Perceptual learning in monocular pattern masking: experiments and explanations by the twin summation gain control model of contrast processing

Hierarchical Bayesian perceptual template modeling of mechanisms of spatial attention in central and peripheral cuing

The external noise paradigm and perceptual template model (PTM) have successfully been applied to characterize observer properties and mechanisms of observer state changes (e.g. attention and perceptual learning) in several research domains, focusing on individual level analysis. In this study, we developed a new hierarchical Bayesian perceptual template model (HBPTM) to model the trial-by-trial data from all individuals and conditions in a published spatial cuing study within a single structure and compared its performance to that of a Bayesian Inference Procedure (BIP), which separately infers the posterior distributions of the model parameters for each individual subject without the hierarchical structure. The HBPTM allowed us to compute the joint posterior distribution of the hyperparameters and parameters at the population, observer, and experiment levels and make statistical inferences at all these levels. In addition, we ran a large simulation study that varied the number of observers and number of trials in each condition and demonstrated the advantage of the HBPTM over the BIP across all the simulated datasets. Although it is developed in the context of spatial attention, the HBPTM and its extensions can be used to model data from the external noise paradigm in other domains and enable predictions of human performance at both the population and individual levels.

Current directions in visual perceptual learning

The visual expertise of adult humans is jointly determined by evolution, visual development, and visual perceptual learning. Perceptual learning refers to performance improvements in perceptual tasks after practice or training in the task. It occurs in almost all visual tasks, ranging from simple feature detection to complex scene analysis. In this Review, we focus on key behavioral aspects of visual perceptual learning. We begin by describing visual perceptual learning tasks and manipulations that influence the magnitude of learning, and then discuss specificity of learning. Next, we present theories and computational models of learning and specificity. We then review applications of visual perceptual learning in visual rehabilitation. Finally, we summarize the general principles of visual perceptual learning, discuss the tension between plasticity and stability, and conclude with new research directions.

The Effects of tDCS Across the Spatial Frequencies and Orientations that Comprise the Contrast Sensitivity Function

Transcranial Direct Current Stimulation (tDCS) has recently been employed in traditional psychophysical paradigms in an effort to measure direct manipulations on spatial frequency channel operations in the early visual system. However, the effects of tDCS on contrast sensitivity have only been measured at a single spatial frequency and orientation. Since contrast sensitivity is known to depend on spatial frequency and orientation, we ask how the effects of anodal and cathodal tDCS may vary according to these dimensions. We measured contrast sensitivity with sinusoidal gratings at four different spatial frequencies (0.5, 4, 8, and 12 cycles/°), two orientations (45° Oblique and Horizontal), and for two stimulus size conditions [fixed size (3°) and fixed period (1.5 cycles)]. Only contrast sensitivity measured with a 45° oblique grating with a spatial frequency of 8 cycles/° (period = 1.5 cycles) demonstrated clear polarity specific effects of tDCS, whereby cathodal tDCS increased and anodal tDCS decreased contrast sensitivity. Overall, effects of tDCS were largest for oblique stimuli presented at high spatial frequencies (i.e., 8 and 12 cycles/°), and were small or absent at lower spatial frequencies, other orientations and stimulus size. Thus, the impact of tDCS on contrast sensitivity, and therefore on spatial frequency channel operations, is opposite in direction to other behavioral effects of tDCS, and only measurable in stimuli that generally elicit lower contrast sensitivity (e.g., oblique gratings with period of 1.5 cycles at spatial frequencies above the peak of the contrast sensitivity function).

