Dual Learning Systems Research Articles

Effect of explicit dimensional instruction on speech category learning.

Learning nonnative speech categories is often considered a challenging task in adulthood. This difficulty is driven by cross-language differences in weighting critical auditory dimensions that differentiate speech categories. For example, previous studies have shown that differentiating Mandarin tonal categories requires attending to dimensions related to pitch height and direction. Relative to native speakers of Mandarin, the pitch direction dimension is underweighted by native English speakers. In the current study, we examined the effect of explicit instructions (dimension instruction) on native English speakers' Mandarin tone category learning within the framework of a dual-learning systems (DLS) model. This model predicts that successful speech category learning is initially mediated by an explicit, reflective learning system that frequently utilizes unidimensional rules, with an eventual switch to a more implicit, reflexive learning system that utilizes multidimensional rules. Participants were explicitly instructed to focus and/or ignore the pitch height dimension, the pitch direction dimension, or were given no explicit prime. Our results show that instruction instructing participants to focus on pitch direction, and instruction diverting attention away from pitch height, resulted in enhanced tone categorization. Computational modeling of participant responses suggested that instruction related to pitch direction led to faster and more frequent use of multidimensional reflexive strategies and enhanced perceptual selectivity along the previously underweighted pitch direction dimension.

Rule-based and information-integration categorization during an incidental learning task

Research in visual category learning supports the existence of dual category-learning systems with distinct neurobiological substrates. Rule-based category learning is engaged by category input distributions that vary orthogonally in perceptual space whereas information integration learning is engaged when categories are defined across multiple input dimensions. Investigators have recently begun to explore these dual systems in audition, including phonetic category learning. However, investigations of dual category learning systems have tended to use category training tasks in which participants actively search for category-relevant dimensions, make overt category labeling decisions, and receive explicit feedback about the correctness of their responses. Recent neuroimaging research highlights the fact that overt category training tasks like this engage learning systems that differ from those engaged by more incidental category learning. Since most natural category learning occurs under more incidental conditions, it is important to understand how training tasks interact with category learning systems. The aim of the present research is to investigate the interaction of input distribution and task. We examine nonspeech auditory category learning across the same perceptual input space for rule-based and information-integration categories in incidental and overt training tasks to characterize how training task interacts with input category distributions.

Accounting for negative automaintenance in pigeons: a dual learning systems approach and factored representations.

Animals, including Humans, are prone to develop persistent maladaptive and suboptimal behaviours. Some of these behaviours have been suggested to arise from interactions between brain systems of Pavlovian conditioning, the acquisition of responses to initially neutral stimuli previously paired with rewards, and instrumental conditioning, the acquisition of active behaviours leading to rewards. However the mechanics of these systems and their interactions are still unclear. While extensively studied independently, few models have been developed to account for these interactions. On some experiment, pigeons have been observed to display a maladaptive behaviour that some suggest to involve conflicts between Pavlovian and instrumental conditioning. In a procedure referred as negative automaintenance, a key light is paired with the subsequent delivery of food, however any peck towards the key light results in the omission of the reward. Studies showed that in such procedure some pigeons persisted in pecking to a substantial level despite its negative consequence, while others learned to refrain from pecking and maximized their cumulative rewards. Furthermore, the pigeons that were unable to refrain from pecking could nevertheless shift their pecks towards a harmless alternative key light. We confronted a computational model that combines dual-learning systems and factored representations, recently developed to account for sign-tracking and goal-tracking behaviours in rats, to these negative automaintenance experimental data. We show that it can explain the variability of the observed behaviours and the capacity of alternative key lights to distract pigeons from their detrimental behaviours. These results confirm the proposed model as an interesting tool to reproduce experiments that could involve interactions between Pavlovian and instrumental conditioning. The model allows us to draw predictions that may be experimentally verified, which could help further investigate the neural mechanisms underlying theses interactions.

Dual learning processes underlying human decision-making in reversal learning tasks: functional significance and evidence from the model fit to human behavior

Humans are capable of correcting their actions based on actions performed in the past, and this ability enables them to adapt to a changing environment. The computational field of reinforcement learning (RL) has provided a powerful explanation for understanding such processes. Recently, the dual learning system, modeled as a hybrid model that incorporates value update based on reward-prediction error and learning rate modulation based on the surprise signal, has gained attention as a model for explaining various neural signals. However, the functional significance of the hybrid model has not been established. In the present study, we used computer simulation in a reversal learning task to address functional significance in a probabilistic reversal learning task. The hybrid model was found to perform better than the standard RL model in a large parameter setting. These results suggest that the hybrid model is more robust against the mistuning of parameters compared with the standard RL model when decision-makers continue to learn stimulus-reward contingencies, which can create abrupt changes. The parameter fitting results also indicated that the hybrid model fit better than the standard RL model for more than 50% of the participants, which suggests that the hybrid model has more explanatory power for the behavioral data than the standard RL model.

