A Bayesian Theory of Sequential Causal Learning and Abstract Transfer

Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause‐effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre‐training (or even post‐training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue‐outcome co‐occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge.     

Specific effects of acute moderate exercise on cognitive control

The main issue of this study was to determine whether cognitive control is affected by acute moderate exercise. Twelve participants [4 females (VO_{2 max} = 42 ml/kg/min) and 8 males (VO_{2 max} = 48 ml/kg/min)] performed a Simon task while cycling at a carefully controlled workload intensity corresponding to their individual ventilatory threshold. The distribution-analytical technique and the delta plot analysis [Ridderinkhof, K. R. (2002). Activation and suppression in conflict tasks: Empirical clarification through distributional analyses. In W. Prinz & B. Hommel (Eds.), Common mechanisms in perception and action. Attention and performance (Vol. 19, pp. 494–519). Oxford: Oxford University Press.] were used to assess the role of selective response inhibition in resolving response conflict. Results showed that cognitive processes appeared to be differently affected by acute moderate exercise. Reaction time results confirmed that performance is better (faster without change in accuracy) when the cognitive task is performed simultaneously with exercise. Between-trial adjustments (post-conflict and post-error) highlighted that cognitive control adjustments are also fully efficient during exercise. However, the effect of congruency (Simon effect) appeared to be more pronounced during exercise compared to rest which suggests that the response inhibition is deteriorated during exercise. The present findings suggest that acute moderate exercise differently affects some specific aspects of cognitive functions.     

A computational model of fractionated conflict-control mechanisms in task-switching

A feature of human cognition is the ability to monitor and adjust one's own behavior under changing circumstances. A dynamic balance between controlled and rapid responding is needed to adapt to a fluctuating environment. We suggest that cognitive control may include, among other things, two distinct processes. Incongruent stimuli may drive top-down facilitation of task-relevant responses to bias performance toward exploitation vs. exploration. Task or response switches may generally slow responses to bias toward accuracy vs. speed and exploration vs. exploitation. Behavioral results from a task switching study demonstrate these two distinct processes as revealed by higher-order sequential effects. A computational model implements the two conflict-control mechanisms, which allow it to capture many complex and novel sequential effects. Lesion studies with the model demonstrate that the model is unable to capture these effects without the conflict-control loops and show how each monitoring component modulates cognitive control. The results suggest numerous testable predictions regarding the neural substrates of cognitive control.     

Sequential sampling models of human text classification

Text classification involves deciding whether or not a document is about a given topic. It is an important problem in machine learning, because automated text classifiers have enormous potential for application in information retrieval systems. It is also an interesting problem for cognitive science, because it involves real world human decision making with complicated stimuli. This paper develops two models of human text document classification based on random walk and accumulator sequential sampling processes. The models are evaluated using data from an experiment where participants classify text documents presented one word at a time under task instructions that emphasize either speed or accuracy, and rate their confidence in their decisions. Fitting the random walk and accumulator models to these data shows that the accumulator provides a better account of the decisions made, and a “balance of evidence” measure provides the best account of confidence. Both models are also evaluated in the applied information retrieval context, by comparing their performance to established machine learning techniques on the standard Reuters‐21578 corpus. It is found that they are almost as accurate as the benchmarks, and make decisions much more quickly because they only need to examine a small proportion of the words in the document. In addition, the ability of the accumulator model to produce useful confidence measures is shown to have application in prioritizing the results of classification decisions.     

Discontinuity in the enumeration of sequentially presented auditory and visual stimuli

The seeking of discontinuity in enumeration was recently renewed because Cowan [Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24, 87–185; Cowan, N. (2005). Working memory capacity. Hove: Psychology Press] suggested that it allows evaluating the limit of the focus of attention, currently estimated at four items. A strong argument in favour of a general constraint of the cognitive system is that similar discontinuities should be observed in modalities different from the classic simultaneous presentation of visual objects. Recently, data were provided on tactile stimuli, but the authors diverged in their conclusion about the existence of such discontinuity [Gallace, A., Tan, H. Z., & Spence, C. (2006). Numerosity judgments for tactile stimuli distributed over the body surface. Perception, 35(2), 247–266; Riggs, K. J., Ferrand, L., Lancelin, D., Fryziel, L., Dumur, G., & Simpson, A. (2006). Subitizing in tactile perception. Psychological Science, 17(4), 271–272]. Following a similar rationale, our study aimed at evaluating discontinuity in the enumeration of auditory and visual stimuli presented sequentially. The clear and similar discontinuity observed in error rates, response times and given responses for both modalities favours the general capacity limit view, but also questions the size of this capacity, because the discontinuity occurred here at size 2. However, the masking of stimuli in sensory memory could not be entirely discarded.     

