What's in a name: The role of verbalization in reinforcement learning.

(e.g., characters or fractals) and concrete stimuli (e.g., pictures of everyday objects) are used interchangeably in the reinforcement-learning literature. Yet, it is unclear whether the same learning processes underlie learning from these different stimulus types. In two preregistered experiments (N = 50 each), we assessed whether abstract and concrete stimuli yield different reinforcement-learning performance and whether this difference can be explained by verbalization. We argued that concrete stimuli are easier to verbalize than abstract ones, and that people therefore can appeal to the phonological loop, a subcomponent of the working-memory system responsible for storing and rehearsing verbal information, while learning. To test whether this verbalization aids reinforcement-learning performance, we administered a reinforcement-learning task in which participants learned either abstract or concrete stimuli while verbalization was hindered or not. In the first experiment, results showed a more pronounced detrimental effect of hindered verbalization for concrete than abstract stimuli on response times, but not on accuracy. In the second experiment, in which we reduced the response window, results showed the differential effect of hindered verbalization between stimulus types on accuracy, not on response times. These results imply that verbalization aids learning for concrete, but not abstract, stimuli and therefore that different processes underlie learning from these types of stimuli. This emphasizes the importance of carefully considering stimulus types. We discuss these findings in light of generalizability and validity of reinforcement-learning research.

Automated facial expression measurement in a longitudinal sample of 4- and 8-month-olds: Baby FaceReader 9 and manual coding of affective expressions.

Facial expressions are among the earliest behaviors infants use to express emotional states, and are crucial to preverbal social interaction. Manual coding of infant facial expressions, however, is laborious and poses limitations to replicability. Recent developments in computer vision have advanced automated facial expression analyses in adults, providing reproducible results at lower time investment. Baby FaceReader 9 is commercially available software for automated measurement of infant facial expressions, but has received little validation. We compared Baby FaceReader 9 output to manual micro-coding of positive, negative, or neutral facial expressions in a longitudinal dataset of 58 infants at 4 and 8 months of age during naturalistic face-to-face interactions with the mother, father, and an unfamiliar adult. Baby FaceReader 9's global emotional valence formula yielded reasonable classification accuracy (AUC = .81) for discriminating manually coded positive from negative/neutral facial expressions; however, the discrimination of negative from neutral facial expressions was not reliable (AUC = .58). Automatically detected a priori action unit (AU) configurations for distinguishing positive from negative facial expressions based on existing literature were also not reliable. A parsimonious approach using only automatically detected smiling (AU12) yielded good performance for discriminating positive from negative/neutral facial expressions (AUC = .86). Likewise, automatically detected brow lowering (AU3+AU4) reliably distinguished neutral from negative facial expressions (AUC = .79). These results provide initial support for the use of selected automatically detected individual facial actions to index positive and negative affect in young infants, but shed doubt on the accuracy of complex a priori formulas.

Robustness of the cognitive gains in 7-month-old bilingual infants: A close multi-center replication of Kovács and Mehler (2009).

We present an exact replication of Experiment 2 from Kovács and Mehler's 2009 study, which showed that 7-month-old infants who are raised bilingually exhibit a cognitive advantage. In the experiment, a sound cue, following an AAB or ABB pattern, predicted the appearance of a visual stimulus on the screen. The stimulus appeared on one side of the screen for nine trials and then switched to the other side. In the original experiment, both mono- and bilingual infants anticipated where the visual stimulus would appear during pre-switch trials. However, during post-switch trials, only bilingual children anticipated that the stimulus would appear on the other side of the screen. The authors took this as evidence of a cognitive advantage. Using the exact same materials in combination with novel analysis techniques (Bayesian analyses, mixed effects modeling and cluster based permutation analyses), we assessed the robustness of these findings in four babylabs (N = 98). Our results did not replicate the original findings: although anticipatory looks increased slightly during post-switch trials for both groups, bilingual infants were not better switchers than monolingual infants. After the original experiment, we presented additional trials to examine whether infants associated sound patterns with cued locations, for which we did not find any evidence either. The results highlight the importance of multicenter replications and more fine-grained statistical analyses to better understand child development. HIGHLIGHTS: We carried out an exact replication across four baby labs of the high-impact study by Kovács and Mehler (2009). We did not replicate the findings of the original study, calling into question the robustness of the claim that bilingual infants have enhanced cognitive abilities. After the original experiment, we presented additional trials to examine whether infants correctly associated sound patterns with cued locations, for which we did not find any evidence. The use of novel analysis techniques (Bayesian analyses, mixed effects modeling and cluster based permutation analyses) allowed us to draw better-informed conclusions.

