Information-integration Category Research Articles

Feedback and observational learning differ in effectiveness during category learning in early school aged children and adults.

When learning new categories, do children benefit from the same types of training as adults? We compared the effects of feedback-based training with observational training in young adults (ages 18-25) and early school aged children (ages 6-7) across two different multimodal category learning tasks: conjunctive rule based and information integration. We used multimodal stimuli that varied across a visual feature (rotation speed of the "planet" stimulus) and an auditory feature (pitch frequency of a pure tone stimulus). We found an interaction between age and training type for the rule-based category task, such that adults performed better in feedback training than in observational training, whereas training type had no significant effect on children's category learning performance. Overall adults performed better than children in learning both the rule based and information integration category structures. In information integration category learning, feedback versus observational training did not have a significant effect on either adults' or children's category learning. Computational modelling revealed that children defaulted to univariate rules in both tasks. The finding that children do not benefit from feedback training and can learn successfully via observational learning has implications for the design of educational interventions appropriate for children.

The spacing effect in remote information-integration category learning.

The present experiments examined whether the temporal distribution of procedural category learning experiences would impact learning outcomes. Participants completed the remote category learning experiments on a smartphone in one of two learning conditions: massed or distributed. Consistent with expectations, distributed learners in both experiments reached higher accuracy levels than massed learners. In Experiment 1 the effect disappeared after accounting for reaction time differences, suggesting that it was driven by attentional mechanisms. In Experiment 2, the spacing advantage was only present for previously studied items during a post-learning test, suggesting a role of consolidation. In both experiments, it seems likely that temporal spacing helped participants discover the optimal information-integration categorization strategy. These results suggest that adult category learning is facilitated by temporal spacing. Future work may further explore the effects of temporal and contextual distinctiveness of learning experiences on category learning outcomes.

Auditory Category Learning in Children With Dyslexia.

Developmental dyslexia is proposed to involve selective procedural memory deficits with intact declarative memory. Recent research in the domain of category learning has demonstrated that adults with dyslexia have selective deficits in Information-Integration (II) category learning that is proposed to rely on procedural learning mechanisms and unaffected Rule-Based (RB) category learning that is proposed to rely on declarative, hypothesis testing mechanisms. Importantly, learning mechanisms also change across development, with distinct developmental trajectories in both procedural and declarative learning mechanisms. It is unclear how dyslexia in childhood should influence auditory category learning, a critical skill for speech perception and reading development. We examined auditory category learning performance and strategies in 7- to 12-year-old children with dyslexia (n = 25; nine females, 16 males) and typically developing controls (n = 25; 13 females, 12 males). Participants learned nonspeech auditory categories of spectrotemporal ripples that could be optimally learned with either RB selective attention to the temporal modulation dimension or procedural integration of information across spectral and temporal dimensions. We statistically compared performance using mixed-model analyses of variance and identified strategies using decision-bound computational models. We found that children with dyslexia have an apparent selective RB category learning deficit, rather than a selective II learning deficit observed in prior work in adults with dyslexia. These results suggest that the important skill of auditory category learning is impacted in children with dyslexia and throughout development, individuals with dyslexia may develop compensatory strategies that preserve declarative learning while developing difficulties in procedural learning. https://doi.org/10.23641/asha.25148519.

Procedural auditory category learning is selectively disrupted in developmental language disorder.

Speech communication depends on accurate perception and identification of speech sounds, which vary across talkers and word or sentence contexts. The ability to map this variable input onto discrete speech sound representations relies on categorization. Recent research and theoretical models implicate the procedural learning system in the ability to learn novel speech and non-speech categories. This connection is particularly intriguing because several language disorders that demonstrate linguistic impairments are proposed to stem from procedural learning and memory dysfunction. One such disorder, Developmental Language Disorder (DLD), affects 7.5% of children and persists into adulthood. While DLD is associated with general linguistic impairments, it is not yet clear how fundamental perceptual and cognitive processes supporting language are impacted, such as the ability to learn novel auditory categories. We examined auditory category learning in children with DLD and typically developed (TD) children using two well-matched nonspeech auditory category learning challenges to draw upon presumed procedural (information-integration) versus declarative (rule-based) learning systems. We observed impaired information-integration category learning and intact rule-based category learning in the DLD group. Quantitative model-based analyses revealed reduced use of, and slower shifting to, optimal procedural-based strategies in DLD and slower shifting to but similarly efficient use of optimal hypothesis-testing strategies. The dissociation is consistent with the Procedural Deficit Hypothesis of language disorders and supports the theoretical distinction of multiple category learning systems. These findings demonstrate that highly controlled experimental tasks assessing perceptual and cognitive abilities can relate to real-world challenges facing individuals with DLD in forming stable linguistic representations.

