The Founder’s Medal is the top honor given to a graduate of Vanderbilt University. Cornelius Vanderbilt’s gifts to the university included endowment of this award, given since 1877 for first honors in each graduating class. Akash Umakantha, who has been working in the CatLab since the end of his freshman year, is this year’s recipient from the School of Engineering at Vanderbilt. Congratulations Akash!
Akash Umakantha, from West Chester, Ohio, is Founder’s Medalist for the School of Engineering. He graduated with a bachelor of engineering in electrical and biomedical engineering. Umakantha has been a researcher at Cold Spring Harbor Laboratory, the Vanderbilt Radiation Effects and Reliability Group and the Vanderbilt Department of Psychology. He has presented his research on models of decision-making at two international conferences. Working in Professor of Psychology Tom Palmeri’s laboratory after freshman year, he learned about mathematical models of decision-making and how to simulate complex mathematical equations on a computer. That experience inspired him to pursue an academic career in neuroscience and scientific computing. Umakantha served as an engineering tutor, and he volunteered in a 6th grade classroom through Vanderbilt Student Volunteers for Science. He is a member of engineering honor society Tau Beta Pi. Next fall, Umakantha will attend Carnegie Mellon University to pursue doctoral studies in neural computation and machine learning.
The Bob Fox Award of Excellence in Post-Doctoral Research is granted to post-doctoral fellows in the Department of Psychology at Vanderbilt who have demonstrated outstanding achievement in research; it is named in honor of Robert “Bob” Fox for his essential role in guiding the evolution of Vanderbilt’s Psychology Department over a five-decade period starting in the mid-60s.
Jenn earned her PhD at Vanderbilt with Isabel Gauthier and Thomas Palmeri and has continued on at Vanderbilt as a post-doctoral fellow. She previously won the Nunnally Dissertation Award and the Pat Burns Graduate Student Research Award from the department. She has 30 peer-reviewed publications and is an Associate Editor at JEP:General. She also spearheaded the PeePs (Particularly Exciting Experiments in Psychology) newsletter that highlights research published in the six experimental psychology journals from APA.
The William F. Hodges Teaching Assistant Award recognizes outstanding achievement as a teaching assistant by a graduate student in the Department of Psychology at Vanderbilt. William Hodges was an undergraduate and a graduate student at Vanderbilt in the 1960s. After his untimely death in 1992, family and friends established the William F. Hodges Teaching Assistant Award at Vanderbilt to honor outstanding teaching assistants in the department.
May is a third year graduate student in the CatLab. She has completed a Certificate in College Teaching from the Center for Teaching and has TAed for a wide array of courses in the department, including PSY208 (Principles of Experimental Design), PSY209 (Quantitative Methods), and PSY225 (Cognitive Psychology); this semester, she is TAing for a statistics course in Psychology and Human Development. Adriane Seiffert, for whom May TAed in PSY208 and PSY209, noted that her work was “exemplary in both courses”, and that students commented that “she was responsive and helpful – gave exact answers to questions”, “conveyed the material in a way she knew would be effective, logical and memorable”. Geoff Woodman, for whom May TAed in PSY225, noted that she “jumped on a week’s worth of lectures when given the opportunity.”
We have a new paper in press:
Mack, M.L., & Palmeri, T.J. (in press). The dynamics of categorization: Unraveling rapid categorization. Journal of Experimental Psychology: General. [PDF]
We explore a puzzle of visual object categorization: Under normal viewing conditions, you spot something as a dog fastest, but at a glance, you spot it faster as an animal. During speeded category verification, a classic basic-level advantage is commonly observed (Rosch, Mervis, Gray, Johnson, & Boyes-Braem, 1976), with categorization as a dog faster than as an animal (superordinate) or Golden Retriever (subordinate). A different story emerges during ultra-rapid categorization with limited exposure duration (<30ms), with superordinate categorization faster than basic or subordinate categorization (Thorpe, Fize, & Marlot, 1996). These two widely cited findings paint contrary theoretical pictures about the time course of object categorization, yet no study has previously investigated them together. Over five experiments, we systematically examined two experimental factors that could explain the qualitative difference in categorization across the two paradigms: exposure duration and category trial context. Mapping out the time course of object categorization by manipulating exposure duration and the timing of a post-stimulus mask revealed that brief exposure durations favor superordinate-level categorization, but with more time a basic-level advantage emerges. But this superordinate advantage was modulated significantly by target category trial context. With randomized target categories, the superordinate advantage was eliminated; and with “blocks” of only four repetitions of superordinate categorization within an otherwise randomized context, the advantage for the basic-level was eliminated. Contrary to some theoretical accounts that dictate a fixed priority for certain levels of abstraction in visual processing and access to semantic knowledge, the dynamics of object categorization are flexible, depending jointly on the level of abstraction, time for perceptual encoding, and category context.
