The neural mechanisms underlying behavioral improvement in the detection or discrimination of visual stimuli following learning are still ill understood. Studies in nonhuman primates have shown relatively small and, across studies, variable effects of fine discrimination learning in primary visual cortex when tested outside the context of the learned task. At later stages, such as extrastriate area V4, extensive practice in fine discrimination produces more consistent effects upon responses and neural tuning. In V1 (...) and V4, the effects of learning were most prominent in those neurons that can contribute the most reliable information about the trained stimuli. I suggest that, depending on the particulars of the task demands, neurons at various stages of stimulus and task processing can change their tuning and responses, so that execution of the task will produce a higher frequency of reward. I speculate that the sort of changes that will occur depend on the task and on stimulus analysis require- ments, and they may vary from changes in bottom-up stimulus processing ⁄ tuning within early visual areas or more efficient readout of early visual areas to top-down driven changes in response proper- ties of these areas. (shrink)

Several authors have characterized a striking phenomenon of perceptual learning in visual discrimination tasks. This learning process is selective for the stimulus characteristics and location in the visual field. Since the human visual system exploits symmetry for object recognition we were interested in exploring how it learns to use preattentive symmetry cues for discriminating simple, meaningless, forms. In this study, similar to previous studies of perceptual learning, we asked whether the effects of practice (...) acquired in the discrimination of pairs of shape with a specific orientation of the symmetry axis would transfer to the discrimination of shapes with different orientation of symmetry axis, or to shapes presented in different areas of the visual field. We found that there was no learning transfer between forms with very different axes of symmetry (90° apart). Interestingly, however, we found a transfer of learning effect to horizontally oriented symmetry axis from a condition with an axis of symmetry differing by 45°. Also it appears that some subjects took a longer time to learn than the typical fast learning paradigm would predict. Data showed that when observers practice discrimination of meaningless symmetric forms, consistent improvement in the performance occurs. This improvement is lasting over days, and it tends to be specific for the area of the visual field trained. We will discuss results from some of the observers whose learning was not fast, but who actually improved with more practice and with large time intervals (1 day) between training sessions. (shrink)

Sequence learning is fundamental to a wide range of cognitive functions. Explaining how sequences—and the relations between the elements they comprise—are learned is a fundamental challenge to cognitive science. However, although hundreds of articles addressing this question are published each year, the actual learning mechanisms involved in the learning of sequences are rarely investigated. We present three experiments that seek to examine these mechanisms during a typing task. Experiments 1 and 2 tested learning during typing single (...) letters on each trial. Experiment 3 tested for “chunking” of these letters into “words.” The results of these experiments were used to examine the mechanisms that could best account for them, with a focus on two particular proposals: statistical transitional probability learning and discriminative error-driven learning. Experiments 1 and 2 showed that error-driven learning was a better predictor of response latencies than either n-gram frequencies or transitional probabilities. No evidence for chunking was found in Experiment 3, probably due to interspersing visual cues with the motor response. In addition, learning occurred across a greater distance in Experiment 1 than Experiment 2, suggesting that the greater predictability that comes with increased structure leads to greater learnability. These results shed new light on the mechanism responsible for sequence learning. Despite the widely held assumption that transitional probability learning is essential to this process, the present results suggest instead that the sequences are learned through a process of discriminative learning, involving prediction and feedback from prediction error. (shrink)

