How The Mind Work

How The Mind Work Is Important factor that we must put into consideration everyday of our life. because the mind is a central organ and engine upon which other human perception and behavours is build upon. it is like a driven force that propel and gear us towards taking the most crucial daily decision of our life everyday. with the mind we are in control of our thousgt, character action, and above all our destiny. the mind is always at work everyday of our life trying to channel us to either due the rigth thing on the wrong thing.

PRINCIPLE FUNCTION OF THE MIND

1. The mind is the body's control center. It keeps the body working smoothly and it looks after thoughts, feelings and memory  and how the human relate to the environment is virtually control by the mind.
2.Looking at it, form this perspective, seems very easy to remember. But the mind, as part of the neurological system is much more complicated than that. I think that neurology is the most difficult part of medicine to study on, you can only do it if you really love it.
3.The mind is like  the central processing unite of the human body that is a right definition in today's context. I am not aware of the scientific aspects of the brain and so it was very good to read all those what you have written. It was some learning. it help to co-ordinate, execute and transmit action round the body of his possessors

Information Processing Of the mind

The invention of electronic computers in the 1940s, along with the development of mathematical information theory, led to a realization that the mind and the  brains can potentially be understood as information processing systems. This concept formed the basis of the field of cybernetics, and eventually gave rise to the field now known as computational neuroscience. The earliest attempts at cybernetics were somewhat crude in that they treated the mind and the brain as essentially a digital computer in disguise, as for example in John von Neumann's 1958 book, The Computer and the Brain. Over the years, though, accumulating information about the electrical responses of brain cells recorded from behaving animals has steadily moved theoretical concepts in the direction of increasing realism.

Model of a neural circuit in the cerebellum, as proposed by James S. Albus

The essence of the information processing approach is to try to understand brain function in terms of information flow and implementation of algorithms. One of the most influential early contributions was a 1959 paper titled What the frog's eye tells the frog's brain: the paper examined the visual responses of neurons in the retina and optic tectum of frogs, and came to the conclusion that some neurons in the tectum of the frog are wired to combine elementary responses in a way that makes them function as "bug perceivers".A few years later David Hubel and Torsten Wiesel discovered cells in the primary visual cortex of monkeys that become active when sharp edges move across specific points in the field of view—a discovery that eventually brought them a Nobel Prize. Follow-up studies in higher-order visual areas found cells that detect binocular disparity, color, movement, and aspects of shape, with areas located at increasing distances from the primary visual cortex showing increasingly complex responses.Other investigations of brain areas unrelated to vision have revealed cells with a wide variety of response correlates, some related to memory, some to abstract types of cognition such as space.
Theorists have worked to understand these response patterns by constructing mathematical models of neurons and neural networks, which can be simulated using computers. Some useful models are abstract, focusing on the conceptual structure of neural algorithms rather than the details of how they are implemented in the brain; other models attempt to incorporate data about the biophysical properties of real neurons.No model on any level is yet considered to be a fully valid description of brain function, though. The essential difficulty is that sophisticated computation by neural networks requires distributed processing in which hundreds or thousands of neurons work cooperatively—current methods of brain activity recording are only capable of isolating action potentials from a few dozen neurons at a time

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