Implicit and explicit category learning by capuchin monkeys (Cebus apella)

The Anticipatory and Task-Driven Nature of Visual Perception

Humans have a remarkable capacity to arrange and rearrange perceptual input according to different categorizations. This begs the question whether the categorization is exclusively a higher visual or amodal process, or whether categorization processes influence early visual areas as well. To investigate this we scanned healthy participants in a magnetic resonance imaging scanner during a conceptual decision task in which participants had to answer questions about upcoming images of animals. Early visual cortices (V1 and V2) contained information about the current visual input, about the granularity of the forthcoming categorical decision, as well as perceptual expectations about the upcoming visual stimulus. The middle temporal gyrus, the anterior temporal lobe, and the inferior frontal gyrus were also involved in the categorization process, constituting an attention and control network that modulates perceptual processing. These findings provide further evidence that early visual processes are driven by conceptual expectations and task demands.

Not All Procedural Learning Tasks Are Difficult for Adults With Developmental Language Disorder

Purpose The experiment reported here compared two hypotheses for the poor statistical and artificial grammar learning often seen in children and adults with developmental language disorder (DLD; also known as specific language impairment). The procedural learning deficit hypothesis states that implicit learning of rule-based input is impaired, whereas the sequential pattern learning deficit hypothesis states that poor performance is only seen when learners must implicitly compute sequential dependencies. The current experiment tested learning of an artificial grammar that could be learned via feature activation, as observed in an associatively organized lexicon, without computing sequential dependencies and should therefore be learnable on the sequential pattern learning deficit hypothesis, but not on the procedural learning deficit hypothesis. Method Adults with DLD and adults with typical language development (TD) listened to consonant-vowel-consonant-vowel familiarization words from one of two artificial phonological grammars: Family Resemblance (two out of three features) and a control (exclusive OR, in which both consonants are voiced OR both consonants are voiceless) grammar in which no learning was predicted for either group. At test, all participants rated 32 test words as to whether or not they conformed to the pattern in the familiarization words. Results Adults with DLD and adults with TD showed equal and robust learning of the Family Resemblance grammar, accepting significantly more conforming than nonconforming test items. Both groups who were familiarized with the Family Resemblance grammar also outperformed those who were familiarized with the OR grammar, which, as predicted, was learned by neither group. Conclusion Although adults and children with DLD often underperform, compared to their peers with TD, on statistical and artificial grammar learning tasks, poor performance appears to be tied to the implicit computation of sequential dependencies, as predicted by the sequential pattern learning deficit hypothesis.

A Dissociative Framework for Understanding Same-Different Conceptualization

Cognitive, comparative, and developmental psychologists have long been interested in humans' and animals' ability to respond to abstract relations. Cross-species research has used relational matching-to-sample (RMTS) tasks in which participants try to find stimulus pairs that "match" because they express the same abstract relation (same or different). Researchers seek to understand the cognitive processes that underlie successful matching, and the cognitive constraints that create species differences in these tasks. Here we describe a dissociative framework drawn from cognitive neuroscience. It has strong potential to illuminate the area of same-different conceptualization. It has already influenced comparative research on categorization and metacognition. This dissociative framework also shows that species differences in same-different conceptualization have resonance with species differences in other comparative domains.

Play to Win: Action Video Game Experience and Attention Driven Perceptual Exploration in Categorization Learning

