Auditory information-integration category learning in young children and adults

Highlights

• Adults outperform young children during information-integration category learning.

• Children who show adult-level performance also use adult-like decision strategies.

• Children’s performance was not related to verbal working memory or age.

Abstract

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.

Introduction

Children demonstrate a remarkable ability to learn complex auditory categories, as illustrated by their acquisition of the complex speech categories of a native language. Within the first year of life, infants’ experience in a language community leads them to better distinguish phonetic categories from within the native language and to more poorly distinguish nonnative categories that do not align with the native language (Kuhl et al., 2006, Werker and Tees, 1984). This is thought to be a result of native-language speech category learning and the warping of perceptual space that accompanies it. This category learning continues throughout childhood, with phonetic categorization not fully adult-like until after at least 12 years of age (Idemaru and Holt, 2013, Nittrouer, 2004, Nittrouer et al., 1993, Zevin, 2012). Although it is clear that auditory categories continue to develop across childhood, very little is known about the developmental course of the learning mechanisms available to support such category learning.

Part of the reason for this is that it is impossible to control and manipulate children’s history of speech experience. For this reason, auditory category learning across artificial nonspeech categories can be a useful tool to reveal learning mechanisms available to conquer the important challenge of native-language speech category learning. In the current study, we investigated young (5- to 7-year-old) children’s nonspeech information-integration (II) auditory category learning, a learning challenge that has been compared to the demands of speech category learning, with targeted hypotheses developed from an influential model of adult category learning (Chandrasekaran, Koslov, & Maddox, 2014).

One well-studied model for understanding category learning, the competition between verbal and implicit systems (COVIS) model (Ashby, Alfonso-Reese, Turken, & Waldron, 1998), implicates at least two systems involved in category learning. Although primarily developed to account for adult visual category learning, the COVIS model recently has been expanded to auditory and speech category learning (Chandrasekaran et al., 2014, Chandrasekaran et al., 2014). To better understand the mechanisms that give rise to complex communication and speech perception, it is necessary to illuminate the cognitive processes involved in auditory category learning and to observe how these differ in children and adults.

The dual systems of the COVIS model are the explicit (reflective) and implicit (reflexive) systems. A large literature makes the case that the nature of the distributions of exemplars that define categories is important in determining which system is optimal for learning (for review, see Ashby & Maddox, 2011). When exemplars are sampled such that the optimal boundary distinguishing categories can be defined by a simple verbalizable rule across input dimensions that can be attended to selectively, the explicit system is advantaged in learning. Such rule-based categories are thought to be optimally learned through the explicit system and to involve selective attention and working memory processes mediated, at least in part, via involvement of the prefrontal cortex (PFC) (Ashby et al., 1998, Nomura et al., 2007). Another component of the explicit system, the head of the striatum’s caudate nucleus, is thought to be involved in feedback processing and switching among rules (Filoteo et al., 2005, Tricomi and Fiez, 2008). Thus, through hypothesis generation, rule selection and application, and switching among rules during learning, the explicit system is well matched to drive responses for rule-based category learning tasks that require selective attention to the individual dimensions defining category exemplars.

In contrast, an implicit procedural learning system is thought to dominate learning when category exemplars are defined by distributions that require integration across multiple dimensions—such that no single dimension can uniquely determine category membership (Ashby & Maddox, 2011). According to the dual systems approach implemented in the COVIS model, such II categories are optimally learned through procedural learning mechanisms of an implicit system (Ashby, Ell, & Waldron, 2003) that involves the body and tail of the caudate nucleus in the striatum (Filoteo and Maddox, 2007, Nomura et al., 2007). Moreover, because speech categories are highly multidimensional and not typically distinguished by single acoustic dimensions (Holt & Lotto, 2006), a case can be made for the involvement of the implicit system in speech category acquisition (Chandrasekaran et al., 2014, Yi et al., 2016).

The explicit system and implicit system are thought to be distinct and to compete during learning (Ashby et al., 1998). The explicit system is thought to be the default system that initially drives responses among adult learners. With additional training or experience through feedback, responses shift from being driven by the explicit system to being driven by the implicit system when the structure of the categories demands it (Ashby et al., 1998). This competitive dynamic is inferred from results demonstrating that unidimensional rule-based strategies tend to dominate early learning, even when integration strategies are optimal for the categorization challenge (Ashby and Crossley, 2010, Ashby and Maddox, 2011, Ashby et al., 1999). When the categories to be learned are II categories, rule-based strategies do not lead to success and feedback gradually pushes the implicit system to drive responses and motor system output (Ashby and Maddox, 2011, Ashby et al., 1998). The initial involvement of the explicit system is beneficial for rule-based category learning, which therefore typically proceeds more quickly than II category learning (Ashby & Maddox, 2011). For II categories there is a delay in engaging the optimal implicit learning system and thus learning is slower, with optimal strategies emerging later in learning (Ashby & Maddox, 2011).

The brain regions involved in the dual learning systems model undergo distinct patterns of development. The striatally mediated implicit category learning system matures earlier than the explicit system. The caudate nucleus matures early in development and is thought to be fully adult-like by 7 years of age (Casey et al., 2004). More generally, procedural memory and learning systems are thought to be fully adult-like by about 10 years of age, in contrast to the protracted developmental course of declarative memory systems involved in the explicit system such as the PFC and medial temporal lobe (Diamond, 2002, Finn et al., 2016).

