Curiosity-based learning in infants: a neurocomputational approach

Infants evaluate informativeness of evidence and predict causal events as revealed in theta oscillations and predictive looking

This study investigates 16-month-old infants' sensitivity to the informativeness of evidence and its potential link to infants' ability to draw accurate causal inferences and predict unfolding events. Employing concurrent EEG and eye tracking, data from 66 infants revealed significantly increased theta oscillatory activity when infants expected to see causally unconfounded evidence compared to confounded evidence, suggesting heightened cognitive engagement in anticipation of informative evidence. Crucially, this difference was more pronounced in the subset of infants who later made correct predictions, suggesting that they had correctly inferred the causal structure based on the evidence presented. This research sheds light on infants' motivation to seek explanatory causal information, suggesting that even at 16 months, infants can strategically direct attention to situations conducive to acquiring informative evidence, potentially laying the groundwork for the impressive abilities of humans to rapidly acquire knowledge and develop causal theories of the world.

Helpless infants are learning a foundation model

Humans have a protracted postnatal helplessness period, typically attributed to human-specific maternal constraints causing an early birth when the brain is highly immature. By aligning neurodevelopmental events across species, however, it has been found that humans are not born with especially immature brains compared with animal species with a shorter helpless period. Consistent with this, the rapidly growing field of infant neuroimaging has found that brain connectivity and functional activation at birth share many similarities with the mature brain. Inspired by machine learning, where deep neural networks also benefit from a 'helpless period' of pre-training, we propose that human infants are learning a foundation model: a set of fundamental representations that underpin later cognition with high performance and rapid generalisation.

A transdisciplinary view on curiosity beyond linguistic humans: animals, infants, and artificial intelligence

Curiosity is a core driver for life-long learning, problem-solving and decision-making. In a broad sense, curiosity is defined as the intrinsically motivated acquisition of novel information. Despite a decades-long history of curiosity research and the earliest human theories arising from studies of laboratory rodents, curiosity has mainly been considered in two camps: 'linguistic human' and 'other'. This is despite psychology being heritable, and there are many continuities in cognitive capacities across the animal kingdom. Boundary-pushing cross-disciplinary debates on curiosity are lacking, and the relative exclusion of pre-linguistic infants and non-human animals has led to a scientific impasse which more broadly impedes the development of artificially intelligent systems modelled on curiosity in natural agents. In this review, we synthesize literature across multiple disciplines that have studied curiosity in non-verbal systems. By highlighting how similar findings have been produced across the separate disciplines of animal behaviour, developmental psychology, neuroscience, and computational cognition, we discuss how this can be used to advance our understanding of curiosity. We propose, for the first time, how features of curiosity could be quantified and therefore studied more operationally across systems: across different species, developmental stages, and natural or artificial agents.

Curiosity and the dynamics of optimal exploration

What drives our curiosity remains an elusive and hotly debated issue, with multiple hypotheses proposed but a cohesive account yet to be established. This review discusses traditional and emergent theories that frame curiosity as a desire to know and a drive to learn, respectively. We adopt a model-based approach that maps the temporal dynamics of various factors underlying curiosity-based exploration, such as uncertainty, information gain, and learning progress. In so doing, we identify the limitations of past theories and posit an integrated account that harnesses their strengths in describing curiosity as a tool for optimal environmental exploration. In our unified account, curiosity serves as a 'common currency' for exploration, which must be balanced with other drives such as safety and hunger to achieve efficient action.

Individual differences in processing speed and curiosity explain infant habituation and dishabituation performance

Habituation and dishabituation are the most prevalent measures of infant cognitive functioning, and they have reliably been shown to predict later cognitive outcomes. Yet, the exact mechanisms underlying infant habituation and dishabituation are still unclear. To investigate them, we tested 106 8-month-old infants on a classic habituation task and a novel visual learning task. We used a hierarchical Bayesian model to identify individual differences in sustained attention, learning performance, processing speed and curiosity from the visual learning task. These factors were then related to habituation and dishabituation. We found that habituation time was related to individual differences in processing speed, while dishabituation was related to curiosity, but only for infants who did not habituate. These results offer novel insights in the mechanisms underlying habituation and serve as proof of concept for hierarchical models as an effective tool to measure individual differences in infant cognitive functioning. RESEARCH HIGHLIGHTS: We used a hierarchical Bayesian model to measure individual differences in infants' processing speed, learning performance, sustained attention, and curiosity. Faster processing speed was related to shorter habituation time. High curiosity was related to stronger dishabituation responses, but only for infants who did not habituate.

