Martin Zettersten

Behavioral flexibility—the ability to adapt behavior in response to changing conditions—is commonly measured using reversal learning tasks, where individuals must inhibit a previously rewarded response and adopt a new one after contingencies change. Despite widespread use, task comparability across species remains unclear. We systematically reviewed 206 empirical studies (2014–2023) spanning eight taxa: invertebrates, fishes, amphibians and reptiles, birds, rodents, non-human primates, humans, and other mammals. We extracted species coverage, sampling, learning and reversal criteria, cue types, and outcome measures, and characterized cross-taxon variation using nonparametric tests, correlation analyses, linear discriminant analyses, and model-based robustness checks. We identify three methodological obstacles. First, research is highly imbalanced, concentrated on humans, birds, and rodents. Most animal diversity remains virtually untested, with under 1% of described species represented in five of the seven non-human taxa. Second, research is taxonomically fragmented: 99% of studies examine only one taxon, limiting direct comparisons. Third, methodological standards diverge dramatically across taxa. Humans consistently face the strictest learning criteria, while other taxa typically use lower thresholds. Mean reversal phases differ more than threefold across taxa: single-reversal designs predominate in amphibians and reptiles, fishes, and invertebrates, whereas multi-reversal protocols are relatively more frequent in humans and non-human primates. Sample sizes, evaluation window lengths, cue types, and outcome measures also show taxon-specific patterns. These systematic design differences complicate cross-taxon comparisons, blurring the line between true cognitive variation and methodological artifacts. Greater methodological coordination and broader taxonomic coverage are needed, and emerging large-scale collaborations offer a promising path forward.

The ability to learn and apply rules lies at the heart of cognition. In a seminal study, Marcus et al. (1999) reported that 7‐month‐old infants learned abstract rules over syllable sequences and were able to generalize those rules to novel syllable sequences. Dozens of studies have since replicated that finding and extended it using different rules, modalities, stimuli, participants (human adults and non‐human animals) and experimental procedures. Yet questions remain about the generalizability of the core findings in Marcus et al., and sources of variation across these findings. In the current study, we address this issue by testing 839 infants (650 after exclusions) of a wide age range (5;0–12;0 months) in a multi‐laboratory (30 laboratories, [31 samples]) conceptual replication of the Marcus et al. study. This study and the analysis plan were submitted as a registered report. A mixed‐model analysis of the looking times at consistent versus inconsistent test trials indicated no significant effect. The current study therefore finds no evidence for rule‐learning; to the contrary, a Bayesian analysis of the data indicated strong evidence for a null effect. This was similarly the case for the moderating factors that were part of the design: mono‐ versus multilingualism, age, and experimental paradigm; none of these factors showed significant effects. Robustness analyses indicated that the results were not different in the case of different choices in the (pre‐)processing of the data. A follow‐up analysis for single labs indicated that there was no evidence of rule‐learning in 30 of the 31 contributed samples. The current finding raises fundamental issues about rule‐learning that are presented in the Discussion section.

Being a fluent language user involves recognizing words as they unfold in time. How does this skill develop over the course of early childhood? And how does facility in word recognition relate to the growth of vocabulary knowledge? We address these questions using data from Peekbank, an open database of experiments measuring children’s eye movements during early word recognition. In an observational study of 26 datasets from over 2500 children ages 6 months to 6 years, we show that word recognition becomes faster, more accurate, and less variable across development, consistent with a process of skill learning. Factor analysis reveals covariation of word recognition speed and accuracy with children’s vocabulary size in cross-sectional analysis. Further, across a range of longitudinal models, speed, accuracy, and vocabulary were coupled. Children with overall faster word recognition tended to show faster vocabulary growth, though developmental growth in word recognition skill was not specifically associated with growth in vocabulary. Together, these findings support the view that word recognition is a skill that develops gradually across early childhood and that this skill is deeply intertwined with early language learning.

