Unsupervised statistical learning in newly hatched chicks

Statistical learning beyond words in human neonates

Interest in statistical learning in developmental studies stems from the observation that 8-month-olds were able to extract words from a monotone speech stream solely using the transition probabilities (TP) between syllables (Saffran et al., 1996). A simple mechanism was thus part of the human infant's toolbox for discovering regularities in language. Since this seminal study, observations on statistical learning capabilities have multiplied across domains and species, challenging the hypothesis of a dedicated mechanism for language acquisition. Here, we leverage the two dimensions conveyed by speech -speaker identity and phonemes- to examine (1) whether neonates can compute TPs on one dimension despite irrelevant variation on the other and (2) whether the linguistic dimension enjoys an advantage over the voice dimension. In two experiments, we exposed neonates to artificial speech streams constructed by concatenating syllables while recording EEG. The sequence had a statistical structure based either on the phonetic content, while the voices varied randomly (Experiment 1) or on voices with random phonetic content (Experiment 2). After familiarisation, neonates heard isolated duplets adhering, or not, to the structure they were familiarised with. In both experiments, we observed neural entrainment at the frequency of the regularity and distinct Event-Related Potentials (ERP) to correct and incorrect duplets, highlighting the universality of statistical learning mechanisms and suggesting it operates on virtually any dimension the input is factorised. However, only linguistic duplets elicited a specific ERP component, potentially an N400 precursor, suggesting a lexical stage triggered by phonetic regularities already at birth. These results show that, from birth, multiple input regularities can be processed in parallel and feed different higher-order networks.

Abstract processing of syllabic structures in early infancy

Syllables are one of the fundamental building blocks of early language acquisition. From birth onwards, infants preferentially segment, process and represent the speech into syllable-sized units, raising the question of what type of computations infants are able to perform on these perceptual units. Syllables are abstract units structured in a way that allows grouping phonemes into sequences. The goal of this research was to investigate 4-to-5-month-old infants' ability to encode the internal structure of syllables, at a target age when the language system is not yet specialized on the sounds and the phonotactics of native languages. We conducted two experiments in which infants were first familiarized to lists of syllables implementing either CVC (consonant-vowel-consonant) or CCV (consonant-consonant-vowel) structures, then presented with new syllables implementing both structures at test. Experiments differ in the degree of phonological similarity between the materials used at familiarization and test. Results show that infants were able to differentiate syllabic structures at test, even when test syllables were implemented by combinations of phonemes that infants did not hear before. Only infants familiarized with CVC syllables discriminated the structures at test, pointing to a processing advantage for CVC over CCV structures. This research shows that, in addition to preferentially processing the speech into syllable-sized units, during the first months of life, infants are also capable of performing fine-grained computations within such units.

The dynamics of statistical learning in visual search and its interaction with salience processing: An EEG study

Visual attention can be guided by statistical regularities in the environment, that people implicitly learn from past experiences (statistical learning, SL). Moreover, a perceptually salient element can automatically capture attention, gaining processing priority through a bottom-up attentional control mechanism. The aim of our study was to investigate the dynamics of SL and if it shapes attentional target selection additively with salience processing, or whether these mechanisms interact, e.g. one gates the other. In a visual search task, we therefore manipulated target frequency (high vs. low) across locations while, in some trials, the target was salient in terms of colour. Additionally, halfway through the experiment, the high-frequency location changed to the opposite hemifield. EEG activity was simultaneously recorded, with a specific interest in two markers related to target selection and post-selection processing, respectively: N2pc and SPCN. Our results revealed that both SL and saliency significantly enhanced behavioural performance, but also interacted with each other, with an attenuated saliency effect at the high-frequency target location, and a smaller SL effect for salient targets. Concerning processing dynamics, the benefit of salience processing was more evident during the early stage of target selection and processing, as indexed by a larger N2pc and early-SPCN, whereas SL modulated the underlying neural activity particularly later on, as revealed by larger late-SPCN. Furthermore, we showed that SL was rapidly acquired and adjusted when the spatial imbalance changed. Overall, our findings suggest that SL is flexible to changes and, combined with salience processing, jointly contributes to establishing attentional priority.

