Theories Of Perceptual Learning Research Articles

EXPRESS: Resisting the Urge to Calculate: The Relation Between Inhibitory Control and Perceptual Cues in Arithmetic Performance.

Subtle visual manipulations to the presentation of mathematical notation influence the way that students perceive and solve problems. While there is a consistent impact of perceptual cues on students' problem solving, other cognitive skills such as inhibitory control may interact with perceptual cues to impact students' arithmetic problem-solving performance. We present an online experiment in which college students completed a version of the Stroop task followed by arithmetic problems in which the spacing between numbers and operators was either congruent (e.g., 2 + 3×4) or incongruent (e.g., 2+3 × 4) to the order of precedence. We found that students were comparably accurate between problem types but might have spent longer responding to problems with congruent than incongruent spacing. There was no main effect of inhibitory control on students' performance on these problems. However, an exploratory analysis on a combined performance measure of accuracy and response time revealed an interaction between problem type and inhibitory control. Students with higher inhibitory control performed better on congruent vs. incongruent problems whereas students with lower inhibitory control performed worse on congruent vs. incongruent problems. Together, these results suggest that the relation between inhibitory control and arithmetic performance may not be straightforward. Further, this work advances perceptual learning theory and contributes new findings on the contexts in which perceptual cues, such as spacing, influence arithmetic performance.

Drift diffusion models of perceptual learning indicate long-term improvements in sensitivity and short-term fluctuations in caution.

Evidence-accumulation models have enabled strong theoretical advances in our understanding of decision-making. Yet most of these models assume stationary performance; when concerned with performance improvements, dynamic versions of these models are critical to inform the mechanisms of learning. This is particularly true because most domains of learning, from low-level perception to more complex skills, involve changes in both choices (e.g., accuracy) and the speed at which those choices can be made (i.e., response time). Evidence-accumulation models provide frameworks for understanding these joint changes. Using data from participants completing a dynamic random dot-motion direction discrimination task over 4 daily sessions for a total of 2800 trials, we characterized alterations in both perceptual sensitivity [drift rate] and response caution [boundary separation] across multiple possible timescales. Nonlinear mixed-effect Bayesian Wiener diffusion models were applied to estimate individuals’ trajectories of performance change in joint RT and accuracy distributions, with different models allowing for various dynamics. For example, the models could be stable across the entirety of the training, changing as a continuous function of trial number, or changing continuously within sessions, but varying across sessions. Model comparisons then used estimates of Bayes Factors as well as approximations to leave-one-out cross-validation. The best-fitting model of perceptual improvements included sensitivity changing as a continuous, exponential function of trial number (i.e., 1 through 2800), but response caution changing continuously within each daily session and in an independent manner across sessions. Such results uncover two different processes producing the full pattern of behavior across the entire trajectory of experience, one involving a continuous tuning of perceptual sensitivity, and another more idiosyncratic process describing how participants convert perceptual evidence into behavioral decisions. Theories of perceptual learning involving multiple timescales of change are thus supported, with distinct processes and outcomes associated with each time scale.

Effects of experience on recognition of speech produced with a face mask

Over the past two years, face masks have been a critical tool for preventing the spread of COVID-19. While previous studies have examined the effects of masks on speech recognition, much of this work was conducted early in the pandemic. Given that human listeners are able to adapt to a wide variety of novel contexts in speech perception, an open question concerns the extent to which listeners have adapted to masked speech during the pandemic. In order to evaluate this, we replicated Toscano and Toscano (PLOS ONE 16(2):e0246842, 2021), looking at the effects of several types of face masks on speech recognition in different levels of multi-talker babble noise. We also examined the effects of listeners’ self-reported frequency of encounters with masked speech and the effects of the implementation of public mask mandates on speech recognition. Overall, we found that listeners’ performance in the current experiment (with data collected in 2021) was similar to that of listeners in Toscano and Toscano (with data collected in 2020) and that performance did not differ based on mask experience. These findings suggest that listeners may have already adapted to masked speech by the time data were collected in 2020, are unable to adapt to masked speech, require additional context to be able to adapt, or that talkers also changed their productions over time. Implications for theories of perceptual learning in speech are discussed.