Categorization learning is a fundamental and complex cognitive ability. The present EEG study examined how much action video gamers differ from non-gamers in the usage of visual exploration and attention driven perceptual analyses during a categorization learning task. Seventeen healthy right-handed non-gamers and 16 healthy right-handed action video gamers performed a visual categorization task with 14 ring stimuli, which were divided into two categories. All stimuli had the same structure but differed with respect to their color combinations and were forming two categories including a prototype, five typical stimuli and one exception. The exception shared most similarities with the prototype of the opposite group. Prototypes and typical stimuli were correctly categorized at an early stage of the experiment, whereas the successful categorization of exceptions occurred later. The behavioral data yield evidence that action video gamers perform correct categorizations of exceptions earlier than non-gamers. Additionally, groups differed with respect to differential expressions of the attention related P150 ERP component (early perceptual analysis) and the N170 ERP component, which reflected differential processing demands for the stimulus material. In comparison to non-gamers, the analyses of the eye movements yield for action video gamers different, more central fixations possibly indicating covert peripheral processing. For both groups fixations as well as saccades decrease and in the case of exceptions, one of the two segments that are decisive for correct categorization shows higher fixation rates at the end of the experiment. These findings indicate for both groups a learning process regarding the stimulus material. Regarding the group differences, we interpret the results to indicate that action video gamers show a different stimulus exploration, use an enhanced early perceptual analysis of the stimulus material and therefore may detect changes in objects faster and learned the belonging of the stimuli to their categories in an earlier trial phase.

The transfer of category knowledge by macaques (Macaca mulatta) and humans (Homo sapiens)

Cognitive psychologists distinguish implicit, procedural category learning (stimulus-response associations learned outside declarative cognition) from explicit-declarative category learning (conscious category rules). These systems are dissociated by category learning tasks with either a multidimensional, information-integration (II) solution or a unidimensional, rule-based (RB) solution. In the present experiments, humans and two monkeys learned II and RB category tasks fostering implicit and explicit learning, respectively. Then they received occasional transfer trials-never directly reinforced-drawn from untrained regions of the stimulus space. We hypothesized that implicit-procedural category learning-allied to associative learning-would transfer weakly because it is yoked to the training stimuli. This result was confirmed for humans and monkeys. We hypothesized that explicit category learning-allied to abstract category rules-would transfer robustly. This result was confirmed only for humans. That is, humans displayed explicit category knowledge that transferred flawlessly. Monkeys did not. This result illuminates the distinctive abstractness, stimulus independence, and representational portability of humans' explicit category rules. (PsycINFO Database Record

Categorization: The View from Animal Cognition

Exemplar, prototype, and rule theory have organized much of the enormous literature on categorization. From this theoretical foundation have arisen the two primary debates in the literature-the prototype-exemplar debate and the single system-multiple systems debate. We review these theories and debates. Then, we examine the contribution that animal-cognition studies have made to them. Animals have been crucial behavioral ambassadors to the literature on categorization. They reveal the roots of human categorization, the basic assumptions of vertebrates entering category tasks, the surprising weakness of exemplar memory as a category-learning strategy. They show that a unitary exemplar theory of categorization is insufficient to explain human and animal categorization. They show that a multiple-systems theoretical account-encompassing exemplars, prototypes, and rules-will be required for a complete explanation. They show the value of a fitness perspective in understanding categorization, and the value of giving categorization an evolutionary depth and phylogenetic breadth. They raise important questions about the internal similarity structure of natural kinds and categories. They demonstrate strong continuities with humans in categorization, but discontinuities, too. Categorization's great debates are resolving themselves, and to these resolutions animals have made crucial contributions.

Self-control assessments of capuchin monkeys with the rotating tray task and the accumulation task

Recent studies of delay of gratification in capuchin monkeys using a rotating tray (RT) task have shown improved self-control performance in these animals in comparison to the accumulation (AC) task. In this study, we investigated whether this improvement resulted from the difference in methods between the rotating tray task and previous tests, or whether it was the result of greater overall experience with delay of gratification tasks. Experiment 1 produced similar performance levels by capuchins monkeys in the RT and AC tasks when identical reward and temporal parameters were used. Experiment 2 demonstrated a similar result using reward amounts that were more similar to previous AC experiments with these monkeys. In Experiment 3, monkeys performed multiple versions of the AC task with varied reward and temporal parameters. Their self-control behavior was found to be dependent on the overall delay to reward consumption, rather than the overall reward amount ultimately consumed. These findings indicate that these capuchin monkeys' self-control capacities were more likely to have improved across studies because of the greater experience they had with delay of gratification tasks. Experiment 4 and Experiment 5 tested new, task-naïve monkeys on both tasks, finding more limited evidence of self-control, and no evidence that one task was more beneficial than the other in promoting self-control. The results of this study suggest that future testing of this kind should focus on temporal parameters and reward magnitude parameters to establish accurate measures of delay of gratification capacity and development in this species and perhaps others.