Zero-shot learning is dedicated to solving the classification problem of unseen categories, while generalized zero-shot learning aims to classify the samples selected from both seen classes and unseen classes, in which “seen” and “unseen” classes indicate whether they can be used in the training process, and if so, they indicate seen classes, and vice versa. Nowadays, with the promotion of deep learning technology, the performance of zero-shot learning has been greatly improved. Generalized zero-shot learning is (...) a challenging topic that has promising prospects in many realistic scenarios. Although the zero-shot learning task has made gratifying progress, there is still a strong deviation between seen classes and unseen classes in the existing methods. Recent methods focus on learning a unified semantic-aligned visual representation to transfer knowledge between two domains, while ignoring the intrinsic characteristics of visual features which are discriminative enough to be classified by itself. To solve the above problems, we propose a novel model that uses the discriminative information of visual features to optimize the generative module, in which the generative module is a dual generation network framework composed of conditional VAE and improved WGAN. Specifically, the model uses the discrimination information of visual features, according to the relevant semantic embedding, synthesizes the visual features of unseen categories by using the learned generator, and then trains the final softmax classifier by using the generated visual features, thus realizing the recognition of unseen categories. In addition, this paper also analyzes the effect of the additional classifiers with different structures on the transmission of discriminative information. We have conducted a lot of experiments on six commonly used benchmark datasets. The experimental results show that our model outperforms several state-of-the-art methods for both traditional as well as generalized zero-shot learning. (shrink)

A number of recent studies have documented rapid changes in behavioural sensory acuity induced by aversive learning in the olfactory and auditory modalities. The effect of aversive learning on the discrimination of low-level features in the visual system of humans remains unclear. Here, we used a psychophysical staircase procedure to estimate discrimination thresholds for oriented grating stimuli, before and after differential aversive learning. We discovered that when a target grating orientation was conditioned with an (...) aversive loud noise, it subsequently led to an improvement of discrimination acuity in nearly all subjects. However, no such change was observed in a control group conditioned to an orientation shifted by ±90° from the target. Our findings cannot be explained by contextual learning or sensitisation factors. The results converge with those reported in the olfactory modality and provide further evidence that early sensory systems can be rapidly modified by recently experienced reinforcement histories. (shrink)

Japanese eels ( Anguilla japonica ) were trained on a spatial-learning paradigm in a pool placed in an experimental room where several extra-maze cues were present. Four tubes were placed in the pool, of which one was open and could be entered by the eels. The open tube was placed at a fixed position in the pool and contained a triangular block that served as an intra-maze cue. The eels learned to identify the open tube, and their performance was (...) maintained when the pool was rotated. However, they were unable to maintain their performance in a dark room, which suggests that spatial learning is based on visual cues. To determine the influence of the extra- and intra-maze cues, the tube with the triangle was moved to a new position and another open tube was kept in its place. The eels chose either the tube at the original position or the tube with the triangle at its new position, suggesting that spatial discrimination may be based on either extra- or intra-maze cues. We thus conclude that the eels employed an adjunctive strategy of multiple cues. In the next experiment, the eels were trained to visually discriminate the position of the stimulus (triangle), which changed in every trial. After the training, the eels were submitted to a test in which, in addition to the triangular pattern, a rectangular pattern was introduced. The eels discriminated between the tubes with the triangular and rectangular patterns, suggesting that they had the ability to discriminate visual patterns. (shrink)

Whether pattern-parsing mechanisms are specific to language or apply across multiple cognitive domains remains unresolved. Formal language theory provides a mathematical framework for classifying pattern-generating rule sets (or “grammars”) according to complexity. This framework applies to patterns at any level of complexity, stretching from simple sequences, to highly complex tree-like or net-like structures, to any Turing-computable set of strings. Here, we explored human pattern-processing capabilities in the visual domain by generating abstract visual sequences made up of abstract tiles (...) differing in form and color. We constructed different sets of sequences, using artificial “grammars” (rule sets) at three key complexity levels. Because human linguistic syntax is classed as “mildly context-sensitive,” we specifically included a visual grammar at this complexity level. Acquisition of these three grammars was tested in an artificial grammar-learning paradigm: after exposure to a set of well-formed strings, participants were asked to discriminate novel grammatical patterns from non-grammatical patterns. Participants successfully acquired all three grammars after only minutes of exposure, correctly generalizing to novel stimuli and to novel stimulus lengths. A Bayesian analysis excluded multiple alternative hypotheses and shows that the success in rule acquisition applies both at the group level and for most participants analyzed individually. These experimental results demonstrate rapid pattern learning for abstract visual patterns, extending to the mildly context-sensitive level characterizing language. We suggest that a formal equivalence of processing at the mildly context sensitive level in the visual and linguistic domains implies that cognitive mechanisms with the computational power to process linguistic syntax are not specific to the domain of language, but extend to abstract visual patterns with no meaning. (shrink)

