People   

Justin Halberda, PhD.

halberda@jhu.edu
website | curriculum vitae

phone: 410-516-6289

I have interests in visual attention and visual working memory. Recently, this has led to interests in set-based representations (e.g. number of items, average size, average orientation, centroid). Such representations collapse across many individuals to represent general tendencies of a group of items. I am also interested in the psychophysics of numerical estimation; the innate ability to approximate the number of items in a set.

Hee Yeon Im
PhD Student, 5th-Year
heeyeon.im@jhu.edu
I have broad research interests in visual perception, attention, and how they interact. I have focussed on how the visual system optimizes the use of its limited resources and what heuristics are involved in efficient coding of the visual scene. Representing general descriptions (such as holistic processing of a gist and statistical properties) instead of every detail of the visual scene is one way to economize on the limited capacity of the visual system. To understand how the visual system represents these general descriptions, I am currently working on the neural mechanisms of the represenation of ensemble features (e.g., the processes of averaging size or orientation and approximating the number of objects) and set-based representation.

Darko Odic
PhD Student, 4th-Year
darko.odic@jhu.edu

Despite initial impressions, human cognition is not unified, and, at any given time, different kinds of mental representations concurrently interact and influence our behaviour. My research focuses on how various mental representations develop, how they differ in kind from one another, how they interact to successfully guide our behaviour. I seek to answer these questions through work on both children (through the Lab for Child Development), and adults. Currently, I am exploring how different kinds of number representations interact with one another, with language, and with other cognitive systems. I am specifically interested in the relationships between the Approximate Number System, visual-short term memory, and spatial representations. I hope to use these insights to answer questions about the nature of human thought, its limits, the covergence of varying representations on coherent behaviours, and how all these relate to consciousness and to the impression of unification.

Hrag Pailian
PhD Student, 3rd-Year

Models of VWM place focus on how much information can be stored to characterize the architecture of the system and determine the format of representations. However, my approach towards accomplishing these goals has been to focus on the computations that the system allows us to perform on such information. As such, I have particularly been interested in determining whether the limit for manipulating information is independent of that for storing information, and whether original representations are updated or remain separate once they have been subjected to a computation. Furthermore, I have also developed a novel method, the Flicker paradigm, which incorporates the multiple computations involved during information processing, to allow for storage constraints to be studied within the context of how VWM is flexibly used in the real world. By adopting an algorithmic approach towards studying VWM, and investigating how it also interfaces with visual selective attention, long-term memory, and ensemble processing, I ultimately strive to answer the question: “What is the unit of VWM?”.

Robert Eisinger
Undergraduate

Robert Eisinger is an undergraduate student at the Johns Hopkins University studying computer science, mathematics, computer integrated surgery, and pre-medical sciences. He is currently the head research coordinator at the Vision & Cognition Lab and has independently developed several mobile applications. He enjoys questioning fundamental processes taking place in the mind, with special attention to the vision-related processes - especially subitizing, the approximate number system, visual working memory and related capacities, representation of number, counting, and image parsing and extraction.

VCL Alumni   

Alex Friedman

Undergraduate Research Assistant


B.S. Psychology

Spring 2008

 

Ryan Ly

Undergraduate Research Assistant


B.A. Neuroscience

M.S. Computer Science


currently pursuing a Ph.D. in Computational Neuroscience at Princeton University.

Billy Prin

Undergraduate Research Assistant


B.S. Computer Science
Fall 2007