A hierarchy of cortical responses to sequence violations in three-month-old infants

The adult human brain quickly adapts to regular temporal sequences, and emits a sequence of novelty responses when these regularities are violated. These novelty responses have been interpreted as error signals that reflect the difference between the incoming signal and predictions generated at multiple cortical levels. Do infants already possess such a hierarchy of violation-detection mechanisms? Using high-density recordings of event-related potentials during an auditory local–global violation paradigm, we show that three-month-old infants process novelty in temporal sequences at two distinct levels. Violations of local expectancies, such as perceiving a deviant vowel “a” after repeated presentation of another vowel i-i-i, elicited an early auditory mismatch response. Conversely, violations of global expectancies, such as hearing the rare sequence a-a-a-a instead of the frequent sequence a-a-a-i, modulated this early mismatch response and led to a late frontal negative slow wave, whose cortical sources included the left inferior frontal region. These results suggest that the infant brain already possesses two dissociable systems for temporal sequence learning.     

Revisiting Chinese‐speaking children's understanding of argument structure

A causative verb is likely to appear in a sentence with two noun arguments, whereas a noncausative verb tends to appear in a sentence with a single argument. The present research investigates from what point children learning Chinese begin to show this knowledge of argument structure. Two‐, 3‐, 4‐, and 5‐year‐old children were tested using a forced‐choice pointing task. The results showed that Chinese‐speaking children aged 2 years could associate a transitive construction with a causative event, whereas they were not able to map an intransitive construction to a noncausative event even after reaching 5 years of age. The reason why Chinese children have such difficulty in learning knowledge of intransitive construction is discussed, focusing on (a) the semantic properties of certain intransitive verbs, which have been found not only in Chinese but also in other languages, and (b) the ellipsis of arguments, which is characteristic of Chinese.     

Imminent Danger? Probabilistic Classification Learning of Threat-Related Information in Obsessive-Compulsive Disorder

A tendency to overestimate threat has been shown in individuals with OCD. We tested the hypothesis that this bias in judgment is related to difficulties in learning probabilistic associations between events. Thirty participants with OCD and 30 matched healthy controls completed a learning experiment involving 2 variants of a probabilistic classification learning task. In the neutral weather-prediction task, rainy and sunny weather had to be predicted. In the emotional task danger of an epidemic from virus infection had to be predicted (epidemic-prediction task). Participants with OCD were as able as controls to improve their prediction of neutral events across learning trials but scored significantly below healthy controls on the epidemic-prediction task. Lower performance on the emotional task variant was significantly related to a heightened tendency to overestimate threat. Biased information processing in OCD might thus hamper corrective experiences regarding the probability of threatening events.     

What Do the Theologically Educated Look Like?

What do the theologically educated look like? Nine outcomes of a theological education are suggested that respond to this question, outcomes particularly pertinent to the contemporary cultural setting and mission challenge of Western Europe. These outcomes are compared with the nine learning outcomes that the Church of England uses at the present time to assess candidates for ordained ministry. In the light of this comparison some broad recommendations are made for future emphases in theological education.     

Children Use Temporal Cues to Learn Causal Directionality

The ability to learn the direction of causal relations is critical for understanding and acting in the world. We investigated how children learn causal directionality in situations in which the states of variables are temporally dependent (i.e., autocorrelated). In Experiment 1, children learned about causal direction by comparing the states of one variable before versus after an intervention on another variable. In Experiment 2, children reliably inferred causal directionality merely from observing how two variables change over time; they interpreted Y changing without a change in X as evidence that Y does not influence X. Both of these strategies make sense if one believes the variables to be temporally dependent. We discuss the implications of these results for interpreting previous findings. More broadly, given that many real‐world environments are characterized by temporal dependency, these results suggest strategies that children may use to learn the causal structure of their environments.     

Implicit Transfer of Reversed Temporal Structure in Visuomotor Sequence Learning

Some spatio‐temporal structures are easier to transfer implicitly in sequential learning. In this study, we investigated whether the consistent reversal of triads of learned components would support the implicit transfer of their temporal structure in visuomotor sequence learning. A triad comprised three sequential button presses ([1][2][3]) and seven consecutive triads comprised a sequence. Participants learned sequences by trial and error, until they could complete it 20 times without error. Then, they learned another sequence, in which each triad was reversed ([3][2][1]), partially reversed ([2][1][3]), or switched so as not to overlap with the other conditions ([2][3][1] or [3][1][2]). Even when the participants did not notice the alternation rule, the consistent reversal of the temporal structure of each triad led to better implicit transfer; this was confirmed in a subsequent experiment. These results suggest that the implicit transfer of the temporal structure of a learned sequence can be influenced by both the structure and consistency of the change.     

SAwSu: An Integrated Model of Associative and Reinforcement Learning

Successfully explaining and replicating the complexity and generality of human and animal learning will require the integration of a variety of learning mechanisms. Here, we introduce a computational model which integrates associative learning (AL) and reinforcement learning (RL). We contrast the integrated model with standalone AL and RL models in three simulation studies. First, a synthetic grid‐navigation task is employed to highlight performance advantages for the integrated model in an environment where the reward structure is both diverse and dynamic. The second and third simulations contrast the performances of the three models in behavioral experiments, demonstrating advantages for the integrated model in accounting for behavioral data.     

When Fluency Signals Truth: Prior Successful Reliance on Fluency Moderates the Impact of Fluency on Truth Judgments

Repeated statements are more frequently judged to be true. One position relates this so‐called “truth effect” to metacognitive experiences of fluency, suggesting that repeated statements are more frequently judged to be true because they are processed more fluently. Although most prior research focused on why repetition influences truth judgments, considerably less is known about when fluency is used as information. The present research addresses this question and investigates whether reliance on fluency is moderated by learning experiences. Specifically, we focus on changes in the reliance on fluency over the course of time. A series of experiments reveals that fluency is more likely to be used in truth judgments when previous reliance on fluency has resulted in valid judgments, compared with when previous reliance on fluency was misleading. These findings suggest that reliance on fluency in judgments is a finely tuned process that takes prior experiences with fluency‐based judgments into account. Copyright © 2013 John Wiley & Sons, Ltd.     

On the Decision to Explore New Alternatives: The Coexistence of Under‐ and Over‐exploration

The decision whether to explore new alternatives or to choose from familiar ones is implicit in many of our daily activities. How is this decision made? When will deviation from optimal exploration be observed? The current paper examines exploration decisions in the context of a multi‐alternative “decisions from experience” task. In each trial, participants could choose a familiar option (the status quo) or a new alternative (risky exploration). The observed exploration rates were more sensitive to the frequent outcome from choosing new alternatives than to the average outcome. That is, the implicit decision whether to explore a new alternative reflects underweighting of rare events: Over‐exploration was documented in “Rare Disasters” environments, and insufficient exploration was evident in “Rare Treasures” environments. In addition, the results reveal a decrease in exploration of new alternatives over time even when it is always optimal and some exploration even when it is never reinforcing. These results can be captured with models that share a distinction between “data collection” and “outcome‐driven” decision modes. Under the data collection mode, the decision maker collects information about the environment, to be used in future choices. Under the outcome‐driven mode, the decision maker relies on small samples of previous experiences with familiar versus unfamiliar alternatives, before the selection of a specific alternative. The predictive value of a two‐parameter “explorative sampler” quantification of these assumptions is demonstrated. Copyright © 2013 John Wiley & Sons, Ltd.