Buy an essay on Neural Networks

We should start with a quote of an outstanding Canadian psychologist and the father of cognitive psychobiology Donald O. Hebb: “A large brain, like large government, may not be able to do simple things in a simple way”. The scholar was inspired by James, Freud and Watson as well as worked in the intellectual climate created by John Fulton, J. Dusser de Barenne and Warren McCulloch.
Though human brain study dates back thousands of years, modern era of neuron network research is influenced with Donald Hebb’s book “The Organization of Behavior” published in 1949 where he formulated his dual trace mechanism, described his understanding of how the neurons’ function contributed to learning as a psychological process. The book reinforced and developed the theories of twentieth-century neurophysiologists McCulloch and Pitts concerning the work of neurons. The book contains invaluable experience of the scholar’s work in brain surgery and his human behavior research that eventually brought together the biological brain function with the higher function of the mind. Earlier scientists unsuccessfully strived to explain the connections between neurons, their theories failed to thoroughly explain how the brain and the mind were connected. They regarded the connections as a one-way process and were mainly grounded on the theory of stimulus and response.
Using neuroscientific principles Hebb managed to bring the mind and behavior data into a single theory that described the way neural pathways were strengthened each time they were used. The theory came to be known as Hebbian theory and the corresponding method of learning was called Hebbian learning. Judging from the theory’s key postulates the following Hebb’s Law is formulated: “Neurons that fire together wire together”. The scholar conducted experiments and created the Adult Comprehension Test and the Picture Anomaly Test that facilitated the research and manifested that lack of stimulation led to diminished brain function and even hallucinations. His Picture Anomaly Test proved for the first time that the right temporal lobe was involved in visual recognition and large part of frontal lobe removal scarcely influenced intelligence. So, he showed the interrelation of the role of frontal lobes and the age proving that they were instrumental only in the early life. On maintaining skepticism towards all theories Hebb himself described his theory as “pseudo-behavioristic”, as he moved away from behaviorism and worked with higher mental processes like thinking and perception. In his theory Hebb considered how a stimulus and a response interacted when there was a lapse between them. Making arousal a key in his work, the scholar asserted that “thoughts mediated the responses by collaborating with sensory input to determine which of a number of possible responses could be made”. Another key feature of his learning theory was the facilitative process, among the main concepts were reactivity and plasticity. Hebb emphasized the strong connection between motivation and learning and never separated them. In “Hebb synapse” he boldly claimed: “When an axon of cell A is near enough to excite 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”. He defined the cell-assembly proposal and explained phase sequence claiming that thinking is the sequential activation of cell-assemblies.
His work definitely arose from a rich tradition of research and has inspired a number of investigators who study the mechanisms of learning at all levels of brain function. They tested and validated Hebb’s neuropsychological theory and discussed his contribution into neuroscience in articles, symposia, books and what not. Hebb’s model of working with the mind not only had a great impact on psychologists and opened up the way for the creation of computational machines, moreover, his ideas are still used in contemporary artificial neural networks.



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