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.

Sistema de aprendizaje dual: ¿Una respuesta a la empleabilidad de los jóvenes?

The crisis of youth employment points out only one aspect of the labor market because of the dimensions of its own. Around the world a “dual learning system” has emerged. This system seeks to remove some of the obstacles that young people face when trying to insert themselves into the workforce: the lack of skills and mostly, work experience. This model combines theoretical learning at school with hands-on training at a company in such a way that it enhances the skills acquired by the trainees to respond to the needs of the company while at the same time, young people can better their own employability. The system has been successful in the countries where it has emerged (after a series of historical-cultural events and has developed over the span of 100 years). This model is quite complex: it requires building up the right kind of relation between school and companies and a detailed planning to ensure both the provision and the quality of the training, in addition to engaging social participation. With this, the question itself is whether the system has the same results in other countries.

Elevated depressive symptoms enhance reflexive but not reflective auditory category learning

In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed.

Modelling individual differences in the form of Pavlovian conditioned approach responses: a dual learning systems approach with factored representations.

Reinforcement Learning has greatly influenced models of conditioning, providing powerful explanations of acquired behaviour and underlying physiological observations. However, in recent autoshaping experiments in rats, variation in the form of Pavlovian conditioned responses (CRs) and associated dopamine activity, have questioned the classical hypothesis that phasic dopamine activity corresponds to a reward prediction error-like signal arising from a classical Model-Free system, necessary for Pavlovian conditioning. Over the course of Pavlovian conditioning using food as the unconditioned stimulus (US), some rats (sign-trackers) come to approach and engage the conditioned stimulus (CS) itself – a lever – more and more avidly, whereas other rats (goal-trackers) learn to approach the location of food delivery upon CS presentation. Importantly, although both sign-trackers and goal-trackers learn the CS-US association equally well, only in sign-trackers does phasic dopamine activity show classical reward prediction error-like bursts. Furthermore, neither the acquisition nor the expression of a goal-tracking CR is dopamine-dependent. Here we present a computational model that can account for such individual variations. We show that a combination of a Model-Based system and a revised Model-Free system can account for the development of distinct CRs in rats. Moreover, we show that revising a classical Model-Free system to individually process stimuli by using factored representations can explain why classical dopaminergic patterns may be observed for some rats and not for others depending on the CR they develop. In addition, the model can account for other behavioural and pharmacological results obtained using the same, or similar, autoshaping procedures. Finally, the model makes it possible to draw a set of experimental predictions that may be verified in a modified experimental protocol. We suggest that further investigation of factored representations in computational neuroscience studies may be useful.

Tests of a dual-system model of speech category learning

In the visual domain, more than two decades of work posits the existence of dual category learning systems. The reflective system uses working memory to develop and test rules for classifying in an explicit fashion. The reflexive system operates by implicitly associating perception with actions that lead to reinforcement. Dual-systems models posit 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 second language (L2) speech learning has not been systematically examined. Here monolingual, native speakers of American English were trained to categorize Mandarin tones produced by multiple talkers. Our computational modeling approach demonstrates that learners use reflective and reflexive strategies during tone category learning. Successful learners use talker-dependent, reflective analysis early in training and reflexive strategies by the end of training. Our results demonstrate that dual-learning systems are operative in L2 speech learning. Critically, learner strategies directly relate to individual differences in category learning success.

Dual-learning systems during speech category learning

Dual-system models of visual category learning posit the existence of an explicit, hypothesis-testing reflective system, as well as an implicit, procedural-based reflexive system. The reflective and reflexive learning systems are competitive and neurally dissociable. Relatively little is known about the role of these domain-general learning systems in speech category learning. Given the multidimensional, redundant, and variable nature of acoustic cues in speech categories, our working hypothesis is that speech categories are learned reflexively. To this end, we examined the relative contribution of these learning systems to speech learning in adults. Native English speakers learned to categorize Mandarin tone categories over 480 trials. The training protocol involved trial-by-trial feedback and multiple talkers. Experiments 1 and 2 examined the effect of manipulating the timing (immediate vs. delayed) and information content (full vs. minimal) of feedback. Dual-system models of visual category learning predict that delayed feedback and providing rich, informational feedback enhance reflective learning, while immediate and minimally informative feedback enhance reflexive learning. Across the two experiments, our results show that feedback manipulations that targeted reflexive learning enhanced category learning success. In Experiment 3, we examined the role of trial-to-trial talker information (mixed vs. blocked presentation) on speech category learning success. We hypothesized that the mixed condition would enhance reflexive learning by not allowing an association between talker-related acoustic cues and speech categories. Our results show that the mixed talker condition led to relatively greater accuracies. Our experiments demonstrate that speech categories are optimally learned by training methods that target the reflexive learning system.