Robustness of the rule-learning effect in 7-month-old infants: A close, multicenter replication of Marcus et al. (1999).

We conducted a close replication of the seminal work by Marcus and colleagues from 1999, which showed that after a brief auditory exposure phase, 7-month-old infants were able to learn and generalize a rule to novel syllables not previously present in the exposure phase. This work became the foundation for the theoretical framework by which we assume that infants are able to learn abstract representations and generalize linguistic rules. While some extensions on the original work have shown evidence of rule learning, the outcomes are mixed, and an exact replication of Marcus et al.'s study has thus far not been reported. A recent meta-analysis by Rabagliati and colleagues brings to light that the rule-learning effect depends on stimulus type (e.g., meaningfulness, speech vs. nonspeech) and is not as robust as often assumed. In light of the theoretical importance of the issue at stake, it is appropriate and necessary to assess the replicability and robustness of Marcus et al.'s findings. Here we have undertaken a replication across four labs with a large sample of 7-month-old infants (N = 96), using the same exposure patterns (ABA and ABB), methodology (Headturn Preference Paradigm), and original stimuli. As in the original study, we tested the hypothesis that infants are able to learn abstract "algebraic" rules and apply them to novel input. Our results did not replicate the original findings: infants showed no difference in looking time between test patterns consistent or inconsistent with the familiarization pattern they were exposed to.

Impaired learning to dissociate advantageous and disadvantageous risky choices in adolescents.

Adolescence is characterized by a surge in maladaptive risk-taking behaviors, but whether and how this relates to developmental changes in experience-based learning is largely unknown. In this preregistered study, we addressed this issue using a novel task that allowed us to separate the learning-driven optimization of risky choice behavior over time from overall risk-taking tendencies. Adolescents (12-17 years old) learned to dissociate advantageous from disadvantageous risky choices less well than adults (20-35 years old), and this impairment was stronger in early than mid-late adolescents. Computational modeling revealed that adolescents' suboptimal performance was largely due to an inefficiency in core learning and choice processes. Specifically, adolescents used a simpler, suboptimal, expectation-updating process and a more stochastic choice policy. In addition, the modeling results suggested that adolescents, but not adults, overvalued the highest rewards. Finally, an exploratory latent-mixture model analysis indicated that a substantial proportion of the participants in each age group did not engage in experience-based learning but used a gambler's fallacy strategy, stressing the importance of analyzing individual differences. Our results help understand why adolescents tend to make more, and more persistent, maladaptive risky decisions than adults when the values of these decisions have to be learned from experience.

Improving the generalizability of infant psychological research: The ManyBabies model.

Yarkoni's analysis clearly articulates a number of concerns limiting the generalizability and explanatory power of psychological findings, many of which are compounded in infancy research. ManyBabies addresses these concerns via a radically collaborative, large-scale and open approach to research that is grounded in theory-building, committed to diversification, and focused on understanding sources of variation.

Characterising Eye Movement Events with an Unsupervised Hidden Markov Model.

Eye-tracking allows researchers to infer cognitive processes from eye movements that are classified into distinct events. Parsing the events is typically done by algorithms. Here we aim at developing an unsupervised, generative model that can be fitted to eye-movement data using maximum likelihood estimation. This approach allows hypothesis testing about fitted models, next to being a method for classification. We developed gazeHMM, an algorithm that uses a hidden Markov model as a generative model, has few critical parameters to be set by users, and does not require human coded data as input. The algorithm classifies gaze data into fixations, saccades, and optionally postsaccadic oscillations and smooth pursuits. We evaluated gazeHMM's performance in a simulation study, showing that it successfully recovered hidden Markov model parameters and hidden states. Parameters were less well recovered when we included a smooth pursuit state and/or added even small noise to simulated data. We applied generative models with different numbers of events to benchmark data. Comparing them indicated that hidden Markov models with more events than expected had most likely generated the data. We also applied the full algorithm to benchmark data and assessed its similarity to human coding and other algorithms. For static stimuli, gazeHMM showed high similarity and outperformed other algorithms in this regard. For dynamic stimuli, gazeHMM tended to rapidly switch between fixations and smooth pursuits but still displayed higher similarity than most other algorithms. Concluding that gazeHMM can be used in practice, we recommend parsing smooth pursuits only for exploratory purposes. Future hidden Markov model algorithms could use covariates to better capture eye movement processes and explicitly model event durations to classify smooth pursuits more accurately.

