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Course Info

  • Course Number / Code:
  • 9.29J (Spring 2004) 
  • Course Title:
  • Introduction to Computational Neuroscience 
  • Course Level:
  • Undergraduate 
  • Offered by :
  • Massachusetts Institute of Technology (MIT)
    Massachusetts, United States  
  • Department:
  • Brain and Cognitive Sciences 
  • Course Instructor(s):
  • Prof. Sebastian Seung 
  • Course Introduction:
  •  


  • 9.29J / 9.912J / 8.261J Introduction to Computational Neuroscience



    Spring 2004




    Course Highlights


    This course features a selection of downloadable lecture notes, and problem sets in the assignments section.


    Course Description


    This course gives a mathematical introduction to neural coding and dynamics. Topics include convolution, correlation, linear systems, game theory, signal detection theory, probability theory, information theory, and reinforcement learning. Applications to neural coding, focusing on the visual system are covered, as well as Hodgkin-Huxley and other related models of neural excitability, stochastic models of ion channels, cable theory, and models of synaptic transmission.

    Visit the Seung Lab Web site.



    Technical Requirements


    Special software is required to use some of the files in this course: .mat, and .m.

     

ACKNOWLEDGEMENT:
This course content is a redistribution of MIT Open Courses. Access to the course materials is free to all users.






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