Wednesday, 27 June 2012

The politics of small scale vs integrative neuroscience


A question I wonder about. The dramatic changes in recent human history facilitated by technology allow us to look at the small scale of the world and as a result we derived such massive insights almost all of science and education is driven by paradigms and methods that we think it is inevitable to burrow down in this manner, or try to derive understanding of systems from bottom up digging out parts and simple elegant formulas in the hope it all integrates.  Well it did, up to a point, and that is the incomplete neuroscience we have.

This golden age is over, but the way we think about science in this manner pervades in such a manner it presents many barriers to try and persuade scientists to look at the large scale top down approach to brain complexity here.  These are clear over-arching structures which organize function proposed here, and they are controversial because lets face it its kind of nice to be educated with tomes of complexity that seem beyond us. So we hack at parts happy to do our bit for the next generation.  Well we have done enough. Now is the integrative time to start bringing parts together. What does the top down approach I bring say intrinsically ? That there may be no single low level model to explain all neuroscience. And by implication this also has ramifications for the computational neurosciences which require these insights from neuroscience.

This post is kind of a rant, but its not really because I have known since I started publishing in this areas that neuroscience is going to be increasingly integrative and so will end here with a recap of that. One of the first journal editors to approve my work was Denis Noble CBE. I was kind of amazed at how open he was to it, till I realized he had earlier in his career pioneered small scale biocomputation and physics approaches but had later moved towards top down system thinking. Not only that he was providing funding advice to European Bioscience policy to be more integrative something like 10 years ago and we can see this is what is now happening. But its a good idea to lay out where we are and why the approach to neuroscience here still has maybe a decade before its generally acceptable. So start with some nonsense to lighten things up.  Sometimes in my presentations to others, (particularly high level neuro conferences) I notice this can be the result ! While my work is constantly evolving, I cannot always get a good dialogue with the audience.


ABSTRACT: Longitudinal studies (lanzalaco et al., 2014) elicited the above startle response after a group of final year medical students were exposed to dipole neurology theory while follow up studies indicated evidence of PTSD in some students. . CONCLUSION: 0.5 litres scotch whisky with gradual exposure to the theory may be the effective treatment for postgraduate neuroscientists exposed to dipole neurology theory.

Ok kidding aside, this is a hard approach to hit neuroscientists with. If you pull my paper, you can see there is no problem getting into the nitty gritty minutiae  of neuron function and complex bioscience mappings, such that i was able to attempt to falsify my 2003 proposal that the small scale neuron distribution is consistent with large scale structure (sure I understand I could have been trying to make everything fit, so I had it peer reviewed more than is usual). I don’t have anything against traditional approaches and keep up to date with small scale neuroscience. As a supported of Whole Brain emulation I hope we can scan neurons to the nanoscale and beyond. What I do question is that the methods and approaches currently used to unravel brain complexity are not adequate to complete the job fully. I propose that by using the method of letting nature tell us what unfolds from the origin of entire brain structures in biophysics, this will contribute an enormous high level understanding.  As there is nobody else doing this,  I concentrate on that and the result is the style you see here is very different to neuroscience you know. I doubt you will see one neural component on this site, although there is plenty in depth on those in my 2009 paper. Because basically so much small scale work has been done, this approach I propose fails if it not consistent with the bulk of it. I couldn't build this theory without the decades of small scale neuroscience available to integrate which is fine work indeed and proceeds to be so.  Dividing up complexity has self organized to create a massive amount of grants and job stability within a global community. The interactions are endless ! 

There are already very many high level neuroscience theories but nothing like this. What we did previously was we would usually leave an attempt at high level maps to senior professors, thinking only a lifetimes experience reflecting on all thats been done can lead to any worthwhile high level review, and we hope such a review will reveal the entire system.  But since it never happened for so long we are kind of trained to think that this cannot happen based on the confusion with the current amount of small level data.

Now think about what I said previously. We are also kind of addicted to believing in science that good answers are in the small scale breakdown.  Well sure, clearly a lot of the small stuff is of course revealing a lot.  It also cannot be denied model as proposed here are the highest level integration you will find (if you accept its premise). The brain does have clear morphologies, and I hope my case is clear (or will become so) thats where the highest level functional answers are to be found.  Interest in the high level brain function derived from structure is amazingly not present in the experts in the field, even when given prolonged exposure and all questions answered as to any doubts. We really believe the solution is to be found in neurons or other bits and pieces. Is it not clear yet that's not working ? 



