A computational developmental model for specificity and transfer in perceptual learning

Pupil Size Is Sensitive to Low-Level Stimulus Features, Independent of Arousal-Related Modulation

Similar to a camera aperture, pupil size adjusts to the surrounding luminance. Unlike a camera, pupil size is additionally modulated both by stimulus properties and by cognitive processes, including attention and arousal, though the interdependence of these factors is unclear. We hypothesized that different stimulus properties interact to jointly modulate pupil size while remaining independent from the impact of arousal. We measured pupil responses from human observers to equiluminant stimuli during a demanding rapid serial visual presentation (RSVP) task at fixation and tested how response amplitude depends on contrast, spatial frequency, and reward level. We found that under constant luminance, unattended stimuli evoke responses that are separable from changes caused by general arousal or attention. We further uncovered a double-dissociation between task-related responses and stimulus-evoked responses, suggesting that different sources of pupil size modulation are independent of one another. Our results shed light on neural pathways underlying pupillary response.

Autonomous Programming for General Purposes: Theory

The universal Turing Machine (TM) is a model for Von Neumann computers — general-purpose computers. A human brain, linked with its biological body, can inside-skull-autonomously learn a universal TM so that he acts as a general-purpose computer and writes a computer program for any practical purposes. It is unknown whether a robot can accomplish the same. This theoretical work shows how the Developmental Network (DN), linked with its robot body, can accomplish this. Unlike a traditional TM, the TM learned by DN is a super TM — Grounded, Emergent, Natural, Incremental, Skulled, Attentive, Motivated, and Abstractive (GENISAMA). A DN is free of any central controller (e.g., Master Map, convolution, or error back-propagation). Its learning from a teacher TM is one transition observation at a time, immediate, and error-free until all its neurons have been initialized by early observed teacher transitions. From that point on, the DN is no longer error-free but is always optimal at every time instance in the sense of maximal likelihood, conditioned on its limited computational resources and the learning experience. This paper extends the Church–Turing thesis to a stronger version — a GENISAMA TM is capable of Autonomous Programming for General Purposes (APFGP) — and proves both the Church–Turing thesis and its stronger version.

Bottom-up and top-down influences at untrained conditions determine perceptual learning specificity and transfer

Perceptual learning is often orientation and location specific, which may indicate neuronal plasticity in early visual areas. However, learning specificity diminishes with additional exposure of the transfer orientation or location via irrelevant tasks, suggesting that the specificity is related to untrained conditions, likely because neurons representing untrained conditions are neither bottom-up stimulated nor top-down attended during training. To demonstrate these top-down and bottom-up contributions, we applied a “continuous flash suppression” technique to suppress the exposure stimulus into sub-consciousness, and with additional manipulations to achieve pure bottom-up stimulation or top-down attention with the transfer condition. We found that either bottom-up or top-down influences enabled significant transfer of orientation and Vernier discrimination learning. These results suggest that learning specificity may result from under-activations of untrained visual neurons due to insufficient bottom-up stimulation and/or top-down attention during training. High-level perceptual learning thus may not functionally connect to these neurons for learning transfer.

DOI:http://dx.doi.org/10.7554/eLife.14614.001

People can become more sensitive to small changes in what they are seeing – such as detecting a slight change in the angle of a particular line – with practice. This process is called perceptual learning, but the improvement is often specific such that it is typically lost if the line moves to a new place, or a different line angle is used. Previous work does show that it is possible to transfer the learning to a new location or angle if the individual also practices another, seemingly irrelevant, task at the same or a later time – such as judging how bright the line is.

To understand what might be happening to produce these seemingly conflicting results, Xiong et al. used a technique called “continuous flash suppression” with human volunteers. This approach meant that the volunteers were shown an object (such as an angled line) in one eye, while their other eye viewed white noise similar to the “snowflakes” seen on an old-fashioned un-tuned television screen. The flashing snowflakes in one eye meant that the volunteers were not consciously aware of the presence of the angled line in the other eye.

The experiments revealed that perceptual learning at the new location or line angle happened when a subconsciously-observed object was shown in the new location or angle, or when the volunteers were asked to pay attention to the “subconscious object” when no object was actually there. This suggests that perceptual learning can happen in new conditions both through ‘bottom-up’ processes, which rely entirely on information coming in from the senses, and ‘top-down’ processes, which are influenced by what a person is aware of and paying attetion to. What is more, the results suggest that the classical observations of specificity in perceptual learning are likely to be a result of the lack of bottom-up and top-down influences in the untrained condition, when the volunteers work hard to improve their performance with the trained condition.

Future studies could directly look at what is going on in the brain when perceptual learning becomes less specific, for example by using a technique like functional magnetic resonance imaging to measure brain activity.

DOI:http://dx.doi.org/10.7554/eLife.14614.002

Is improved contrast sensitivity a natural consequence of visual training?