Sensitivity to the role of an animated agent from observed interactions in newborn chicks (Gallus gallus)

Few month old human infants are able to detect the social roles of artificial agents and consistently choose the object behaving as 'approacher' rather than 'repulser'. This preference has been considered evidence of a pre-linguistic and pre-cultural origin of the social mind. Similar preferences have not been described in other species, though comparative data could help clarify the nature of this phenomenon and its evolutionary origin. In this study, we investigated sensitivity to the social role of an artificial agent in domestic chicks. Birds offer an excellent model to study the evolutionary roots of cognitive abilities, since they separated from mammals over 300 Ma. Moreover, the investigation of newly hatched chicks allows control for previous experience. After being exposed to computer-presented animations depicting an interaction among two agents, chicks underwent a free choice test among those same objects. While no initial evidence of a clear preference emerged from the planned analysis, chicks in the experimental condition showed a preference for the 'approacher' when controlling for side bias, mirroring human infants behaviour. This suggests the existence of an early ability to discriminate agents from their interactions, independent from any social experience.

Integrated effects of top-down attention and statistical learning during visual search: An EEG study

The present study aims to investigate how the competition between visual elements is solved by top-down and/or statistical learning (SL) attentional control (AC) mechanisms when active together. We hypothesized that the "winner" element that will undergo further processing is selected either by one AC mechanism that prevails over the other, or by the joint activity of both mechanisms. To test these hypotheses, we conducted a visual search experiment that combined an endogenous cueing protocol (valid vs. neutral cue) and an imbalance of target frequency distribution across locations (high- vs. low-frequency location). The unique and combined effects of top-down control and SL mechanisms were measured on behaviour and amplitudes of three evoked-response potential (ERP) components (i.e., N2pc, P1, CNV) related to attentional processing. Our behavioural results showed better performance for validly cued targets and for targets in the high-frequency location. The two factors were found to interact, so that SL effects emerged only in the absence of top-down guidance. Whereas the CNV and P1 only displayed a main effect of cueing, for the N2pc we observed an interaction between cueing and SL, revealing a cueing effect for targets in the low-frequency condition, but not in the high-frequency condition. Thus, our data support the view that top-down control and SL work in a conjoint, integrated manner during target selection. In particular, SL mechanisms are reduced or even absent when a fully reliable top-down guidance of attention is at play.

Domestic hens succeed at serial reversal learning and perceptual concept generalisation using a new automated touchscreen device

Improving the welfare of farm animals depends on our knowledge on how they perceive and interpret their environment; the latter depends on their cognitive abilities. Hence, limited knowledge of the range of cognitive abilities of farm animals is a major concern. An effective approach to explore the cognitive range of a species is to apply automated testing devices, which are still underdeveloped in farm animals. In screen-like studies, the uses of automated devices are few in domestic hens. We developed an original fully automated touchscreen device using digital computer-drawn colour pictures and independent sensible cells adapted for cognitive testing in domestic hens, enabling a wide range of test types from low to high complexity. This study aimed to test the efficiency of our device using two cognitive tests. We focused on tasks related to adaptive capacities to environmental variability, such as flexibility and generalisation capacities as this is a good start to approach more complex cognitive capacities. We implemented a serial reversal learning task, categorised as a simple cognitive test, and a delayed matching-to-sample (dMTS) task on an identity concept, followed by a generalisation test, categorised as more complex. In the serial reversal learning task, the hens performed equally for the two changing reward contingencies in only three reversal stages. In the dMTS task, the hens increased their performance rapidly throughout the training sessions. Moreover, to the best of our knowledge, we present the first positive result of identity concept generalisation in a dMTS task in domestic hens. Our results provide additional information on the behavioural flexibility and concept understanding of domestic hens. They also support the idea that fully automated devices would improve knowledge of farm animals' cognition.

Statistical Learning in Vision

Vision and learning have long been considered to be two areas of research linked only distantly. However, recent developments in vision research have changed the conceptual definition of vision from a signal-evaluating process to a goal-oriented interpreting process, and this shift binds learning, together with the resulting internal representations, intimately to vision. In this review, we consider various types of learning (perceptual, statistical, and rule/abstract) associated with vision in the past decades and argue that they represent differently specialized versions of the fundamental learning process, which must be captured in its entirety when applied to complex visual processes. We show why the generalized version of statistical learning can provide the appropriate setup for such a unified treatment of learning in vision, what computational framework best accommodates this kind of statistical learning, and what plausible neural scheme could feasibly implement this framework. Finally, we list the challenges that the field of statistical learning faces in fulfilling the promise of being the right vehicle for advancing our understanding of vision in its entirety. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Are prime numbers special? Insights from the life sciences

Prime numbers have been attracting the interest of scientists since the first formulation of Euclid’s theorem in 300 B.C. Nowadays, physicists and mathematicians continue to formulate new theorems about prime numbers, trying to comprehensively explain their articulated properties. However, evidence from biology and experimental psychology suggest that prime numbers possess distinctive natural properties that pre-exist human grasping. The present work aims at reviewing the existing literature on prime numbers in the life sciences, including some recent experimental contributions employing newly hatched domestic chicks as animal model to test for spontaneous mechanisms allowing discrimination of primes from non-primes. Our overarching goal is that of discussing some instances of prime numbers in nature, with particular reference to their peculiar, non-mathematical, perceptual properties.

