José E. Náñez

Perceptual learning without perception

The brain is able to adapt rapidly and continually to the surrounding environment, becoming increasingly sensitive to important and frequently encountered stimuli. It is often claimed that this adaptive learning is highly task-specific, that is, we become more sensitive to the critical signals in the tasks we attend to. Here, we show a new type of perceptual learning, which occurs without attention, without awareness and without any task relevance. Subjects were repeatedly presented with a background motion signal so weak that its direction was not visible; the invisible motion was an irrelevant background to the central task that engaged the subjects attention. Despite being below the threshold of visibility and being irrelevant to the central task, the repetitive exposure improved performance specifically for the direction of the exposed motion when tested in a subsequent suprathreshold test. These results suggest that a frequently presented feature sensitizes the visual system merely owing to its frequency, not its relevance or salience.

Advances in visual perceptual learning and plasticity

Visual perceptual learning (VPL) is defined as a long-term improvement in performance on a visual task. In recent years, the idea that conscious effort is necessary for VPL to occur has been challenged by research suggesting the involvement of more implicit processing mechanisms, such as reinforcement-driven processing and consolidation. In addition, we have learnt much about the neural substrates of VPL and it has become evident that changes in visual areas and regions beyond the visual cortex can take place during VPL.

Location-Specific Cortical Activation Changes during Sleep after Training for Perceptual Learning

Visual perceptual learning is defined as performance enhancement on a sensory task and is distinguished from other types of learning and memory in that it is highly specific for location of the trained stimulus. The location specificity has been shown to be paralleled by enhancement in functional magnetic resonance imaging (fMRI) signal in the trained region of V1 after visual training. Although recently the role of sleep in strengthening visual perceptual learning has attracted much attention, its underlying neural mechanism has yet to be clarified. Here, for the first time, fMRI measurement of human V1 activation was conducted concurrently with a polysomnogram during sleep with and without preceding training for visual perceptual learning. As a result of predetermined region-of-interest analysis of V1, activation enhancement during non-rapid-eye-movement sleep after training was observed specifically in the trained region of V1. Furthermore, improvement of task performance measured subsequently to the post-training sleep session was significantly correlated with the amount of the trained-region-specific fMRI activation in V1 during sleep. These results suggest that as far as V1 is concerned, only the trained region is involved in improving task performance after sleep.

Young infant's perception of object unity in two-dimensional displays

Two-dimensional displays were used to investigate the perception of object unity in 48 2-month-old and 48 4-month-old infants. The infants were habituated to a computer-generated display depicting a rod in motion behind a box. Posthabituation test trials consisted of two rod pieces (broken rod) and a complete rod, presented three times each in alternation. The 4-month-olds looked longer at the broken rod than at the complete rod, suggesting that the hidden unity of the rod behind the box was inferred. This finding replicates results with real-object displays and indicates that computer-generated displays may be successfully employed to study questions of object unity in infants. The 2-month-olds looked equally at both test displays. Two months of age may represent a transitional period, from responding to what is directly visible in a visual display to inferring the existence of the occluded portions of objects. Alternatively, infants at this young age may not be sensitive to the visual information that specifies object unity in the displays.

A small number of abnormal brain connections predicts adult autism spectrum disorder

Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no classifiers have been strictly validated for independent cohorts. Here we overcome these difficulties by developing a novel machine-learning algorithm that identifies a small number of FCs that separates ASD versus TD. The classifier achieves high accuracy for a Japanese discovery cohort and demonstrates a remarkable degree of generalization for two independent validation cohorts in the USA and Japan. The developed ASD classifier does not distinguish individuals with major depressive disorder and attention-deficit hyperactivity disorder from their controls but moderately distinguishes patients with schizophrenia from their controls. The results leave open the viable possibility of exploring neuroimaging-based dimensions quantifying the multiple-disorder spectrum.

Two cases requiring external reinforcement in perceptual learning

The role of external reinforcement is an issue of much debate and uncertainty in perceptual learning research. Although it is commonly acknowledged that external reinforcement, such as performance feedback, can aid in perceptual learning (M. H. Herzog & M. Fahle, 1997), there are many examples in which it is not required (K. Ball & R. Sekuler, 1987; M. Fahle, S. Edelman, & T. Poggio, 1995; A. Karni & D. Sagi, 1991; S. P. McKee & G. Westheimer, 1978; L. P. Shiu & H. Pashler, 1992). Additionally, learning without external reinforcement can occur even for stimuli that are irrelevant to the subjects task (A. R. Seitz & T. Watanabe, 2003). It has been thus hypothesized that internal reinforcement can serve a similar role as external reinforcement in learning (M. H. Herzog & M. Fahle, 1998; A. Seitz & T. Watanabe, 2005). This idea suggests that perceptual learning should occur in the absence of external reinforcement provided that easy exemplars are utilized as a basis for the subject to generate internal reinforcement. Here, we report results from two studies that show that this is not always the case. In the first study, subjects participated in two sessions of a motion direction discrimination task with low-contrast dots moving in directions separated by 90 degrees. In the second study, subjects participated in 12 orientation-discrimination sessions using oriented bars (oriented either 70 degrees or 110 degrees) that were masked by spatial noise. Trials of different signal levels (yielding psychometric functions ranging from chance to ceiling) were randomly interleaved. In both studies, subjects experiencing external reinforcement showed significant learning, whereas subjects receiving no external reinforcement failed to show learning. We conclude that while internal reinforcement is an important learning signal, the presence of easy exemplars is not sufficient to generate reinforcement signals.