Real-time MEG neurofeedback training of posterior alpha activity modulates subsequent visual detection performance

It has been demonstrated that alpha activity is lateralized when attention is directed to the left or right visual hemifield. We investigated whether real-time neurofeedback training of the alpha lateralization enhances participants' ability to modulate posterior alpha lateralization and causes subsequent short-term changes in visual detection performance. The experiment consisted of three phases: (i) pre-training assessment, (ii) neurofeedback phase and (iii) post-training assessment. In the pre- and post-training phases we measured the threshold to covertly detect a cued faint Gabor stimulus presented in the left or right hemifield. During magnetoencephalography (MEG) neurofeedback, two face stimuli superimposed with noise were presented bilaterally. Participants were cued to attend to one of the hemifields. The transparency of the superimposed noise and thus the visibility of the stimuli were varied according to the momentary degree of hemispheric alpha lateralization. In a double-blind procedure half of the participants were provided with sham feedback. We found that hemispheric alpha lateralization increased with the neurofeedback training; this was mainly driven by an ipsilateral alpha increase. Surprisingly, comparing pre- to post-training, detection performance decreased for a Gabor stimulus presented in the hemifield that was un-attended during neurofeedback. This effect was not observed in the sham group. Thus, neurofeedback training alters alpha lateralization, which in turn decreases performances in the untrained hemifield. Our findings suggest that alpha oscillations play a causal role for the allocation of attention. Furthermore, our neurofeedback protocol serves to reduce the detection of unattended visual information and could therefore be of potential use for training to reduce distractibility in attention deficit patients, but also highlights that neurofeedback paradigms can have negative impact on behavioral performance and should be applied with caution.

What is the primary cause of individual differences in contrast sensitivity?

One of the primary objectives of early visual processing is the detection of luminance variations, often termed image contrast. Normal observers can differ in this ability by at least a factor of 4, yet this variation is typically overlooked, and has never been convincingly explained. This study uses two techniques to investigate the main source of individual variations in contrast sensitivity. First, a noise masking experiment assessed whether differences were due to the observer's internal noise, or the efficiency with which they extracted information from the stimulus. Second, contrast discrimination functions from 18 previous studies were compared (pairwise, within studies) using a computational model to determine whether differences were due to internal noise or the low level gain properties of contrast transduction. Taken together, the evidence points to differences in contrast gain as being responsible for the majority of individual variation across the normal population. This result is compared with related findings in attention and amblyopia.

Perceptual learning in Vision Research

Reports published in Vision Research during the late years of the 20th century described surprising effects of long-term sensitivity improvement with some basic visual tasks as a result of training. These improvements, found in adult human observers, were highly specific to simple visual features, such as location in the visual field, spatial-frequency, local and global orientation, and in some cases even the eye of origin. The results were interpreted as arising from the plasticity of sensory brain regions that display those features of specificity within their constituting neuronal subpopulations. A new view of the visual cortex has emerged, according to which a degree of plasticity is retained at adult age, allowing flexibility in acquiring new visual skills when the need arises. Although this "sensory plasticity" interpretation is often questioned, it is commonly believed that learning has access to detailed low-level visual representations residing within the visual cortex. More recent studies during the last decade revealed the conditions needed for learning and the conditions under which learning can be generalized across stimuli and tasks. The results are consistent with an account of perceptual learning according to which visual processing is remodeled by the brain, utilizing sensory information acquired during task performance. The stability of the visual system is viewed as an adaptation to a stable environment and instances of perceptual learning as a reaction of the brain to abrupt changes in the environment. Training on a restricted stimulus set may lead to perceptual overfitting and over-specificity. The systemic methodology developed for perceptual learning, and the accumulated knowledge, allows us to explore issues related to learning and memory in general, such as learning rules, reinforcement, memory consolidation, and neural rehabilitation. A persistent open question is the neuro-anatomical substrate underlying these learning effects.

Enhancing the contrast sensitivity function through action video game training

The contrast sensitivity function (CSF) is routinely assessed in clinical evaluation of vision and is the primary limiting factor in how well one sees. CSF improvements are typically brought about by correction of the optics of the eye with eyeglasses, contact lenses or surgery. We found that the very act of action video game playing also enhanced contrast sensitivity, providing a complementary route to eyesight improvement.