Many studies have shown that training and testing conditions modulate specificity of visual learning to trained stimuli and tasks. In visually impaired populations, generalizability of visual learning to untrained stimuli/tasks is almost always reported, with contrast sensitivity (CS) featuring prominently among these collaterally-improved functions. To understand factors underlying this difference, we measured CS for direction and orientation discrimination in the visual periphery of three groups of visually-intact subjects. Group 1 trained on an orientation discrimination task with static Gabors whose luminance contrast was decreased as performance improved. Group 2 trained on a global direction discrimination task using high-contrast random dot stimuli previously used to recover motion perception in cortically blind patients. Group 3 underwent no training. Both forms of training improved CS with some degree of specificity for basic attributes of the trained stimulus/task. Group 1's largest enhancement was in CS around the trained spatial/temporal frequencies; similarly, Group 2's largest improvements occurred in CS for discriminating moving and flickering stimuli. Group 3 saw no significant CS changes. These results indicate that CS improvements may be a natural consequence of multiple forms of visual training in visually intact humans, albeit with some specificity to the trained visual domain(s).

Vernier perceptual learning transfers to completely untrained retinal locations after double training: a "piggybacking" effect

Perceptual learning, a process in which training improves visual discrimination, is often specific to the trained retinal location, and this location specificity is frequently regarded as an indication of neural plasticity in the retinotopic visual cortex. However, our previous studies have shown that "double training" enables location-specific perceptual learning, such as Vernier learning, to completely transfer to a new location where an irrelevant task is practiced. Here we show that Vernier learning can be actuated by less location-specific orientation or motion-direction learning to transfer to completely untrained retinal locations. This "piggybacking" effect occurs even if both tasks are trained at the same retinal location. However, piggybacking does not occur when the Vernier task is paired with a more location-specific contrast-discrimination task. This previously unknown complexity challenges the current understanding of perceptual learning and its specificity/transfer. Orientation and motion-direction learning, but not contrast and Vernier learning, appears to activate a global process that allows learning transfer to untrained locations. Moreover, when paired with orientation or motion-direction learning, Vernier learning may be "piggybacked" by the activated global process to transfer to other untrained retinal locations. How this task-specific global activation process is achieved is as yet unknown.

The role of alpha-rhythm states in perceptual learning: insights from experiments and computational models

During the past two decades growing evidence indicates that brain oscillations in the alpha band (~10 Hz) not only reflect an "idle" state of cortical activity, but also take a more active role in the generation of complex cognitive functions. A recent study shows that more than 60% of the observed inter-subject variability in perceptual learning can be ascribed to ongoing alpha activity. This evidence indicates a significant role of alpha oscillations for perceptual learning and hence motivates to explore the potential underlying mechanisms. Hence, it is the purpose of this review to highlight existent evidence that ascribes intrinsic alpha oscillations a role in shaping our ability to learn. In the review, we disentangle the alpha rhythm into different neural signatures that control information processing within individual functional building blocks of perceptual learning. We further highlight computational studies that shed light on potential mechanisms regarding how alpha oscillations may modulate information transfer and connectivity changes relevant for learning. To enable testing of those model based hypotheses, we emphasize the need for multidisciplinary approaches combining assessment of behavior and multi-scale neuronal activity, active modulation of ongoing brain states and computational modeling to reveal the mathematical principles of the complex neuronal interactions. In particular we highlight the relevance of multi-scale modeling frameworks such as the one currently being developed by "The Virtual Brain" project.

Psychophysical factors that have been applied to clinical perimetry

Perimetry is the most common clinical diagnostic test procedure for evaluating the status of peripheral visual function in the management of ocular and neurologic diseases. This procedure has an extended history, and its design, implementation and interpretation is dependent on many principles that have been developed through visual psychophysical studies of target size, target duration, background adaptation level, chromatic characteristics and other stimulus properties (see Greve, 1973; Johnson, 1994, chap. 17, 1996, 2008, 2010, chap. 23; Johnson & Keltner, 1998, chap. 7; Johnson & Sample, 2002, chap. 22; Johnson & Wall, 2011, chap. 35; Wall & Johnson, 2005, chap. 2 for reviews). This paper will provide a general overview of the history of perimetry, selection of stimulus parameters, development of test strategies, clinical testing conditions, new procedures and approaches to perimetry, experimental design, analysis and interpretation methods, hypothesis testing, prediction and forecasting procedures, and other related topics. It is somewhat paradoxical that although there have been major advances in all of these areas that have significantly enhanced the utility and value of this clinical diagnostic test, the fundamental methodology has remained mostly unchanged for thousands of years. It is hoped that this overview will be of assistance to investigators and clinicians who wish to use or modify this diagnostic procedure for their ongoing career activities.