Socio-cultural norms in ecological psychology: The education of intention

Although it is a common claim in the ecological psychology literature that our perception of the environment’s affordances is influenced by socio-cultural norms, an explanation of how this is possible remains to be offered. In this paper, I outline an account of this phenomenon by focusing on the ecological theory of perceptual learning. Two main theses are defended. First, I argue that to account for how socio-cultural norms can influence perception, we must pay attention not only to the education of attention but to the education of intention too. Consequently, I offer some ideas about how intention can be socio-normatively educated. Secondly, I hold that the education of intention occurs via the acquisition of habit-based preferences for particular actions. I claim that once we understand how these habit-based preferences relate to socio-cultural norms, the hypothesis that norms must be represented in the individual’s mind for them to influence affordance perception is no longer needed. If this hypothesis is on the right track, we can have an explanation for how perception can be normatively shaped and direct (non-mediated by internal representations and inferences) at the same time.

The impact of algebra worked example presentations on student learning

AbstractWorked examples are effective learning tools for algebraic equation solving. However, they are typically presented in a static concise format, which only displays the major derivation steps in one static image. The current work explores how worked examples that vary in their extensiveness (i.e., detail) and degree of dynamic presentation (i.e., static vs. sequential line‐by‐line vs. dynamic format that demonstrates the problem‐solving process) impact learning. We conducted an online experiment in which 230 algebra students completed a pretest, studied worked examples in one of six presentation conditions, and completed a posttest. We found that overall, students improved from pretest to posttest after viewing the worked examples; we did not find significant differences on posttest performance between worked example presentations. These results have implications for the design of worked examples in online tutoring systems as well as for cognitive load theory and perceptual learning theory in the design of worked examples.

On the certainty of entanglements with ecocide: pragmatic action for responsive pedagogy inspired by ecological psychology and permaculture

ABSTRACT Inspired by youth concerns for environmental justice and pathways forward that sustain diverse biology, we draw upon ecological psychology to theorise learning. This novel proposition, against the tide of cognitive constructivism, proffers a non-dualist paradigm more aligned with the purpose and intent of those seeking ecological justice and responds to calls for theory to support place-based education. Additionally, theory from ecological psychology lends support for understanding how ecocide is sustained and why work that inspired the environmental movement over half a century ago, such as Rachel Carson’s Silent Spring has seemingly remained ignored and derided in the broader public realm. We provide some clues as to how that ignorance is perpetuated via understandings of perceptual learning theory. Finally, we map a pathway forward to respond with permaculture activism and offer a unique and solutions-based narrative that inspires hope in the face of catastrophe.

Visual complexity of shapes: a hierarchical perceptual learning model

Understanding how people perceive the visual complexity of shapes has important theoretical as well as practical implications. One school of thought, driven by information theory, focuses on studying the local features that contribute to the perception of visual complexity. Another school, in contrast, emphasizes the impact of global characteristics of shapes on perceived complexity. Inspired by recent discoveries in neuroscience, our model considers both local features of shapes: edge lengths and vertex angles, and global features: concaveness, and is in 92% agreement with human subjective ratings of shape complexity. The model is also consistent with the hierarchical perceptual learning theory, which explains how different layers of neurons in the visual system act together to yield a perception of visual shape complexity.

Latent inhibition in young children: A developmental effect?

Previous research by Kaniel & Lubow in 1986 found that young children (aged 4-5 years) exhibited poorer learning (latent inhibition) to preexposed stimuli than older children (aged 7-10 years). The aim of our research was to develop a computer-based, child-friendly study that would replicate and extend the work of Kaniel & Lubow in a way that ruled out other, attention-based explanations of their effect. One hundred and four children and 32 undergraduate students took part in our experiment. This consisted of a preexposure/study phase in which participants were asked to press computer keys in response to clipart pictures of animals and dinosaurs. Each animal or dinosaur picture was preceded by one of 2 "warning signals" that acted as the preexposed stimuli (to which no response was required). In the test phase that followed, the participants had to either press the spacebar or withhold their response to each preexposed stimulus and two novel stimuli. They learned which response was correct by trial and error using the feedback provided. The accuracy and reaction time (RT) of the responses during the test phase were analyzed and indicated that the youngest children showed significantly lower mean accuracy and longer mean response times to the preexposed stimuli than to stimuli they had not been preexposed to. In contrast, the older children showed no significant differences in their responses to preexposed and novel stimuli. These results are consistent with those found by Kaniel & Lubow and as such provide additional evidence for latent inhibition in young children. We discuss the implications for theories of perceptual learning in humans. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Mechanisms of perceptual learning: Prolonged intermixed preexposure reduces the effectiveness of the unique and the common elements.