The time course of explicit and implicit categorization

Contemporary theory in cognitive neuroscience distinguishes, among the processes and utilities that serve categorization, explicit and implicit systems of category learning that learn, respectively, category rules by active hypothesis testing or adaptive behaviors by association and reinforcement. Little is known about the time course of categorization within these systems. Accordingly, the present experiments contrasted tasks that fostered explicit categorization (because they had a one-dimensional, rule-based solution) or implicit categorization (because they had a two-dimensional, information-integration solution). In Experiment 1, participants learned categories under unspeeded or speeded conditions. In Experiment 2, they applied previously trained category knowledge under unspeeded or speeded conditions. Speeded conditions selectively impaired implicit category learning and implicit mature categorization. These results illuminate the processing dynamics of explicit/implicit categorization.

Generalization of category knowledge and dimensional categorization in humans (Homo sapiens) and nonhuman primates (Macaca mulatta)

A theoretical framework within neuroscience distinguishes humans' implicit and explicit systems for category learning. We used a perceptual-categorization paradigm to ask whether nonhumans share elements of these systems. Participants learned categories that foster implicit or explicit categorization in humans, because they had a multidimensional, information-integration (II) solution or a unidimensional, rule-based (RB) solution. Then humans and macaques generalized their category knowledge to new, untested regions of the stimulus space. II generalization was impaired, suggesting that II category learning is conditioned and constrained by stimulus generalization to its original, trained stimulus contexts. RB generalization was nearly seamless, suggesting that RB category knowledge in humans and monkeys has properties that grant it some independence from the original, trained stimulus contexts. These findings raise the questions of (a) how closely macaques' dimensional categorization verges on humans' explicit/declarative categorization, and (b) how far macaques' dimensional categorization has advanced beyond that in other vertebrate species.

Exploring Potential Mechanisms Underlying the Lack of Uncertainty Monitoring in Capuchin Monkeys

In a widely used animal-metacognition paradigm, monkeys are positively reinforced with food for correct classifications of stimuli as sparse or dense and punished with timeouts for incorrect responses, but they also have access to an "uncertainty" response that moves them to the next trial without either of these forms of feedback. Rhesus monkeys use this uncertainty response most often for trials on which they are at greatest risk for making an error, suggesting that they are monitoring their ability to make these classifications. Capuchin monkeys do not succeed to the same degree on these tasks-conceivably as a result of differential contingencies in place in all existing studies between the sparse/dense responses (food delivery or timeout) and the uncertainty response (avoidance of a timeout but also no chance for food reward). Here, we used a novel variation of this task in which the outcomes of the three response classes (sparse, dense, uncertain) were functionally equivalent. All responses simply determined the delay interval before presentation of a second task (matching-to-sample), and that task yielded potential food rewards. Overall, capuchin monkeys used the dense and sparse responses appropriately, including some animals that had no prior experience in performing this classification task. However, none used the uncertainty response appropriately even when it was placed on the same contingency plane as the dense and sparse responses. This suggests that the failure of capuchin monkeys to use an uncertainty response is not the result of that response producing a qualitatively different outcome compared to the dense and sparse responses.

