The course introduces neuroscience as a specialized discipline. Goal of the course is to provide a detailed description of the logic of the nervous system from the perspectives of Physiology, evolution, organization, development, physiology and emergent properties like synaptic plasticity.
Course content includes: Electrical properties of the neurons, Ionic basis of membrane potential, generation of action potential, synaptic transmission and plasticity and emerging areas of astrocytic and glial feedback. Evolution and organization of the nervous system; and development of the nervous system are also discussed in detail.
This course is designed to gain skills to create your own models. The course will span a range of scales of single macromolecules to complete organisms. Basic modeling skills, including dimensional analysis, identification of
variables, and ODE formulation. Probabilistic modeling skills, including stochastic simulation. Data analysis methods, including maximum likelihood and Bayesian methods. Computer programming using a general-purpose platform like MATLAB or Python, with short codes written from scratch. Dynamical systems, particularly feedback control, with phase portrait methods.
This course builds from Neurobiology I and focuses on higher functions of the nervous
system. It focusses on systems level functions like, Visual Systems, Olfaction, Auditory system, Motor systems, Learning and memory, Processing of emotion, Arousal and circadian rhythms. Neurological disorders and Imaging techniques are also discussed