Email updates

Keep up to date with the latest news and content from BMC Neuroscience and BioMed Central.

This article is part of the supplement: Eighteenth Annual Computational Neuroscience Meeting: CNS*2009

Open Access Poster presentation

Fundamental principles by which the brain could process information: an information management perspective

Eugen Oetringer1*, Manuel F Casanova2 and Michael Fitzgerald3

Author Affiliations

1 (a private research initiative)

2 Department of Psychiatry, University of Louisville, Louisville, KY 40292-1702, USA

3 Department of Psychiatry, Trinity College Dublin, Dublin, 8, Ireland

For all author emails, please log on.

BMC Neuroscience 2009, 10(Suppl 1):P115  doi:10.1186/1471-2202-10-S1-P115

The electronic version of this article is the complete one and can be found online at:

Published:13 July 2009

© 2009 Oetringer et al; licensee BioMed Central Ltd.


One of the authors discovered that certain unconventional treatments for dyslexia, ADHD and other mental conditions use the same techniques that are used to remove capacity bottlenecks in large computers. Breakthrough experiences from one of those treatments led to the question: Would it be possible to build an information management model through which the capacity bottleneck theory could be confirmed?


An architectural approach, as used in the information technology industry, brought two extremely limiting criteria to the forefront: the speed at which neurons operate and the enormous complexity that comes with computer-style parallel processing. Any such model had to be within the low speed requirement of about 100 straight-line neurons between thought and muscle activation, avoid computer-style parallel processing and yet allow for massive parallel processing.


The architectural approach led to only eight fundamental design criteria. When those were put next to fundamental architectural criteria as known from the brain (columns, the layers of the neocortex, etc.), the information management model emerged. It became a two-way neural network switching model.


Based on this model and in line with the emerging view of the brain operating in a self-organizing, pattern-forming and dynamic way, we propose fundamental principles by which neurons/patterns associate with each other, how neurons/patterns could activate each other, how the more relevant patterns/associations surface above the chaos of information and how the brain could process information in general.