In three experiments, rats were given intermixed or blocked preexposure to two similar compound stimuli, AX and BX. In Experiment 1, following preexposure, animals were given appetitive conditioning training with the compound AX. A subsequent generalization test showed better discrimination between AX and BX in the group given intermixed than in the one given blocked preexposure. Experiments 2 and 3 assessed the nature of the learning mechanisms underlying this instance of the perceptual learning effect. Experiment 2 assessed the associability of the common and unique elements (X and A); animals in the group given intermixed preexposure showed poorer conditioning with both the X and the A elements than those given blocked preexposure. Experiment 3 further assessed the perceptual effectiveness of the distinctive element A using a superimposition test (the capacity of A to interfere with the conditioned response commanded by an independent conditioned stimulus). The results showed, in line with the outcome of Experiment 2, that the unique element A is more salient following blocked than intermixed preexposure. These results are discussed by reference to current theories of perceptual learning. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Roving: The causes of interference and re-enabled learning in multi-task visual training.

People routinely perform multiple visual judgments in the real world, yet, intermixing tasks or task variants during training can damage or even prevent learning. This paper explores why. We challenged theories of visual perceptual learning focused on plastic retuning of low-level retinotopic cortical representations by placing different task variants in different retinal locations, and tested theories of perceptual learning through reweighting (changes in readout) by varying task similarity. Discriminating different (but equivalent) and similar orientations in separate retinal locations interfered with learning, whereas training either with identical orientations or sufficiently different ones in different locations released rapid learning. This location crosstalk during learning renders it unlikely that the primary substrate of learning is retuning in early retinotopic visual areas; instead, learning likely involves reweighting from location-independent representations to a decision. We developed an Integrated Reweighting Theory (IRT), which has both V1-like location-specific representations and higher level (V4/IT or higher) location-invariant representations, and learns via reweighting the readout to decision, to predict the order of learning rates in different conditions. This model with suitable parameters successfully fit the behavioral data, as well as some microstructure of learning performance in a new trial-by-trial analysis.

Assessing the frequency of general fingerprint patterns by fingerprint examiners and novices

The rarity of general fingerprint patterns should be taken into account in the assessment of fingerprint evidence to provide a more complete assessment of fingerprint evidence than when only considering the minutiae. This should be done because, the rarer the corresponding pattern, the stronger the support for the hypothesis that the fingermark stems from the same source as the reference fingerprint. Fingerprint examiners’ experience should enable them to provide meaningful assessments of the frequencies of these general patterns according to the theories of perceptual learning, exemplar theory of categorization and visual statistical learning. In this study we examined the accuracy of fingerprint examiners’ and novices’ judgments on the rarity of general fingerprint patterns.We found that fingerprint examiners seem to have acquired some knowledge about the rarity of general patterns, but had difficulty expressing this knowledge quantitatively using a novel sub-classification of general patterns. As a consequence, their judgments were not accurate and they did not perform better on this task than novices. For both participant groups judgments of more common patterns were more accurate. However, examiners did outperform novices in rank ordering general patterns from common to rare. We conclude that our study does not show that fingerprint examiners have expertise in explicitly judging frequencies of novel sub-classifications of general fingerprint patterns, but our results do indicate that the examiners have acquired knowledge about the rarity of patterns that novices do not possess.

Distributional learning for speech reflects cumulative exposure to a talker's phonetic distributions.

