Computational Neuroscience

The human brain, perhaps the most complex, sophisticated, and complicated learning system, controls virtually every aspect of our behavior. Neuroscience is the study of the brain, and computational neuroscience divides this study into three subspecialties: neural coding, biophysics of neurons, and neural networks. The course is primarily aimed at high school students that are interested in learning how the brain processes information. The course will start with a basic introduction to the structure and function of the central nervous system, and then include a study of the neurophysiology of the neuron, electrophysiological approaches to record from neurons, as well as mathematical and/or computer-based models that help explain existing biological data. The course will provide a simple introduction to basic computational methods of the brain from the cellular level and the network level with the aim of explaining what nervous systems do and how they function. Basic techniques of modeling biophysics, excitable membranes, small network and large-scale network systems will be introduced. The range of topics include simulations of electrical properties of membrane channels, single cells, neuronal networks, learning and memory models, and models of synaptic transmission, thereby providing a theoretical framework that encapsulates our emerging understanding of the sensory, motor, and cognitive functions of the brain. A main goal of this course also is to provide students with a broad overview of the many practical applications in the field of computational neuroscience and review neuroengineering methods and technologies that enable the study of and therapeutic solutions for diseases of the brain or damage to the CNS, particularly for research or clinical application in the neurosciences.