Structure and Capacity of Hippocampal Memory: The Convergence-Zone model
Active from 1994 - 2000
Inspired by Damasio's convergence-zone idea, the inputs to the memory are assumed to be represented locally in perceptual maps, and the memory encoding is a sparse random pattern in the hippocampus. Such a memory can be analyzed mathematically and simulated computationally, and it suggests how the hippocampal memory can have a high capacity even with sparse connectivity and a relatively small number of computational units. One-shot storage is shown to require large learning rates, and temporary storage (during transfer to neocortex) possible through weight normalization.
Mark Moll Formerly affiliated Visitor "last name" at isi edu
Jonathan Abbey Undergraduate Alumni jonabbey [at] arlut utexas edu