Stable, flexible, common, and distinct behaviors support rule-based and information-integration category learning

The ability to organize variable sensory signals into discrete categories is a fundamental process in human cognition thought to underlie many real-world learning problems. Decades of research suggests that two learning systems may support category learning and that categories with different distributional structures (rule-based, information-integration) optimally rely on different learning systems. However, it remains unclear how the same individual learns these different categories and whether the behaviors that support learning success are common or distinct across different categories. In two experiments, we investigate learning and develop a taxonomy of learning behaviors to investigate which behaviors are stable or flexible as the same individual learns rule-based and information-integration categories and which behaviors are common or distinct to learning success for these different types of categories. We found that some learning behaviors are stable in an individual across category learning tasks (learning success, strategy consistency), while others are flexibly task-modulated (learning speed, strategy, stability). Further, success in rule-based and information-integration category learning was supported by both common (faster learning speeds, higher working memory ability) and distinct factors (learning strategies, strategy consistency). Overall, these results demonstrate that even with highly similar categories and identical training tasks, individuals dynamically adjust some behaviors to fit the task and success in learning different kinds of categories is supported by both common and distinct factors. These results illustrate a need for theoretical perspectives of category learning to include nuances of behavior at the level of an individual learner.

Impaired and Spared Auditory Category Learning in Developmental Dyslexia

Categorization has a deep impact on behavior, but whether category learning is served by a single system or multiple systems remains debated. Here, we designed two well-equated nonspeech auditory category learning challenges to draw on putative procedural (information-integration) versus declarative (rule-based) learning systems among adult Hebrew-speaking control participants and individuals with dyslexia, a language disorder that has been linked to a selective disruption in the procedural memory system and in which phonological deficits are ubiquitous. We observed impaired information-integration category learning and spared rule-based category learning in the dyslexia group compared with the neurotypical group. Quantitative model-based analyses revealed reduced use of, and slower shifting to, optimal procedural-based strategies in dyslexia with hypothesis-testing strategy use on par with control participants. The dissociation is consistent with multiple category learning systems and points to the possibility that procedural learning inefficiencies across categories defined by complex, multidimensional exemplars may result in difficulty in phonetic category acquisition in dyslexia.

Using diverging predictions from classical and quantum models to dissociate between categorization systems

Quantum probability theory has successfully provided accurate descriptions of behavior in the areas of judgment and decision making, and here we apply the same principles to two category learning tasks, one task using information-integration categories and the other using rule-based categories. Since information-integration categories lack verbalizable descriptions, unlike rule-based ones, we assert that an information-integration categorization decision results from an intuitive probabilistic reasoning system characterized by quantum probability theory, whereas a rule-based categorization decision results from a logical, rational probabilistic reasoning system characterized classical probability theory. In our experiment, participants learn to categorize simple, visual stimuli as members of either category S or category K during an acquisition phase, and then rate the likelihood on a scale of 0 to 5 that a stimulus belongs to one category and subsequently perform the same likelihood rating for the other category during a transfer phase. Following the principle of complementarity in quantum theory, we expect the category likelihood ratings to exhibit order effects in the information-integration task, but not in the rule-based task. In the information-integration task, we found definitive order effects in the likelihood ratings. But, in the rule-based task, we found that the order effects in the likelihood ratings are not significant.

Auditory and visual category learning in musicians and nonmusicians.