A decade of ManyBabies research, testing thousands of babies across hundreds of labs, has shown that some, but not all findings in infant research replicate well. Collectively, these projects have shown us that our methods carry limitations that larger samples alone cannot resolve. Here we present three lessons that point toward a more reliable, inclusive developmental science. A decade of ManyBabies research, testing thousands of babies across hundreds of labs, has shown that some, but not all findings in infant research replicate well. Collectively, these projects have shown that current methods carry limitations that larger samples alone cannot resolve. Here three lessons that point toward a more reliable, inclusive developmental science are presented.

Being a fluent language user involves recognizing words as they unfold in time. How does this skill develop over the course of early childhood? And how does facility in word recognition relate to the growth of vocabulary knowledge? We address these questions using data from Peekbank, an open database of experiments measuring children’s eye movements during early word recognition. In an observational study of 26 datasets from over 2,500 children ages 6 months – 6 years, we show that word recognition becomes faster, more accurate, and less variable across development, consistent with a process of skill learning. Factor analysis reveals covariation of word recognition speed and accuracy with children’s vocabulary size in cross-sectional analysis. Further, across a range of longitudinal models, speed, accuracy, and vocabulary were coupled. Children with overall faster word recognition tended to show faster vocabulary growth, though developmental growth in word recognition skill was not specifically associated with growth in vocabulary. Together, these findings support the view that word recognition is a skill that develops gradually across early childhood and that this skill is deeply intertwined with early language learning.

We use language to communicate our thoughts. But is language merely the expression of thoughts, which are themselves produced by other, nonlinguistic parts of our minds? Or does language play a more transformative role in human cognition, allowing us to have thoughts that we otherwise could (or would) not have? Recent developments in artificial intelligence (AI) and cognitive science have reinvigorated this old question. We argue that language may hold the key to the emergence of both more general AI systems and central aspects of human intelligence. We highlight two related properties of language that make it such a powerful tool for developing domain-general abilities. First, language offers compact representations that make it easier to represent and reason about many abstract concepts (e.g., exact numerosity). Second, these compressed representations are the iterated output of collective minds. In learning a language, we learn a treasure trove of culturally evolved abstractions. Taken together, these properties mean that a sufficiently powerful learning system exposed to language—whether biological or artificial—learns a compressed model of the world, reverse engineering many of the conceptual and causal structures that support human (and human-like) thought.

We investigate the roles of linguistic and sensory experience in the early-produced visual, auditory, and abstract words of congenitally-blind toddlers, deaf toddlers, and typically-sighted/hearing peers. We also assess the role of language access by comparing early word production in children learning English or American Sign Language (ASL) from birth, versus at a delay. Using parental report data on child word production from the MacArthur-Bates Communicative Development Inventory, we found evidence that while children produced words referring to imperceptible referents before age 2, such words were less likely to be produced relative to words with perceptible referents. For instance, blind (vs. sighted) children said fewer highly visual words like “blue” or “see”; deaf signing (vs. hearing) children produced fewer auditory signs like hear. Additionally, in spoken English and ASL, children who received delayed language access were less likely to produce words overall. These results demonstrate and begin to quantify how linguistic and sensory access may influence which words young children produce.

How do infants become word meaning experts? This registered report investigated the structure of infants' early lexical representations by manipulating the typicality of exemplars from familiar animal categories. 14- to 18-month-old infants (N = 84; 51 female; M = 15.7 months; race/ethnicity: 64% White, 8% Asian, 2% Hispanic, 1% Black, and 23% multiple categories; participating 2022–2023) were tested on their ability to recognize typical and atypical category exemplars after hearing familiar basic-level category labels. Infants robustly recognized both typical (d = 0.79, 95% CI [0.54, 1.03]) and atypical (d = 0.70, 95% CI [0.46, 0.94]) exemplars, with no significant difference between typicality conditions (d = 0.14, 95% CI [−0.08, 0.35]). These results support a broad-to-narrow account of infants' early word meanings. Implications for the role of experience in the development of lexical knowledge are discussed.