Word-decoding as a function of temporal processing in the visual system.

This study explored the relation between visual processing and word-decoding ability in a normal reading population. Forty participants were recruited at Arizona State University. Flicker fusion thresholds were assessed with an optical chopper using the method of limits by a 1-deg diameter green (543 nm) test field. Word decoding was measured using reading-word and nonsense-word decoding tests. A non-linguistic decoding measure was obtained using a computer program that consisted of Landolt C targets randomly presented in four cardinal orientations, at 3-radial distances from a focus point, for eight compass points, in a circular pattern. Participants responded by pressing the arrow key on the keyboard that matched the direction the target was facing. The results show a strong correlation between critical flicker fusion thresholds and scores on the reading-word, nonsense-word, and non-linguistic decoding measures. The data suggests that the functional elements of the visual system involved with temporal modulation and spatial processing may affect the ease with which people read

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

A Call to Address Academic Difficulties Resulting from the COVID-19-Related Change in Education Delivery

As the corona virus pandemic forced school closures worldwide, online platforms have become invaluable tools for allowing instruction to continue smoothly and, hopefully, for mitigating the severity of any student learning disruptions associated with the COVID-19 forced school closures. Although distance-learning is currently necessary, it is a blunt tool that may prove to be inadequate, compared to face-to-face teaching content delivery, for meeting students’ educational needs resulting from COVID-19-forced school closures. It is very likely that the sudden shift to distance-learning has will disadvantage many students who are not experienced with or prepared for the dramatic changes that have occurred in the delivery of formal education. Here, we proffer a call to education-scholars to engage in investigations designed to provide research-informed knowledge and understanding of what pedagogical methodologies are needed for addressing learning deficiencies inherent in distance-learning instruction, and to effectuate the changes needed to provide an equitable educational experience to all students, during the uncertain times of the COVID-19 pandemic

Correlation between CFF thresholds and Landolt C test scores (F(17) = 25.45, r = .78, r² = .61, p<.01).

<p>Correlation between CFF thresholds and Landolt C test scores (F(17) = 25.45, r = .78, r² = .61, p<.01).</p

Sample of the Nonsense-word Decoding Test Sheet.

<p>Sample of the Nonsense-word Decoding Test Sheet.</p

Correlation between CFF threshold and Word Decoding Test scores (F(39) = 125.46, r = .88, r^{2 =}.76, p<.01), and Nonsense-word Decoding Test scores (F(39) = 168.36, r = .90, r² = .81, p<.01).

<p>Correlation between CFF threshold and Word Decoding Test scores (F(39) = 125.46, r = .88, r^2 =.76, p<.01), and Nonsense-word Decoding Test scores (F(39) = 168.36, r = .90, r² = .81, p<.01).</p

Sample of the Word Decoding Test Sheet.

<p>Sample of the Word Decoding Test Sheet.</p

Decoding Reveals Plasticity in V3A as a Result of Motion Perceptual Learning

<div><p>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.</p> </div