Effects of advice on experienced-based learning in adolescents and adults.

Recent studies that compared effects of pre-learning advice on experience-based learning in adolescents and adults have yielded mixed results. Previous studies on this topic used choice tasks in which age-related differences in advice-related learning bias and exploratory choice behavior are difficult to dissociate. Moreover, these studies did not examine whether effects of advice depend on working memory load. In this preregistered study (in adolescents [13-15 years old] and adults [18-31 years old]), we addressed these issues by factorially combining advice and working memory load manipulations in an estimation task that does not require choices and hence eliminates the influence of known age-related differences in exploration. We found that advice guided participants' initial estimates in both age groups. When advice was correct, this improved estimation performance, especially in adolescents when working memory load was high. When advice was incorrect, it had a longer-lasting effect on adolescents' performance than on adults' performance. In contrast to previous findings in choice tasks, we found no evidence that advice biased learning in either age group. Taken together, our results suggest that learning in an estimation task improves between adolescence and adulthood but that the effects of advice on learning do not differ substantially between adolescents and adults.

WALD-EM: Wald accumulation for locations and durations of eye movements.

Describing, analyzing, and explaining patterns in eye movement behavior is crucial for understanding visual perception. Further, eye movements are increasingly used in informing cognitive process models. In this article, we start by reviewing basic characteristics and desiderata for models of eye movements. Specifically, we argue that there is a need for models combining spatial and temporal aspects of eye-tracking data (i.e., fixation durations and fixation locations), that formal models derived from concrete theoretical assumptions are needed to inform our empirical research, and custom statistical models are useful for detecting specific empirical phenomena that are to be explained by said theory. In this article, we develop a conceptual model of eye movements, or specifically, fixation durations and fixation locations, and from it derive a formal statistical model-meeting our goal of crafting a model useful in both the theoretical and empirical research cycle. We demonstrate the use of the model on an example of infant natural scene viewing, to show that the model is able to explain different features of the eye movement data, and to showcase how to identify that the model needs to be adapted if it does not agree with the data. We conclude with discussion of potential future avenues for formal eye movement models. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The development of gaze following in monolingual and bilingual infants: A multi-laboratory study.

Determining the meanings of words requires language learners to attend to what other people say. However, it behooves a young language learner to simultaneously encode relevant non-verbal cues, for example, by following the direction of their eye gaze. Sensitivity to cues such as eye gaze might be particularly important for bilingual infants, as they encounter less consistency between words and objects than monolingual infants, and do not always have access to the same word-learning heuristics (e.g., mutual exclusivity). In a preregistered study, we tested the hypothesis that bilingual experience would lead to a more pronounced ability to follow another's gaze. We used a gaze-following paradigm developed by Senju and Csibra (Current Biology, 18, 2008, 668) to test a total of 93 6- to 9-month-old and 229 12- to 15-month-old monolingual and bilingual infants, in 11 laboratories located in 8 countries. Monolingual and bilingual infants showed similar gaze-following abilities, and both groups showed age-related improvements in speed, accuracy, frequency, and duration of fixations to congruent objects. Unexpectedly, bilinguals tended to make more frequent fixations to on-screen objects, whether or not they were cued by the actor. These results suggest that gaze sensitivity is a fundamental aspect of development that is robust to variation in language exposure.

Uncertainty-driven regulation of learning and exploration in adolescents: A computational account.