Across three experiments, we compare the ability of amateur musicians and nonmusicians in learning artificial auditory and visual categories that can be described as either rule-based (RB) or information-integration (II) category structures. RB categories are optimally learned using a reflective reasoning process, whereas II categories are optimally learned by integrating information from two stimulus dimensions at a reflexive, predecisional processing stage. We found that musicians have selective advantages for learning auditory RB categories, specifically when they are instructed about the dimensions that define the categories. In Experiment 1, musicians enrolled in a music college demonstrated advantages over nonmusicians in learning auditory RB categories defined on frequency and duration dimensions but did not demonstrate differences in learning auditory II categories or either visual RB or II categories. In Experiment 2, a broader online sample of musicians who were not instructed about the dimensions did not demonstrate any advantage in auditory or visual learning. In Experiment 3, an online sample of musicians when given dimension instructions demonstrated early advantages over nonmusicians for auditory RB but not visual RB categories. Musicians do not demonstrate a global categorization advantage. Musicians' category learning advantage is limited to their modality of expertise, is enhanced with dimension instructions, and is specific to categories that can be described with verbalizable rules. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

When instructions don't help: Knowing the optimal strategy facilitates rule-based but not information-integration category learning.

Providing verbal or written instructions on how to perform optimally in a task is one of the most common ways to teach beginners. This practice is so widely accepted that scholarship primarily focuses on how to provide instructions, not whether these instructions help or not. Here we investigate the benefits of prior instruction on rule-based (RB) category-learning, in which the optimal strategy is a simple explicit rule, and information-integration (II) category-learning, in which the optimal strategy is similarity-based. Participants (N = 58) learned either RB or II categories, with or without verbal and written instruction about the optimal categorization strategy. Instructions significantly improved performance with RB categories but had no effect with II categories. The theoretical and practical implication of these results is discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Visual category learning: Navigating the intersection of rules and similarity.

Visual categorization is fundamental to expertise in a wide variety of disparate domains, such as radiology, art history, and quality control. The pervasive need to master visual categories has served as the impetus for a vast body of research dedicated to exploring how to enhance the learning process. The literature is clear on one point: no category learning technique is always superior to another. In the present review, we discuss how two factors moderate the efficacy of learning techniques. The first, category similarity, refers to the degree of featural overlap of exemplars. The second moderator, category type, concerns whether the features that define category membership can be mastered through learning processes that areimplicit/non-verbal (information-integration categories) or explicit/verbal (rule-based categories). The literature on each moderator has been conducted almost entirely in isolation, such that their potential interaction remains underexplored. We address this gap in the literature by reviewing empirical and theoretical evidence that these two moderators jointly influence the efficacy of learning techniques.

Differing effects of gain and loss feedback on rule-based and information-integration category learning.

Although most category-learning studies use feedback for training, little attention has been paid to how individuals use feedback value and framing of feedback as gains or losses to support learning. We compared learning of rule-based (RB) and information-integration (II) categories with point-valued feedback in which participants gained or lost higher point values for more difficult category members (those closer to the decision bound). We implemented point-valued feedback in four different conditions: Gain (earn points for correct answers), Loss (lose points for incorrect answers), Gain+Loss (earn points for correct answers and lose points for incorrect answers), and Control (accuracy feedback only without point gain or loss). Participants were trained until they reached criterion. Overall, point-valued feedback led to better learning than control conditions. However, the patterns differed across category-learning tasks. In the II task participants reached learning criterion fastest when they received both Gains and Losses. This is consistent with the reliance of II learning on reinforcement-based mechanisms and research showing common coding of gains and losses in neural regions underlying II learning. In contrast, in the RB task, participants reached criterion most rapidly when they received either Gains or Losses, but not both Gains and Losses together. The relative impairment in the Gain+Loss condition in RB learning may be due to conflicting executive function demands for interpreting and using the separate Gain and Loss information, and is consistent with reliance of RB learning on explicit hypothesis-testing mechanisms.

Left Inferior Frontal Gyrus Integrates Multisensory Information in Category Learning.

Humans are able to categorize things they encounter in the world (e.g., a cat) by integrating multisensory information from the auditory and visual modalities with ease and speed. However, how the brain learns multisensory categories remains elusive. The present study used functional magnetic resonance imaging to investigate, for the first time, the neural mechanisms underpinning multisensory information-integration (II) category learning. A sensory-modality-general network, including the left insula, right inferior frontal gyrus (IFG), supplementary motor area, left precentral gyrus, bilateral parietal cortex, and right caudate and globus pallidus, was recruited for II categorization, regardless of whether the information came from a single modality or from multiple modalities. Putamen activity was higher in correct categorization than incorrect categorization. Critically, the left IFG and left body and tail of the caudate were activated in multisensory II categorization but not in unisensory II categorization, which suggests this network plays a specific role in integrating multisensory information during category learning. The present results extend our understanding of the role of the left IFG in multisensory processing from the linguistic domain to a broader role in audiovisual learning.

