ln my previous post, I referred to the hidden depths of the brain without including much of a description of what goes on in those depths.
Neuroscience is still working on that problem. But even though Robert Burton, a neurologist and neuroscientist, wrote the book I spoke about in the blog post (On Being Certain: Believing You Are Right Even When You're Not) in 2008, the basic points he makes are still valid.
(Neuroscience doesn't evolve that fast.)
Here's passages from his chapter on Neural Networks that will give you a good feel for how the hidden layer of the brain operates. Fascinating stuff.
As you can read below, the brain operates very differently from how most people believe it does -- as a reliable instrument for knowing reality as it is, a phrase that often pops up in spiritual books that aren't grounded in neuroscience.
Yes, in large part we humans agree on the basics of how the world is. If that wasn't the case, traffic signals would be useless. Most of us see red as red, green as green, and know that red means stop and green means go.
But as Burton says in these excerpts, there's a tremendous amount of personal subjectivity in what our brain presents to us as reflective of reality. And this isn't a bad thing, not that we can do anything about it. Life would be boring if we all experienced the world in the same way.
In the human brain, a typical neuron receives incoming information from approximately ten thousand other neurons. Each bit of information either stimulates (positive input) or inhibits (negative input) cell firing.
The neuron acts like a small calculator.
If the sum of the inputs reaches a critical threshold level, an electrical charge travels down the nerve fiber (axon) to the region where neurotransmitters are stored. The transmitters are released into the synaptic cleft -- a tiny gap between adjacent neurons. If a neurotransmitter finds a receptive site (receptor) on the adjacent neuron, the process will be repeated on this adjacent neuron.
...Despite a veritable symphony of interacting mechanisms, the neuron ultimately has only two options -- it either fires or it doesn't. At this most basic level, the brain might appear like a massive compilation of on-off switches. But the connections between neurons are not fixed entities.
Rather they are in constant flux -- being strengthened or diminished by ongoing stimuli.
Connections are enhanced with use, weakened with neglect, and are themselves affected by other connections to the same neurons. Once we leave the individual synapse between two neurons, the complexity skyrockets -- from individual neurons to a hundred billion brain cells each with thousands of connections.
Although unraveling how individual neurons collectively create thought remains the Holy Grail of neuroscience, the artificial intelligence (AI) community has given us some intriguing clues as to how this might occur.
Using the biological neuron and its connections as the model, AI scientists have been able to build artificial neural networks (ANN) that can play chess and poker, read faces, recognize speech, and recommend books on Amazon.com.
While standard computer programs work line by line, yes or no, all eventualities programmed in advance, the ANN takes an entirely different approach. The ANN is based upon mathematical programs that are initially devoid of any specific values. The programmers only provide the equations; incoming information determines how connections are formed and how strong each connection will be in relationship with all the other connections (or weightings).
There is no predictable solution to a problem -- rather as one connection changes, so do all the others. These shifting interrelationships are the basis for "learning." The AI community has labeled this virtual space where the weightings take place as the hidden layer.
...In the human brain, the hidden layer doesn't exist as a discrete interface of specific anatomic structure; rather it resides within the connections between all neurons involved in any neural network.
...The hidden layer, a term normally considered AI jargon, offers a powerful metaphor for the brain's processing of information. It is in the hidden layer that all elements of biology (from genetic predispositions to neurotransmitter variations and fluctuations) and all past experience, whether remembered or long forgotten, affect the processing of incoming information.
It is the interface between incoming sensory data and a final perception, the anatomic crossroad where nature and nurture intersect. It is why your red is not my red, your idea of beauty isn't mine, why eyewitnesses offer differing accounts of an accident, or why we don't put all our money on the same roulette number.
...Now let's up the ante and watch a human neural network in action. A bright light is briefly flashed into your eyes. The retina turns the flash of light into electrical data that travel along the optic nerves and into the brain (input).
But instead of a direct route to consciousness with a precise and unaltered duplication of the flash, the data first goes to a subconscious holding station where it is scrutinized, evaluated, and discussed by a screening committee representing all of your biological tendencies and past experiences. This committee meets behind closed doors, operating outside of consciousness in the hidden layer.
Consider each committee member as being one set of neural connections.
One might represent a childhood memory of having seen a similar flash of light when a toaster shorted out and started an electrical fire; the second is a general alarm system that has recently become highly sensitive and vigilant to the possibility of terrorism; the third is composite memory of rock concerts; the fourth is a genetically based predisposition for a heightened startle reflex for bright lights.
Each member has his own opinion and each gets one vote.
After hearing all the arguments, each committee member casts his vote and they are tallied (weighted). At the most elemental level, a decision is made -- either to entirely suppress the flash or send it on to consciousness (output). The degree of awareness generated is yet another function of this decision -- ranging from a barely noticed flash at the periphery of vision to a bright flash, front and center.
The childhood memory votes yes: Send the flash into awareness. The terrorist alarm network, fearing that the flash could indicate an explosion, votes yes. The rock concert memory is blasé, has seen the same flashes a zillion times at rock concerts, and feels the flash should be ignored. It votes no. The genetic predisposition reflexively votes yes.
The third member is outvoted, and the flash is sent on high priority into consciousness. You look around, heart pounding, on high alert for everything from a gunshot to a terrorist bomb exploding. But you are at a wedding, and everyone is taking pictures of the bride. You sigh and tell yourself not to be so anxious.
...To get an idea of the magnitude of this process, imagine billions of committee members, each with at least ten thousand hands reaching out to shake hands, prod, poke, seduce, or fend off the other members. Miraculously, this orgy of utter chaos is transformed into a relatively seamless and focused stream of consciousness.
...The schema of the hidden layer provides a conceptual model of a massive web of neuronal connections microscopically interwoven throughout the brain. Such neural networks are the brain's real power brokers, the influence peddlers and decision makers hard at work behind the closed doors of darkened white matter. How consciousness occurs remains an utter mystery, but conceptually, it must arise out of these hidden layers.
The concept of neural networks also helps explain why established habits, beliefs, and judgments are so difficult to change.
Imagine the gradual formation of a riverbed. The initial flow of water might be completely random -- there are no preferred routes in the beginning. But once a creek has been formed, water is more likely to follow the newly created path of least resistance. As the water continues, the creek deepens and a river develops.
...The brain is only human; it, too, relies on established ways.
As interneuronal connections increase, they become more difficult to overcome. A hitch in your golf swing, biting your nails, persisting with a faulty idea, not dumping your dot.com stocks in late 1999 -- habits, whether mental or physical, are exasperating examples of the power of these microscopic linkages.