Criteria instability and the isolated option effect

In two-stage choices, decision makers often compare a new (isolated) option with the winner from the first stage. Previous research has identified a choice advantage for an isolated option, ostensibly due to loss aversion. We propose an alternative mechanism suggesting that instability of the criteria used in each choice stage is the main driver of the isolated option effect. Results from a series of experiments support the criteria instability account and not loss aversion as the explanation for the isolated option effect.     

Using diffusion models to understand clinical disorders

Sequential sampling models provide an alternative to traditional analyses of reaction times and accuracy in two-choice tasks. These models are reviewed with particular focus on the diffusion model (Ratcliff, 1978) and how its application can aid research on clinical disorders. The advantages of a diffusion model analysis over traditional comparisons are shown through simulations and a simple lexical decision experiment. Application of the diffusion model to a clinically relevant topic is demonstrated through an analysis of data from nonclinical participants with high- and low-trait anxiety in a recognition memory task. The model showed that after committing an error, participants with high-trait anxiety responded more cautiously by increasing their boundary separation, whereas participants with low-trait anxiety did not. The article concludes with suggestions for ways to improve and broaden the application of these models to studies of clinical disorders.     

Auditory cueing facilitates temporospatial accuracy of sequential movements

Effectively executing goal-directed behaviours requires both temporal and spatial accuracy. Previous work has shown that providing auditory cues enhances the timing of upper-limb movements. Interestingly, alternate work has shown beneficial effects of multisensory cueing (i.e., combined audiovisual) on temporospatial motor control. As a result, it is not clear whether adding visual to auditory cues can enhance the temporospatial control of sequential upper-limb movements specifically. The present study utilized a sequential pointing task to investigate the effects of auditory, visual, and audiovisual cueing on temporospatial errors. Eighteen participants performed pointing movements to five targets representing short, intermediate, and large movement amplitudes. Five isochronous auditory, visual, or audiovisual priming cues were provided to specify an equal movement duration for all amplitudes prior to movement onset. Movement time errors were then computed as the difference between actual and predicted movement times specified by the sensory cues, yielding delta movement time errors (ΔMTE). It was hypothesized that auditory-based (i.e., auditory and audiovisual) cueing would yield lower movement time errors compared to visual cueing. The results showed that providing auditory relative to visual priming cues alone reduced ΔMTE particularly for intermediate amplitude movements. The results further highlighted the beneficial impact of unimodal auditory cueing for improving visuomotor control in the absence of significant effects for the multisensory audiovisual condition.     

A multi-attribute extension of the secretary problem: Theory and experiments

We present a generalization of a class of sequential search problems with ordinal ranks, referred to as “secretary” problems, in which applicants are characterized by multiple attributes. We then present a procedure for numerically computing the optimal search policy and test it in two experiments with incentive-compatible payoffs. With payoffs dependent on the absolute ranks of the attributes, we test the optimal search model with both symmetric (Experiment 1) and asymmetric (Experiment 2) search problems. In both experiments we find that, relative to the optimal search policy, subjects stop the search too early. Our results show that this bias is largely driven by a propensity to stop prematurely on applicants of intermediate (relative) quality.     

A computational model of sequential movement learning with a signal mimicking dopaminergic neuron activities

We present a computational model of approach learning in a simulated maze environment. Our maze environment and training method mimics those used in the experimental literature. We show that our model learns the correct sequence of six decisions that lead to the location of positive reinforcement and in a manner consistent with experimental observations. Our model exhibits many properties that are characteristic of animal learning in maze environments including delay conditioning, secondary conditioning, and backward chaining. Finally, we map our model to the basal ganglia and show that a signal in our model that is responsible for learning has the same temporal properties as dopamine, the neurotransmitter believed to play an important part in learning decision sequences.