About

Dr. Daphna Buchsbaum is the Principal Investigator of the Computational Cognitive Development Lab at Brown University. Her research focuses on understanding how humans and nonhuman animals, specifically dogs, develop causal and social reasoning abilities. The lab investigates how children and dogs learn about the world's causal structure, including physical and social causation, through experimental and computational techniques. This research addresses fundamental questions about cognition, such as how humans construct sophisticated mental representations from simple perceptual inputs and how these cognitive abilities develop over time. The lab's studies with dogs explore their physical problem-solving skills and social learning, using interactive games and training exercises designed to engage the animals. Similarly, research with children involves interactive games that examine their understanding of physical causation and social or psychological causation. Dr. Buchsbaum has been recognized for her contributions to the field, including a promotion to Associate Professor with tenure at Brown University effective July 1, 2025, and receiving the prestigious Wriston Fellowship from Brown University. Her work has been featured in various publications and media, highlighting the innovative research conducted in the Brown Dog Lab and the Computational Cognitive Development Lab.

Research topics

• Psychology
• Cognitive psychology
• Artificial Intelligence
• Computer Science
• Neuroscience
• Cognitive science
• Social psychology
• Biology
• Zoology
• Mathematics
• Developmental psychology
• Psychotherapist

Selected publications

• Children, but not capuchins, rationally integrate social and physical information when deciding which actions to copy

  2025-08-19 · 1 citations

  articleOpen access1st authorCorresponding

  Unlike other primates, young children have been shown to exhibit seemingly irrational overimitation—faithfully copying unnecessary steps from a demonstration. We tested 3- to 5-year-old children (N = 39) and capuchin monkeys (N = 21) on a causal reasoning task in which a sequence of two actions was demonstrated, followed by reward production. We manipulated (1) causal plausibility and (2) the degree and nature of demonstrator intentionality, to explore the hypothesis that children—but not capuchins—integrate information about demonstrator intent and causal relations to infer which actions are necessary. We compared both species’ behavior to Bayesian computational models with the same varying social and physical expectations. Our results suggest that both species can learn from causal demonstrations, and that their copying behavior is affected by both the demonstration’s causal plausibility and the demonstrator’s communicative cues, but that children may be unique in interpreting communicative cues as having pedagogical intent.

  PublisherOA PDFDOI

• Investigating Sensitivity to Shared Information and Personal Experience in Children’s Use of Majority Information

  Open Mind · 2025-01-01

  articleOpen accessSenior author

  Abstract Children and adults alike rely on others to learn about the world, but also need to be able to determine the strength of both their own evidence as well as the evidence that other people provide, particularly when different sources of information disagree. For example, if two informants agree on a belief but share the same evidence, their testimony is statistically dependent on each other, and may be weaker evidence for that belief than two informants who draw on different pieces of evidence to support that belief. Across three experiments (total N = 492), we examine how 4- and 5-year-old children evaluate statistical dependency on a task where they must determine which of two jars that toys were drawn from. A majority of informants, whose testimony could draw from the same evidence or different evidence, always endorsed one jar. Then, children were presented with a dissenting informant or their own personal data that was consistent with the other jar. Children showed no sensitivity to statistical dependency, choosing the majority with equal probability regardless of the independence of their testimony, but also systematically overweighted their own personal data, endorsing the jar consistent with their own evidence more often than would be predicted by an optimal Bayesian model. In contrast, children made choices consistent with this model on a similar task in which the data was presented to children without testimony. Our findings suggest that young children treat majorities as broadly informative, but that the challenges of inferring others’ experiences may lead them to rely on concrete, visible evidence when it is available.

  PublisherDOI

• Learning Children’s Conceptual Spaces using Deep Metric Learning.

  2025-09-15

  articleOpen accessSenior author

  Children learn to represent the world around them in meaningful categories that allow them to generalize past experiences. Understanding how these categorical representations develop is fundamental to cognitive science. However, capturing the structure of human conceptual knowledge is a challenging experimental task. The most prominent approach, Multidimensional Scaling (MDS), usually requires participants to produce many similarity judgments, leading to long experiments. Moreover, the representations found by MDS are limited to the fixed set of experimental stimuli and have to be reconstructed for every new item. In contrast, we present a more flexible machine-learning method that can generalize to novel stimuli. This method uses a child-friendly task that allows researchers to uncover the development of categories with fewer participant judgments. We evaluate our approach on simulated data and find that it can accurately reveal representations even when trained on data generated by groups that categorize differently. We then analyze data from the World Color Survey and find that we can recover language-specific color organization when aggregating languages that only share the same number of basic color terms. Finally, we use the method in a developmental experiment and find age-dependent differences in how complex fruit stimuli are organized. These differences were consistent with participants' reasoning and additional experimental measures. Our results suggest that our approach is applicable in psychological tasks and opens the possibility of examining children's developing psychological spaces in new detail.

  PublisherOA PDFDOI

• Evaluating Dogs’ Real‐World Visual Environment and Attention

  Cognitive Science · 2025-06-01

  articleOpen accessSenior author

  Dogs have a unique evolutionary relationship with humans, yet little is known about the visual information available to them or how they direct their visual attention within their environment. The present study, inspired by comparable work in infants, classified the items available to be gazed at by dogs during a common daily event, a walk. We then explored the statistics over the availability of those categories and over the dogs' visual attention. Using a head-mounted eye-tracking apparatus that was custom-designed for dogs, 11 dogs walked on a predetermined route outdoors under naturalistic conditions generating a total of 11,698 gazes for analysis. Image stills from these fixations were analyzed using computer vision techniques to explore the items present, the space within the visual field those items occupied, and which of the items the dog was gazing at. On average, dogs looked proportionally most at buses, plants, people, the pavement, and construction equipment; however, there were significant individual differences. The results of this project provide a foundational step toward understanding how dogs look at and interact with their physical world, opening up avenues for future research into how they learn and make decisions, both independently and with a human social partner.