The Role of Corticostriatal Systems in Speech Category Learning

One of the most difficult category learning problems for humans is learning nonnative speech categories. While feedback-based category training can enhance speech learning, the mechanisms underlying these benefits are unclear. In this functional magnetic resonance imaging study, we investigated neural and computational mechanisms underlying feedback-dependent speech category learning in adults. Positive feedback activated a large corticostriatal network including the dorsolateral prefrontal cortex, inferior parietal lobule, middle temporal gyrus, caudate, putamen, and the ventral striatum. Successful learning was contingent upon the activity of domain-general category learning systems: the fast-learning reflective system, involving the dorsolateral prefrontal cortex that develops and tests explicit rules based on the feedback content, and the slow-learning reflexive system, involving the putamen in which the stimuli are implicitly associated with category responses based on the reward value in feedback. Computational modeling of response strategies revealed significant use of reflective strategies early in training and greater use of reflexive strategies later in training. Reflexive strategy use was associated with increased activation in the putamen. Our results demonstrate a critical role for the reflexive corticostriatal learning system as a function of response strategy and proficiency during speech category learning.

Mechanisms of object recognition: what we have learned from pigeons

Behavioral studies of object recognition in pigeons have been conducted for 50 years, yielding a large body of data. Recent work has been directed toward synthesizing this evidence and understanding the visual, associative, and cognitive mechanisms that are involved. The outcome is that pigeons are likely to be the non-primate species for which the computational mechanisms of object recognition are best understood. Here, we review this research and suggest that a core set of mechanisms for object recognition might be present in all vertebrates, including pigeons and people, making pigeons an excellent candidate model to study the neural mechanisms of object recognition. Behavioral and computational evidence suggests that error-driven learning participates in object category learning by pigeons and people, and recent neuroscientific research suggests that the basal ganglia, which are homologous in these species, may implement error-driven learning of stimulus-response associations. Furthermore, learning of abstract category representations can be observed in pigeons and other vertebrates. Finally, there is evidence that feedforward visual processing, a central mechanism in models of object recognition in the primate ventral stream, plays a role in object recognition by pigeons. We also highlight differences between pigeons and people in object recognition abilities, and propose candidate adaptive specializations which may explain them, such as holistic face processing and rule-based category learning in primates. From a modern comparative perspective, such specializations are to be expected regardless of the model species under study. The fact that we have a good idea of which aspects of object recognition differ in people and pigeons should be seen as an advantage over other animal models. From this perspective, we suggest that there is much to learn about human object recognition from studying the "simple" brains of pigeons.

Toward a dual-learning systems model of speech category learning

More than two decades of work in vision posits the existence of dual-learning systems of category learning. The reflective system uses working memory to develop and test rules for classifying in an explicit fashion, while the reflexive system operates by implicitly associating perception with actions that lead to reinforcement. Dual-learning systems models hypothesize that in learning natural categories, learners initially use the reflective system and, with practice, transfer control to the reflexive system. The role of reflective and reflexive systems in auditory category learning and more specifically in speech category learning has not been systematically examined. In this article, we describe a neurobiologically constrained dual-learning systems theoretical framework that is currently being developed in speech category learning and review recent applications of this framework. Using behavioral and computational modeling approaches, we provide evidence that speech category learning is predominantly mediated by the reflexive learning system. In one application, we explore the effects of normal aging on non-speech and speech category learning. Prominently, we find a large age-related deficit in speech learning. The computational modeling suggests that older adults are less likely to transition from simple, reflective, unidimensional rules to more complex, reflexive, multi-dimensional rules. In a second application, we summarize a recent study examining auditory category learning in individuals with elevated depressive symptoms. We find a deficit in reflective-optimal and an enhancement in reflexive-optimal auditory category learning. Interestingly, individuals with elevated depressive symptoms also show an advantage in learning speech categories. We end with a brief summary and description of a number of future directions.

Cross-modal information integration in category learning

An influential theoretical perspective describes an implicit category-learning system that associates regions of perceptual space with response outputs by integrating information preattentionally and predecisionally across multiple stimulus dimensions. In this study, we tested whether this kind of implicit, information-integration category learning is possible across stimulus dimensions lying in different sensory modalities. Humans learned categories composed of conjoint visual-auditory category exemplars comprising a visual component (rectangles varying in the density of contained lit pixels) and an auditory component (in Exp. 1, auditory sequences varying in duration; in Exp. 2, pure tones varying in pitch). The categories had either a one-dimensional, rule-based solution or a two-dimensional, information-integration solution. Humans could solve the information-integration category tasks by integrating information across two stimulus modalities. The results demonstrated an important cross-modal form of sensory integration in the service of category learning, and they advance the field's knowledge about the sensory organization of systems for categorization.

