Associative Learning Account Research Articles

The development of body representations: an associative learning account.

Representing one's own body is of fundamental importance to interact with our environment, yet little is known about how body representations develop. One account suggests that the ability to represent one's own body is present from birth and supports infants' ability to detect similarities between their own and others' bodies. However, in recent years evidence has been accumulating for alternative accounts that emphasize the role of multisensory experience obtained through acting and interacting with our own body in the development of body representations. Here, we review this evidence, and propose an integrative account that suggests that through experience, infants form multisensory associations that facilitate the development of body representations. This associative account provides a coherent explanation for previous developmental findings, and generates novel hypotheses for future research.

Learning to fear outgroups: An associative learning explanation for the development and reduction of intergroup anxiety

AbstractPavlovian conditioning is a form of associative learning shown to contribute to the development and reduction of clinical anxiety and fear, and more recently, intergroup anxiety and fear. The current review provides a synthesis of the literature on associative learning of fear toward outgroups. Findings are reviewed that outline how fear toward the outgroup, relative to the ingroup, can be preferentially learnt and is resistant to extinction‐based techniques. Novel future research directions for intergroup anxiety are then identified based upon previous research on clinical anxiety. It is proposed that processes known to enhance the extinction of specific phobia should be investigated with social stimuli. Specifically, it is argued that exploring cognitive factors during extinction and conducting extinction in multiple contexts may provide new avenues to pursue intergroup harmony through reduced intergroup anxiety. The review concludes by suggesting innovative research designs are needed to validate an associative learning account of fear toward outgroups outside of experimental settings.

Emotion processing fails to modulate putative mirror neuron response to trained visuomotor associations

Recent neuroimaging studies have demonstrated that activation of the putative human mirror neuron system (MNS) can be elicited via visuomotor training. This is generally interpreted as supporting an associative learning account of the mirror neuron system (MNS) that argues against the ontogeny of the MNS to be an evolutionary adaptation for social cognition. The current study assessed whether a central component of social cognition, emotion processing, would influence the MNS activity to trained visuomotor associations, which could support a broader role of the MNS in social cognition. Using functional magnetic resonance imaging (fMRI), we assessed repetition suppression to the presentation of stimulus pairs involving a simple hand action and a geometric shape that was either congruent or incongruent with earlier association training. Each pair was preceded by an image of positive, negative, or neutral emotionality. In support of an associative learning account of the MNS, repetition suppression was greater for trained pairs compared with untrained pairs in several regions, primarily supplementary motor area (SMA) and right inferior frontal gyrus (rIFG). This response, however, was not modulated by the valence of the emotional images. These findings argue against a fundamental role of emotion processing in the mirror neuron response, and are inconsistent with theoretical accounts linking mirror neurons to social cognition.

Increasing Predictive Estimations Without Further Learning

The peak of learned responding normally occurs at the learning stimulus itself, but can shift to a different stimulus after discriminative learning. This provides important information about the nature of the generalization mechanism, and reveals alternative pathways through which learned responses can increase. Over two experiments, we established the peak-shift effect in a human predictive learning paradigm. Participants were asked to predict the occurrence of a neutral outcome (drawing of a lightning bolt) based on preceding geometrical figures (rings of different sizes). During learning, the middle-sized ring was sometimes followed by the outcome, whereas a larger ring was never followed by the outcome. At test, we presented larger and smaller rings (Experiment 1), or only a slightly smaller ring (Experiment 2). We consistently observed highest prediction of the outcome to the slightly smaller ring. Predictive estimations in humans can reach their height to stimuli that have never actually participated in the learning experiences. We argue that the results are most in line with an associative learning account, rather than an adaptation-level or a rule-learning account.

Reconciling genetic evolution and the associative learning account of mirror neurons through data-acquisition mechanisms.

An associative learning account of mirror neurons should not preclude genetic evolution of its underlying mechanisms. On the contrary, an associative learning framework for cognitive development should seek heritable variation in the learning rules and in the data-acquisition mechanisms that construct associative networks, demonstrating how small genetic modifications of associative elements can give rise to the evolution of complex cognition.

An associative learning account of branding effects of sponsorship

For sponsors, the essence of commercial sponsorship is the right of being associated with the sponsored organisation, which can later be leveraged for branding purposes. The branding power of sponsorship relies on its associative power, and consumers learn sponsorship in two qualitatively distinctive ways: evaluative conditioning and predictive learning. These two processes can lead to different branding outcomes (e.g., a decrease in brand loyalty, but an increase in perceived quality). This study stresses the limitations of traditional theoretical accounts in explaining branding effects of sponsorship and proposes that associative learning would be the fundamental branding mechanism of sponsorship marketing. Specifically, this study examines the multivariate relationships between a set of learning variables (i.e., sport involvement, event involvement, event attitude, emotional experience, brand knowledge, and brand-event relatedness) and a set of branding effect variables (i.e., perceived quality, attitudinal loyalty, and behavioural intention). Through a series of canonical correlation analyses on a survey data, we found evidence to support the associative learning account of branding effects.

Influences of Cognitive Control on Numerical Cognition—Adaptation by Binding for Implicit Learning

Recently, an associative learning account of cognitive control has been suggested (Verguts & Notebaert, 2009). In this so-called adaptation by binding theory, Hebbian learning of stimulus-stimulus and stimulus-response associations is assumed to drive the adaptation of human behavior. In this study, we evaluated the validity of the adaptation-by-binding account for the case of implicit learning of regularities within a stimulus set (i.e., the frequency of specific unit digit combinations in a two-digit number magnitude comparison task) and their association with a particular response. Our data indicated that participants indeed learned these regularities and adapted their behavior accordingly. In particular, influences of cognitive control were even able to override the numerical distance effect--one of the most robust effects in numerical cognition research. Thus, the general cognitive processes involved in two-digit number magnitude comparison seem much more complex than previously assumed. Multi-digit number magnitude comparison may not be automatic and inflexible but influenced by processes of cognitive control being highly adaptive to stimulus set properties and task demands on multiple levels.

