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Computer Modeling of the Brain

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Course DatesWeeksMeeting TimesStatusInstructor(s)CRNEnrollment
July 10, 2017 - July 21, 20172M-F 8:30A-11:20AOpenGabriela Manzano-Nieves
Hyeyoung Shin

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Course Description

The human brain is one of the most complicated and mysterious systems on the planet. In recent decades, a huge push has been made to understand the brain through computer modeling. A large number of scientists have been involved in the development of these models not only to advance our understanding and treatments of neurological and psychiatric illnesses, but also to help us understand what underlies daily human experiences ranging from memory to vision to decision making. These models allow scientists to combine results from a variety of other research to try and create a better picture of how the brain works or to reveal gaps in our understanding of the brain. This modeling forms the basis of a field of neuroscience known as computational neuroscience.

The purpose of this course is to threefold: to introduce students to a number of topics in neuroscience, to give students an understanding of how computational neuroscience works and advances our understanding of science, and to enable students to create their own basic models of neurons and neural circuits in the MATLAB programming language.

This course will cover a broad range of topics, including:

  1. How do we remember things and how are memories stored at the molecular level?
  2. How do the electrical properties of neurons allow them to send information across the nervous system?
  3. How does the eye transform what we see into electrical impulses, and how do those impulses encode what we see?
  4. How do studies in computational neuroscience help us in answering the above questions?

In each unit, students will learn both about the topic itself, as well as gain exposure to the history and current state of research on the topic. Throughout each unit, students will work to develop their own models of the system in MATLAB and develop basic programming proficiency.

In this course, students will learn to do the following:

  1. Describe and recognize past and current questions in the field of computational neuroscience.
  2. Identify the advantages and limits of computer modeling in advancing our understanding of the brain.
  3. Make rudimentary computational models in MATLAB to model basic biological systems, ranging from proteins at a single synapse to an area of the brain.
  4. Develop a conceptual understanding of core neural function and apply it to new problems and questions.

This course assumes basic proficiency in high school level algebra, though some familiarity with high school biology will be useful. No previous programming experience is required.

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