Assessing the Sensitivity of EEG-Based Frequency-Tagging as a Metric for Statistical Learning

Statistical learning (SL) is hypothesized to play an important role in language development. However, the measures typically used to assess SL, particularly at the level of individual participants, are largely indirect and have low sensitivity. Recently, a neural metric based on frequency-tagging has been proposed as an alternative measure for studying SL. We tested the sensitivity of frequency-tagging measures for studying SL in individual participants in an artificial language paradigm, using non-invasive electroencephalograph (EEG) recordings of neural activity in humans. Importantly, we used carefully constructed controls to address potential acoustic confounds of the frequency-tagging approach, and compared the sensitivity of EEG-based metrics to both explicit and implicit behavioral tests of SL. Group-level results confirm that frequency-tagging can provide a robust indication of SL for an artificial language, above and beyond potential acoustic confounds. However, this metric had very low sensitivity at the level of individual participants, with significant effects found only in 30% of participants. Comparison of the neural metric to previously established behavioral measures for assessing SL showed a significant yet weak correspondence with performance on an implicit task, which was above-chance in 70% of participants, but no correspondence with the more common explicit 2-alternative forced-choice task, where performance did not exceed chance-level. Given the proposed ubiquitous nature of SL, our results highlight some of the operational and methodological challenges of obtaining robust metrics for assessing SL, as well as the potential confounds that should be taken into account when using the frequency-tagging approach in EEG studies.

Neural processes underlying statistical learning for speech segmentation in dogs

To learn words, humans extract statistical regularities from speech. Multiple species use statistical learning also to process speech, but the neural underpinnings of speech segmentation in non-humans remain largely unknown. Here, we investigated computational and neural markers of speech segmentation in dogs, a phylogenetically distant mammal that efficiently navigates humans' social and linguistic environment. Using electroencephalography (EEG), we compared event-related responses (ERPs) for artificial words previously presented in a continuous speech stream with different distributional statistics. Results revealed an early effect (220-470 ms) of transitional probability and a late component (590-790 ms) modulated by both word frequency and transitional probability. Using fMRI, we searched for brain regions sensitive to statistical regularities in speech. Structured speech elicited lower activity in the basal ganglia, a region involved in sequence learning, and repetition enhancement in the auditory cortex. Speech segmentation in dogs, similar to that of humans, involves complex computations, engaging both domain-general and modality-specific brain areas. VIDEO ABSTRACT.

Lateralized Declarative-Like Memory for Conditional Spatial Information in Domestic Chicks (Gallus gallus)

Declarative memory is an explicit, long-term memory system, used in generalization and categorization processes and to make inferences and to predict probable outcomes in novel situations. Animals have been proven to possess a similar declarative-like memory system. Here, we investigated declarative-like memory representations in young chicks, assessing the roles of the two hemispheres in memory recollection. Chicks were exposed for three consecutive days to two different arenas (blue/yellow), where they were presented with two panels, each depicting a different stimulus (cross/square). Only one of the two stimuli was rewarded, i.e., it hid a food reward. The position (left/right) of the rewarded stimulus remained constant within the same arena, but it differed between the two arenas (e.g., reward always on the left in the blue context and on the right in the yellow one). At test, both panels depicted the rewarded stimulus, thus chicks had to remember food position depending on the previously experienced contextual rule. Both binocular and right-eye monocularly-tested chicks correctly located the reward, whereas left-eye monocularly-tested chicks performed at the chance level. We showed that declarative-like memory of integrated information is available at early stages of development, and it is associated with a left hemisphere dominance.