  PublisherOA PDFDOI

• Preschool Children's Learning and Generalization of Continuous Causal Functions

  Underline Science Inc. · 2025-06-18

  otherOpen access

  Many causal relations can be represented by continuous functions that map inputs to outputs. Can young children learn continuous causal functions and generalize them from observed data to new scenarios? We found that 4- and 5-year-olds can represent continuous functions with different abstract forms. After observing a few input-output pairs, children can accurately infer positive linear and step functions by predicting the outputs of novel input values. They also have emerging knowledge of negative linear and triangular functions. While children do not yet make consistently accurate predictions for these functions, they can distinguish these functions from the positive linear function and show inferential patterns that are consistent with the respective functions. Like adults and older children, preschoolers show an inductive bias towards positive linear functions. Their understanding of negative linear functions--which strongly requires inhibiting this inductive bias--improves with age.

  PublisherDOI

• Resource-rational belief revision can mitigate as well as amplify polarization

  Underline Science Inc. · 2025-06-18

  otherOpen access

  People's beliefs sometimes diverge after observing the same information, which has been interpreted as evidence of irrationality. This behaviour has been proposed to result from people's limited cognitive resources and motivated reasoning, but how belief revision differs across these explanations has not been formalized or compared to a rational norm. Further, while people may be biased relative to a normative ideal, they may still make optimal choices given their limited cognitive resources, or rationally balance the utility of holding accurate beliefs with the belief's intrinsic utility. Across two studies, we develop and test a unified computational account of belief polarization under these proposed mechanisms, showing that people's performance on a belief updating task best fits a limited-resource Bayesian model; external motivations may contribute to divergence (or convergence) by determining what pre-existing information people consider relevant to a situation, rather than by changing how people evaluate new information in isolation.

  PublisherDOI

• Point Comprehension In Adults

  Open MIND · 2025-05-07

  otherOpen accessSenior author

  We aim to establish a baseline for how adults understand pointing gestures.

  PublisherOA PDFDOI

• Resource-rational belief revision can mitigate as well as amplify polarization

  2025-05-14

  preprintOpen accessSenior author

  People's beliefs sometimes diverge after observing the same information, which has been interpreted as evidence of irrationality. This behaviour has been proposed to result from people's limited cognitive resources and motivated reasoning, but how belief revision differs across these explanations has not been formalized or compared to a rational norm. Further, while people may be biased relative to a normative ideal, they may still make optimal choices given their limited cognitive resources, or rationally balance the utility of holding accurate beliefs with the belief's intrinsic utility. Across two studies, we develop and test a unified computational account of belief polarization under these proposed mechanisms, showing that people's performance on a belief updating task best fits a limited-resource Bayesian model; external motivations may contribute to divergence (or convergence) by determining what pre-existing information people consider relevant to a situation, rather than by changing how people evaluate new information in isolation.

  PublisherDOI

• An introduction to rational constructivism in cognitive development

  2025-02-04

  preprintOpen access

  Rational constructivism is a contemporary theory of cognitive development that aims to reconcile the existence of sophisticated cognitive abilities early in ontological development with the profound cognitive change we observe across childhood. The theory draws inspiration from computational cognitive science to describe children’s reasoning, concept learning, and revision as a form of probabilistic inference. Like previous constructivist theories, rational constructivism proposes that children generate and revise their own theories using the knowledge they obtain from the world; this information is integrated by using efficient, probabilistic inferential learning mechanisms to tweak or radically revise their existing theories, representations and beliefs. The paper begins with a general overview of the theory of rational constructivism, covering its key theoretical commitments and predictions. We then describe how it accounts for the empirically observed patterns of both incremental and radical developmental change observed in childhood and discuss the cognitive mechanisms of those conceptual changes. Finally, we sketch out a general computational framework for it, and address open questions and directions for future research.

  PublisherDOI

• Can children and adults balance majority size with information quality in learning from preferences?

  Journal of Experimental Psychology General · 2025-03-24

  articleSenior author

  = 241) balance the number of endorsements for a given option with the quality of the informants' source of information when deciding which of two boxes contains the better option. When choosing between two different boxes endorsed by groups of equal sizes, both children (Experiments 1-3) and adults (Experiment 6) tend to choose boxes endorsed by informants with visual access to the boxes over informants with hearsay. However, children's choices were biased toward the larger group when the size of the group conflicted with the quality of the source of the groups' information (Experiments 4 and 5), while adults more often chose the option endorsed by the group with the higher quality information (Experiment 6). Children were more likely to conform to a majority opinion when compared with both adults and to a normative computational model that endorses a group proportional to the number of independent, direct observations made by that group's informants. These findings suggest that, while adults balance the size of a majority with the quality of the informants' information source, preschoolers can evaluate when groups differ in the source of their information but may assume that the presence of a majority endorsing an option is inherently informative over and above the information source group members' testimony relied on. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

  PublisherDOI

Frequent coauthors

• Emma C. Tecwyn

  York St John University

  33 shared

• Julia Espinosa

  Harvard University

  32 shared

• Madeline Helmer Pelgrim

  Brown University

  29 shared

• Emily E. Bray

  20 shared

• Madeline H. Pelgrim

  Providence College

  19 shared

• C.-N. Alexandrina Guran

  University of Vienna

  18 shared

• Sarah‐Elizabeth Byosiere

  18 shared

• Christoph J. Völter

  University of Veterinary Medicine Vienna

  16 shared

Labs

• Computational Cognitive Development LabPI

Awards & honors

• Association for Psychological Science Rising Star (2018)
• ESRC Future Research Leaders grant