Chris Chatham's Homepage
Christopher H. Chatham
2nd year Grad student (pursuing PhD in Cognitive Neuroscience)
University of Colorado, Boulder
I am interested in computational approaches to developmental cognitive neuroscience. In other words, we use neural network models to simulate age-related changes in cognition and the mechanisms underlying the growth of the mind. Knowledge gleaned from these techniques could be applied to the design of novel adaptive toys ("smart toys"), the design of autonomous robots (also known as developmental robotics, or autonomous mental development) and to improving our understanding of how the mind emerges from the brain.
My current research involves using a novel child-adapted version of the AX-CPT task to investigate the development of active maintenance in childhood, and how that may relate to other executive functions (shifting/switching, inhibition, and updating). I have recently extended a neural network model by Morton & Munakata to simulate negative feedback in the Dimensional Change Card Sort task. I am also working on a novel variation of Piaget's classic A-Not-B task, one that may shed light on the contribution of one brain region in particular to perseveration.
In the future I hope to utilize both neural network modeling and latent factor analysis to identify exactly how executive functions develop, and what factors may support or enhance this process.
Related Boulder links:
Yuko Munakata's homepage (my research advisor)
Cognitive Development Center
Center for Lifelong Learning and Design (constructing intelligent systems to amplify human capabilities)
Neuroscience Program at CU-Boulder
Institute of Cognitive Science at CU-Boulder
Front Range Robotics club
Boulder Cafe Scientifique
Currently enrolled : University of Colorado, Boulder (pursuing joint PhD in Cognitive Neuroscience )
BA, University of Pennsylvania (Psychology and Communications)
also St. Paul's School, Brooklandville MD
A simple algorithm for creating balanced latin square experimental designs
An even simpler algorithm for calculating the number of degrees subtended by an onscreen image
My guest lecture on knowledge representation, categorization, and metaphor
My presentation on psychoacoustics and Renier Plomp's article "The Ear as a Frequency Analyzer"
My presentation on visual processing, spatial frequencies and the figure vs. ground illusion
My presentation on neural network models of memory, and why we have a hippocampus
My presentation on the interaction of prefrontal cortex with medial temporal lobe in long-term memory tasks
My presentation on self-organizing models of semantic learning
My presentation on the distinct processes of Executive Function and Working Memory
First Year Project Proposal and Presentation and Stimuli and Pilot
My Blog: Developing Intelligence and my list of recommended reading
A reconstruction of the lorenz attractor by Seth McGinnis
here is another great illustration of the lorenz atrractor from the University of Arizona