What took neurons from jellyfish to building complex computational structures ?  Radial glia.  More complex structures will have more complexity around the glia evolution. Images of glia and goldfish visual system.  http://webvision.umh.es/webvision/Nona.html

The final completion which puts it all together is in developmental mechanics and Radial Glia.  A good percentage of the neuroscience community is supposed to at least try and understand how this system works at the highest level possible, yet it does not appear to happen.  Looking at current plans at the top level of neuroscience, the plan is now to increase resources to pour into even more high resolution detail. Clearly the system needs understood at micro and lower levels and the components are cells, BUT this could get ridiculous in terms of being blinded from seeing the forest. Not from the trees, but the branches and leaves and cells and their DNA/molecules. The awe with which we introduced to the small world, never leaves.  Yet nature has no rules which says complexity has to be focused on the small world.  It keeps piling more levels one substrate on top of another. DNA - cells - building of larger lifeforms - Radial glia is the top level of the complexity of brain evolution and development of structure. A recent report "Cis-regulatory control of corticospinal system development and evolution" defines what differentiated mammals from the rest of clade craniata (creatures with skulls). The SOX transcription factors assist reelin a key molecule in maintaining radial glia structure. See "Populations of Radial Glial Cells Respond Differently to Reelin and Neuregulin1 in a Ferret Model of Cortical Dysplasia". Physical evolution has been slowing down and the changes in our brain are centered around humans being the substrate for cultures and tribal/national civilization. We are now seeking to use our consciousness to develop ourselves as the substrate for advanced information systems which will operate on top of civilization (see the new science of substrate independent minds).  i.e. Nature is constantly developing mechanisms to build at the highest level of complexity and scale as is possible. Look into complex systems and they will explode with increased functionality when a new means of top down control and organization evolves.

The current situation in neuroscience is akin to a native culture coming across an incomplete wheel, amazed it its engineering detail, as well as what it is they start concentrating on the spokes, then breaking the spokes apart. Years later they start having meetings on various theories about the parts ensues. More plans are made to melt the parts or perform chemistry on them. When all we had to do was rebuild the high level structure of the wheel to understand its functional properties.  The same applies here. Just look at the large structures (and their integration), then complete them (as you see in my morphology images) and you get the high level principles. From there you have a wheel and you can spin it and understand its function. The answer was so simple all this time.  Complexity has defeated us. We have become blinded by the huge amount of data we created tearing apart the system. Want to compound that ? Then go for more of the same. 




Current state of neuroscience. We dont know what this objects function is, so lets invent increased levels of high resolution micro-scanning to figure it out. The answer is rebuild the large structure to complete it, then you can spin that and understand its highest level function. What do i mean spin the brain or rebuild the structure ?   You can read this paper which introduces this theory and completes the structure, or this which gets more into the high level functions.i.e. Actually spin the structure in theory means understand then run the computation of the high level magnetic dipole/linear expansion structure of the radial glia (or for developed minds glia and ventricular zones) filled with neurons and traditional small scale structure/function.   

An expensive simulation will be required to achieve this in practice, but the idea to get into this is so simple.  This is why I attack the premise of ground up brain simulation projects, even with every part known it will be incomplete, because the brains structure like that wheel is incomplete (read the papers or more of this site). Yes a brain has small scale function of no doubt, thats what neuroscience today is focused on. Its a bad idea to stick to that when a high level solution appears. This is a multi-level problem, both top down and bottom up integration at the same time is more intelligent than keep burrowing smaller because thats the habit. The majority of neuroscience today is bottom up. Understandable as there is more complexity there, but how much of that is to run the brain on OS (operating system) Biology. i.e. How much is redundant in comparison to the evolution of high level structure ? It may turn out to be lets take a guess at a 50/50 ratio of top down/bottom up if we get rid of the DNA/cellular substrate. I Dont actually know, but it requires looked at.  Another problem is whats considered top down in neuroscience is not from the top at all, but about half way to a 2/3 up. We will get into this later in these lengthy posts.

Sure there are countless cases where the small approach is justified and those scientists or groups have strong beliefs and/or rationale, but we are discussing the general situation in an average lab here. Why ? usual reasons, group politics, current investment, resource issues. Of course all the disease mechanisms require that detail. And of course Whole Brain Emulation which i support. However I still think there is also intuitive re-activity to stepping onto a top down perspective. 

Is this really over-simplified ?

For ten years I had denial (often obtuse) these are not the structures I claimed. Now with recent independent evidence, the next issue I deal with from scientists is denial of computational ramifications. i.e. its moved to along the lines of "Ok, so lets say those structures are as claimed, they are probably meaningless structures with no computational meaning or relevant organizing principles to neuroscience" .   These dodge the issue, and are similar to those i dealt with before I had some lab evidence the cortex dipole concept was plausible.





What dominates science today, social status, position and access to resources

More bio-resolution creates more questions which creates demands for more funds=more jobs, more status which builds the current situation. So we get less answers about more and more. Not that we arent finding out a lot, especially for disease and low level functions. So clearly there are good reasons. The result is nobody understands the system, and even more prevalent is giving the idea up of understanding it becomes part of education.  If status is about looking to be seen to go for a reduced version of understanding in a certain way, thats what today's scientist will do to survive. There will be no high level quest. There cant be when no project can understand all the data we produced.  To get back to the high level, requires a break from the way we are going about breaking the system. However I can finish with not complaining, because actually its not so bad where I am. In Europe this has been accepted and stated for some time now. In European funding the pressure is to integrate and this has influenced the USA.  SO the good news is that at least large scale integration is proposed to be the next big scientific approach. But will it actually happen. In my next post i try to highlight these projects will still not be top down enough. They are going to need entire morphology principles to complete the big picture.

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