Effects of Induced Mood on Attention and Decision Strategies in Risky Choice.

The effects of induced incidental moods on patterns of information search and decision outcomes were investigated in a risky choice task with mixed-domain problems. Viewing of short videos was used to induce either happy or sad mood in participants, who then made choices between pairs of options consisting of a probabilistic gain coupled with a probabilistic loss. Eyetracking measures of information search, specifically frequencies of transitions between key aspects of the decision alternatives, were analyzed and related to use of heuristic or analytic compensatory strategies. Data were also gathered in a control condition, where participants were instructed to use an EV-calculation strategy, a prototypical integrative compensatory strategy. Results showed significant differences in choices and attention transitions between the EV-instruction and the induced mood conditions, but minimal differences between the happy and sad induced mood conditions. Participants in the induced mood conditions showed relatively more evidence of heuristic strategy use, but analytic strategies remained the modal strategy in all conditions. Importantly, key types of attention transitions were shown to reliably predict the frequency of observed choices consistent with optimal (EV- maximizing) and certain heuristic strategies.

The influence of sleep on emotional and cognitive processing is primarily trait- (but not state-) dependent.

Human studies of sleep and cognition have established thatdifferent sleep stages contribute to distinct aspects of cognitive and emotional processing. However, since the majority of these findings are based on single-night studies, it is difficult to determine whether such effects arise due to individual, between-subject differences in sleep patterns, or from within-subject variations in sleep over time. In the current study, weinvestigated the longitudinal relationship between sleep patterns and cognitive performance by monitoring both in parallel, daily, for a week. Using two cognitive tasks - one assessing emotional reactivity to facial expressions and the other evaluating learning abilities in a probabilistic categorization task - we found that between-subjectdifferences in the average time spent in particular sleep stages predicted performance in these tasks far more than within-subject daily variations. Specifically, the typical time individualsspent in Rapid-Eye Movement (REM) sleep and Slow-Wave Sleep (SWS) was correlated to their characteristic measures of emotional reactivity, whereas the typical time spent in SWS and non-REM stages 1 and 2 was correlated to their success in category learning. These effects were maintained even when sleep properties werebased onbaseline measures taken prior to the experimental week. In contrast, within-subject daily variations in sleep patterns only contributed to overnight difference in one particular measure of emotional reactivity. Thus, we conclude that the effects of natural sleep onemotional cognition and categorylearning are more trait-dependent than state-dependent, and suggest ways to reconcile these results with previous findings in the literature.

Striving for perfection and falling short: The influence of goals on probability matching.

Probability matching in sequential prediction tasks is argued to occur because participants implicitly adopt the unrealistic goal of perfect prediction of sequences. Biases in the understanding of randomness then lead them to generate mixed rather than pure sequences of predictions in attempting to achieve this goal. In Study 1, N = 350 participants predicted 100 trials of a binary-outcome event. Two factors were manipulated: probability bias (the outcomes were equiprobable or distributed with a 75%-25% bias), and goal type-namely, whether single-trial predictions or the perfect prediction of four-trial sequences was emphasized and rewarded. As we hypothesized, predicting sequences led to more probability-matching behavior than did predicting single trials, for both the bias and no-bias conditions. In Study 1B, we added a control condition to distinguish the effects of the grouped presentation of trials from the effects of sequence-level perfect-prediction rewards. The results supported goal type rather than presentation format as the cause of the Study 1 differences in matching between the sequence and single-trial conditions. In Study 2, all participants (N = 300) predicted the outcomes for five-trial sequences, but with different goal levels being rewarded: 60%, 80%, or 100% correct predictions. The 100% goal resulted in the most probability matching, as hypothesized. Paradoxically, using the inferior strategy of probability matching may be triggered by adopting an unrealistic perfect-prediction goal.

Cognitive tools shape thought: diagrams in design.

Thinking often entails interacting with cognitive tools. In many cases, notably design, the predominant tool is the page. The page allows externalizing, organizing, and reorganizing thought. Yet, the page has its own properties that by expressing thought affect it: path, proximity, place, and permanence. The effects of these properties were evident in designs of information systems created by students Paths were interpreted as routes through components. Proximity was used to group subsystems. Horizontal position on the page was used to express temporal sequence and vertical position to reflect real-world spatial position. The permanence of designs on the page guided but also constrained generation of alternative designs. Cognitive tools both reflect and affect thought.

Conventional wisdom: negotiating conventions of reference enhances category learning.

Collaborators generally coordinate their activities through communication, during which they readily negotiate a shared lexicon for activity-related objects. This social-pragmatic activity both recruits and affects cognitive and social-cognitive processes ranging from selective attention to perspective taking. We ask whether negotiating reference also facilitates category learning or might private verbalization yield comparable facilitation? Participants in three referential conditions learned to classify imaginary creatures according to combinations of functional features-nutritive and destructive-that implicitly defined four categories. Remote partners communicated in the Dialogue condition. In the Monologue condition, participants recorded audio descriptions for their own later use. Controls worked silently. Dialogue yielded better category learning, with wider distribution of attention. Monologue offered no benefits over working silently. We conclude that negotiating reference compels collaborators to find communicable structure in their shared activity; this social-pragmatic constraint accelerates category learning and likely provides much of the benefit recently ascribed to learning labeled categories.

Observed attention allocation processes in category learning.

In two empirical studies of attention allocation during category learning, we investigate the idea that category learners learn to allocate attention optimally across stimulus dimensions. We argue that "optimal" patterns of attention allocation are model or process specific, that human learners do not always optimize attention, and that one reason they fail to do so is that under certain conditions the cost of information retrieval or use may affect the attentional strategy adopted by learners. We empirically investigate these issues using a computer interface incorporating an "information-board" display that collects detailed information on participants' patterns of attention allocation and information search during learning trials. Experiment 1 investigated the effects on attention allocation of distributing perfectly diagnostic features across stimulus dimensions versus within one dimension. The overall pattern of viewing times supported the optimal attention allocation hypothesis, but a more detailed analysis produced evidence of instance- or category-specific attention allocation, a phenomenon not predicted by prominent computational models of category learning. Experiment 2 investigated the strategies adopted by category learners encountering redundant perfectly predictive cues. Here, the majority of participants learned to distribute attention optimally in a cost-benefit sense, allocating attention primarily to only one of the two perfectly predictive dimensions. These results suggest that learners may take situational costs and benefits into account, and they present challenges for computational models of learning that allocate attention by weighting stimulus dimensions.