Saturday, May 09, 2009
Primary Neurocomputational Principle
Primary Neurocomputational Principle: Innate Intelligence maximizes the computational information developed by the neuron and its inputs to no more than the limit imposed by the information capacity of the axon whose capacity is set by optimizing the energy efficiency of its ability to signal other neurons (transmit the developing information).
Energy Use by the Brain: Organisms in the natural environment are highly efficient in their use of their available energy, and sometimes even more important, their cooling resources. That is, the use of food and water by organisms is often associated with processes that become sensible when we suppose one or both of these resources are scarce. And scarce they are at the margins, the place where evolution/ natural selection occurs fastest. It is at the interfacial niches of marginal survival that competition is most severe and mutations would be most beneficial, thus leading to higher rates of evolution. Clearly at such places of marginal survivability, energy efficiency will be very important. So we have good reason to expect that organisms are made up of and use energy efficient processes.
In this context of energy , neural processing is rather expensive. The adult human the brain accounts for20% or more of our total energy use and it consumes on the order of 20-25 watts. In young children, whose brains are nearly as large as an adults, the energy use by this organ can account for nearly 50% of the caloric intake.
Current research implies that more than 85% of the energy used by brain goes toward restoring the ion fluxes across neuronal membranes that are the biophysical basis of computation and communication in the neocortex. Thus neural informational processing although perhaps five to six orders of magnitude more energy efficient than man-made computation, is a considerable expense for the organism.
Because of such energy costs, natural selection (or intelligent design for maximal survival) has optimized energy use as well as information processing in constructing the way neurons compute, process, develop, filter, integrate and communicate.
In all of its functions, the brain seeks optimum efficiency, or the path of least resistance. If one particular function is not accessible, the brain will automatically go on to the next most efficient process for doing that particular task. If the second task is not available, it will go on to the third or the fourth most efficient way. Because each alternative process is less efficient, it becomes more stressful and energy expensive
The brain will keep searching for an appropriate processing method, until eventually the activity may become so subconsciously stressful (energy greedy) that the person will choose to give up trying to do the task altogether. If it is a conscious activity, the individual will give up the fatiguing activity. If the process is unconscious, the individual will decrease the energy partitioning to that process, making this unconscious activity minimized, nonfunctional or detrimental to the whole, depending on where the process is located in the physiological hierarchy.
