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| − | <big>''' | + | <big> '''Modeling and Identifying Neural Systems''' </big> |
| − | + | '''Instructor:''' <big> [http://limbs.lcsr.jhu.edu/User:Scarver Sean G. Carver, Ph.D.]</big>, Postdoctoral Fellow, Psychological and Brain Sciences, The Johns Hopkins University. | |
| − | + | '''Semester:''' Spring 2009. | |
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| − | + | '''Seventy-five Word Description:''' This course introduces the paradigms of computational neuroscience and develops skills for modeling neurons and networks of neurons. The course teaches recent developments in neural system identification -- providing systematic tools for building models of neurons and networks based on experimental data. Student's final projects will include original research testing these methods on simulated data. | |
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| + | '''Background:''' Neural modeling is often pursued in an ad hoc way. Researchers add the mechanisms they know about, but need to wave their hands about the ones they don't. They necessarily make many simplifying assumptions but often include many details that are not needed to parsimoniously capture the phenomena. [[Background|'''More...''']] | ||
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| + | '''Course Mechanics:''' This class will be a hands on experience. Pending approval, class will meet twice a week in the Kreiger computer classroom. Each meeting will last about 1.5 hours. In addition, there will be three hours per week of supervised computer laboratory time. Attendence during the laboratory time will be optional. The purpose of the laboratory time is to allow students, if they choose, to complete computer assignments with the help of the instructor. An effort will be made to design the weekly homework sets to allow most students to complete most of the homework during the laboratory time. Grading will be determined 50% by weekly homework and 50% by final projects. Presently, I am not planning exams. | ||
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| + | Textbook, prerequisites and syllabus to be finalized soon. | ||
Revision as of 01:44, 16 August 2008
Modeling and Identifying Neural Systems
Instructor: Sean G. Carver, Ph.D., Postdoctoral Fellow, Psychological and Brain Sciences, The Johns Hopkins University.
Semester: Spring 2009.
Seventy-five Word Description: This course introduces the paradigms of computational neuroscience and develops skills for modeling neurons and networks of neurons. The course teaches recent developments in neural system identification -- providing systematic tools for building models of neurons and networks based on experimental data. Student's final projects will include original research testing these methods on simulated data.
Background: Neural modeling is often pursued in an ad hoc way. Researchers add the mechanisms they know about, but need to wave their hands about the ones they don't. They necessarily make many simplifying assumptions but often include many details that are not needed to parsimoniously capture the phenomena. More...
Course Mechanics: This class will be a hands on experience. Pending approval, class will meet twice a week in the Kreiger computer classroom. Each meeting will last about 1.5 hours. In addition, there will be three hours per week of supervised computer laboratory time. Attendence during the laboratory time will be optional. The purpose of the laboratory time is to allow students, if they choose, to complete computer assignments with the help of the instructor. An effort will be made to design the weekly homework sets to allow most students to complete most of the homework during the laboratory time. Grading will be determined 50% by weekly homework and 50% by final projects. Presently, I am not planning exams.
Textbook, prerequisites and syllabus to be finalized soon.