Perceptual learning involves an improvement in perceptual judgment with practice, which is often specific to stimulus or task factors. Perceptual learning has been shown on a range of visual tasks but very little research has explored chromatic perceptual learning. Here, we use two low level perceptual threshold tasks and a supra-threshold target detection task to assess chromatic perceptual learning and category effects. Experiment 1 investigates whether chromatic thresholds reduce as a result of training and at (...) what level of analysis learning effects occur. Experiment 2 explores the effect of category training on chromatic thresholds, whether training of this nature is category specific and whether it can induce categorical responding. Experiment 3 investigates the effect of category training on a higher level, lateralized target detection task, previously found to be sensitive to category effects. The findings indicate that performance on a perceptual threshold task improves following training but improvements do not transfer across retinal location or hue. Therefore, chromatic perceptual learning is category specific and can occur at relatively early stages of visual analysis. Additionally, category training does not induce category effects on a low level perceptual threshold task, as indicated by comparable discrimination thresholds at the newly learned hue boundary and adjacent test points. However, category training does induce category effects on a supra-threshold target detection task. Whilst chromatic perceptual learning is possible, learnt category effects appear to be a product of left hemisphere processing, and may require the input of higher level linguistic coding processes in order to manifest. (shrink)

Performance in perceptual tasks often improves with practice. This effect is known as ‘perceptual learning,’ and it has been the source of a great deal of interest and debate over the course of the last century. Here, we consider the effects of perceptual learning within the context of signal detection theory. According to signal detection theory, the improvements that take place with perceptual learning can be due to increases in internal signal strength or decreases in internal noise. (...) We used a combination of psychophysical techniques (external noise masking and double‐pass response consistency) that involve corrupting stimuli with externally added noise to discriminate between the effects of changes in signal and noise as observers learned to identify sets of unfamiliar visual patterns. Although practice reduced thresholds by as much as a factor of 14, internal noise remained virtually fixed throughout training, indicating learning served to predominantly increase the strength of the internal signal. We further examined the specific nature of the changes that took place in signal strength by correlating the externally added noise with observer's decisions across trials (response classification). This technique allowed us to visualize some of the changes that took place in the linear templates used by the observers as learning occurred, as well as test the predictions of a linear template‐matching model. Taken together, the results of our experiments offer important new theoretical constraints on models of perceptual learning. (shrink)

PurposeIf an individual has been blind since birth due to a treatable eye condition, ocular treatment is urgent. Even a brief period of visual deprivation can alter the development of the visual system. The goal of our structured scoping review was to understand how we might better support children with delayed access to ocular treatment for blinding conditions.MethodWe searched MEDLINE, Embase and Global Health for peer-reviewed publications that described the impact of early and extended bilateral visual deprivation.ResultsOf (...) 551 reports independently screened by two authors, 42 studies met our inclusion criteria. Synthesizing extracted data revealed several trends. The data suggests persistent deficits in visual acuity, contrast sensitivity, global motion, and visual-motor integration, and suspected concerns for understanding complex objects and faces. There is evidence for resilience in color perception, understanding of simple shapes, discriminating between a face and non-face, and the perception of biological motion. There is currently insufficient data about specific habilitation strategies to update low vision services, but there are several insights to guide future research in this domain.ConclusionThis summary will help guide the research and services provision to help children learn to see after early and extended blindness. (shrink)

[opening paragraph]: The authors are to be congratulated for this daring and imaginative attempt to discuss art and aesthetic experience in neurological terms. The core of the argument is the relevance of the peak shift effect to our understanding of aesthetics. The application of this well-known principle of animal discrimination learning certainly does seem plausible and appropriate in the context.