Efficient speech perception requires listeners to maintain an exquisite tension between stability of the language architecture and flexibility to accommodate variation in the input, such as that associated with individual talker differences in speech production. Achieving this tension can be guided by top-down learning mechanisms, wherein lexical information constrains interpretation of speech input, and by bottom-up learning mechanisms, in which distributional information in the speech signal is used to optimize the mapping to speech sound categories. An open question for theories of perceptual learning concerns the nature of the representations that are built for individual talkers: do these representations reflect long-term, global exposure to a talker or rather only short-term, local exposure? Recent research suggests that when lexical knowledge is used to resolve a talker's ambiguous productions, listeners disregard previous experience with a talker and instead rely on only recent experience, a finding that is contrary to predictions of Bayesian belief-updating accounts of perceptual adaptation. Here we use a distributional learning paradigm in which lexical information is not explicitly required to resolve ambiguous input to provide an additional test of global versus local exposure accounts. Listeners completed two blocks of phonetic categorization for stimuli that differed in voice-onset-time, a probabilistic cue to the voicing contrast in English stop consonants. In each block, two distributions were presented, one specifying /g/ and one specifying /k/. Across the two blocks, variance of the distributions was manipulated to be either narrow or wide. The critical manipulation was order of the two blocks; half of the listeners were first exposed to the narrow distributions followed by the wide distributions, with the order reversed for the other half of the listeners. The results showed that for earlier trials, the identification slope was steeper for the narrow-wide group compared to the wide-narrow group, but this difference was attenuated for later trials. The between-group convergence was driven by an asymmetry in learning between the two orders such that only those in the narrow-wide group showed slope movement during exposure, a pattern that was mirrored by computational simulations in which the distributional statistics of the present talker were integrated with prior experience with English. This pattern of results suggests that listeners did not disregard all prior experience with the talker, and instead used cumulative exposure to guide phonetic decisions, which raises the possibility that accommodating a talker's phonetic signature entails maintaining representations that reflect global experience.

An examination of students' perceptions of the Kekulé resonance representation using a perceptual learning theory lens

Students in chemistry often demonstrate difficulty with the principle of resonance. Despite many attempts to mitigate this difficulty, there have been few attempts to examine the root cause of these issues. In this study, students were assessed for their perception of Kekulé structures based on perceptual learning theory, which is grounded in cognitive mechanisms of visual perception. The data from this assessment shows that students are perceiving inappropriate clues from this representation, which infers that the image itself might be an impediment to learning about resonance. Employment of a metarepresentational competence approach was used to address these misperceptions.

Neural mechanisms of motion perceptual learning in noise.

Practice improves our perceptual ability. However, the neural mechanisms underlying this experience-dependent plasticity in adult brain remain unclear. Here, we studied the long-term neural correlates of motion perceptual learning. Subjects' behavioral performance and BOLD signals were tracked before, immediately after, and 2 weeks after practicing a motion direction discrimination task in noise over six daily sessions. Parallel to the specificity and persistency of the behavioral learning effect, we found that training sharpened the cortical tuning in MT, and enhanced the connectivity strength from MT to the intraparietal sulcus (IPS, a motion decision-making area). In addition, the decoding accuracy for the trained motion direction was improved in IPS 2 weeks after training. The dual changes in the sensory and the high-level cortical areas suggest that learning refines the neural representation of the trained stimulus and facilitates the information transmission in the decision process. Our findings are consistent with the functional specialization in the visual cortex, and provide empirical evidence to the reweighting theory of perceptual learning at a large spatial scale. Hum Brain Mapp 38:6029-6042, 2017. © 2017 Wiley Periodicals, Inc.

Visual Perceptual Learning and Models.

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

Visual training improves perceptual grouping based on basic stimulus features.

Training on visual tasks improves performance on basic and higher order visual capacities. Such improvement has been linked to changes in connectivity among mediating neurons. We investigated whether training effects occur for perceptual grouping. It was hypothesized that repeated engagement of integration mechanisms would enhance grouping processes. Thirty-six participants underwent 15 sessions of training on a visual discrimination task that required perceptual grouping. Participants viewed 20 × 20 arrays of dots or Gabor patches and indicated whether the array appeared grouped as vertical or horizontal lines. Across trials stimuli became progressively disorganized, contingent upon successful discrimination. Four visual dimensions were examined, in which grouping was based on similarity in luminance, color, orientation, and motion. Psychophysical thresholds of grouping were assessed before and after training. Results indicate that performance in all four dimensions improved with training. Training on a control condition, which paralleled the discrimination task but without a grouping component, produced no improvement. In addition, training on only the luminance and orientation dimensions improved performance for those conditions as well as for grouping by color, on which training had not occurred. However, improvement from partial training did not generalize to motion. Results demonstrate that a training protocol emphasizing stimulus integration enhanced perceptual grouping. Results suggest that neural mechanisms mediating grouping by common luminance and/or orientation contribute to those mediating grouping by color but do not share resources for grouping by common motion. Results are consistent with theories of perceptual learning emphasizing plasticity in early visual processing regions.

Learning to perceive in the sensorimotor approach: Piaget's theory of equilibration interpreted dynamically.

