Ray Kurzweil - How to Create a Mind - The Secret of Human Thought Revealed

Discoveries in neuroscience have established convincingly the key role played by the hierarchical capabilities of the neocortex as well as offered evidence for the pattern recognition theory of mind (PRTM). This evidence is distributed among many observations and analyses, a portion of which I will review here. Canadian psychologist Donald O. Hebb (1904–1985) made an initial attempt to explain the neurological basis of learning. In 1949 he described a mechanism in which neurons change physiologically based on their experience, thereby providing a basis for learning and brain plasticity: “Let us assume that the persistence or repetition of a reverberatory activity (or ‘trace’) tends to induce lasting cellular changes that add to its stability…. When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A ’s efficiency, as one of the cells firing B , is increased.” 2 This theory has been stated as “cells that fire together wire together” and has become known as Hebbian learning. Aspects of Hebb’s theory have been confirmed, in that it is clear that brain assemblies can create new connections and strengthen them, based on their own activity. We can actually see neurons developing such connections in brain scans. Artificial “neural nets” are based on Hebb’s model of neuronal learning.

The central assumption in Hebb’s theory is that the basic unit of learning in the neocortex is the neuron. The pattern recognition theory of mind that I articulate in this book is based on a different fundamental unit: not the neuron itself, but rather an assembly of neurons, which I estimate to number around a hundred. The wiring and synaptic strengths within each unit are relatively stable and determined genetically—that is, the organization within each pattern recognition module is determined by genetic design. Learning takes place in the creation of connections between these units, not within them, and probably in the synaptic strengths of those interunit connections.

Recent support for the basic module of learning’s being a module of dozens of neurons comes from Swiss neuroscientist Henry Markram (born in 1962), whose ambitious Blue Brain Project to simulate the entire human brain I describe in chapter 7. In a 2011 paper he describes how while scanning and analyzing actual mammalian neocortex neurons, he was “search[ing] for evidence of Hebbian assemblies at the most elementary level of the cortex.” What he found instead, he writes, were “elusive assemblies [whose] connectivity and synaptic weights are highly predictable and constrained.” He concludes that “these findings imply that experience cannot easily mold the synaptic connections of these assemblies” and speculates that “they serve as innate, Lego-like building blocks of knowledge for perception and that the acquisition of memories involves the combination of these building blocks into complex constructs.” He continues:

Functional neuronal assemblies have been reported for decades, but direct evidence of clusters of synaptically connected neurons…has been missing…. Since these assemblies will all be similar in topology and synaptic weights, not molded by any specific experience, we consider these to be innate assemblies…. Experience plays only a minor role in determining synaptic connections and weights within these assemblies…. Our study found evidence [of] innate Lego-like assemblies of a few dozen neurons…. Connections between assemblies may combine them into super-assemblies within a neocortical layer, then in higher-order assemblies in a cortical column, even higher-order assemblies in a brain region, and finally in the highest possible order assembly represented by the whole brain…. Acquiring memories is very similar to building with Lego. Each assembly is equivalent to a Lego block holding some piece of elementary innate knowledge about how to process, perceive and respond to the world…. When different blocks come together, they therefore form a unique combination of these innate percepts that represents an individual’s specific knowledge and experience. 3

The “Lego blocks” that Markram proposes are fully consistent with the pattern recognition modules that I have described. In an e-mail communication, Markram described these “Lego blocks” as “shared content and innate knowledge.” 4 I would articulate that the purpose of these modules is to recognize patterns, to remember them, and to predict them based on partial patterns. Note that Markram’s estimate of each module’s containing “several dozen neurons” is based only on layer V of the neocortex. Layer V is indeed neuron rich, but based on the usual ratio of neuron counts in the six layers, this would translate to an order of magnitude of about 100 neurons per module, which is consistent with my estimates.

The consistent wiring and apparent modularity of the neocortex has been noted for many years, but this study is the first to demonstrate the stability of these modules as the brain undergoes its dynamic processes.

Another recent study, this one from Massachusetts General Hospital, funded by the National Institutes of Health and the National Science Foundation and published in a March 2012 issue of the journal Science , also shows a regular structure of connections across the neocortex. 5 The article describes the wiring of the neocortex as following a grid pattern, like orderly city streets: “Basically, the overall structure of the brain ends up resembling Manhattan, where you have a 2-D plan of streets and a third axis, an elevator going in the third dimension,” wrote Van J. Wedeen, a Harvard neuroscientist and physicist and the head of the study.

In a Science magazine podcast, Wedeen described the significance of the research: “This was an investigation of the three-dimensional structure of the pathways of the brain. When scientists have thought about the pathways of the brain for the last hundred years or so, the typical image or model that comes to mind is that these pathways might resemble a bowl of spaghetti—separate pathways that have little particular spatial pattern in relation to one another. Using magnetic resonance imaging, we were able to investigate this question experimentally. And what we found was that rather than being haphazardly arranged or independent pathways, we find that all of the pathways of the brain taken together fit together in a single exceedingly simple structure. They basically look like a cube. They basically run in three perpendicular directions, and in each one of those three directions the pathways are highly parallel to each other and arranged in arrays. So, instead of independent spaghettis, we see that the connectivity of the brain is, in a sense, a single coherent structure.”

Whereas the Markram study shows a module of neurons that repeats itself across the neocortex, the Wedeen study demonstrates a remarkably orderly pattern of connections between modules. The brain starts out with a very large number of “connections-in-waiting” to which the pattern recognition modules can hook up. Thus if a given module wishes to connect to another, it does not need to grow an axon from one and a dendrite from the other to span the entire physical distance between them. It can simply harness one of these axonal connections-in-waiting and just hook up to the ends of the fiber. As Wedeen and his colleagues write, “The pathways of the brain follow a base-plan established by…early embryogenesis. Thus, the pathways of the mature brain present an image of these three primordial gradients, physically deformed by development.” In other words, as we learn and have experiences, the pattern recognition modules of the neocortex are connecting to these preestablished connections that were created when we were embryos.