A simplified description of the operation of a neuron is that it processes the electric currents which arrive on its dendrites and transmits the resulting electrical currents to other connected neurons using its axon. A simple explanation of the processing step is that the cell sums up the incoming signals and produces an output signal only if this sum exceeds some threshold; i.e. only if the total input signal is big enough will the cell `fire' an output signal to its neighbors.
Once the cell fires, an electrical signal travels down the axon at a speed of around 100 meters per second (200 mph). These currents are very small by usual standards. The typical voltage difference between the outside and inside of a nerve cell is 70 millivolts (one millivolt is one thousandth of a volt). This is to be compared with the voltage at a power socket in your home of 110 volts - a thousand times bigger. This signal is passed onto other neurons at the synapse points in the following way.
The pulse reaches the end of the axon branch and causes the release of certain chemicals called neurotransmitters. These diffuse across the synaptic gap (a distance of some one-hundredth of a micron) to be picked up by so-called receptors on the ends of the dendrites of a neighbor neuron. This absorption process on the new cell changes its electrical state. If there are sufficient incoming signals to this neighbor neuron, this change in its electrical state can be big enough to generate a new pulse in the neuron. Thus the process repeats in this new cell. This cell is itself connected to many others and in this way a wave of electrical activity can be set up. Different types of brain activity correspond to different patterns of firings.
While we are born with a complete set of neurons, the connections between them are determined in major part by a learning process; external stimuli coming in the form of electrical currents from the sensory cells cause patterns of nerve impulses to be set up. These impulses can alter the strength of the coupling between different neurons. While the overall program for determining which neurons should be connected together is under genetic control, it is external stimuli which are crucially important in determining what network connections are made. Indeed, to some extent out brains are continually rewiring themselves to cope with passing experience. This particularly true for small children who are born with a full complement of neurons but a relatively primitive set of connections - a useful set of network connections must be learnt during the early years.
It is also true that the levels of various neurotransmitters are, in part, determined by early experiences. The overall functioning of the brain is strongly influenced by such chemical balances. For example, the neurotransmitter seratonin plays a role in regulating aggression; a lack of dopamine, another such chemical, reduces frontal lobe activity and has been associated with schizophrenia. Endorphins play a role in the system which produces sensations of pain and pleasure. It is becoming increasingly clear that certain traits of personality may be determined in major part by biochemistry. This opens up the possibility of a "chemically improved" society and all the profound implications that implies.
The fact that our neurons can rewire themselves "on the fly" has the consequence that our brains are amazingly robust - if a given neuron dies (which will have happened to something like 20 percent of our original neurons by the time we die!), our brain automatically undergoes a rewiring process in which new connections are made to circumvent the defunct neuron. It is also the origin of the amazing diversity in peoples' types and abilities. Intelligence is determined partly by genetics (the program that governs the overall structure of what connections should be set up) and partly by our experience which can influence very strongly the nature and quality of our neural networks.
Two neurons are not merely joined or not - the nature of the synaptic connection between them determines whether one neuron firing has a strong or weak effect on the other - we talk of the strength of a connection between them. A strong connection between two neurons means that it it more likely that one of the neurons firing will stimulate the other to fire - with a weak connection it may only happen occasionally depending on the state of very many more neurons for example. Of course, this connection strength feature has much to do with the presence or absence of certain neurotransmitters since they are crucial in determining the size of electrical signal which can pass between neurons.
This notion of dynamically changing connection strengths is thought to be important for memory function - new memories are stored not on individual neurons but by adjusting the strengths of connections between neurons. A simple rule appears to govern this process: the connection between two neurons will strengthen if more often than not the two neurons fire together. This is often called the Hebb rule.
Thus the operation of the cell depends on both electrical and chemical properties - those of the neurotransmitter molecules. There are a number of types of these neurotransmitters (research has identified at least fifty distinct types of neurotransmitter).
Some, referred to as exciter neurotransmitters act to trigger the receiving neuron, while others called inhibitors act to damp out signals in the neighbor neuron. For example, one particular such inhibitor chemical called GABA acts to prevent abnormal or parasitic muscle movements. The degeneration of certain synaptic sites rich in GABA provokes an illness called Huntington's Chorea, whose symptoms are almost incessant involuntary movements. The famous folk singer Woodie Guthrie succumbed to this genetic disease.
Much use has been made of the way that these neurotransmitter chemicals are used by neurons. Tranquilizers act by modifying the natural chemicals in the synaptic gap and drugs such as LSD by altering the balance of various neurotransmitters. This can cause very dramatic effects; for example, sounds can be perceived as colors. The new drug Prozac also acts directly to remedy chemical imbalances in the brain.
We may ask the question: what is about the structure of neurons and their organization which determines the amazing computational power of the brain? Certainly it is not the raw processing power of a single neuron - it takes about one-thousandth of a second for a cell to return to a normal state after firing. This is the minimum time before the neuron can process another incoming signal. While this seems quite a short time it is ridiculously slow compared to even a modest home computer whose silicon chip can perform operations in the incredibly short time of one-hundred-millionth of a second.
The secret lies in the very number of neurons - many tens of billions as we have said. If these neurons can be made to work efficiently and simultaneously on a given task it is clear that the effective power of the brain is very much larger than current computers. The hint that such a scenario may indeed be realized lies in the detailed structure of the brain in terms of the connections between neurons. It is clear that in order for neurons to cooperate in performing some function, they must be able to talk to each other. We know that each neuron has many tens of thousands of connections to other neurons that function as communication channels. These connections have an incredibly complicated structure - different portions of the brain have different types of connection pattern, while these different sectors of the brain are themselves linked together by further specialized networking. We still have only the crudest understanding of why these neural pathways are connected up the way they are. But it is surely the very detailed way in which these connections are made that is at the heart of the power of the brain as a thinking machine.
The very complexity of these neural networks poses a formidable barrier to understanding. Nobody knows in detail how the individual firings of neurons coupled to their interconnections can lead to all of the features observed - short and long term memory, complex pattern recognition, logical reasoning, emotion and consciousness. Indeed, it is not known how even the lower level unconscious functions such as those which regulate breathing and heart rate emerge out of the complicated mutual interaction of millions of neurons. Furthermore, it is generally believed that at least a partial understanding will be necessary in order to build truly intelligent machines.
Nevertheless, we are making rapid progress in understanding some of the simpler aspects of these systems in part through the study of computers whose architecture resembles that of the brain. These computers go under the name of artificial neural networks and will form a large part of this course.
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