The COVIS model depicts the implicit system as independent from the developmentally sensitive working memory abilities that it posits to influence categorization via the explicit system (Ashby and Maddox, 2011, Ashby et al., 1998). Instead, the implicit system is thought to build up category representations as procedurally learned stimulus–response associations acquired over the course of experience rather than via hypothesis testing. Thus, within the COVIS model, the striatally mediated implicit system is predicted to operate independently from involvement of PFC development and from developmental constraints on working memory capacity.

This independence from working memory abilities might suggest the possibility that children may learn II categories similarly to adults, in contrast to the protracted development of rule-based category learning (Reetzke, Maddox, & Chandrasekaran, 2016). Yet, despite this prediction, a study of visual II category learning in 8- to 12-year-old children found that although many children were able to optimally integrate across the dimensions during learning, adults outperformed children overall (Huang-Pollock, Maddox, & Karalunas, 2011). The authors argued that children’s poorer II category learning relative to adults may have been due to the developmentally immature PFC’s involvement in switching control from early involvement of the explicit system in the learning task (as posited by the COVIS model; Ashby et al., 1998) to the implicit system. However, 8- to 12-year-old children are arguably fairly far along the trajectory of PFC development. From this single study, it remains unclear whether younger children, who have less well-developed working memory and switching abilities, may approach II category learning differently than either adults or older children, as examined in previous studies.

Aside from this single developmental study, several other areas of research have investigated the role of working memory in II category learning by taxing working memory resources during learning or investigating individual differences in working memory capacity in adults. However, this empirical literature reveals a lack of consensus about the involvement of working memory in II category learning. Whereas some studies have shown that there is no effect of increasing working memory demands on II category learning in adults (Maddox et al., 2004, Maddox et al., 2004, Miles and Minda, 2011, Waldron and Ashby, 2001, Zeithamova and Maddox, 2007), other studies have reported that II category learning can actually be facilitated by increased working memory demand (Filoteo, Lauritzen, & Maddox, 2010; but see Newell, Moore, Wills, & Milton, 2013). Yet other studies have found II category learning to be impaired by increased working memory demand (Miles et al., 2014, Zeithamova and Maddox, 2006; but see Newell, Dunn, & Kalish, 2010).

It may be possible to resolve these seemingly contradictory effects in the literature through a developmental perspective regarding the nature of the shift of control from the explicit system to the implicit system. Several hypotheses about the nature of the interaction between the explicit and implicit systems can be proposed and tested by examining II category learning in young children and adults.

One hypothesis is that lower working memory resources may improve II category learning in some circumstances, perhaps by hastening the shift in control from the explicit system to the implicit system. By this hypothesis, young children should outperform adults in II category learning because the explicit system quickly taxes the available working memory resources and becomes less efficient, allowing the implicit system to drive responses earlier in learning. Thus, young children would show better performance than adults and a propensity to shift toward optimal integration strategies early in learning as the implicit system takes control.

An alternative hypothesis is that lower working memory resources may diminish II category learning by preventing the shift in control from the explicit system to the implicit system. With this hypothesis, young children should perform worse than adults in II category learning because there are not enough resources to shift the control between systems. This hypothesis suggests that the switch from the explicit system to the implicit system may involve working memory or other developmentally sensitive abilities. Thus, young children would show worse performance than adults and demonstrate an overreliance on suboptimal rule-based strategies because there is a failure in the shift from the explicit system to the implicit system. This impairment hypothesis is also consistent with a single system approach, whereby category learning occurs under a single system sensitive to working memory demands (Kalish et al., 2017, Lewandowsky et al., 2012, Newell et al., 2011). From a single system perspective, better working memory capacity and a better developed PFC should lead adults to outperform children in II category learning.

A third hypothesis is that lower working memory capacity will have no effect on II learning because the implicit system itself and the shift between the explicit and implicit systems are independent from working memory abilities and involvement of the PFC. With this hypothesis, young children and adults should learn II categories equivalently and demonstrate similar strategy patterns during learning.

These three opposing hypotheses center on the involvement of an explicit system and an implicit system in learning—a core tenant of the COVIS model. Because the current formulation of the COVIS model does not expand on the precise mechanism of the shift between these two systems during learning and whether working memory is involved or not, these opposing predictions are all generally consistent with the COVIS model. As a result, there is the need for empirical data that may help to resolve these theoretical ambiguities. In this spirit, the current study investigated the potential role of working memory in the shift between the learning systems more directly than previous research.

The current study extended prior developmental research on II category learning to a younger age group and into the auditory modality to understand the differences in performance and strategies in young children and adults. It also tested competing hypotheses regarding the involvement of working memory in II category learning that arise from contrasting findings in the prior literature to understand how the explicit and implicit systems might interact to influence learning at distinct stages of development. Because there have been no studies of auditory II category learning to inform the mechanisms that may be available to children to support the extended development of speech categories through childhood, it would be theoretically revealing to examine II category learning in young children.

We examined auditory II category learning in 5- to 7-year-old children and adults. We estimated decision strategies at play across category learning using decision-bound computational models to monitor the shift from the explicit system to the implicit system. Finally, we measured verbal working memory capacity as a measure of reliance on the explicit system and to observe how individual differences in working memory capacity might relate to performance (Zeithamova & Maddox, 2007).