Perceptual learning of motion leads to faster flicker perception.

Critical flicker fusion thresholds (CFFT) describe when quick amplitude modulations of a light source become undetectable as the frequency of the modulation increases. The threshold at which CFF occurs has been shown to remain constant under repeated testing. Additionally, CFF thresholds are correlated with various measures of intelligence, and have been regarded by clinicians as a general measure of cortical processing capacity. For these reasons, CFF is used as a cognitive indicator in drug studies, as a measure of fatigue, and has been suggested as a diagnostic measure for various brain diseases. Here we report that CFFT increases dramatically in subjects who are trained with a motion-direction learning procedure. Control tasks demonstrate that CFFT changes are tightly coupled with improvements in discriminating the direction of motion stimuli, and are likely related to plasticity in low-level visual areas that are specialized to process motion signals. This plasticity is long-lasting and is retained for at least one year after training. Combined, these results show that CFFT relates to a specialized sensory process and bring into question that CFFT is a measure of high-level, or general, processes.

Decoding reveals plasticity in V3A as a result of motion perceptual learning.

Visual perceptual learning (VPL) is defined as visual performance improvement after visual experiences. VPL is often highly specific for a visual feature presented during training. Such specificity is observed in behavioral tuning function changes with the highest improvement centered on the trained feature and was originally thought to be evidence for changes in the early visual system associated with VPL. However, results of neurophysiological studies have been highly controversial concerning whether the plasticity underlying VPL occurs within the visual cortex. The controversy may be partially due to the lack of observation of neural tuning function changes in multiple visual areas in association with VPL. Here using human subjects we systematically compared behavioral tuning function changes after global motion detection training with decoded tuning function changes for 8 visual areas using pattern classification analysis on functional magnetic resonance imaging (fMRI) signals. We found that the behavioral tuning function changes were extremely highly correlated to decoded tuning function changes only in V3A, which is known to be highly responsive to global motion with human subjects. We conclude that VPL of a global motion detection task involves plasticity in a specific visual cortical area.

Enhanced Spontaneous Oscillations in the Supplementary Motor Area Are Associated with Sleep-Dependent Offline Learning of Finger-Tapping Motor-Sequence Task

Sleep is beneficial for various types of learning and memory, including a finger-tapping motor-sequence task. However, methodological issues hinder clarification of the crucial cortical regions for sleep-dependent consolidation in motor-sequence learning. Here, to investigate the core cortical region for sleep-dependent consolidation of finger-tapping motor-sequence learning, while human subjects were asleep, we measured spontaneous cortical oscillations by magnetoencephalography together with polysomnography, and source-localized the origins of oscillations using individual anatomical brain information from MRI. First, we confirmed that performance of the task at a retest session after sleep significantly increased compared with performance at the training session before sleep. Second, spontaneous δ and fast-σ oscillations significantly increased in the supplementary motor area (SMA) during post-training compared with pretraining sleep, showing significant and high correlation with the performance increase. Third, the increased spontaneous oscillations in the SMA correlated with performance improvement were specific to slow-wave sleep. We also found that correlations of δ oscillation between the SMA and the prefrontal and between the SMA and the parietal regions tended to decrease after training. These results suggest that a core brain region for sleep-dependent consolidation of the finger-tapping motor-sequence learning resides in the SMA contralateral to the trained hand and is mediated by spontaneous δ and fast-σ oscillations, especially during slow-wave sleep. The consolidation may arise along with possible reorganization of a larger-scale cortical network that involves the SMA and cortical regions outside the motor regions, including prefrontal and parietal regions.

Iris color and age-related changes in lens optical density.

PURPOSE Epidemiologic evidence indicates that dark iris color increases risk of age-related cataract. No information is currently available, however, on the effects of iris color on the lens prior to cataract development. In this study, we relate iris color to lens optical density (OD) in individuals without frank cataract. METHODS 90 subjects with blue or green irises (light color) were compared with 87 subjects having hazel, brown, or black irises (dark color). Lens OD was measured psychophysically by comparing scotopic thresholds obtained at 410 (measuring) and 550 nm (reference). Stimuli were presented in Maxwellian view. RESULTS The groups with light and with dark iris color did not differ significantly in smoking habits, dietary patterns, or age. Despite other similarities between the groups, lens OD was significantly (p < 0.024) higher in the group with dark irises. The higher OD of the dark iris group was due to differences in the older subjects (> 45 years, p < 0.005), rather than the younger subjects (20-45 years) who showed no differences in lens OD. CONCLUSION Our data indicate that iris pigmentation may be directly related to age-associated increases in lens OD.