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<h2>NEUSCI 490: Seminar in Computational Neuroscience</h2> | ||
<p>Computational Neuroscience, in brief, is concerned with the use of computational tools (statistics, ML, simulations, modeling, etc) to study the computations of the brain (perception, decision-making, memory, motor planning, etc). In this course we will hear about the cutting-edge research of leading computational neuroscientists in Seattle in discussion-oriented lectures by the researchers themselves. Homework assignments are short written responses to prompts based on reading one of their latest papers, and there is no final exam. 1 Credit. This course is ideal for anyone looking for a deep (but sparse) dive into the latest computational neuroscience research, with ample opportunity for direct discussion of the work with the researchers themselves. Feel free to contact me with any questions - [email protected]. | ||
<p>Computational Neuroscience, in brief, is concerned with the use of computational tools (statistics, ML, simulations, modeling, etc) to study the computations of the brain (perception, decision-making, memory, motor planning, etc). In this course we will hear about the cutting-edge research of leading computational neuroscientists in Seattle in discussion-oriented lectures by the researchers themselves. Homework assignments are short written responses to prompts based on reading one of their latest papers, and there is no final exam. 1 Credit. This course is ideal for anyone looking for a deep (but sparse) dive into the latest computational neuroscience research, with ample opportunity for direct discussion of the work with the researchers themselves. Feel free to contact me with any questions - [email protected]. See the course catalog entry <a href="https://myplan.uw.edu/course/#/courses/NEUSCI490">here</a>. | ||
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<p><h3>Lecturers for Fall 2024</h3> | ||
<p><ul> | ||
<li>Adrienne Fairhall (UW Neurobiology & Biophysics)</li> | ||
<li>Eric Shea-Brown (UW Applied Math)</li> | ||
<li>Nathan Kutz (UW Applied Math)</li> | ||
<li>Anna Gillespie (UW Neurobiology & Biophysics)</li> | ||
<li>Uygar Sümbül (Allen Institute)</li> | ||
<li>Anitha Pasupathy (UW Neurobiology & Biophysics)</li> | ||
<li>Ali Shojaie (UW Biostatistics)</li> | ||
<li>Adrienne Fairhall (UW Neurobiology & Biophysics)</li> | ||
<li>Eric Shea-Brown (UW Applied Math)</li> | ||
<li>Ulises Pereira-Obilinovic (Allen Institute)</li> | ||
<li>Nick Steinmetz (UW Neurobiology & Biophysics and course director)</li> | ||
</ul> | ||
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<p><h3>Lecturers for Fall 2023</h3> | ||
<p><ul> | ||
<li>Adrienne Fairhall</li> | ||
<li>Eric Shea-Brown</li> | ||
<li>Eli Shlizerman</li> | ||
<li>Anna Gillespie</li> | ||
<li>Bing Brunton</li> | ||
<li>Christof Koch</li> | ||
<li>Edgar Walker</li> | ||
<li>Matt Golub</li> | ||
<li>Nick Steinmetz</li> | ||
</ul> | ||
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<p><h3>Lecturers for Fall 2022</h3> | ||
<p><ul> | ||
<li>Adrienne Fairhall</li> | ||
<li>Eric Shea-Brown</li> | ||
<li>Rajesh Rao</li> | ||
<li>Anton Arkhipov</li> | ||
<li>Bing Brunton</li> | ||
<li>Saskia deVries</li> | ||
<li>Wyeth Bair</li> | ||
<li>Sama Ahmed</li> | ||
<li>Nick Steinmetz</li> | ||
</ul> | ||
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<p><h3>Lecturers for Fall 2021</h3> | ||
<p><ul> | ||
<li>Adrienne Fairhall</li> | ||
<li>Eric Shea-Brown</li> | ||
<li>Rajesh Rao</li> | ||
<li>Anton Arkhipov</li> | ||
<li>Fred Rieke</li> | ||
<li>Amy Orsborn</li> | ||
<li>Wyeth Bair</li> | ||
<li>Saskia deVries</li> | ||
<li>Geoff Boynton</li> | ||
<li>Nick Steinmetz</li> | ||
</ul> | ||
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<p><h3>Lecturers for Fall 2020</h3> | ||
<p><ul> | ||
<li>Adrienne Fairhall</li> | ||
<li>Eric Shea-Brown</li> | ||
<li>Beth Buffalo</li> | ||
<li>Anton Arkhipov</li> | ||
<li>Bing Brunton</li> | ||
<li>Amy Orsborn</li> | ||
<li>Wyeth Bair</li> | ||
<li>Saskia deVries</li> | ||
<li>John Tuthill</li> | ||
<li>Nick Steinmetz</li> | ||
</ul> | ||
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