Out of control: An associative account of congruency effects in sequence learning

The demonstration of a sequential congruency effect in sequence learning has been offered as evidence for control processes that act to inhibit automatic response tendencies (Jiménez, Lupiáñez, & Vaquero, 2009) via unconscious conflict monitoring. Here we propose an alternative interpretation of this effect based on the associative learning of chains of sequenced contingencies. This account is supported by simulations with a Simple Recurrent Network, an associative (connectionist) model of sequence learning. We argue that the control- and associative-based accounts differ in their predictions concerning the magnitude of the sequential congruency effect across training. These predictions are tested by reanalysing data from a study by Shanks, Wilkinson, and Channon (2003). The results support the associative learning account which explains the sequential congruency effect without appealing to control processes (either conscious or unconscious).

Correspondences between what infants see and know about causal and self-propelled motion

The associative learning account of how infants identify human motion rests on the assumption that this knowledge is derived from statistical regularities seen in the world. Yet, no catalog exists of what visual input infants receive of human motion, and of causal and self-propelled motion in particular. In this manuscript, we demonstrate that the frequency with which causal agency and self-propelled motion appear in the visual environment predicts infants’ understanding of these motions. In an observational study, an infant wearing a head-mounted camera saw people act as agents in causal events three times more often than he saw people engaged in self-propelled motion. Subsequent experiments with the habituation paradigm revealed that infants begin to generalize self-propulsion to agents in causal events between 10 and 14months of age. However, infants cannot generalize causal agency to a self-propelled object at 14 or 18months unless the object exhibits additional cues to animacy. The results are discussed within a domain-general framework of learning about human action.

Selectivity in Infant Social Referencing.

In laboratory studies of social referencing, infants as young as 12 months have been reported to prefer looking at the experimenter over the caregiver for clarifying information. From an expertise perspective, such behavior could be interpreted as if the infant seeks information from others and can discriminate between persons who have or do not have relevant information to provide in the laboratory. If this is the case, higher order cognitive capacities might be involved in infant selectivity in looking in social referencing situations. However, it has also been proposed that associative learning processes might account for infant preferences in such studies. To examine whether an expertise perspective or if more basic learning processes best explain infant selectivity in looking, 40 12-month-old infants were assigned to 1 of 2 comparable conditions. The experimenter versus the caregiver presented an ambiguous toy and delivered positive information about the toy. The infants preferred to look at the experimenter and they regulated their behavior more in accordance with information coming from the experimenter. Thus, an associative learning account cannot explain infant preferences in looking. The results are discussed in terms of an expertise perspective.

The development of a general associative learning account of skill acquisition in a relative arrival-time judgment task.

Current theory assumes that individuals only use information from the immediate environment to perform relative arrival-time judgment tasks. This article presents a theoretical analysis of the memory requirements of this task. The authors present an analysis of the inputs to the memory system and the processes that map those inputs onto outputs. The analysis generates a set of predictions regarding the specificity of transfer and the role of context during learning. In 3 experiments, participants decided whether pairs of aircraft would violate a minimum separation standard or pass each other safely. Participants were presented with pairs of aircraft in which properties of the pair varied along 3 structural and 3 surface dimensions. Contexts were defined by the co-occurrence of specific values along stimulus dimensions and the use of a neutral label. The results suggest that transfer was limited by the dimensions that were varied in training and the context in which those dimensions were varied. The discussion focuses on the problems that complex tasks like relative judgment pose for associative learning mechanisms and the development of precise models of cognition.

The etiology of phobias: a nonassociative account

Theories of the origin and maintenance of fears and phobias have had a profound influence on the kinds of treatments employed in the phobic disorders. In view of this influence, the present review considers the considerable controversy surrounding the major etiological models. First, the various forms of the associative learning account are examined. It is argued that each of these approaches has failed to provide a comprehensive account of the onset of the phobic disorders. Second, evidence for a nonassociative account is considered. It is argued that this latter model can more adequately account for the majority of experimental and clinical findings in most phobic conditions. Future directions for research on the etiology of phobias are discussed.

Connectionist Accounts of the Inverse Base-rate Effect in Categorization

Two experiments replicated the ‘inverse base-rate effect’ reported in categorization studies by Medin & Edelson. In Experiment I subjects were presented with the case histories of hypothetical medical patients and had to diagnose which illness they thought each patient was suffering from on the basis of the symptoms they had. On some trials (AB-→1), patients had two symptoms, A and B, and the correct diagnosis was disease 1. On other trials (AC-→2)patients had symptoms A and C and the correct diagnosis was disease 2. Feedback was provided on each trial about the correct diagnosis. Symptom A was common to both diseases, but subjects saw more AB-→1 than AC-→2 trials. On subsequent test trials subjects were more likely to choose disease 1 than disease 2 as their diagnosis for patients who had just symptom A, in accordance with the base-rates of the two diseases. However, on test trials where patients had both symptoms B and C, which had never previously occurred together, subjects were more likely to choose disease 2, contrary not only to the underlying base-rates, but also to the predictions of a well-established connectionist model of categorization. A variety of alternative connectionist models are considered. In Experiment 2 it was found that a necessary condition for the inverse base-rate effect is that symptom A is more strongly associated with disease 1 than disease 2, which is consistent with an associative learning account which appeals to the notion of competition between symptoms. A new connectionist learning model, using a learning algorithm based on Wagner's theory of associative learning, is shown to be able to reproduce the main results.