Healthy adults flexibly adapt their learning strategies to ongoing changes in uncertainty, a key feature of adaptive behaviour. However, the developmental trajectory of this ability is yet unknown, as developmental studies have not incorporated trial-to-trial variation in uncertainty in their analyses or models. To address this issue, we compared adolescents' and adults' trial-to-trial dynamics of uncertainty, learning rate, and exploration in two tasks that assess learning in noisy but otherwise stable environments. In an estimation task-which provides direct indices of trial-specific learning rate-both age groups reduced their learning rate over time, as self-reported uncertainty decreased. Accordingly, the estimation data in both groups was better explained by a Bayesian model with dynamic learning rate (Kalman filter) than by conventional reinforcement-learning models. Furthermore, adolescents' learning rates asymptoted at a higher level, reflecting an over-weighting of the most recent outcome, and the estimated Kalman-filter parameters suggested that this was due to an overestimation of environmental volatility. In a choice task, both age groups became more likely to choose the higher-valued option over time, but this increase in choice accuracy was smaller in the adolescents. In contrast to the estimation task, we found no evidence for a Bayesian expectation-updating process in the choice task, suggesting that estimation and choice tasks engage different learning processes. However, our modeling results of the choice task suggested that both age groups reduced their degree of exploration over time, and that the adolescents explored overall more than the adults. Finally, age-related differences in exploration parameters from fits to the choice data were mediated by participants' volatility parameter from fits to the estimation data. Together, these results suggest that adolescents overestimate the rate of environmental change, resulting in elevated learning rates and increased exploration, which may help understand developmental changes in learning and decision-making.

Cognitive flexibility training has direct and near transfer effects, but no far transfer effects, in preschoolers.

The current project studied the direct, near transfer, and far transfer effects of cognitive flexibility training in two experiments with 117 3-year-olds. In both Experiments 1 and 2, children performed three Dimensional Change Card Sorting (DCCS) tasks in a pre-training/training/post-training design. The training consisted of giving corrective feedback in the training DCCS task. In Experiment 2, in addition, three other executive control tasks were administered during pre-training and post-training. Results showed a direct effect of feedback in the training DCCS task and transfer of this effect to the post-training DCCS task after 1 week with different sorting rules and different stimuli. These findings show that preschoolers learned to switch sorting rules in the context of the DCCS task, independent of the specific sorting rules, and that this effect is not transient. No support was found for transfer to the other executive control tasks. A possible explanation is that the feedback mainly improved rule switching, an ability that is specifically required for performing a cognitive flexibility task but not the other executive control tasks.

Looking (for) patterns: Similarities and differences between infant and adult free scene-viewing patterns.

Systematic tendencies such as the center and horizontal bias are known to have a large influence on how and where we move our eyes during static onscreen free scene viewing. However, it is unknown whether these tendencies are learned viewing strategies or are more default tendencies in the way we move our eyes. To gain insight into the origin of these tendencies we explore the systematic tendencies of infants (3 - 20-month-olds, N = 157) and adults (N = 88) in three different scene viewing data sets. We replicated com-mon findings, such as longer fixation durations and shorter saccade amplitudes in infants compared to adults. The leftward bias was never studied in infants, and our results indi-cate that it is not present, while we did replicate the leftward bias in adults. The general pattern of the results highlights the similarity between infant and adult eye movements. Similar to adults, infants' fixation durations increase with viewing time and the depend-encies between successive fixations and saccades show very similar patterns. A straight-forward conclusion to draw from this set of studies is that infant and adult eye movements are mainly driven by similar underlying basic processes.

Cognitive strategies revealed by clustering eye movement transitions.

In cognitive tasks, solvers can adopt different strategies to process information which may lead to different response behavior. These strategies might elicit different eye movement patterns which can thus provide substantial information about the strategy a person uses. However, these strategies are usually hidden and need to be inferred from the data. After an overview of existing techniques which use eye movement data for the identification of latent cognitive strategies, we present a relatively easy to apply unsuper-vised method to cluster eye movement recordings to detect groups of different solution processes that are applied in solving the task. We test the method's performance using simulations and demonstrate its use on two examples of empirical data. Our analyses are in line with presence of different solving strategies in a Mastermind game, and suggest new insights to strategic patterns in solving Progressive matrices tasks.

The Quality of Response Time Data Inference: A Blinded, Collaborative Assessment of the Validity of Cognitive Models.

Most data analyses rely on models. To complement statistical models, psychologists have developed cognitive models, which translate observed variables into psychologically interesting constructs. Response time models, in particular, assume that response time and accuracy are the observed expression of latent variables including 1) ease of processing, 2) response caution, 3) response bias, and 4) non-decision time. Inferences about these psychological factors, hinge upon the validity of the models' parameters. Here, we use a blinded, collaborative approach to assess the validity of such model-based inferences. Seventeen teams of researchers analyzed the same 14 data sets. In each of these two-condition data sets, we manipulated properties of participants' behavior in a two-alternative forced choice task. The contributing teams were blind to the manipulations, and had to infer what aspect of behavior was changed using their method of choice. The contributors chose to employ a variety of models, estimation methods, and inference procedures. Our results show that, although conclusions were similar across different methods, these "modeler's degrees of freedom" did affect their inferences. Interestingly, many of the simpler approaches yielded as robust and accurate inferences as the more complex methods. We recommend that, in general, cognitive models become a typical analysis tool for response time data. In particular, we argue that the simpler models and procedures are sufficient for standard experimental designs. We finish by outlining situations in which more complicated models and methods may be necessary, and discuss potential pitfalls when interpreting the output from response time models.