Given that domestication provided animals with more stable environmental conditions, artificial selection by humans has likely affected animals' ability to learn novel contingencies and their ability to adapt to changing environments. In addition, the selection for specific traits in domestic animals might have an additional impact on subjects' behavioural flexibility, but also their general learning performance, due to a re-allocation of resources towards parameters of productivity. To test whether animals bred for high productivity would experience a shift towards lower (...) learning performance, we compared the performance of dwarf goats and dairy goats in a visual discrimination learning and reversal learning task. Goats were tested individually in a test compartment and were rewarded by choosing either a white or a black cup presented by the experimenter on a sliding board behind a crate. Once they reached a designated learning criterion in the initial learning task, they were transferred to the reversal learning task. To increase the heterogeneity of our test sample, data was collected by two experimenters at two research stations following a similar protocol. Goats of both selection lines did not differ in the initial discrimination learning task in contrast to the subsequent reversal learning task. Dairy goats reached the learning criterion slower compared to dwarf goats. Our results may indicate that the selection for milk production might have affected behavioural flexibility in goats. These differences in adapting to changing environmental stimuli might have an impact on animal welfare e.g., when subjects have to adapt to new environments or changes in housing and management routines. (shrink)

Alcohol use disorder is a burden to society creating social and health problems. Detection of AUD and its effects on the brain are difficult to assess. This problem is enhanced by the comorbid use of other substances such as nicotine that has been present in previous studies. Recent machine learning algorithms have raised the attention of researchers as a useful tool in studying and detecting AUD. This work uses AUD and controls samples free of any other substance use to (...) assess the performance of a set of commonly used machine learning classifiers detecting AUD from resting state functional network connectivity derived from independent component analysis. The cohort used included 51 alcohol dependent subjects and 51 control subjects. Despite alcohol, none of the 102 subjects reported use of nicotine, cannabis or any other dependence or habit formation substance. Classification features consisted of whole brain rsFNC estimates undergoing a feature selection process using a random forest approach. Features were then fed to 10 different machine learning classifiers to be evaluated based on their classification performance. A neural network classifier showed the highest performance with an area under the curve of 0.79. Other good performers with similar AUC scores were logistic regression, nearest neighbor, and support vector machine classifiers. The worst results were obtained with Gaussian process and quadratic discriminant analysis. The feature selection outcome pointed to functional connections between visual, sensorimotor, executive control, reward, and salience networks as the most relevant for classification. We conclude that AUD can be identified using machine learning classifiers in the absence of nicotine comorbidity. (shrink)

Perception of music and speech is based on similar auditory skills, and it is often suggested that those with enhanced music perception skills may perceive and learn novel words more easily. The current study tested whether music perception abilities are associated with novel word learning in an ambiguous learning scenario. Using a cross-situational word learning (CSWL) task, nonmusician adults were exposed to word-object pairings between eight novel words and visual referents. Novel words were either non-minimal pairs (...) differing in all sounds or minimal pairs differing in their initial consonant or vowel. In order to be successful in this task, learners need to be able to correctly encode the phonological details of the novel words and have sufficient auditory working memory to remember the correct word-object pairings. Using the Mistuning Perception Test (MPT) and the Melodic Discrimination Test (MDT), we measured learners’ pitch perception and auditory working memory. We predicted that those with higher MPT and MDT values would perform better in the CSWL task and in particular for novel words with high phonological overlap (i.e., minimal pairs). We found that higher musical perception skills led to higher accuracy for non-minimal pairs and minimal pairs differing in their initial consonant. Interestingly, this was not the case for vowel minimal pairs. We discuss the results in relation to theories of second language word learning such as the Second Language Perception model (L2LP). (shrink)