Christoph T. Weidemann, Ph.D.

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]

By popular request: How to pronounce my name

IPA: [link] [kɹɪstʰɔf vaɪdəman]
My first name is pronounced similarly to the English pronunciation of "Christopher" without the final "er" sound.
My last name sounds somewhat like the American-English pronounciation of "vitamin".
Here is a recording in three audio formats: ogg [OGG] mp3 [MP3] wav [WAV]

Research Interests

I am interested in human information processing and how it is influenced by attention and learning. My research focuses on investigating the processes responsible for the context-dependent integration of sensory input over time and space and those responsible for the goal-driven interpretation of these percepts. I heavily rely on computational models to guide the design of experiments and analyses. The data I collect, in turn, inform and constrain theoretical accounts.

Integrating sensory input with task context

It is clear that perception relies on a considerable amount of temporal and spatial integration of sensory input. In vision, for example, the firing pattern of neurons in the retina constantly changes due to movements of objects or the eyes, neural fatigue, eye blinks, changes in lighting, etc., yet an observer usually has little difficulty perceiving constant object identity. At the same time, even very similar objects that appear close in time and space can often be discriminated, suggesting that complementary processes that segment the visual stream also exist. I am investigating how sensory input is integrated to generate percepts of varying complexity ranging from letters and words to higher order information about relationships between variables.

Evaluating percepts

Current goals and needs flexibly shape percepts and profoundly affect their impact on behavior. A bench, a tree stump, and a low wall, for example, may all be viewed as examples of the goal category when searching for an object to sit on, whereas only one particular chair serves this function when returning to a seat in a restaurant. I am investigating how percepts are interpreted and how they give rise to context-specific responses measured as choice behavior, EEG activity, and firing patterns of individual neurons recorded from human neurosurgery patients.

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
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 web debates published an interesting related article by Richard M. Stallman titled "Science must `push copyright aside´" [link] .

Peer reviewed articles

Other manuscripts

Davelaar, E. J., Huber, D. E., Xing, T., & Weidemann, C. T. (2009). A habituation account of change detection in same/different judgments Manuscript submitted for publication. [Available upon request.]
Mueller, S. T. & Weidemann, C. T. (2009). Alphabetic letter perceivability, similarity, and bias. Manuscript submitted for publication. [Available upon request.]
Weidemann, C. T., Solway, A., Kahana, M. J., & Fried, I. (2009). Single neurons in the human brain encode task context. Manuscript submitted for publication. [Available upon request.]
Weidemann, C. T., & Rieskamp, J. (2009). Is human covariation assessment based on Bayesian inference? Manuscript submitted for publication. [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 colleagues and collaborators:

David E. Huber: Assistant professor at the Psychology Department, University of California, San Diego
Michael J. Kahana: Professor at the Psychology Department, University of Pennsylvania
Shane T. Mueller: Senior Research Scientist at Klein Associates Division of ARA, Inc.
Jörg Rieskamp: Professor at the Psychology Department, University of Basel, Switzerland
Richard M. Shiffrin: Professor at the Department of Psychological and Brain Sciences, Indiana University
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 re-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 permission of the copyright holder of the associated program. All the programs linked below run on a variety of platforms such as Linux, Windows, and Mac OS.

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.