Dissociations between rule-based and information-integration categorization are not caused by differences in task difficulty

In rule-based (RB) category-learning tasks, the optimal strategy is a simple explicit rule, whereas in information-integration (II) tasks, the optimal strategy is impossible to describe verbally. Many studies have reported qualitative dissociations between training and performance in RB and II tasks. Virtually all of these studies were testing predictions of the dual-systems model of category learning called COVIS. The most prominent alternative account to COVIS is that humans have one learning system that is used in all tasks, and that the observed dissociations occur because the II task is more difficult than the RB task. This article describes the first attempt to test this difficulty hypothesis against anything more than a single set of data. First, two novel predictions are derived that discriminate between the difficulty and multiple-systems hypotheses. Next, these predictions are tested against a wide variety of published categorization data. Overall, the results overwhelmingly reject the difficulty hypothesis and instead strongly favor the multiple-systems account of the many RB versus II dissociations.

Rule-based or information-integration category: processing of the self-face

This study investigated the differences between categorizing the self-face and other faces. Additionally, the study aimed to determine whether self-face categorization is consistent with dual-system categorization, such as in the competition between verbal and implicit systems (COVIS) model, or whether the self-face uses different categorizing methods than those used with other faces. The experiment adopted a dual-task paradigm to examine how participants complete rule-based/information-integration categorization tasks of the self-face/other faces and their method of processing when a numerical Stroop task was introduced. Results indicated that participants processed the self-face better than other faces in rule-based categorization, and there was no significant difference between categorization of the self-face and other faces during a single or dual task. This suggests there is a self-processing advantage in classification tasks; however, categorization based on face stimuli is not consistent with the COVIS model. Face categorization has a self-advantage effect, and categorization of human faces is distinctive from other types of categorization.

Auditory information-integration category learning in young children and adults

Adults outperform children on category learning that requires selective attention to individual dimensions (rule-based categories) due to their more highly developed working memory abilities, but much less is known about developmental differences in learning categories that require integration across multiple dimensions (information-integration categories). The current study investigated auditory information-integration category learning in 5- to 7-year-old children (n = 34) and 18- to 25-year-old adults (n = 35). Adults generally outperformed children during learning. However, some children learned the categories well and used strategies similar to those of adults, as assessed through decision-bound computational models. The results demonstrate that information-integration learning ability continues to develop throughout at least middle childhood. These results have implications for the development of mechanisms that contribute to speech category learning.

Dissociable learning processes, associative theory, and testimonial reviews: A comment on Smith and Church (2018).

Smith and Church (Psychonomic Bulletin & Review, 25, 1565-1584 2018) present a "testimonial" review of dissociable learning processes in comparative and cognitive psychology, by which we mean they include only the portion of the available evidence that is consistent with their conclusions. For example, they conclude that learning the information-integration category-learning task with immediate feedback is implicit, but do not consider the evidence that people readily report explicit strategies in this task, nor that this task can be accommodated by accounts that make no distinction between implicit and explicit processes. They also consider some of the neuroscience relating to information-integration category learning, but do not report those aspects that are more consistent with an explicit than an implicit account. They further conclude that delay conditioning in humans is implicit, but do not report evidence that delay conditioning requires awareness; nor do they present the evidence that conditioned taste aversion, which should be explicit under their account, can be implicit. We agree with Smith and Church that it is helpful to have a clear definition of associative theory, but suggest that their definition may be unnecessarily restrictive. We propose an alternative definition of associative theory and briefly describe an experimental procedure that we think may better distinguish between associative and non-associative processes.

The impact of training methodology and category structure on the formation of new categories from existing knowledge.

