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Category Laboratory at Vanderbilt (Web Page Now Being Revised)

supported by NSF, NEI, and Vanderbilt University

In the CatLab, we study visual cognition, including visual categorization, visual memory, and visual decision making. We study how objects are perceived and represented by the visual system, how visual knowledge is represented and learned, and how visual decisions are made. We approach these questions using a combination of behavioral experiments, cognitive neuroscience techniques, and computational and neural modeling. One line of work, funded by the National Science Foundation, investigates the temporal dynamics of visual object categorization and perceptual expertise for objects and faces. Another line of work, funded by the National Eye Institute, uses computational modeling of visual decision making to predict behavioral dynamics and neural dynamics.

Current Projects

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New Papers

Posted on Jan 28, 2015

New papers in press:

Palmeri, T.J., & Mack, M.L. (in press). How experimental trial context affects perceptual categorization. Frontiers in Psychology.

Logan, G.D., Yamaguchi, M., & Schall, G.D., & Palmeri, T.J. (in press). Inhibitory control in mind and brain 2.0: A blocked-input model of saccadic countermanding. Psychological Review.

Richler, J.J., Palmeri, T.J., & Gauthier, I. (in press). Holistic processing does not require configural variability. Psychonomic Bulletin & Review.

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Special Issue on Model-Based Cognitive Neuroscience

Posted on Dec 5, 2014

Thomas Palmeri from Vanderbilt, Brad Love from University College London, and Brandon Turner from The Ohio State University are co-editing a special issue of the Journal of Mathematical Psychology on Model-Based Cognitive Neuroscience. This special issue aims to explore the growing intersection between cognitive modeling and cognitive neuroscience. Cognitive modeling has a rich history of formalizing and testing hypotheses about cognitive mechanisms within a mathematical and computational language, making exquisite predictions of how people perceive, learn, remember, and decide. Cognitive neuroscience aims to identify neural mechanisms associated with key aspects of cognition, using techniques like neurophysiology, electrophysiology, and structural and functional brain imaging.

These two come together in a powerful new approach called model-based cognitive neuroscience, which can both inform model selection and help interpret neural measures. Cognitive models decompose complex behavior into representations and processes and these latent model states are used to explain the modulation of brain states under different experimental conditions. Reciprocally, neural measures provide data that help constrain cognitive models and adjudicate between competing cognitive models that make similar predictions of behavior. For example, brain measures are related to cognitive model parameters fitted to individual participant data, measures of brain dynamics are related to measures of model dynamics, model parameters are constrained by neural measures, model parameters are used in statistical analyses of neural data, or neural and behavioral data are analyzed jointly within hierarchical modeling framework.

We anticipate this special issue to include a combination of tutorial articles, reviews, and research articles. We invite potential contributors to discuss ideas or plans for submissions with the guest editors of the special issue; we especially want to coordinate plans for tutorials and reviews to minimize potential overlap. A formal expression of interest, including a tentative title and abstract, should be submitted to Thomas Palmeri ( by January 30, 2015.

Anticipated Timeline
Initial Call for Submissions: December 5, 2014
Expression of Interest / Tentative Title and Abstract : January 30, 2015
Open for Initial Submissions: April 1, 2015
Deadline for Initial Submissions: July 30, 2015
We hope to have the special issue finalize by the end of 2015/ beginning of 2016

Editors, Review Board, Ad-hoc Reviewers
The guest co-editors for this special issue of the Journal of Mathematical Psychology will be Thomas Palmeri, Bradley Love, and Brandon Turner; appeals to editorial decisions will be handled by the Editor-in-Chief, Philip Smith. We would like this to be a community effort, so we will invite a subset of contributors to join a review board for the special issue, and we will request other contributors to be willing to review at least one submission.

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NEI Grant Renewed

Posted on Nov 4, 2014

Our NEI Grant Stochastic Models of Visual Decision Making and Visual Search was just renewed for another four years, through end of 2018.

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New papers from the CatLab

Posted on Aug 27, 2014

Shen, J., & Palmeri, T.J. (in press). The perception of a face is greater than the sum of its parts. Psychonomic Bulletin & Review.

Folstein, J., Palmeri, T.J., Van Gulick, A.B., & Gauthier, I. (in press). Category learning stretches neural representations in visual cortex. Current Directions in Psychological Science.