Real-world scene perception in infants: What factors guide attention allocation?

The foci of visual attention were modeled as a function of perceptual salience, adult fixation locations, and attentional control mechanisms (measured in separate tasks) in infants (N = 45, 3- to 15-month-olds) as they viewed static real-world scenes. After controlling for the center bias, the results showed that low-level perceptual salience predicts where infants look. In addition, high-level factors also played a role: Infants fixated parts of the scenes frequently fixated by adults and this effect was stronger for older than younger infants. In line with this finding, infant fixation durations were longer on regions more frequently fixated by adults, implying longer time taken to process the available information. Fixation durations decreased with age, and this decline interacted with orienting skills such that fixation durations decreased faster with age for infants with high orienting skills, relative to infants with low orienting skills. There was a further interaction between fixation durations and selective attention abilities: Infants with low selective attention skills showed a decrease in fixation durations with age, whereas infants with higher selective attention skills showed a slight increase in fixation durations with age. These findings imply that infants' visual processing of static real-world stimuli develops in accord with attentional control.

Infants' center bias in free viewing of real-world scenes.

This study examines how salience and a center bias drive infants' first fixation while looking at complex scenes. Adults are known to have a strong center bias, their first point of gaze is nearly always in the center of the scene. The center bias is likely to be a strategic bias, as looking towards the center minimizes the distance to other parts of the scene and important objects are often located at the center. In an experimental design varying salience regions of scenes and start positions we examined infants' (N = 48, Age = 5-20-month-olds) first fixation after scene onset. The pre-registered hypothesis that infants also have a center bias while looking at real-world scenes was confirmed. The strength of the center bias is correlated with the saliency distribution such that the bias is weaker when the strongest salience is peripheral rather central. In the absence of clear salient regions there still was a strong center bias. These results suggests there is a competition between stimulus-driven factors and a center bias in steering attention from a young age onwards.

Investigating the development of causal inference by studying variability in 2- to 5-year-olds' behavior.

This study investigated the development of young children's causal inference by studying variability in behavior. Two possible sources of variability, strategy use and accuracy in strategy execution, were discriminated and related to age. To this end, a relatively wide range of causal inference trials was administered to children of a relatively broad age range: 2- to 5-year-olds. Subsequently, individuals' response patterns over trials were analyzed with a latent variable technique. The results showed that variability in children's behavior could largely be explained by strategy use. Three different strategies were distinguished, and tentative interpretations suggest these could possibly be labeled as "rational", "associative", and "uncertainty avoidance" strategies. The strategies were found to be related to age, and this age-related strategy use better explained the variability in children's behavior than age-related increase in accuracy of executing a single strategy. This study can be considered a first step in introducing a new, fruitful approach for investigating the development of causal inference.

Gazepath: An eye-tracking analysis tool that accounts for individual differences and data quality.

Eye-trackers are a popular tool for studying cognitive, emotional, and attentional processes in different populations (e.g., clinical and typically developing) and participants of all ages, ranging from infants to the elderly. This broad range of processes and populations implies that there are many inter- and intra-individual differences that need to be taken into account when analyzing eye-tracking data. Standard parsing algorithms supplied by the eye-tracker manufacturers are typically optimized for adults and do not account for these individual differences. This paper presents gazepath, an easy-to-use R-package that comes with a graphical user interface (GUI) implemented in Shiny (RStudio Inc 2015). The gazepath R-package combines solutions from the adult and infant literature to provide an eye-tracking parsing method that accounts for individual differences and differences in data quality. We illustrate the usefulness of gazepath with three examples of different data sets. The first example shows how gazepath performs on free-viewing data of infants and adults, compared to standard EyeLink parsing. We show that gazepath controls for spurious correlations between fixation durations and data quality in infant data. The second example shows that gazepath performs well in high-quality reading data of adults. The third and last example shows that gazepath can also be used on noisy infant data collected with a Tobii eye-tracker and low (60 Hz) sampling rate.