The limitations of automatically generated curricula for continual learning

In many applications, artificial neural networks are best trained for a task by following a curriculum, in which simpler concepts are learned before more complex ones. This curriculum can be hand-crafted by the engineer or optimised like other hyperparameters, by evaluating many curricula. However, this is computationally intensive and the hyperparameters are unlikely to generalise to new datasets. An attractive alternative, demonstrated in influential prior works, is that the network could choose its own curriculum by monitoring its learning. This would be particularly beneficial for continual learning, in which the network must learn from an environment that is changing over time, relevant both to practical applications and in the modelling of human development. In this paper we test the generality of this approach using a proof-of-principle model, training a network on two sequential tasks under static and continual conditions, and investigating both the benefits of a curriculum and the handicap induced by continuous learning. Additionally, we test a variety of prior task-switching metrics, and find that in some cases even in this simple scenario the a network is often unable to choose the optimal curriculum, as the benefits are sometimes only apparent with hindsight, at the end of training. We discuss the implications of the results for network engineering and models of human development.

Children's affective involvement in early word learning

The current study set out to examine the underlying physiological mechanisms of and the emotional response associated with word learning success in young 3-year-old predominantly white children. In particular, we examined whether children's physiological arousal following a word learning task predicts their word learning success and whether successful learning in turn predicts children's subsequent positive emotions. We presented children (n = 50) with a cross-situational word learning task and measured their pupillary arousal following completion of the task, as well as changes to their upper body posture following completion of the task, as indices of children's emotions following task completion. Children who showed greater physiological arousal following the novel word recognition task (n = 40) showed improved subsequent word recognition performance. We found that children showed more elevated posture after completing a familiar word learning task compared to completing a novel word learning task (n = 33) but results on children's individual learning success and postural elevation were mixed. We discuss the findings with regards to children's affective involvement in word learning.

Curiosity enhances incidental object encoding in 8-month-old infants

Recent research with adults indicates that curiosity induced by uncertainty enhances learning and memory outcomes and that the resolution of curiosity has a special role in curiosity-driven learning. However, the role of curiosity-based learning in early development is unclear. Here we presented 8-month-old infants with a novel looking time procedure to explore (a) whether uncertainty-induced curiosity enhances learning of incidental information and (b) whether uncertainty-induced curiosity leads infants to seek uncertainty resolution over novelty. In Experiment 1, infants saw blurred images to induce curiosity (Curiosity sequence) or a clear image (Non-curiosity sequence) followed by presentation of incidental objects. Despite looking equally to the incidental objects in both sequences, in a subsequent object recognition phase infants looked longer to incidental objects presented in the Non-curiosity condition compared with the Curiosity condition, indicating that curiosity induced by blurred pictures enhanced the processing of the incidental object, leading to a novelty preference for the incidental object shown in the Non-Curiosity condition. In Experiment 2, a blurred picture of a novel toy was first presented, followed by its corresponding clear picture paired with a clear picture of a new novel toy side by side. Infants showed no preference for either image, providing no evidence for a drive to resolve uncertainty. Overall, the current experiments suggest that curiosity has a broad attention-enhancing effect in infancy. Taking into account existing studies with older children and adults, we propose a developmental change in the function of curiosity, from this attentional enhancement to more goal-directed information seeking in older children and adults.

Discourse with Few Words: Coherence Statistics, Parent-Infant Actions on Objects, and Object Names

The data for early object name learning is often conceptualized as a problem of mapping heard names to referents. However, infants do not hear object names as discrete events but rather in extended interactions organized around goal-directed actions on objects. The present study examined the statistical structure of the nonlinguistic events that surround parent naming of objects. Parents and 12-month -old infants were left alone in a room for 10 minutes with 32 objects available for exploration. Parent and infant handling of objects and parent naming of objects were coded. The four measured statistics were from measures used in the study of coherent discourse: (1) a frequency distribution in which actions were frequently directed to a few objects and more rarely to other objects; (2) repeated returns to the high-frequency objects over the 10-minute play period; (3) clustered repetitions, continuity, of actions on objects; and (4) structured networks of transitions among objects in play that connected all the played-with objects. Parent naming was infrequent but related to the statistics of object-directed actions. The implications of the discourse-like stream of actions are discussed in terms of learning mechanisms that could support rapid learning of object names from relatively few name-object co-occurrences.

