030909
Well, I think I finally begin to understand Dennett’s idea of multiple competing drafts. What he’s getting at is very much along the lines of my flow of patterns concept.
What characterizes processes in the brain? Lateral inhibition seems to be a fundamental process that has been adopted in the course of evolution because it has the effect of sharpening boundaries. Hebbian learning seems also to be a fundamental process that has been adopted in the course of evolution because it has the effect of collecting similar patterns of activation together. Taking the simple Hebbian learning paradigm as a starting point, evolution has selected a number of variants for preservation and refinement: populations of neurons vary in terms of their “plasticity per unit time” and their plasticity as a function of neurochemical modulators.
On the outputs (efferents) side, it may be that lateral inhibition is what helps resolve race conditions. There is clearly some sort of winner take all process on the efferents side, although its scope is clearly not global because we can in fact walk and chew gum at the same time.
Suppose each neuron in the brain is connected to about 10,000 other neurons, and suppose arbitrarily that on the order in half of those connections are afferent and the other half are efferent. Then if there are about 20 billion neurons in the brain and each receives input from 5000 other neurons, there must be about 100 trillion synapses in the brain[1] and who knows how to factor in the 200 billion glial cells that cluster around certain synapses. This calculation makes me wonder about the distribution of glial cells. There clearly are many fewer glial cells and there are synapses. Something I read makes me think that the glial cells are associated with axonal synapses, but even that, at least if my estimation of 5000 axonal synapses per neuron is correct, still leaves many fewer glial cells than synapses. About the only additional assumption I might make would be that the glia are associated with axonal synapses on cell bodies. That might make the numbers come out right, but I don’t think so. So I guess I’m still left puzzling over the distribution of glial cells.
Nonetheless, 100 trillion synapses is a lot of synapses. Now go back and think about the so-called Chinese room puzzle. The hapless person in this room is busily simulating with pencil and paper the activity of 100 trillion synapses. It will take an awfully long time to simulate even a few seconds of brain activity. Suppose the simulation interval (granularity) is one millisecond. To simulate a second will require evaluating 100,000 trillion synapses. Suppose the person is very fast and can update the state of a synapse in a second. A year is about 30 million seconds. 100,000 trillion seconds is roughly 3 billion years.
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[1] Jeff Hawkins 2004 (p.210) estimates 32 trillion, but he doesnt say how. Hawkins, Jeff with Blakeslee, Sandra. 2004. On Intelligence. New York: Times Books, Henry Holt and Company.