Stability and individual variability of social attachment in imprinting

Filial imprinting has become a model for understanding memory, learning and social behaviour in neonate animals. This mechanism allows the youngs of precocial bird species to learn the characteristics of conspicuous visual stimuli and display affiliative response to them. Although longer exposures to an object produce stronger preferences for it afterwards, this relation is not linear. Sometimes, chicks even prefer to approach novel rather than familiar objects. To date, little is known about how filial preferences develop across time. This study aimed to investigate filial preferences for familiar and novel imprinting objects over time. After hatching, chicks were individually placed in an arena where stimuli were displayed on two opposite screens. Using an automated setup, the duration of exposure and the type of stimuli were manipulated while the time spent at the imprinting stimulus was monitored across 6 days. We showed that prolonged exposure (3 days vs 1 day) to a stimulus produced robust filial imprinting preferences. Interestingly, with a shorter exposure (1 day), animals re-evaluated their filial preferences in functions of their spontaneous preferences and past experiences. Our study suggests that predispositions influence learning when the imprinting memories are not fully consolidated, driving animal preferences toward more predisposed stimuli.

Evidence of ordinal position encoding of sequences extracted from continuous speech

Infants' capacity to extract statistical regularities from sequential information is impressive and well documented. However, statistical learning's underlying mechanism remains mostly unknown, and its role in language acquisition is still under debate. To shed light on these issues, here we address the question of which information human subjects extract and encode after familiarisation with a continuous sequence of stimuli and its dependence on the type of segmentation cues and on the stimuli modality. Specifically, we investigate whether adults and 5-month-old infants learn the syllables' co-occurrence in the stream or generate a representation of the Words that include syllables' ordinal position. We test if subtle pauses signalling word boundaries change the encoding and, in adults, if it varies across modalities. In six behavioural experiments, we show that: (i) Adults and infants learn the streams' statistical structure. (ii) Ordinal encoding emerges in the auditory modality, and pauses enhanced it. However, (iii) ordinal encoding seems to depend on the learning stage and not on pauses marking Words' edges. Interestingly, (iv) for visual presentation of orthographic syllables, we do not find evidence of ordinal encoding in adults. Our results support the emergence, in the auditory modality, of a Word representation where its constituents are associated with an ordinal position at play already early in life, bringing new insights into speech processing and language acquisition. Additionally, we successfully use for the first time pupillometry in an infant segmentation task.

Different mechanisms underlie implicit visual statistical learning in honey bees and humans

The ability of developing complex internal representations of the environment is considered a crucial antecedent to the emergence of humans' higher cognitive functions. Yet it is an open question whether there is any fundamental difference in how humans and other good visual learner species naturally encode aspects of novel visual scenes. Using the same modified visual statistical learning paradigm and multielement stimuli, we investigated how human adults and honey bees (Apis mellifera) encode spontaneously, without dedicated training, various statistical properties of novel visual scenes. We found that, similarly to humans, honey bees automatically develop a complex internal representation of their visual environment that evolves with accumulation of new evidence even without a targeted reinforcement. In particular, with more experience, they shift from being sensitive to statistics of only elemental features of the scenes to relying on co-occurrence frequencies of elements while losing their sensitivity to elemental frequencies, but they never encode automatically the predictivity of elements. In contrast, humans involuntarily develop an internal representation that includes single-element and co-occurrence statistics, as well as information about the predictivity between elements. Importantly, capturing human visual learning results requires a probabilistic chunk-learning model, whereas a simple fragment-based memory-trace model that counts occurrence summary statistics is sufficient to replicate honey bees' learning behavior. Thus, humans' sophisticated encoding of sensory stimuli that provides intrinsic sensitivity to predictive information might be one of the fundamental prerequisites of developing higher cognitive abilities.

Statistical learning in domestic chicks is modulated by strain and sex

Statistical learning is a key mechanism for detecting regularities from a variety of sensory inputs. Precocial newborn domestic chicks provide an excellent model for (1) exploring unsupervised forms of statistical learning in a comparative perspective, and (2) elucidating the ecological function of statistical learning using imprinting procedures. Here we investigated the role of the sex of the chicks in modulating the direction of preference (for familiarity or novelty) in a visual statistical learning task already employed with chicks and human infants. Using both automated tracking and direct human coding, we confirmed chicks' capacity to recognize the presence of a statistically defined structure underlying a continuous stream of shapes. Using a different chicken strain than previous studies, we were also able to highlight sex differences in chicks' propensity to approach the familiar or novel sequence. This could also explain a previous failure to reveal statistical learning in chicks which sex was however not determined. Our study confirms chicks' ability to track visual statistics. The pivotal role of sex in determining familiarity or novelty preferences in this species and the interaction with the animals' strain highlight the importance to contextualize comparative research within the ecology of each species.

