Course Information

Course Name	Turkish	Hesaplamalı Sinirbilimi
	English	Computational Neuroscience
Course Code	BLU 621E	Credit	Lecture (hour/week)	Recitation (hour/week)	Laboratory (hour/week)
Semester	-	3	3	-	-
Course Language		English
Course Coordinator		Murat Okatan
Course Objectives		1. To introduce the main elements of the nervous system from molecular scale to the scale of the organism in terms of structure and function. 2. Explanation of the biophysics of electrical events in the nervous system and their mathematical modeling. 3. Data collection with brain-computer-interfaces and analysis of the collected data by statistical signal processing methods. 4. Likelihood-based models of neural activity and their use in neural decoding.
Course Description		Central and peripheral nervous systems and their substructures. Sensory systems. Anatomy and physiology of neurons and glia. Nernst and Goldman Equations. Electrical equivalent circuit of the cell membrane. Hodgkin-Huxley Equations. Brain-computer interfaces. Recording techniques. Spike sorting. Spike train analysis using point-process Generalized Linear Models. Spike train decoding.
Course Outcomes		Students who take this course will learn: 1) How the anatomy and physiology of the nervous system mediates the flow and processing of information, 2) How this information processing is observed using extracellular recording technology, 3) How extracellular recordings are explained through statistical modeling and signal processing, 4) Modelling and decoding of the activity of individual and populations of neurons.
Pre-requisite(s)		Calculus, Probability and Statistics
Required Facilities
Other
Textbook		[1] Eric R. Kandel, James H. Schwartz, Thomas M. Jessell, Steven A. Siegelbaum, A. J. Hudspeth, Principles of Neural Science, Fifth Edition, McGraw Hill Medical Books, 2013. [2] Yudi Pawitan, In All Likelihood: Statistical Modelling and Inference Using Likelihood, Oxford University Press, 2001. [3] D.J. Daley, D. Vere-Jones, An Introduction to the Theory of Point Processes, Volume 1, Springer, 2007. [4] P. McCullagh, John A. Nelder, Generalized Linear Models, Chapman & Hall/CRC, 1989. [5] Richard D. Keynes, Nerve and Muscle, Fourth Edition, Cambridge University Press, 2011.
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