Shen, J., Mack, M.L., & Palmeri, T.J. (in press). Studying real-world perceptual expertise. Frontiers in Cognition.

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NSF REU Supplement awarded

Posted on Jul 15, 2014

The CatLab has just been awarded a $19,500 supplementary grant from the National Science Foundation for a Research Experience for Undergraduates. Academic year REU students will receive a $3000 stipend per semester. Summer REU students will receive a $5000 stipend, a $1500 housing and meal allowance, and $250 travel allowance. Interested undergraduates should contact Professor Palmeri at for information on how to apply.

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Braden Purcell wins Jum Nunnally Dissertation Award

Posted on Apr 22, 2014

Congratulations to Braden Purcell for winning the 2014 Jum Nunnally Dissertation Award! This makes the third CatLab PhD student to win this prestigious award, along with Mike Mack in 2011 and Jenn Richler in 2010.

The Jum Nunnally Dissertation Award recognizes a recent outstanding doctoral dissertation in the Department of Psychology. The recipient receives a certificate and a $500 award. Jum Nunnally came to Vanderbilt in 1960. In 1961, he became the second chair of the department. He served as chair from 1961-1964 and again from 1967-1970. Under Jum’s leadership, the department grew substantially in stature, including significant increases in both the number and quality of the faculty. A memorial fund to support student awards was established in 1982 by his friends and family. Proceeds from this fund were used to establish the Jum Nunnally Dissertation Award in 2010.

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Two new postdocs join the CatLab

Posted on Apr 1, 2014

Brent Miller joins to lab as a postdoctoral fellow this month with a background in computer engineering and psychology. He comes from the University of California, Irvine, where he received his PhD in 2014 with Mark Steyvers. Brent is broadly interested in how the mechanisms of information storage, retrieval, and encoding affect judgment and decision making. Previously, he used computational modeling to show how certain decision behavior necessarily arises from probabilistic information representation in the brain. As a postdoctoral fellow at Vanderbilt, he will work on developing and testing computational models of behavior and neurophysiology in our collaboration with Jeff Schall and Gordon Logan.

Jeff Annis will receive his PhD from the University of South Florida this summer, where he has been studying the relationship between memory and perception via sequential dependencies with Ken Malmberg. Jeff is interested in the mechanisms and representations involved in memory and categorization. He will join the lab as postdoctoral fellow this summer to use computational models and empirical investigations to understand the dynamics of perceptual expertise.

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Paper to appear in PNAS

Posted on Jan 8, 2014

Zandbelt, B.B., Purcell, B.A., Palmeri, T.J., Logan, G.D., Schall, J.D. (2014). Response times from ensembles of accumulators. Proceedings of the National Academy of Sciences. [PDF]

Decision making is explained by psychologists through stochastic accumulator models and by neurophysiologists through the activity of neurons believed to instantiate these models. This paper investigated an overlooked scaling problem: How does a response time (RT) that can be explained by a single model accumulator arise from numerous, redundant accumulator neurons, each of which individually appears to explain the variability of RT? 

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Three new contributions to edited volumes

Posted on Jan 8, 2014

Three new papers. Two in the Oxford Handbook of Computational and Mathematical Psychology and one in An Introduction to Model-Based Cognitive Neuroscience.

Palmeri, T.J., Schall, J.D. & Logan, G.D. (in press). Neurocognitive modeling of perceptual decision making. To appear in J.R. Busemeyer, J. Townsend, Z.J. Wang, & A. Eidels (Eds.), Oxford Handbook of Computational and Mathematical Psychology, Oxford University Press. [PDF]

Nosofsky, R.M., & Palmeri, T.J. (in press). Exemplar-based random walk model. To appear in J.R. Busemeyer, J. Townsend, Z.J. Wang, & A. Eidels (Eds.), Oxford Handbook of Computational and Mathematical Psychology, Oxford University Press. [PDF]

Logan, G.D., Schall, J.D., & Palmeri, T.J. (in press). Inhibitory control in mind and brain: The mathematics and neurophysiology of the underlying computation. To appear in B. Forstmann & E.J. Wagenmakers (Eds.), An Introduction to Model-Based Cognitive Neuroscience, Springer Neuroscience. [PDF]

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