Non-human animals detect the rhythmic structure of a familiar tune

The musical motives of a song emerge from the temporal arrangement of discrete tones. These tones normally have few durational values, and are organized in structured groups to create metrical patterns. In the present study we show that the ability to detect the rhythmic structure of a song, while ignoring surface changes, is also present in other species. We familiarized rats (Rattus norvegicus) with an excerpt of the Happy Birthday song. During test, we presented the animals with (i) the same excerpt of the familiarization, (ii) a constant-pitch version of the excerpt that reduced melodic intervals to only one tone (i.e., isotonic) but preserved rhythmic structure, and (iii) a rhythmically scrambled version of the excerpt that preserved the melodic intervals. The animals discriminated the rhythmically scrambled version from the versions that preserved the original rhythm. This demonstrates that rats were sensitive to at least some parts of the rhythmic structure of the tune. Together with previous findings, the present set of results suggests that the emergence of rhythmic musical universals might be based on principles shared with other species.

The prevalence and importance of statistical learning in human cognition and behavior

Statistical learning, the ability to extract regularities from the environment over time, has become a topic of burgeoning interest. Its influence on behavior, spanning infancy to adulthood, has been demonstrated across a range of tasks, both those labeled as tests of statistical learning and those from other learning domains that predated statistical learning research or that are not typically considered in the context of that literature. Given this pervasive role in human cognition, statistical learning has the potential to reconcile seemingly distinct learning phenomena and may be an under-appreciated but important contributor to a wide range of human behaviors that are studied as unrelated processes, such as episodic memory and spatial navigation.

Automated Study Challenges the Existence of a Foundational Statistical-Learning Ability in Newborn Chicks

What mechanisms underlie learning in newborn brains? Recently, researchers reported that newborn chicks use unsupervised statistical learning to encode the transitional probabilities (TPs) of shapes in a sequence, suggesting that TP-based statistical learning can be present in newborn brains. Using a preregistered design, we attempted to reproduce this finding with an automated method that eliminated experimenter bias and allowed more than 250 times more data to be collected per chick. With precise measurements of each chick's behavior, we were able to perform individual-level analyses and substantially reduce measurement error for the group-level analyses. We found no evidence that newborn chicks encode the TPs between sequentially presented shapes. None of the chicks showed evidence for this ability. Conversely, we obtained strong evidence that newborn chicks encode the shapes of individual objects, showing that this automated method can produce robust results. These findings challenge the claim that TP-based statistical learning is present in newborn brains.

A common probabilistic framework for perceptual and statistical learning

System-level learning of sensory information is traditionally divided into two domains: perceptual learning that focuses on acquiring knowledge suitable for fine discrimination between similar sensory inputs, and statistical learning that explores the mechanisms that develop complex representations of unfamiliar sensory experiences. The two domains have been typically treated in complete separation both in terms of the underlying computational mechanisms and the brain areas and processes implementing those computations. However, a number of recent findings in both domains call in question this strict separation. We interpret classical and more recent results in the general framework of probabilistic computation, provide a unifying view of how various aspects of the two domains are interlinked, and suggest how the probabilistic approach can also alleviate the problem of dealing with widely different types of neural correlates of learning. Finally, we outline several directions along which our proposed approach fosters new types of experiments that can promote investigations of natural learning in humans and other species.

Traces of statistical learning in the brain's functional connectivity after artificial language exposure

Our environment is full of statistical regularities, and we are attuned to learn about these regularities by employing Statistical Learning (SL), a domain-general ability that enables the implicit detection of probabilistic regularities in our surrounding environment. The role of brain connectivity on SL has been previously explored, highlighting the relevance of structural and functional connections between frontal, parietal, and temporal cortices. However, whether SL can induce changes in the functional connections of the resting state brain has yet to be investigated. To address this question, we applied a pre-post design where participants (n = 38) were submitted to resting-state fMRI acquisition before and after in-scanner exposure to either an artificial language stream (formed by 4 concatenated words) or a random audio stream. Our results showed that exposure to an artificial language stream significantly changed (corrected p < 0.05) the functional connectivity between Right Posterior Cingulum and Left Superior Parietal Lobule. This suggests that functional connectivity between brain networks supporting attentional and working memory processes may play an important role in statistical learning.

