Computational Neurology is the learning of brain and its function through information processing structures that make up the nervous system. Computational Neurology comprises the use of computer simulations and theoretical models to study the function of the brain and nervous system. Computational neuroscience, different from psychological connectionism, and also from learning concepts of disciplines such as neural networks, machine learning and computational learning theory. It highlights descriptions of functional and biologically realistic neurons and their dynamics and physiology. These models catch the basic highlights of the natural framework at numerous spatial-fleeting scales, from layer streams, proteins, and compound coupling to organize motions, columnar and topographic design, and learning and memory. These computational models are used to frame hypotheses that can be directly tested by biological or psychological experiments.