Laurence Maloney

About

Laurence Thomas Maloney is a Professor of Psychology and Neural Science at New York University. His research focuses on visual perception, decision making, and movement planning, with a particular interest in how organisms gather information and act on it. Maloney's central research interest is the comparison of human performance to models of performance based on mathematical statistics, physics, and mathematics. He completed his undergraduate studies in mathematics at Yale University in 1973, where he also took courses in computer science and automata theory. After graduation, he spent six years as a systems programmer designing operating systems before pursuing a Ph.D. in Psychology at Stanford University, which he obtained in 1985. During his time at Stanford, he studied color vision, issues of representation and measurement, and signal detection theory and statistical modeling. His doctoral dissertation concerned surface color perception and color constancy. Maloney has held academic positions at the University of Michigan, Ann Arbor, and has been a member of the vision group at New York University since then. His work has been recognized with numerous awards, including the Humboldt Research Award, the Troland Research Award, a Fulbright Scholar Award, a Guggenheim Fellowship, and fellowships from several scientific societies. His research and contributions have significantly advanced understanding in the fields of visual perception and cognitive modeling.

Research topics

• Computer Science
• Artificial Intelligence
• Psychology
• Cognitive psychology
• Mathematics
• Econometrics
• Statistics
• Social psychology
• Economics
• Physics

Selected publications

• The anticipation of events in time

  Nature Communications · 2019-12-20 · 54 citations

  articleOpen access

  Humans anticipate events signaled by sensory cues. It is commonly assumed that two uncertainty parameters modulate the brain's capacity to predict: the hazard rate (HR) of event probability and the uncertainty in time estimation which increases with elapsed time. We investigate both assumptions by presenting event probability density functions (PDFs) in each of three sensory modalities. We show that perceptual systems use the reciprocal PDF and not the HR to model event probability density. We a…

  PublisherOA PDFDOI

• Two sources of uncertainty independently modulate temporal expectancy

  Proceedings of the National Academy of Sciences · 2021 · 45 citations

  The environment is shaped by two sources of temporal uncertainty: the discrete probability of whether an event will occur and-if it does-the continuous probability of when it will happen. These two types of uncertainty are fundamental to every form of anticipatory behavior including learning, decision-making, and motor planning. It remains unknown how the brain models the two uncertainty parameters and how they interact in anticipation. It is commonly assumed that the discrete probability of whe…

  PublisherOA PDFDOI

• The bounded rationality of probability distortion

  Proceedings of the National Academy of Sciences · 2020 · 44 citations

  Senior authorCorresponding

  In decision making under risk (DMR) participants' choices are based on probability values systematically different from those that are objectively correct. Similar systematic distortions are found in tasks involving relative frequency judgments (JRF). These distortions limit performance in a wide variety of tasks and an evident question is, Why do we systematically fail in our use of probability and relative frequency information? We propose a bounded log-odds model (BLO) of probability and rela…

  PublisherOA PDFDOI

• Measuring and Modeling Visual Appearance

  Annual Review of Vision Science · 2020 · 23 citations

  1st authorCorresponding

  In studying visual perception, we seek to develop models of processing that accurately predict perceptual judgments. Much of this work is focused on judgments of discrimination, and there is a large literature concerning models of visual discrimination. There are, however, non-threshold visual judgments, such as judgments of the magnitude of differences between visual stimuli, that provide a means to bridge the gap between threshold and appearance. We describe two such models of suprathreshold j…

  PublisherDOI

• Sub-optimality in motor planning is not improved by explicit observation of motor uncertainty

  Scientific Reports · 2019-10-16 · 21 citations

  articleOpen access

  To make optimal decisions under risk, one must correctly weight potential rewards and penalties by the probabilities of receiving them. In motor decision tasks, the uncertainty in outcome is a consequence of motor uncertainty. When participants perform suboptimally as they often do in such tasks, it could be because they have insufficient information about their motor uncertainty: with more information, their performance could converge to optimal as they learn their own motor uncertainty. Altern…

  PublisherOA PDFDOI

Recent grants

• Surface color perception and illuminant cues in dynamic three-dimensional scenes

  NSF · $324k · 2011–2014

• NIH Grant R01EY019889

  NIH · $889k · 2015

Frequent coauthors

• Michael S. Landy

  New York University

  40 shared

• Kenneth Knoblauch

  University of South-Eastern Norway

  38 shared

• G Ander

  Ames Research Center

  36 shared

• Gordon L. Shulman

  36 shared

• Lincoln G. Craton

  Stonehill College

  36 shared

• Hang Zhang

  Center for Life Sciences

  36 shared

• Corrine M. Wickens

  Northern Illinois University

  36 shared

• Mary K. Kaiser

  36 shared

Awards & honors

• Humboldt Research Award of the Alexander von Humboldt Founda…
• Troland Research Award of the National Academy of Sciences (…
• Fulbright Scholar Award, Hungary (2014-2015)
• Guggenheim Fellowship, John Simon Guggenheim Foundation (201…
• Fellow, American Association for the Advancement of Science…

Similar researchers at New York University

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• Eero Simoncellih-113
• David Heegerh-95