Tom Beesley

When goals conflict with values: Counterproductive attentional and oculomotor capture by reward-related stimuli

Attention provides the gateway to cognition, by selecting certain stimuli for further analysis. Recent research demonstrates that whether a stimulus captures attention is not determined solely by its physical properties, but is malleable, being influenced by our previous experience of rewards obtained by attending to that stimulus. Here we show that this influence of reward learning on attention extends to task-irrelevant stimuli. In a visual search task, certain stimuli signaled the magnitude of available reward, but reward delivery was not contingent on responding to those stimuli. Indeed, any attentional capture by these critical distractor stimuli led to a reduction in the reward obtained. Nevertheless, distractors signaling large reward produced greater attentional and oculomotor capture than those signaling small reward. This counterproductive capture by task-irrelevant stimuli is important because it demonstrates how external reward structures can produce patterns of behavior that conflict with task demands, and similar processes may underlie problematic behavior directed toward real-world rewards.

How successful is errorless learning in supporting memory for high and low-level knowledge in dementia?

Errorless learning has been shown to be very successful in the rehabilitation of memory problems particularly in patients with severe forms of memory impairment. Much of this research has focused on testing knowledge of specific details studied, ignoring any additional, higher-level knowledge that patients may have acquired during the learning process. Hence, it is pertinent to ask whether errorless learning is equally successful in the acquisition of high and low-level knowledge. In this paper, we present results of several studies comparing the effectiveness of errorless and standard trial-and-error methods in acquisition of high and low-level knowledge in people diagnosed with dementia and non-impaired controls. In Study 1, participants were asked to learn novel face–name–occupation associations; and knowledge across a range of levels, from very general (i.e., high-level) to very specific (i.e., low-level), was examined. For patients with probable Alzheimers disease and controls there was evidence of increased benefit from errorless training in general, but the technique was most beneficial for patients attempting to retrieve specific detail. Study 2 was conducted to address the problem raised by the failure in Study 1 to manipulate learning condition at our highest knowledge level. This novel manipulation was successful, but neither of the patients received the standard benefit from errorless training. Study 3, involving a small group of dementia patients with mixed diagnoses, was conducted to replicate findings from Study 1. Results from the group analysis confirmed that the benefit obtained from errorless learning increased as a function of knowledge specificity, but again several patients failed to show a consistent effect of learning condition. Implications for use of the errorless technique are discussed. This research was funded by the Northcott Devon Medical Association, Exeter, UK.

Attention and associative learning in humans: An integrative review.

This article presents a comprehensive survey of research concerning interactions between associative learning and attention in humans. Four main findings are described. First, attention is biased toward stimuli that predict their consequences reliably (learned predictiveness). This finding is consistent with the approach taken by Mackintosh (1975) in his attentional model of associative learning in nonhuman animals. Second, the strength of this attentional bias is modulated by the value of the outcome (learned value). That is, predictors of high-value outcomes receive especially high levels of attention. Third, the related but opposing idea that uncertainty may result in increased attention to stimuli (Pearce & Hall, 1980), receives less support. This suggests that hybrid models of associative learning, incorporating the mechanisms of both the Mackintosh and Pearce-Hall theories, may not be required to explain data from human participants. Rather, a simpler model, in which attention to stimuli is determined by how strongly they are associated with significant outcomes, goes a long way to account for the data on human attentional learning. The last main finding, and an exciting area for future research and theorizing, is that learned predictiveness and learned value modulate both deliberate attentional focus, and more automatic attentional capture. The automatic influence of learning on attention does not appear to fit the traditional view of attention as being either goal-directed or stimulus-driven. Rather, it suggests a new kind of “derived” attention.

Overt attention and predictiveness in human contingency learning.

Two experiments used eye-tracking procedures to investigate the relationship between attention and associative learning in human participants. These experiments found greater overt attention to cues experienced as predictive of the outcomes with which they were paired, than to cues experienced as nonpredictive. Moreover, this attentional bias persisted into a second training phase when all cues were equally predictive of the outcomes with which they were paired, and it was accompanied by a related bias in the rate of learning about these cues. These findings are consistent with the attentional model of associative learning proposed by Mackintosh (1975), but not with that proposed by Pearce and Hall (1980).

