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Saturday 14 May 2016

N E U R O S C I E N C E



  • How do brains process information?
Neuroscience is the study of the nervous system, particularly the brain. The exact way in which the brain enables thought is one of the great mysteries of science. It has been appreciated for thousands of years that the brain is somehow involved in thought, because of the evidence that strong blows to the head can lead to mental incapacitation. It has also long been known that human brains are somehow different; in about 335  B.C.  Aristotle wrote,  " Of all the animals, man has the largest brain in proportion to his size. "  Still, it was not until the middle of the 18th century that the brain was widely recognized as the seat of consciousness. Before then, candidate locations included the heart, the spleen, and the pineal gland.

Paul Broca's (1824 - 1880) study of aphasia (speech deficit) in brain - damaged patients in 1861 reinvigorated the field and persuaded the medical establishment of the existence of localized areas of the brain responsible for specific cognitive functions. In particular, he showed that speech production was localized to a portion of the left hemisphere now called Broca's area By that time, it was known that the brain consisted of nerve cells or neurons, but it was not until 1873 that Carnillo Golgi (1843 - 1926) developed a staining technique allowing the observation of individual neurons in the brain (see Figure ). 

In Figure 1, the parts of a nerve cell or neuron. Each neuron consists of a cell body, or soma, that contains a cell nucleus. Branching out from the cell body are a number of fibers called dendrites and a single long fiber called the axon. The axon stretches out for a long distance, much longer than the scale in this diagram indicates. Typically they are 1 cm long (100 times the diameter of the cell body), but can reach up to  1  meter.  A  neuron makes connections with 10 to 100,000 other neurons at junctions called synapses. Signals are propagated from neuron to neuron by a complicated electrochemical reaction. The signals control brain activity in the short term, and also enable long - term changes in the position and connectivity of neurons. These mechanisms are thought to form the basis for learning in the brain. Most information processing goes on  in  the cerebral cortex, the outer layer of the brain.  The  basic organizational unit appears to be  a  column of tissue about 0.5  mm  in diameter, extending the full depth of the cortex, which is about  4  mm in humans.  A  column contains about 20,000 neurons.

This technique was used by Santiago Ramon y Cajal (1852 - 1934) in his pioneering studies of the brain's neuronal structures.
We now have some data on the mapping between areas  of  the brain and the parts of the body that they control or from which they receive sensory input. Such mappings are able to change radically over the course of a few weeks, and some animals seem to have multiple maps. Moreover, we do not fully understand how other areas can take over functions when one area is damaged. There  is  almost no theory on how an individual memory is stored.
The measurement of intact brain activity began in  1929  with the invention by Hans Berger of the electroencephalograph  (EEG).  The recent development of functional magnetic resonance imaging  (fMRI)  (Ogawa  et  al.,  1990)  is giving neuro-scientists unprecedentedly detailed images of brain activity, enabling measurements that correspond in interesting ways to ongoing cognitive processes. These are augmented by advances in single - cell recording of neuron activity. Despite these advances, we are still a long way from understanding how any of these cognitive processes actually work.

In figure 2, A  crude comparison of the raw computational resources available to computers (circa  2003) and brains. The computer's numbers have all increased by at least a factor of 10 since the first edition of this book, and  are  expected to do so again this decade. The brain's numbers have not changed in the last 10,000 years.

Brains and digital computers perform quite different tasks and have different properties. Figure  2 shows that there are 1000 times more neurons in the typical human brain than there are gates in the CPU of a typical high - end computer. Moore's Law 9  predicts that the CPU's gate count will equal the brain's neuron count around 2020.  Of  course, little can be inferred from such predictions; moreover, the difference in storage capacity is minor compared to the difference in switching speed and in parallelism. Computer chips can execute an instruction in a nanosecond, whereas neurons are millions of times slower. Brains more than make up for this, however, because all the neurons and synapses are active simultaneously, whereas most current computers have only one or at most a few CPUs. Thus, even though a computer is a million times faster in raw switching speed, the brain ends up being 100,000 times faster at what it does.

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