Knowledge in Sight: Toddlers Plan Efficient Epistemic Actions by Anticipating Learning Gains

Anticipating the learning consequences of actions is crucial to plan efficient information seeking. Such a capacity is needed for learners to determine which actions are most likely to result in learning. Here, we tested the early ontogeny of the human capacity to anticipate the amount of learning gained from seeing. In study 1, we tested infants' capacity to anticipate the availability of sight. Fourteen-month-old infants (N = 72) were invited to search for a toy hidden inside a container. The participants were faster to attempt at opening a shutter when this action allowed them to see inside the container. Moreover, this effect was specifically observed when seeing inside the container was potentially useful to the participants' goals. Thus, infants anticipated the availability of sight, and they calibrated their information-seeking behaviors accordingly. In studies 2 and 3, we tested toddlers' capacity to anticipate whether data would be cognitively useful for their goals. Two-and-a-half-year-olds (N = 72) had to locate a target character hidden among distractors. The participants flipped the characters more often, and were comparatively faster to initiate this action when it yielded access to visual data allowing them to locate the target. Thus, toddlers planned their information-seeking behaviors by anticipating the cognitive utility of sight. In contrast, toddlers did not calibrate their behaviors to the cognitive usefulness of auditory data. These results suggest that cognitive models of learning guide toddlers' search for information. The early developmental onset of the capacity to anticipate future learning gains is crucial for active learning.

The role of social signals in segmenting observed actions in 18-month-old children

Learning about actions requires children to identify the boundaries of an action and its units. Whereas some action units are easily identified, parents can support children's action learning by adjusting the presentation and using social signals. However, currently, little is understood regarding how children use these signals to learn actions. In the current study, we investigate the possibility that communicative signals are a particularly suitable cue for segmenting events. We investigated this hypothesis by presenting 18-month-old children (N = 60) with short action sequences consisting of toy animals either hopping or sliding across a board into a house, but interrupting this two-step sequence either (a) using an ostensive signal as a segmentation cue, (b) using a non-ostensive segmentation cue and (c) without additional segmentation information between the actions. Marking the boundary using communicative signals increased children's imitation of the less salient sliding action. Imitation of the hopping action remained unaffected. Crucially, marking the boundary of both actions using a non-communicative control condition did not increase imitation of either action. Communicative signals might be particularly suitable in segmenting non-salient actions that would otherwise be perceived as part of another action or as non-intentional. These results provide evidence of the importance of ostensive signals at event boundaries in scaffolding children's learning.

Humans monitor learning progress in curiosity-driven exploration

Curiosity-driven learning is foundational to human cognition. By enabling humans to autonomously decide when and what to learn, curiosity has been argued to be crucial for self-organizing temporally extended learning curricula. However, the mechanisms driving people to set intrinsic goals, when they are free to explore multiple learning activities, are still poorly understood. Computational theories propose different heuristics, including competence measures (e.g., percent correct) and learning progress, that could be used as intrinsic utility functions to efficiently organize exploration. Such intrinsic utilities constitute computationally cheap but smart heuristics to prevent people from laboring in vain on unlearnable activities, while still motivating them to self-challenge on difficult learnable activities. Here, we provide empirical evidence for these ideas by means of a free-choice experimental paradigm and computational modeling. We show that while humans rely on competence information to avoid easy tasks, models that include a learning-progress component provide the best fit to task selection data. These results bridge the research in artificial and biological curiosity, reveal strategies that are used by humans but have not been considered in computational research, and introduce tools for probing how humans become intrinsically motivated to learn and acquire interests and skills on extended time scales.

Epidemiologic trends in pediatric ocular injury in the USA from 2010 to 2019

PURPOSE

Epidemiologic studies related to the demographics and trends of ocular injury in the pediatric cohort in the last decade are limited. This study describes epidemiologic trends in consumer product-related pediatric ocular injuries from 2010 to 2019.

METHODS

This is a retrospective observational study utilizing data from the National Electronic Injury Surveillance System (NEISS). Inclusion criteria include pediatric patients ages 1-20 presenting to NEISS emergency departments with an ocular injury from January 1, 2010, to December 31, 2019. Outcome measures include prevalence of ocular injury related to consumer products stratified by age group, sex, and injury setting.