Dual systems of speech category learning across the lifespan.

Although categorization is fundamental to speech processing, little is known about the learning systems that mediate auditory categorization and even less is known about changes across the life span. Vision research supports dual-learning systems that are grounded in neuroscience and are partially dissociable. The reflective, rule-based system is prefrontally mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive, information-integration system is striatally mediated and operates by implicitly associating perception with actions that lead to reinforcement. We examine the extent to which dual-learning systems mediate auditory and speech learning in younger and older adults. We examined auditory category learning when a rule-based strategy (Experiment 1) or information-integration strategy (Experiment 2) was optimal, and found an age-related rule-based deficit, but intact information-integration learning. Experiment 3 examined natural auditory category learning, and found an age-related performance deficit. Computational modeling suggested that this was attributable to older adults' persistent reliance on suboptimal, unidimensional strategies when 2-dimensional strategies were optimal. Working memory capacity was also found to be associated with improved rule-based and natural auditory category learning, but not information-integration category learning. These results suggest that dual-learning systems are operative in speech category learning across the life span, and that performance deficits, when present, are attributable to deficiencies in frontally mediated, rule-based processes.

The Proust effect and the evolution of a dual learning system

AbstractProust's madeleine illustrates the automatic nature of associative learning. Although we agree with Mitchell et al. that no compelling scientific proof for this effect has yet been reported in humans, evolutionary constraints suggest that it should not be discarded: There is no reason by which natural selection should favor individuals who lose a fast and automatic survival tool.

Learning and consolidation of novel spoken words.

Two experiments explored the neural mechanisms underlying the learning and consolidation of novel spoken words. In Experiment 1, participants learned two sets of novel words on successive days. A subsequent recognition test revealed high levels of familiarity for both sets. However, a lexical decision task showed that only novel words learned on the previous day engaged in lexical competition with similar-sounding existing words. Additionally, only novel words learned on the previous day exhibited faster repetition latencies relative to unfamiliar controls. This overnight consolidation effect was further examined using fMRI to compare neural responses to existing and novel words learned on different days prior to scanning (Experiment 2). This revealed an elevated response for novel compared with existing words in left superior temporal gyrus (STG), inferior frontal and premotor regions, and right cerebellum. Cortical activation was of equivalent magnitude for unfamiliar novel words and items learned on the day of scanning but significantly reduced for novel words learned on the previous day. In contrast, hippocampal responses were elevated for novel words that were entirely unfamiliar, and this elevated response correlated with postscanning behavioral measures of word learning. These findings are consistent with a dual-learning system account in which there is a division of labor between medial-temporal systems that are involved in initial acquisition and neocortical systems in which representations of novel spoken words are subject to overnight consolidation.

Maternal attenuation of hypothalamic paraventricular nucleus norepinephrine switches avoidance learning to preference learning in preweanling rat pups

Infant rats learn to prefer stimuli paired with pain, presumably due to the importance of learning to prefer the caregiver to receive protection and food. With maturity, a more ‘adult-like’ learning system emerges that includes the amygdala and avoidance/fear learning. The attachment and ‘adult-like’ systems appear to co-exist in older pups with maternal presence engaging the attachment system by lowering corticosterone (CORT). Specifically, odor–shock conditioning (11 odor–0.5 mA shock trials) in 12-day-old pups results in an odor aversion, although an odor preference is learned if the mother is present during conditioning. Here, we propose a mechanism to explain pups ability to ‘switch’ between the dual learning systems by exploring the effect of maternal presence on hypothalamic paraventricular nucleus (PVN) neural activity, norepinephrine (NE) levels and learning. Maternal presence attenuates both PVN neural activity and PVN NE levels during odor–shock conditioning. Intra-PVN NE receptor antagonist infusion blocked the odor aversion learning with maternal absence, while intra-PVN NE receptor agonist infusion permitted odor aversion learning with maternal presence. These data suggest maternal control over pup learning acts through attenuation of PVN NE to reduce the CORT required for pup odor aversion learning. Moreover, these data also represent pups' continued maternal dependence for nursing, while enabling aversion learning outside the nest to prepare for pups future independent living.