WHATS THIS ALL ABOUT ? : I basically seek highly integrative simplified models for the cortico-limbic system as this appears to be the brains information engine. Approaches are fundamental thermodynamics, computational principles from entire structural morphologies and reading just about everything else that outs there.
QUICK FACTS: Although the brain structures are shown to be EM in nature, this is not a quantum mind theory, quite the reverse. The formalization of this approach leads us to the conclusion we can have QM "style" processes in classical scales and define this via regular logical approaches (based on manifold topology) and thermodynamics.
UPDATE 05/05/2014 : Both CML neuroscience papers are now published here in JAGI special edition on WBE and Connectomics. These are available as open access. There are about nine papers in this edition on Whole Brain emulation all tackling different aspects of the problem.
Two papers were accepted in the same issue of the Journal of Artificial General Intelligence special edition on Brain emulation and Connectomics. They been written and co-authored between myself and Prof Sergio Pissanetzky (who came up with CML). Each paper is focused for different aspects of the problem, The first with primary author Prof Pissanetzky is the introduction for CML. The second where I am primary author is the full realization of the approach described on this site and previous papers how to approach deriving general mammalian computation from the biophysics of brain structure. But this had halted with a major problem. How consistent was this approach with both fundamental physics and information theory. i.e. If principles of intelligence are intrinsic to the evolution of brain structures that fuse complex amalgamations of proteins and biophysics.. then these structural principles should be scaling in some kind of regular manner from fundamental principles of information. Regular neuroscience had no bridging theory for this problem but Causal Mathematical Logic has. CML describes how information algorithms self organize from the most fundamental physical principles (such as least action and entropy).
The application of CML to the "go for everything" approach in the cortico-limbic system proposed here produces the first approach to a complete "information engine" model for the brain (and AGi). This is a big deal in these sciences, but there are many such models.. so this will remain low key for perhaps a decade as it cannot be verified until the final stages of the Human Brain project. If you dont want to read this paper which is complex the basic idea is that a brain simulation (or emulation) has to run on a thermodynamically responsive system. All the process of transcribing the details of the neural parts can be done by current methods, but if its going to be conscious (a word i don't like using).. or better term to "process integrate/ dynamically" as we do.. it will have to produce Event Related Potentials.. and these are best described by CML (or something similar) in terms of thermodynamics. The good news is this predicts no esoteric quantum woo will be required.. and a thermodynamic brain simulator (or emulator) will not have to go to that length to achieve. Obviously I have to qualify this position. So this is in the paper here "Causal Mathematical Logic as a guiding framework for the prediction of “Intelligence Signals” in brain simulations" or PDF here . The Quantum mind objectors will say that Quantum mechanics is still thermodynamic. My reply is we only need to go for the physical theory which describes the thermodynamic resolution the information operates on. Almost all of the neural mutational complexity produces mechanisms at the synapse to glial level. If the thermodynamic description is enough for the entire physical description at this scale, then that means this proposal is the start of a new general physical model for simulators/emulators based on mammalian structures.
The other paper where Prof Pissanetkzy is the lead other here describes more of the mathematical and philosophical foundations. There is also a supplementary section for the above paper linked to here called "Can CML predict solutions for outstanding questions in Whole Brain Emulation (WBE) ?" This will be updated also with the accepted peer review points.
Other current plans are an application I have submitted for labtime to falsify which mechanism produces the dipole flow in development. We need this mechanisms falsified. If is verified we then have a strong justification to propose that the FET flagship Human Brain Project would need to model the cortical column model in the context of the dipole model. That will be called (if it goes through) : Investigation of Ca2+ flow in radial glia to differentiate magnetohydrodynamics from the proposed chemotactic mechanism for the dipole formation in development of the chick forebrain. (UPDATE 21/11/2013) I was not successful in procuring the labtime from Edinburgh University. This work is competing with many traditional applied projects that are directed towards curing medical disorders. Good news is it appears other researchers in Scotland have been discovering dipole flow in neurodevelopment. i.e. This study from Prof. Timothy Newman at Dundee, College of Life sciences.
A 'chemotactic dipole' mechanism for large-scale vortex motion during primitive streak formation in the chick embryo.Phys Biol. 2011 Aug;8(4):045008. doi: 10.1088/1478-3975/8/4/045008. Epub 2011 Jul 12
Back to where all this began...it appears the dipole-multipole concept lab results are appearing as I predicted which is vindicating. But as with the work from Vincent Fleury's Lab in CNRS Paris. I am still not in agreement with these labs on the mechanism. That was the point for my lab request. I predict that Ca2+ flow through the Connexin, Pannexin network in and out of the Radial Glia provides Magnetohydrodynamic flow giving rise to generalized cortex wide guidance pulses for electrotonic components. i.e. Guidance molecules, Intracellular ion gradients and astrotactin adhesion for neurons moving along the Glial fibers. There is more on that on this site here. For those new to this concept, I justify the application for this dipole force in development applying to mammals based on the indirect data meta-analysed from my 2009 publication, and the evolutionary roots of the cortex, which pre-date Clade Avialae (birds !) back to the roots in phylum chordata (sea creatures). A post on that issue here, based on the bio-informatic regression of synapse carried out by the genes to cognition project of Seth Grant. There have been other studies summarized by a scientific american article which reached a similar conclusion.