RESULTS

There were an estimated 636,582 consumer product (CP)-related incidents of ocular injury in children ages 1-20 years with an average age of 9.7 years (SD = 5.92) between 2010 and 2019; 416,378 (65.4%) patients were males with a male-to-female ratio of 1.9:1. The annual incidence of CP-related ocular injury in males decreased from 2010 to 2019 while that in females remained unchanged. The greatest number of injuries occurred in the 1-5-year age group (31%) followed 6-10 group (25%), 16-20 (22%), and 11-15 (21%). Ocular contusion was the most common diagnosis. The most common setting of injury was home (63%). The majority (96%) of patients were treated and released from the ED suggesting a minor injury. Of the 1% of patients admitted to the hospital with ocular injuries, one-fourth were due to an open globe injury. Most ocular injuries occurred in the summer months, and presentation to the ED was more frequent on the weekend than a weekday. Over one-fourth (28%) of injuries were sports-related followed by detergents/chemicals (16%), toys (11%), home workshop equipment (8%), kitchenware (5.0%), and home furniture in (4.4%).

CONCLUSIONS

The frequency and rate of pediatric ocular injuries in the USA decreased during the last decade. Sports and non-powder guns caused the greatest number of eye injuries in the older pediatric cohorts (11-15- and 16-20-year age groups), while detergents/chemicals accounted for nearly 1/3 of all injuries in younger children (1-5 years). Prophylactic measures targeted to specific age groups will be important in reducing eye injuries further.

Parent-Child Joint Behaviors in Novel Object Play Create High-Quality Data for Word Learning

This research takes a dyadic approach to study early word learning and focuses on toddlers' (N = 20, age: 17-23 months) information seeking and parents' information providing behaviors and the ways the two are coupled in real-time parent-child interactions. Using head-mounted eye tracking, this study provides the first detailed comparison of children's and their parents' behavioral and attentional patterns in two free-play contexts: one with novel objects with to-be-learned names (Learning condition) and the other with familiar objects with known names (Play condition). Children and parents in the Learning condition modified their individual and joint behaviors when encountering novel objects with to-be-learned names, which created clearer signals that reduced referential ambiguity and potentially facilitated word learning.

Children's exploratory play tracks the discriminability of hypotheses

Effective curiosity-driven learning requires recognizing that the value of evidence for testing hypotheses depends on what other hypotheses are under consideration. Do we intuitively represent the discriminability of hypotheses? Here we show children alternative hypotheses for the contents of a box and then shake the box (or allow children to shake it themselves) so they can hear the sound of the contents. We find that children are able to compare the evidence they hear with imagined evidence they do not hear but might have heard under alternative hypotheses. Children (N = 160; mean: 5 years and 4 months) prefer easier discriminations (Experiments 1-3) and explore longer given harder ones (Experiments 4-7). Across 16 contrasts, children's exploration time quantitatively tracks the discriminability of heard evidence from an unheard alternative. The results are consistent with the idea that children have an "intuitive psychophysics": children represent their own perceptual abilities and explore longer when hypotheses are harder to distinguish.

Taking parent personality and child temperament into account in child language development

Individual differences have become increasingly important in the study of child development and language. However, despite the important role parents play in children's language, no work has examined how parent personality impacts language development. The current study examines the impact of parent personality as well as child temperament on language development in 460 16- to 30-month-old children and 328 31- to 42-month-old children. Findings from both groups suggest multiple aspects of children's language abilities are correlated with their parent's personality. Specifically, parent consciousness, openness, and agreeableness positively correlate with child vocabulary size and other language abilities. Results also replicate and expand research on child temperament and language - child effortful control and surgency were positively correlated, and negative affect negatively correlated with most language abilities even after controlling for parent personality. Critically, parent and child traits appear to impact a child's language abilities above and beyond well-known predictors of language, such as age.

Does surprise enhance infant memory? Assessing the impact of the encoding context on subsequent object recognition

A discrepancy between what was predicted and what is observed has been linked to increased looking times, changes in brain electrical activity, and increased pupil dilation in infants. These processes associated with heightened attention and readiness to learn might enhance the encoding and memory consolidation of the surprising object, as suggested by both the infant and the adult literature. We therefore investigated whether the presence of surprise during the encoding context enhances subsequent encoding and recognition memory processes for the items that violated infants' expectations. Seventeen-month-olds viewed 20 familiar objects, half of which were labeled correctly, while the other half were mislabeled. Subsequently, infants were presented with a silent recognition memory test where the previously labeled objects appeared along with new images. Pupil dilation was measured, with more dilated pupils indicating (1) surprise during those labeling events where the item was mislabeled and (2) successful retrieval processes during the memory test. Infants responded with more pupil dilation to mislabeling compared to correct labeling. Importantly, despite the presence of a surprise response during mislabeling, infants only differentiated between the previously seen and unseen items at the memory test, offering no evidence that surprise had facilitated the encoding of the mislabeled items.