Stereotype formation: biased by association.

We propose that biases in attitude and stereotype formation might arise as a result of learned differences in the extent to which social groups have previously been predictive of behavioral or physical properties. Experiments 1 and 2 demonstrate that differences in the experienced predictiveness of groups with respect to evaluatively neutral information influence the extent to which participants later form attitudes and stereotypes about those groups. In contrast, Experiment 3 shows no influence of predictiveness when using a procedure designed to emphasize the use of higher level reasoning processes, a finding consistent with the idea that the root of the predictiveness bias is not in reasoning. Experiments 4 and 5 demonstrate that the predictiveness bias in formation of group beliefs does not depend on participants making global evaluations of groups. These results are discussed in relation to the associative mechanisms proposed by Mackintosh (1975) to explain similar phenomena in animal conditioning and associative learning.

The Influence of Blocking on Overt Attention and Associability in Human Learning

Previous studies have demonstrated a retardation in the rate of novel learning about previously blocked cues as compared to appropriate control cues. We report an experiment investigating whether this retardation in novel learning about a blocked cue is accompanied by a reduction in attention to this cue, as anticipated by attentional theories of associative learning. Consistent with these theories, eye gaze measures revealed a reduction in overt attention to the blocked cue both during the compound training phase of the blocking procedure, and also during novel learning with respect to new outcomes. Moreover, the extent of the bias in overt attention away from blocked cues was positively correlated with the subsequent reduction in rate of novel learning about these cues.

Blocking of human causal learning involves learned changes in stimulus processing

Several theories of associative learning propose that blocking reflects changes in the processing devoted to learning about cues. The results of the only direct test of this suggestion in human learning (Kruschke & Blair, 2000) could equally well be explained in terms of, among others, interference in learning or memory. The present study tested this suggestion in a situation in which processing-change and interference accounts predict opposing results. Results support the idea that blocking in human learning can reflect a change in processing of the cues involved.

The effect of predictive history on the learning of sub-sequence contingencies

Two experiments demonstrated that the prior predictive history of a cue governs the extent to which that cue engages in sequence learning. Using a serial reaction time task, we manipulated the predictiveness of the stimulus locations (cues) with respect to the location of the stimulus on the next trial (outcome), such that half of the cues were good predictors of their outcomes, whilst the other half were poorer predictors. Following this, all cues were then paired with novel outcomes. Learning about those cues that were previously established as good predictors proceeded more rapidly than learning for those cues previously established as poor predictors. When the simple recurrent network is modified to include a variable associability parameter, the effects are easily modelled.

Uncertainty and predictiveness determine attention to cues during human associative learning

Prior research has suggested that attention is determined by exploiting what is known about the most valid predictors of outcomes and exploring those stimuli that are associated with the greatest degree of uncertainty about subsequent events. Previous studies of human contingency learning have revealed evidence for one or other of these processes, but differences in the designs and procedures of these studies make it difficult to pinpoint the crucial determinant of whether attentional exploitation or exploration will dominate. Here we present two studies in which we systematically manipulated both the predictiveness of cues and uncertainty regarding the outcomes with which they were associated. This allowed us to demonstrate, for the first time, evidence of both attentional exploration and exploitation within the same experiment. Moreover, while the effect of predictiveness persisted to influence the rate of novel learning about the same cues in a second stage, the effect of uncertainty did not. This suggests that attentional exploration is more sensitive to a change of context than is exploitation. The pattern of data is simulated with a hybrid attentional model.

Learned Predictiveness Effects in Humans : A Function of Learning, Performance, or Both?

Many previous studies of animal and human learning indicate a processing advantage for cues previously experienced as good predictors of outcomes over those experienced as poorer predictors. Four studies of human associative learning investigated whether learned predictiveness acts at the level of learning (modulating the rate at which cue-outcome associations form), performance (modulating the strength of behavioral responses), or both. In Experiments 1-3, it was found that retrospectively altering the learned predictiveness of cues influenced responding to those cues, demonstrating that learned predictiveness influences performance. Experiment 4 indicates that learned predictiveness also influences learning by demonstrating that the learned predictiveness of a cue affects the acquisition of an association between a novel cue and the outcome with which it is paired.