Top down bottom up brain models

Abstract

A recent paper by Eliasmith and Trujillo includes an interesting discussion about the role of and approaches for building large-scale brain models. The authors emphasize connecting the model to behavior and compare top down and bottom up approaches to modeling. In this paper we describe our experience developing the FRAMES model with a mixed top down and bottom up brain modeling approach. The FRAMES model focuses on general purpose high level cognitive behavior. The specific goal of the FRAMES model was to study the mechanisms of biases in sensemaking. The FRAMES model was grounded in the context of behavior by explicitly designing it to perform specific spatial and analytical reasoning tasks. We believe that BICA models like FRAMES will provide critical insights into building next generation machine learning and reasoning. Case studies such as this paper contribute to the engineering foundation of BICA.