Categorization decisions are made thousands of times every day, and a typical adult knows tens of thousands of categories. It is thus relatively rare that adults learn new categories without somehow reorganizing pre-existing knowledge. Yet, most perceptual categorization research has investigated the ability to learn new categories without considering they relation to existing knowledge. In this article, we test the ability of young adults to merge already known categories into new categories as a function of training methodology and category structures using two experiments. Experiment 1 tests participants' ability to merge rule-based or information-integration categories that are either contiguous, semi-contiguous, or non-contiguous in perceptual space using a classification paradigm. Experiment 2 is similar Experiment 1 but uses a YES/NO learning paradigm instead. The results of both experiments suggest a strong effect of the contiguity of the merged categories in perceptual space that depends on the type of category representation that is learned. The type of category representation that is learned, in turn, depends on a complex interaction of the category structures and training task. We conclude by discussing the relevance of these results for categorization outside the laboratory.

Procedural-Memory, Working-Memory, and Declarative-Memory Skills Are Each Associated With Dimensional Integration in Sound-Category Learning.

This paper investigates relationships between procedural-memory, declarative-memory, and working-memory skills and adult native English speakers’ novel sound-category learning. Participants completed a sound-categorization task that required integrating two dimensions: one native (vowel quality), one non-native (pitch). Similar information-integration category structures in the visual and auditory domains have been shown to be best learned implicitly (e.g., Maddox et al., 2006). Thus, we predicted that individuals with greater procedural-memory capacity would better learn sound categories, because procedural memory appears to support implicit learning of new information and integration of dimensions. Seventy undergraduates were tested across two experiments. Procedural memory was assessed using a linguistic adaptation of the serial-reaction-time task (Misyak et al., 2010a,b). Declarative memory was assessed using the logical-memory subtest of the Wechsler Memory Scale-4th edition (WMS-IV; Wechsler, 2009). Working memory was assessed using an auditory version of the reading-span task (Kane et al., 2004). Experiment 1 revealed contributions of only declarative memory to dimensional integration, which might indicate not enough time or motivation to shift over to a procedural/integrative strategy. Experiment 2 gave twice the speech-sound training, distributed over 2 days, and also attempted to train at the category boundary. As predicted, effects of declarative memory were removed and effects of procedural memory emerged, but, unexpectedly, new effects of working memory surfaced. The results may be compatible with a multiple-systems account in which declarative and working memory facilitate transfer of control to the procedural system.

Semisupervised category learning facilitates the development of automaticity.

In the human category of learning, learning is studied in a supervised, an unsupervised, or a semisupervised way. The rare human semisupervised category of learning studies all focus on early learning. However, the impact of the semisupervised category learning late in learning, when automaticity develops, is unknown. Therefore, in Experiment 1, all participants were first trained on the information-integration category structure for 2 days until they reached an expert level. Afterwards, half of the participants learned in a supervised way and the other half in a semisupervised way over two successive days. Both groups received an equal number of feedback trials. Finally, all participants took part in a test day where they were asked to respond as quickly as possible. Participants were significantly faster on this test in the semisupervised group than in the supervised group. This difference was not found on day 2, implying that the no-feedback trials in the semisupervised condition facilitated automaticity. Experiment 2 was designed to test whether the higher number of trials in the semisupervised condition of Experiment 1 caused the faster response times. We therefore created an almost supervised condition where participants almost always received feedback (95%) and an almost unsupervised condition where participants almost never received feedback (5%). All conditions now contained an equal number of trials to the semisupervised condition of Experiment 1. The results show that receiving feedback almost always or almost never led to slower response times than the semisupervised condition of Experiment 1. This confirms the advantage of semisupervised learning late in learning.

Can categorical knowledge be used in visual search?

Smith, Redford, Gent, and Washburn (2005) have proposed a new categorization paradigm called the visual-search categorization task to study how display size affects categorization performance. Their results show that, in a wide range of conditions, category knowledge collapses as soon as multiple stimuli are simultaneously displayed in a scene. This result is surprising and important considering that humans parse and categorize objects from complex scenes on a daily basis. However, Smith et al. only studied one kind of category structure. This article presents the results of three experiments exploring the effect of display size on perceptual categorization as a function of category structure. We show that rule-based and information-integration categories are differently affected by display size in the visual search categorization task. For rule-based structures, target-present and target-absent trials are not much affected by display size. However, the effect of display size is bigger for information-integration category structures, and much more pronounced for target-absent trials than for target-present trials. A follow-up experiment shows that target redundancy (i.e., having more than one target in the display) does not improve performance with information-integration category structures. These results suggest that categories may be learned differently depending on their underlying structure, and that the resulting category representation may influence performance in the visual search categorization task.