Spontaneous Learning of Visual Structures in Domestic Chicks

Simple Summary

Our aim is to investigate the recognition of the structure of multi-element configurations; one mechanism that supports communicative functions in different species. Cognitive mechanisms involved in this ability might not have evolved specifically for communicative use, but derive from other functions. Thus, it is crucial to study these abilities in species that are not vocal learners and with stimuli from other modalities. We know already that domestic chicks can learn the temporal statistical structure of sequences of visual shapes, however their abilities to encode the spatial structure of visual patterns (configurations composed of multiple visual elements presented simultaneously side-by-side) is much less known. Using filial imprinting learning, we showed that chicks spontaneously recognize the structure of their imprinting stimulus, preferring it to one composed of the same elements in different configurations. Moreover, we found that in their affiliative responses chicks give priority to information located at the stimulus edges, a phenomenon that was so far observed only with temporal sequences. This first evidence of a spontaneous edge bias with spatial stimuli further stresses the importance of studying similarities and differences between the processing of linguistic and nonlinguistic stimuli and of stimuli presented in various sensory modalities.

Abstract

Effective communication crucially depends on the ability to produce and recognize structured signals, as apparent in language and birdsong. Although it is not clear to what extent similar syntactic-like abilities can be identified in other animals, recently we reported that domestic chicks can learn abstract visual patterns and the statistical structure defined by a temporal sequence of visual shapes. However, little is known about chicks’ ability to process spatial/positional information from visual configurations. Here, we used filial imprinting as an unsupervised learning mechanism to study spontaneous encoding of the structure of a configuration of different shapes. After being exposed to a triplet of shapes (ABC or CAB), chicks could discriminate those triplets from a permutation of the same shapes in different order (CAB or ABC), revealing a sensitivity to the spatial arrangement of the elements. When tested with a fragment taken from the imprinting triplet that followed the familiar adjacency-relationships (AB or BC) vs. one in which the shapes maintained their position with respect to the stimulus edges (AC), chicks revealed a preference for the configuration with familiar edge elements, showing an edge bias previously found only with temporal sequences.

Why and how the early-life environment affects development of coping behaviours

Understanding the ways in which individuals cope with threats, respond to challenges, make use of opportunities and mediate the harmful effects of their surroundings is important for predicting their ability to function in a rapidly changing world. Perhaps one of the most essential drivers of coping behaviour of adults is the environment experienced during their early-life development. Although the study of coping, defined as behaviours displayed in response to environmental challenges, has a long and rich research history in biology, recent literature has repeatedly pointed out that the processes through which coping behaviours develop in individuals are still largely unknown. In this review, we make a move towards integrating ultimate and proximate lines of coping behaviour research. After broadly defining coping behaviours (1), we review why, from an evolutionary perspective, the development of coping has become tightly linked to the early-life environment (2), which relevant developmental processes are most important in creating coping behaviours adjusted to the early-life environment (3), which influences have been shown to impact those developmental processes (4) and what the adaptive significance of intergenerational transmission of coping behaviours is, in the context of behavioural adaptations to a fast changing world (5). Important concepts such as effects of parents, habitat, nutrition, social group and stress are discussed using examples from empirical studies on mammals, fish, birds and other animals. In the discussion, we address important problems that arise when studying the development of coping behaviours and suggest solutions.

Constraints on Statistical Learning Across Species

Both human and nonhuman organisms are sensitive to statistical regularities in sensory inputs that support functions including communication, visual processing, and sequence learning. One of the issues faced by comparative research in this field is the lack of a comprehensive theory to explain the relevance of statistical learning across distinct ecological niches. In the current review we interpret cross-species research on statistical learning based on the perceptual and cognitive mechanisms that characterize the human and nonhuman models under investigation. Considering statistical learning as an essential part of the cognitive architecture of an animal will help to uncover the potential ecological functions of this powerful learning process.

Infant Statistical Learning

Perception involves making sense of a dynamic, multimodal environment. In the absence of mechanisms capable of exploiting the statistical patterns in the natural world, infants would face an insurmountable computational problem. Infant statistical learning mechanisms facilitate the detection of structure. These abilities allow the infant to compute across elements in their environmental input, extracting patterns for further processing and subsequent learning. In this selective review, we summarize findings that show that statistical learning is both a broad and flexible mechanism (supporting learning from different modalities across many different content areas) and input specific (shifting computations depending on the type of input and goal of learning). We suggest that statistical learning not only provides a framework for studying language development and object knowledge in constrained laboratory settings, but also allows researchers to tackle real-world problems, such as multilingualism, the role of ever-changing learning environments, and differential developmental trajectories.