We are looking for outstanding students interested in a Research Experience for Undergraduates (REU) at the CatLab at Vanderbilt University this summer 2015. Our REU is part of an NSF-funded project entitled Perceptual Categorization in Real-World Expertise. This project uses online behavioral experiments to understand the temporal dynamics of perceptual expertise, measuring and manipulating the dynamics of object recognition and categorization at different levels of abstraction and assessing how those dynamics vary over measured levels of expertise, using computational models to test hypotheses about expertise mechanisms. Students have opportunities to work on projects ranging from the development of online experiments, development of analysis routines, and development and testing of computational models. This REU is especially appropriate for students interested in applying to graduate programs in psychology, vision science, cognitive science, or neuroscience. The REU provides a $5000 summer stipend, $500 per week for ten weeks; an additional $150 per week helps offsets the cost of housing and meals; a $250 travel allowance is also provided. REUs are restricted to undergraduate students currently enrolled in a degree program and must be U.S. citizens, U.S. nationals, or permanent residents of the United States. Undergraduates who are students at Vanderbilt may have the opportunity to continue the REU experience into the 2015-16 academic year.
People with perceptual expertise are skilled at making rapid identifications of specialized objects at a glance, often in poor light and camouflage. Forensic experts can accurately match exemplars to latent fingerprints that may be small, distorted, or smudged. Expert radiologists can quickly categorize medical images as normal or cancerous. Bird experts can identify species at long distances and in poor light. This project examines perception, categorization, and identification along the continuum from novice to expert performance in two real-world perceptual domains: analysis of latent fingerprints and zoological identification of birds. Forensic expertise was chosen because of its real-world importance in criminal and civil investigations and homeland security. Bird expertise was chosen not because it is important to understand bird identification per se, but because it is an excellent domain for studying a broad continuum of real-world expertise with a large and willing subject population. The overall aim is to understand how fundamental perceptual and cognitive mechanisms are tuned and modified by experience and expertise. The models arising from this project will enable us to understand the development of real-world perceptual expertise and to validate theoretically-grounded measures of expert performance.
Why study perceptual expertise? Just as gifted athletes push the limits of their bodies, or prize-winning mathematicians push the limits of their minds, perceptual experts push the limits of their perceptual systems. Perhaps with better markers of perceptual expertise and a better understanding of how people become perceptual experts, we could identify potential perceptual experts more effectively, train new perceptual experts more efficiently, and evaluate existing perceptual experts more thoroughly. Studying perceptual expertise can also help inform our understanding of the kinds of everyday expertise that we all have, such as recognizing faces or reading words. This can yield new insights into education and workforce training along with new insights into how the ravages of brain damage or disease might lead to perceptual and learning deficits and potentially inform future breakthroughs in evaluation, intervention, or treatment.
Following standard practice in my lab for the past two decades, undergraduates will be paired with a senior graduate student or postdoctoral fellow and work with them on a specific concrete project. They will read relevant research pertaining to the project underway and they will attend lab meetings. They will meet regularly with the graduate student or postdoctoral fellow as well as myself to discuss goals, achievements, and challenges. Undergraduates in my lab typically begin by working on an ongoing project but as their skills develop and their interests blossom, they often end up working on new projects more independently. Lab meetings often offer opportunities to discuss broader issues related to topics like responsible conduct of research and professional development.
Please send the following to Professor Thomas Palmeri at firstname.lastname@example.org; we will begin reviewing applications March 1, 2015.
- 1-2 page cover letter describing your educational experience and research background, your interest in the research in the CatLab, and your future goals; please also describe your computer programming experience.
- Resume or vita.
- Name of 2 individuals who could comment on your educational background, experience, and potential for research.
Undergraduate student participants supported with NSF funds in REU programs must be U.S. citizens, U.S. nationals, or permanent residents of the United States. An undergraduate student is a student who is enrolled in a degree program (part-time or full-time) leading to a baccalaureate or associate degree. Students who are transferring from one college or university to another and are enrolled at neither institution during the intervening summer may participate. High school graduates who have been accepted at an undergraduate institution but who have not yet started their undergraduate study are also eligible to participate. Students who have received their bachelor’s degrees and are no longer enrolled as undergraduates are generally not eligible to participate.
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.
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.
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.
Instructions for submission
– The submission website for this journal is located at: http://ees.elsevier.com/jmp/default.asp
– To ensure that all manuscripts are correctly identified for inclusion into the special issue, it is important that authors select SI: Model-Based Cognitive when they reach the “Article Type” step in the submission process
The Perceptual Expertise Network will be celebrating our 30th workshop by inviting current PEN members, previous PEN members, and PEN friends to join us for a day of talks as well as a reunion dinner following the talks. This will be held on May 14th, 2015 at the TradeWinds Island Grand Resort in St. Pete Beach, Florida, as a satellite to the annual VSS conference.
Our NEI Grant Stochastic Models of Visual Decision Making and Visual Search was just renewed for another four years, through end of 2018.
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. (2014). Studying real-world perceptual expertise. Frontiers in Cognition.