Justin Halberda

About

Justin Halberda is a professor in the Department of Psychological & Brain Sciences at Johns Hopkins University, where he also serves as Co-Director of Undergraduate Studies. His research interests include the interaction of vision, cognition, and language. He directs two laboratories that often collaborate: the Laboratory For Child Development, co-directed with Lisa Feigenson, which investigates language acquisition and the role of logical deductive inference in learning new words, working with infants, children, and adults. This lab trains students in eye-tracking and anticipatory-looking paradigms, focusing on the development of logical reasoning abilities and the interaction between quantifier terms and non-linguistic numerical systems. The second lab, the Vision And Cognition Lab, explores the organization of attention, working memory, and how the mind constructs representations of the world from sensory information, utilizing empirical methods and computational modeling. Students are encouraged to collaborate across labs and participate in research studies.

Research topics

• Computer Science
• Psychology
• Linguistics
• Cognitive psychology
• Artificial Intelligence
• Philosophy
• Natural Language Processing
• Mathematics
• Developmental psychology
• History

Selected publications

• Age and Species Comparisons of Visual Mental Manipulation Ability as Evidence for its Development and Evolution

  Scientific Reports · 2020 · 41 citations

  Intelligent behavior is shaped by the abilities to store and manipulate information in visual working memory. Although humans and various non-human animals demonstrate similar storage capacities, the evolution of manipulation ability remains relatively unspecified. To what extent are manipulation limits unique to humans versus shared across species? Here, we compare behavioral signatures of manipulation ability demonstrated by human adults and 6-to-8-year-old children with that of an animal sepa…

  PublisherOA PDFDOI

• Emergence of the Link Between the Approximate Number System and Symbolic Math Ability

  Child Development · 2020 · 31 citations

  Experimentally manipulating Approximate Number System (ANS) precision has been found to influence children's subsequent symbolic math performance. Here in three experiments (N = 160; 81 girls; 3-5 year old) we replicated this effect and examined its duration and developmental trajectory. We found that modulation of 5-year-olds' ANS precision continued to affect their symbolic math performance after a 30-min delay. Furthermore, our cross-sectional investigation revealed that children 4.5 years an…

  PublisherDOI

• Training nonsymbolic proportional reasoning in children and its effects on their symbolic math abilities

  Cognition · 2020 · 26 citations

  DOI

• The mental representation of universal quantifiers

  Linguistics and Philosophy · 2021 · 22 citations

  PublisherDOI

• Linguistic meanings as cognitive instructions

  Annals of the New York Academy of Sciences · 2021 · 20 citations

  Natural languages like English connect pronunciations with meanings. Linguistic pronunciations can be described in ways that relate them to our motor system (e.g., to the movement of our lips and tongue). But how do linguistic meanings relate to our nonlinguistic cognitive systems? As a case study, we defend an explicit proposal about the meaning of most by comparing it to the closely related more: whereas more expresses a comparison between two independent subsets, most expresses a subset-super…

  PublisherDOI

Recent grants

• The Psychophysical Assessment of Number-Sense Acuity

  NSF · $293k · 2009–2012

• NIH Grant R01HD057258

  NIH · $1.6M · 2014

• Empirical Research - Collaborative Research - A Bayesian Approach to Number Reasoning

  NSF · $159k · 2011–2014

Frequent coauthors

• Lisa Feigenson

  Johns Hopkins University

  33 shared

• Darko Odic

  University of British Columbia

  30 shared

• Melissa E. Libertus

  University of Pittsburgh

  24 shared

• Jeffrey Lidz

  University of Maryland, College Park

  19 shared

• Paul M. Pietroski

  Rutgers Sexual and Reproductive Health and Rights

  17 shared

• Hrag Pailian

  Huawei Technologies (Canada)

  16 shared

• Hee Yeon Im

  University of British Columbia

  13 shared

• Tim B. Hunter

  12 shared

Labs

• Justin Halberda LaboratoryPI

Similar researchers at Johns Hopkins University

• Richard Huganirh-210
• Michela Gallagherh-104
• Patricia Janakh-88