The Visual Cognition Laboratory is grateful for funding from the National Library of Medicine at the National Institutes of Health.  The primary purpose of the funded work is to develop new methods of computer-based learning of complex biological systems.  The lab has pursued several large projects with the aid of this funding.

Computer Graphical Model of the Human Brain

 In order to develop new instructional methods for learning neuroanatomy, it was necessary to develop a high-fidelity 3D computer graphical model of the human brain.  Accuracy was required so that when sectional imagery was derived from the model, the imagery would be realistic.  Realism, in turn, permits better transfer of learning to the interpretation of biomedical images (e.g., MRI images).  The source information for the brain model is the images from the Visible Human Project, Vers. 2.0, of the National Library of Medicine.

Computer-Based Learning of Human Neuroanatomy

With the graphical model available, the lab developed several programs for computer-based learning of neuroanatomy.  These models permit a variety of methods of learning whole and sectioned neuroanatomy.  Over the past few years, we have conducted large-scale longitudinal studies of learning, comparing these various methods for efficiency of learning, long-term retention, and transfer of learning to the interpretation of biomedical images.  The first paper through the publication pipeline will be Chariker, Naaz, & Pani (in press; Journal of Educational Psychology). 

Deployment of Instructional Programs in University Classrooms

As our instructional systems have been developed and tested, Dr. Sandra Sephton has collaborated with us on the introduction of these methods into the neuroscience classroom.  As part of this effort, additional interactive graphical atlases have been developed so that students can explore descriptions of neuroanatomy not currently available in the standard programs.  William Mattingly was instrumental in the development of the new atlases.

Study of Cognition in the Interpretation of Microscope Images

One of the really interesting questions in the study of science instruction is what unique cognitive systems are developed in formal instruction of such advanced topics as histology and microanatomy.  In conjunction with Dr. Ronald Fell of the Department of Biology, we have conducted several studies of cognition in the interpretation of microscope images.  Manuscripts reporting this work are in preparation.

Development of New Computational Techniques for Modeling Biological Networks of Tubes

For work such as ours to reach its full potential, there have to be more and better 3D graphical models of anatomy.  We have noticed that many biological structures can be modeled as networks of tubes, and we are developing computational methods for efficiently developing graphical models of these structures.  This work is conducted with the collaboration of William Mattingly and Dr. Dar-Jen Chang of the Department of Computer Engineering and Computer Science.