A theory of the brain - The brain uses both distributed and localist (symbolic) representation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The issue of whether objects and concepts are represented in the brain by single neurons or multiple ones, where the multiple ones are conceived to represent subconcepts or microfeatures, has plagued brain-related sciences for decades, spawning different scientific fields such as artificial intelligence (AI) and connectionism. It is also a source of dispute within some of these scientific fields. In connectionism, for example, there is never ending debate between the theories of localist (in a sense symbolic) and distributed representation. To resolve this conflict, we analyze a highly publicized class of models used by connectionists (distributed representation theorists) for complex cognitive processes and show that, contrary to their claim, they actually depend on localist (symbolic) representation of higher-level concepts in these models. We also find that these connectionist models use processes similar to symbolic computation. Based on this analysis and the accumulating evidence from single-unit recordings in neurophysiology that shows that single cells can indeed encode information about single objects (e.g. a Jennifer Aniston cell in our brains), we propose the theory that the brain uses both forms of representation, localist and distributed, and that both forms may be necessary, depending on the context. Our other conjecture is that the brain uses both forms of computation, symbolic and distributed (parallel). This theory should finally resolve the decades long conflict about representation and computational processes that has generated divisions within our fields and has stalled our progress towards creating brain-like learning systems.

Original languageEnglish (US)
Title of host publication2011 International Joint Conference on Neural Networks, IJCNN 2011 - Final Program
Pages215-221
Number of pages7
DOIs
StatePublished - Oct 24 2011
Event2011 International Joint Conference on Neural Network, IJCNN 2011 - San Jose, CA, United States
Duration: Jul 31 2011Aug 5 2011

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Other

Other2011 International Joint Conference on Neural Network, IJCNN 2011
CountryUnited States
CitySan Jose, CA
Period7/31/118/5/11

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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