Commentary on “In silico modeling system: A national research resource for simulation of complex brain disorders.” A proposed mathematical and computational foundation

To develop the in silico modeling system proposed by Zaven S. Khachaturian and Joseph Lombardo [1], a solid foundation will be necessary, which will allow one to seamlessly transition from concept to theory to algorithm to architecture to software/hardware co-design to simulation to implementation to testing. We propose that we achieve the above goal by a combination of four spaces: (1) the Observation Space (OS), (2) the Disease/Clinician Space (D/CS), (3) the Cerebral Cortex Macro-Modeling Space (CCMaMS), and (4) the Cerebral Cortex Micro-Modeling Space (CCMiMS). These spaces are characterized by the objects that pertain to them. Thus, the OS might consist of one or more spaces used by experimentalists in representing and analyzing the data as, for example, in the principal component analysis of the data. In the D/CS, the clinician combines the results on the analysis of the data obtained from the OS with the understanding and insight provided by the CCMaMS and CCMiMS to arrive at an appropriate diagnosis, treatment, or repair of a diseased brain. The construction of a D/CS will constitute a challenging enterprise. It will probably require a combination of various spaces such as the probability space (composite hypothesis testing); conventional and fuzzy logic theory [2]; graph theory; formal, programming, and natural languages; and the de Figueiredo/Dwyer/Zyla Neural Space for Intelligent Computing [3]. The CCMaMS is the space of populations of cerebral cortex objects (neurons and synapses), as embodied by the average neuron and synapse population densities in the various components, subcomponents, sub-subcomponents of the cortex. A model for such a space for the brain as a ‘‘Super-Cell of Super-Cells’’ (rather than merely a network of networks) has been proposed, analyzed, and tested on the Conel data by de