Many cognitive scientists believe that capabilities like language, perception, and memory are distributed over a large number of neurons operating in parallel, and that learning occurs through the adaptation of connections between these neurons. Using a Parallel Distributed Processing (PDP) framework, researchers simulate neural networks at various levels of abstraction, visualize their activities, and perform statistical and mathematical analysis to gain further insights. While the PDP framework has opened new doors for cognitive scientists and researchers, students at all levels can have a difficult time understanding the operation of such networks.
When I began using PDP networks in my teaching more than 20 years ago, it quickly became clear that for students, simply having the networks described was a poor substitute for seeing them in action. PDP simulations involve integration and optimization over large systems of nonlinear differential equations, making them difficult for students to grasp. For the instructor, the challenge is to avoid overwhelming new students with the computational complexity of the simulations while enabling advanced students to perform more sophisticated explorations.
In PSYCH 209, The Neural Basis of Cognition: A Parallel Distributed Processing Approach, my students use MATLAB® simulations to explore cognitive processes. MATLAB enables them to visualize the networks as they evolve over time and perform simulation and analysis in a single environment.
By Professor James L. McClelland, Stanford University
This aricle was published in the October issue of MATLAB Digest | Academic Edition