Christoph T. Weidemann

University of Pennsylvania
Department of Psychology
3401 Walnut St., Room 302c
Philadelphia, PA 19104, USA

Phone: +1-215-573-3365
Fax: +1-215-746-6848
E-mail: ctw at cogsci. info [e-mail]

Research Interests

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Education

Papers

Links

I am interested in human information processing and how it is influenced and shaped by attention and learning. We constantly receive streams of input from our senses, which effortlessly give rise to percepts that include associations with stored memories. The processes responsible for generating these percepts are computationally very sophisticated — a fact that has become especially clear since researchers have attempted to solve seemingly simple tasks, such as object recognition, by artificial means. A hallmark of human information processing is its remarkable flexibility, which allows a given stimulus to give rise to a vast variety of potential percepts.

My research focuses on three related questions:

How do basic aspects of a stimulus (such as its duration and location), its context, and the learned structure of the environment give rise to a percept?
How are percepts integrated over longer spans of times and locations to enable us to remember where things are in the world and how to get there?
How can processes that influence the perception of a stimulus be distinguished from those that mainly influence its evaluation or the response it elicits?

To answer these questions, I rely on computational models to guide the design of experiments. The behavioral and neurophysiological data I collect, in turn, inform and constrain theoretical accounts.

Graduate education & work experience

Currently:: Post-doctoral research fellow at the Computational Memory Lab
Department of Psychology , University of Pennsylvania ; supervisor: Prof. Michael J. Kahana; Visiting Researcher (Neurosurgery) at the David Geffen School of Medicine at UCLA
August 2006:: PhD in psychology and cognitive science (minors in neuroscience and statistics)
Indiana University, Bloomington ; advisor: Prof. Richard M. Shiffrin
Spring & Summer 2004:: Pre-doctoral research fellow at the Center for Adaptive Behavior and Cognition
Max Planck Institute for Human Development , Berlin, Germany
September 2002:: Diplom (German degree similar to MS/MA ) in psychology
University of Bonn, Germany

Papers

I had to transfer the copyright for some of the articles listed below to the publishers of the journals in which they appeared. However, I am allowed to distribute copies to individuals for personal and/or research use. Your click on any of the links below constitutes your request to me for a personal copy of the linked article. A detailed copyright notice appears in the articles. Nature's webdebates published an interesting related article by Richard M. Stallman titled "Science must `push copyright aside´" [link] .

Peer reviewed articles

Mueller, S. T. & Weidemann, C. T. (2008). Decision noise: An explanation for observed violations of Signal Detection Theory. Psychonomic Bulletin and Review, 15 465-494.
Mueller, S. T., Weidemann, C. T., & Shiffrin, R. M. (2008). Alphabetic letter similarity Matrices. Manuscript in revision ("revise & resubmit") at Acta Psychologica. [Available upon request.]
Weidemann, C. T., Huber, D. E., & Shiffrin, R. M. (2008). Prime diagnosticity in short-term repetition priming: Is primed evidence discounted, even when it reliably indicates the correct answer? Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 257-281.
Weidemann, C. T., Huber, D. E., & Shiffrin, R. M. (2005). Confusion and compensation in visual perception: Effects of spatiotemporal proximity and selective attention. Journal of Experimental Psychology: Human Perception and Performance, 31, 40-61.

Other manuscripts

Weidemann, C. T., Mollison M. V. & Kahana, M. j. (2008). Electrophysiological correlates of high-level perception during spatial navigation. Manuscript submitted for publication. [Available upon request.]
Weidemann, C. T. & Mueller, S. T. (2008). Decision Noise May Mask Criterion Shifts: Reply to Balakrishnan and MacDonald (2008). Manuscript submitted for publication. [Available upon request.]
Weidemann, C. T. & Rieskamp, J. (2008). Is human covariation assessment really Bayesian hypothesis testing? Manuscript in preparation. [Available upon request.]
Weidemann, C. T. (2006). Identifying brief stimuli. Perceptual, preferential, and decisional aspects. Unpublished doctoral dissertation. Departments of Psychological & Brain Sciences and Cognitive Science, Indiana University, Bloomington. [Available upon request.]
Weidemann, C. T. (2002). Effects of prime duration and location in perceptual identification. Unpublished Diplom thesis. Department of Psychology, University of Bonn, Germany. [Available upon request.]

Links

Selected collaborators not linked above:

David E. Huber: Assistant professor at the Psychology Department, University of California, San Diego
Shane T. Mueller: Senior Research Scientist at Klein Associates Division of ARA, Inc.
Jörg Rieskamp: Research scientist at the Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development
Sean Polyn: Consummate scientician

Great software for science:

Below I am posting links to a few selected programs (not written by me) that I find particularly useful for scientific work. All programs linked below are free in the sense that anyone may download, install, use, modify, and distribute them (detailed information can be found on the respective websites linked below). This freedom is particularly valuable for scientific work, because it allows the free sharing of one's work with collaborators, colleagues, students, or anyone else without requiring the recipient to purchase a license for the associated program. I run these programs on Kubuntu [link] Linux [link] , but all programs linked here are also easily installed on other operating systems.

The Python programming language: A nice object oriented programming language, well suited for scientific computing. Of particular interest are Scientific Python (SciPy) and other tools offered by Enthought as well as the Python Experiment Programming Library (PyEPL) and the plotting library Matplotlib . Substantial documentation is available on the Python documentation website .

The R project for statistical computing: A powerful software environment for statistical computing and graphics. Users of Emacs or XEmacs will enjoy the Emacs Speaks Statistics (ESS) mode. Other great languages for scientific computing include Octave , Scilab , and Maxima and there is also a Python interface for R called RPy . Extensive documentation for each of these programs is available at the respective websites.

LaTeX: A high-quality document preparation and typesetting system optimized for technical and scientific documents. Also useful for creating presentations (e.g., with the Beamer class) and posters (e.g., with Per Sederberg's Tkboxen style [available upon request]).

Unison: A great file synchronizer. Not directly science related, but useful for anybody who regularly uses more than one computer and wants to keep them synchronized.