Sampling to learn words: Adults and children sample words that reduce referential ambiguity

How do learners gather new information during word learning? One possibility is that learners selectively sample items that help them reduce uncertainty about new word meanings. In a series of cross-situational word learning tasks with adults and children, we manipulated the referential ambiguity of label-object pairs experienced during training and subsequently investigated which words participants chose to sample additional information about. In the first experiment, adult learners chose to receive additional training on object-label associations that reduce referential ambiguity during cross-situational word learning. This ambiguity-reduction strategy was related to improved test performance. In two subsequent experiments, we found that, at least in some contexts, children (3-8 years of age) show a similar preference to seek information about words experienced in ambiguous word learning situations. In Experiment 2, children did not preferentially select object-label associations that remained ambiguous during cross-situational word learning. However, in a third experiment that increased the relative ambiguity of two sets of novel object-label associations, we found evidence that children preferentially make selections that reduce ambiguity about novel word meanings. These results carry implications for understanding how children actively contribute to their own language development by seeking information that supports learning.

Infant categorization as a dynamic process linked to memory

Recency effects are well documented in the adult and infant literature: recognition and recall memory are better for recently occurring events. We explore recency effects in infant categorization, which does not merely involve memory for individual items, but the formation of abstract category representations. We present a computational model of infant categorization that simulates category learning in 10-month-olds. The model predicts that recency effects outweigh previously reported order effects for the same stimuli. According to the model, infant behaviour at test should depend mainly on the identity of the most recent training item. We evaluate these predictions in a series of experiments with 10-month-old infants. Our results show that infant behaviour confirms the model's prediction. In particular, at test infants exhibited a preference for a category outlier over the category average only if the final training item had been close to the average, rather than distant from it. Our results are consistent with a view of categorization as a highly dynamic process where the end result of category learning is not the overall average of all stimuli encountered, but rather a fluid representation that moves depending on moment-to-moment novelty. We argue that this is a desirable property of a flexible cognitive system that adapts rapidly to different contexts.

Infants tailor their attention to maximize learning

Infants' remarkable learning abilities allow them to rapidly acquire many complex skills. It has been suggested that infants achieve this learning by optimally allocating their attention to relevant stimuli in the environment, but the underlying mechanisms remain poorly understood. Here, we modeled infants' looking behavior during a learning task through an ideal learner that quantified the informational structure of environmental stimuli. We show that saccadic latencies, looking time, and time spent engaged with a stimulus sequence are explained by the properties of the learning environments, including the level of surprise of the stimulus, overall predictability of the environment, and progress in learning the environmental structure. These findings reveal the factors that shape infants' advanced learning, emphasizing their predisposition to seek out stimuli that maximize learning.

Explaining individual differences in infant visual sensory seeking

Individual differences in infants’ engagement with their environment manifest early in development and are noticed by parents. Three views have been advanced to explain differences in seeking novel stimulation. The optimal stimulation hypothesis suggests that individuals seek further stimulation when they are under‐responsive to current sensory input. The processing speed hypothesis proposes that those capable of processing information faster are driven to seek stimulation more frequently. The information prioritization hypothesis suggests the differences in stimulation seeking index variation in the prioritization of incoming relative to ongoing information processing. Ten‐month‐old infants saw 10 repetitions of a video clip and changes in frontal theta oscillatory amplitude were measured as an index of information processing speed. Stimulus‐locked P1 peak amplitude in response to checkerboards briefly overlaid on the video at random points during its presentation indexed processing of incoming stimulation. Parental report of higher visual seeking did not relate to reduced P1 peak amplitude or to a stronger decrease in frontal theta amplitude with repetition, thus not supporting either the optimal stimulation or the processing speed hypotheses. Higher visual seeking occurred in those infants whose P1 peak amplitude was greater than expected based on their theta amplitude. These findings indicate that visual sensory seeking in infancy is explained by a bias toward novel stimulation, thus supporting the information prioritization hypothesis.

