binocular stage of cortical processing. We tested this idea by investigating the influence of stimulus rivalry on the buildup of the threshold elevation aftereffect, a form of contrast adaptation thought to transpire at early cortical stages that include eye-specific neural activity. Weaker threshold elevation aftereffects were observed when the adapting image was engaged in stimulus rivalry than when it was not, indicating diminished buildup of adaptation during stimulus-rivalry suppression. We then confirmed that this reduction occurred, in part, at eye-specific neural stages by showing that suppression of an image at a given moment specifically diminished adaptation associated with the eye viewing the image at that moment. Considered together, these results imply that eye-specific neural events at early cortical processing stages contribute to stimulus rivalry. We have developed a computational model of stimulus rivalry that successfully implements this idea.     

Neural plasticity in adults with amblyopia.

Amblyopia is a neuronal abnormality of vision that is often considered irreversible in adults. We found strong and significant improvement of Vernier acuity in human adults with naturally occurring amblyopia following practice. Learning was strongest at the trained orientation and did not transfer to an untrained task (detection), but it did transfer partially to the untrained eye (primarily at the trained orientation). We conclude that this perceptual learning reflects alterations in early neural processes that are localized beyond the site of convergence of the two eyes. Our results suggest a significant degree of plasticity in the visual system of adults with amblyopia.     

Improving vision in adult amblyopia by perceptual learning

Practicing certain visual tasks leads, as a result of a process termed "perceptual learning," to a significant improvement in performance. Learning is specific for basic stimulus features such as local orientation, retinal location, and eye of presentation, suggesting modification of neuronal processes at the primary visual cortex in adults. It is not known, however, whether such low-level learning affects higher-level visual tasks such as recognition. By systematic low-level training of an adult visual system malfunctioning as a result of abnormal development (leading to amblyopia) of the primary visual cortex during the "critical period," we show here that induction of low-level changes might yield significant perceptual benefits that transfer to higher visual tasks. The training procedure resulted in a 2-fold improvement in contrast sensitivity and in letter-recognition tasks. These findings demonstrate that perceptual learning can improve basic representations within an adult visual system that did not develop during the critical period.     

Correlates of transsaccadic integration in the primary visual cortex of the monkey

We make several eye movements per second when we explore a visual scene. Each eye movement sweeps the scene's projection across the retina and changes its representation in retinotopic areas of the visual cortex, but we nevertheless perceive a stable world. Here we investigate the neuronal correlates of visual stability in the primary visual cortex. Monkeys were trained to make two saccades along a single curve and to ignore another, distracting curve. Attention enhanced neuronal responses to the entire relevant curve before the first saccade. This response enhancement was rapidly reestablished after the saccade, although the image was shifted across the primary visual cortex. We argue that this fast postsaccadic restoration of the attentional response enhancement contributes to the stability of vision across eye movements, and reduces the impact of saccades on visual cognition.     

A neural system for human visual working memory

Working memory is the process of actively maintaining a representation of information for a brief period of time so that it is available for use. In monkeys, visual working memory involves the concerted activity of a distributed neural system, including posterior areas in visual cortex and anterior areas in prefrontal cortex. Within visual cortex, ventral stream areas are selectively involved in object vision, whereas dorsal stream areas are selectively involved in spatial vision. This domain specificity appears to extend forward into prefrontal cortex, with ventrolateral areas involved mainly in working memory for objects and dorsolateral areas involved mainly in working memory for spatial locations. The organization of this distributed neural system for working memory in monkeys appears to be conserved in humans, though some differences between the two species exist. In humans, as compared with monkeys, areas specialized for object vision in the ventral stream have a more inferior location in temporal cortex, whereas areas specialized for spatial vision in the dorsal stream have a more superior location in parietal cortex. Displacement of both sets of visual areas away from the posterior perisylvian cortex may be related to the emergence of language over the course of brain evolution. Whereas areas specialized for object working memory in humans and monkeys are similarly located in ventrolateral prefrontal cortex, those specialized for spatial working memory occupy a more superior and posterior location within dorsal prefrontal cortex in humans than in monkeys. As in posterior cortex, this displacement in frontal cortex also may be related to the emergence of new areas to serve distinctively human cognitive abilities.     

A more biologically plausible learning rule for neural networks.

Many recent studies have used artificial neural network algorithms to model how the brain might process information. However, back-propagation learning, the method that is generally used to train these networks, is distinctly "unbiological." We describe here a more biologically plausible learning rule, using reinforcement learning, which we have applied to the problem of how area 7a in the posterior parietal cortex of monkeys might represent visual space in head-centered coordinates. The network behaves similarly to networks trained by using back-propagation and to neurons recorded in area 7a. These results show that a neural network does not require back propagation to acquire biologically interesting properties.