Prototypes, exemplars, and the natural history of categorization

The article explores-from a utility/adaptation perspective-the role of prototype and exemplar processes in categorization. The author surveys important category tasks within the categorization literature from the perspective of the optimality of applying prototype and exemplar processes. Formal simulations reveal that organisms will often (not always!) receive more useful signals about category belongingness if they average their exemplar experience into a prototype and use this as the comparative standard for categorization. This survey then provides the theoretical context for considering the evolution of cognitive systems for categorization. In the article's final sections, the author reviews recent research on the performance of nonhuman primates and humans in the tasks analyzed in the article. Diverse species share operating principles, default commitments, and processing weaknesses in categorization. From these commonalities, it may be possible to infer some properties of the categorization ecology these species generally experienced during cognitive evolution.

Deferred feedback sharply dissociates implicit and explicit category learning

The controversy over multiple category-learning systems is reminiscent of the controversy over multiple memory systems. Researchers continue to seek paradigms to sharply dissociate explicit category-learning processes (featuring category rules that can be verbalized) from implicit category-learning processes (featuring learned stimulus-response associations that lie outside declarative cognition). We contribute a new dissociative paradigm, adapting the technique of deferred-rearranged reinforcement from comparative psychology. Participants learned matched category tasks that had either a one-dimensional, rule-based solution or a multidimensional, information-integration solution. They received feedback either immediately or after each block of trials, with the feedback organized such that positive outcomes were grouped and negative outcomes were grouped (deferred-rearranged reinforcement). Deferred reinforcement qualitatively eliminated implicit, information-integration category learning. It left intact explicit, rule-based category learning. Moreover, implicit-category learners facing deferred-rearranged reinforcement turned by default and information-processing necessity to rule-based strategies that poorly suited their nominal category task. The results represent one of the strongest explicit-implicit dissociations yet seen in the categorization literature.

Implicit and explicit categorization: a tale of four species

Categorization is essential for survival, and it is a widely studied cognitive adaptation in humans and animals. An influential neuroscience perspective differentiates in humans an explicit, rule-based categorization system from an implicit system that slowly associates response outputs to different regions of perceptual space. This perspective is being extended to study categorization in other vertebrate species, using category tasks that have a one-dimensional, rule-based solution or a two-dimensional, information-integration solution. Humans, macaques, and capuchin monkeys strongly dimensionalize perceptual stimuli and learn rule-based tasks more quickly. In sharp contrast, pigeons learn these two tasks equally quickly. Pigeons represent a cognitive system in which the commitment to dimensional analysis and category rules was not strongly made. Their results may reveal the character of the ancestral vertebrate categorization system from which that of primates emerged. The primate results establish continuity with human cognition, suggesting that nonhuman primates share aspects of humans' capacity for explicit cognition. The emergence of dimensional analysis and rule learning could have been an important step in primates' cognitive evolution.

Pigeons' categorization may be exclusively nonanalytic

Recent theoretical and empirical developments in human category learning have differentiated an analytic, rule-based system of category learning from a nonanalytic system that integrates information across stimulus dimensions. In the present study, the researchers applied this theoretical distinction to pigeons' category learning. Pigeons learned to categorize stimuli varying in the tilt and width of their internal striping. The matched category problems had either a unidimensional (rule-based) or multidimensional (information-integration) solution. Whereas humans and nonhuman primates strongly dimensionalize these stimuli and learn rule-based tasks far more quickly than information-integration tasks, pigeons learned the two tasks equally quickly to the same accuracy level. Pigeons may represent a cognitive system in which the commitment to dimensional analysis and category rules was not strongly made. Their performance could suggest the character of the ancestral vertebrate categorization system from which that of primates emerged.