Learning to perceive is faced with a classical paradox: if understanding is required for perception, how can we learn to perceive something new, something we do not yet understand? According to the sensorimotor approach, perception involves mastery of regular sensorimotor co-variations that depend on the agent and the environment, also known as the “laws” of sensorimotor contingencies (SMCs). In this sense, perception involves enacting relevant sensorimotor skills in each situation. It is important for this proposal that such skills can be learned and refined with experience and yet up to this date, the sensorimotor approach has had no explicit theory of perceptual learning. The situation is made more complex if we acknowledge the open-ended nature of human learning. In this paper we propose Piaget’s theory of equilibration as a potential candidate to fulfill this role. This theory highlights the importance of intrinsic sensorimotor norms, in terms of the closure of sensorimotor schemes. It also explains how the equilibration of a sensorimotor organization faced with novelty or breakdowns proceeds by re-shaping pre-existing structures in coupling with dynamical regularities of the world. This way learning to perceive is guided by the equilibration of emerging forms of skillful coping with the world. We demonstrate the compatibility between Piaget’s theory and the sensorimotor approach by providing a dynamical formalization of equilibration to give an explicit micro-genetic account of sensorimotor learning and, by extension, of how we learn to perceive. This allows us to draw important lessons in the form of general principles for open-ended sensorimotor learning, including the need for an intrinsic normative evaluation by the agent itself. We also explore implications of our micro-genetic account at the personal level.

An easy-to-hard effect after nonreinforced preexposure in a sweetness discrimination.

Experiments 1A and 1B used a taste-aversion procedure with rats to demonstrate that exposure to easily discriminated flavors along a dimension (1 % and 10 % sucrose) can facilitate learning a subsequent hard discrimination (4 % and 7 % sucrose) when one of those flavors is paired with illness. Experiment 1A compared the effects of preexposure to the easily discriminated flavors against exposure to the same stimuli used in the discrimination training or no exposure at all. Experiment 1B replicated the conditions in Experiment 1A, with 2 additional days of training and unrestricted access to the flavors on CS+/CS- trials in discrimination training. Contrary to findings with multidimensional stimuli (Scahill & Mackintosh, Journal of Experimental Psychology: Animal Behavior Processes, 30, 96-103, 2004; Suret & McLaren, The Quarterly Journal of Experimental Psychology, 56B, 30-42, 2003), we found that preexposure to the easily discriminable stimuli varying along a single dimension of sweetness facilitated subsequent discrimination training over the other conditions in each experiment. We discuss the results in terms of the ideas presented by Gibson (1969) and Mackintosh (Psychological Review, 82, 276-298, 1975) and in terms of hedonic variables not considered by theories of perceptual learning.

Perceptual learning and inversion effects: Recognition of prototype-defined familiar checkerboards.

The face inversion effect is a defection in performance in recognizing inverted faces compared with faces presented in their usual upright orientation typically believed to be specific for facial stimuli. McLaren (1997) was able to demonstrate that (a) an inversion effect could be obtained with exemplars drawn from a familiar category, such that upright exemplars were better discriminated than inverted exemplars; and (b) that the inversion effect required that the familiar category be prototype-defined. In this article, we replicate and extend these findings. We show that the inversion effect can be obtained in a standard old/new recognition memory paradigm, demonstrate that it is contingent on familiarization with a prototype-defined category, and establish that the effect is made up of two components. We confirm the advantage for upright exemplars drawn from a familiar, prototype-defined category, and show that there is a disadvantage for inverted exemplars drawn from this category relative to suitable controls. We also provide evidence that there is an N170 event-related potential signature for this effect. These results allow us to integrate a theory of perceptual learning originally proposed by McLaren, Kaye, and Mackintosh (1989) with explanations of the face inversion effect, first reported by Yin.

Perceptual learning transfer: Salience of the common element as a factor contributing to the intermixed/blocked effect.

Rats received intermixed or blocked preexposure to 2 similar flavor compounds, AX and BX. Following preexposure, conditioning trials took place in which a novel compound stimulus NX was paired with an illness-induced unconditioned stimulus. Animals that were given intermixed preexposure to AX and BX showed lower generalization of the aversive response conditioned to NX to a new compound, ZX, than animals that were given blocked preexposure. The results support the proposal that intermixed preexposure reduces the salience of the common element X to a greater extent than blocked preexposure. The way in which current theories of perceptual learning can predict a differential salience of X after intermixed and blocked preexposure is discussed.