Making Sense of the World: Infant Learning From a Predictive Processing Perspective

For human infants, the first years after birth are a period of intense exploration-getting to understand their own competencies in interaction with a complex physical and social environment. In contemporary neuroscience, the predictive-processing framework has been proposed as a general working principle of the human brain, the optimization of predictions about the consequences of one's own actions, and sensory inputs from the environment. However, the predictive-processing framework has rarely been applied to infancy research. We argue that a predictive-processing framework may provide a unifying perspective on several phenomena of infant development and learning that may seem unrelated at first sight. These phenomena include statistical learning principles, infants' motor and proprioceptive learning, and infants' basic understanding of their physical and social environment. We discuss how a predictive-processing perspective can advance the understanding of infants' early learning processes in theory, research, and application.

Learning Process of Gaze Following: Computational Modeling Based on Reinforcement Learning

Many studies have explored factors which influence gaze-following behavior of young infants. However, the results of empirical studies were inconsistent, and the mechanism underlying the contextual modulation of gaze following remains unclear. In order to provide valuable insight into the mechanisms underlying gaze following, we conducted computational modeling using Q-learning algorithm and simulated the learning process of infant gaze following to suggest a feasible model. In Experiment 1, we simulated how communicative cues and infant internal states affect the learning process of gaze following. The simulation indicated that the model in which communicative cues enhance infant internal states is the most feasible to explain the infant learning process. In Experiment 2, we simulated how individual differences in motivation for communication affect the learning process. The results showed that low motivation for communication can delay the learning process and decrease the frequency of gaze following. These simulations suggest that communicative cues may enhance infants' internal states and promote the development of gaze following. Also, initial social motivation may affect the learning process of social behaviors in the long term.

Child-Robot Collaborative Problem-Solving and the Importance of Child's Voluntary Interaction: A Developmental Perspective

The emergence and development of cognitive strategies for the transition from exploratory actions towards intentional problem-solving in children is a key question for the understanding of the development of human cognition. Researchers in developmental psychology have studied cognitive strategies and have highlighted the catalytic role of the social environment. However, it is not yet adequately understood how this capacity emerges and develops in biological systems when they perform a problem-solving task in collaboration with a robotic social agent. This paper presents an empirical study in a human-robot interaction (HRI) setting which investigates children's problem-solving from a developmental perspective. In order to theoretically conceptualize children's developmental process of problem-solving in HRI context, we use principles based on the intuitive theory and we take into consideration existing research on executive functions with a focus on inhibitory control. We considered the paradigm of the Tower of Hanoi and we conducted an HRI behavioral experiment to evaluate task performance. We designed two types of robot interventions, "voluntary" and "turn-taking"-manipulating exclusively the timing of the intervention. Our results indicate that the children who participated in the voluntary interaction setting showed a better performance in the problem solving activity during the evaluation session despite their large variability in the frequency of self-initiated interactions with the robot. Additionally, we present a detailed description of the problem-solving trajectory for a representative single case-study, which reveals specific developmental patterns in the context of the specific task. Implications and future work are discussed regarding the development of intelligent robotic systems that allow child-initiated interaction as well as targeted and not constant robot interventions.

Curiosity-based learning in infants: a neurocomputational approach

Infants are curious learners who drive their own cognitive development by imposing structure on their learning environment as they explore. Understanding the mechanisms by which infants structure their own learning is therefore critical to our understanding of development. Here we propose an explicit mechanism for intrinsically motivated information selection that maximizes learning. We first present a neurocomputational model of infant visual category learning, capturing existing empirical data on the role of environmental complexity on learning. Next we "set the model free", allowing it to select its own stimuli based on a formalization of curiosity and three alternative selection mechanisms. We demonstrate that maximal learning emerges when the model is able to maximize stimulus novelty relative to its internal states, depending on the interaction across learning between the structure of the environment and the plasticity in the learner itself. We discuss the implications of this new curiosity mechanism for both existing computational models of reinforcement learning and for our understanding of this fundamental mechanism in early development.

The Developing Infant Creates a Curriculum for Statistical Learning

New efforts are using head cameras and eye-trackers worn by infants to capture everyday visual environments from the point of view of the infant learner. From this vantage point, the training sets for statistical learning develop as the sensorimotor abilities of the infant develop, yielding a series of ordered datasets for visual learning that differ in content and structure between timepoints but are highly selective at each timepoint. These changing environments may constitute a developmentally ordered curriculum that optimizes learning across many domains. Future advances in computational models will be necessary to connect the developmentally changing content and statistics of infant experience to the internal machinery that does the learning.