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Computational Neuro-Genetic Modelling (CNGM)

From my 2006 draft paper listed below:


"Abstract – Computational Neuro-Genetic Modeling (CNGM) is discussed from the perspective of building Artificial Neural Network architectures starting with substantially pre-defined modules and processes (DNAANNs). This is equivalent to assuming that DNA code in a neuron can ultimately specify function, process and some level of data abstraction beyond the immediate role of genes to produce proteins or to regulate processes, and using that basis as a metaphor for DNA-ANNs. A robust and diverse set of ensembles or modules of DNA-ANNs is sought that is sufficient for a given problem domain, and that generalizes well. The potential advantages that might be derived from highly evolved, fine-grained hybrid genetic/connectionist systems, and some of the implementation challenges that they could present are discussed." Bill Howell, 2006

While my thrust is from the mathematics/ computer science perspective, the concept has obvious parallels to the brain and mind, which is definitely of interest. However, biological substantiation, if this ever occurs, is only appearing very indirectly, so don't take that side of it too seriously. On the other hand, work by Michael Meany's group in Montreal, John Mattick's group at the University of Queensland in Brisbane, and possibly Sandra Pen˜a de Ortiz in Puerto Rico, shows that work in genetics is proceeding along many fronts that may provide eventual substantiation for a biological basis to CNGM. Furthermore, work by Gary Marcus at New York University deals with modelling the growth of the brain, and this is even more of a challenge than the CNGM described here, and indeed is a necessary basis for it.

My concepts and thinking are explained in the following documents, only one of which has been submitted in quality format:


Unfortunately, my electronic documents from the formative 1997-1999 period, and earlier overview of material circa 1994-965 regarding hierarchical/ structured neural networks are no longer readable. However, there is a huge amount of research into highly structured systems of Artificial Neural Networks and the benefits that are being sought.


Directory of available files for this webpage:



Last updated: 05May07, original 27Jan07