Teaching

• • Offered in Fall

  • This course will introduce students to the fundamental principles and methods of the statistical analysis of neural and behavioral data. A major focus of the course will be on how to properly design experiments to test hypotheses, how to avoid common misconceptions and errors in data analysis and how to report statistics correctly in manuscripts submitted for publication. This course will am at providing a rigorous foundation of general statistical principles that can be applied generally, with an emphasis on material of high relevance to biology and neuroscience.

• • Offered in Fall

  • Fall 2020 syllabus [Stony Brook log-in required]

  • A broad introduction to neural computation. This course will discuss what counts as 'computation' and in what sense the brain computes, how it computes, and whether those computations look anything like those performed by digital computers. These ideas and concepts will be introduced through examples of computation in the brain, including the neural bases of sensory perception, decision making, learning and memory, and motor control. Students will learn through in-class demonstrations and activities, as well as homework assignments that give students the opportunity to analyze real neural recordings relevant to each of the topic modules.

Graduate courses

• • NEU 501 Neuroscience bootcamp, "Introduction to simple models of neuronal networks" (Summer 2018-2020)

  • BNB 562 Introduction to Neuroscience II, "The sensory consequences of motor commands" (Spring 2019-2020)

Undergraduate courses

• • BIO 338 From Synapse to Circuit: Self-organization of the Brain, Lectures on network models of memory (Fall 2019)

  • AMS/BIO 332 Computational Modeling of Physiological Systems, Lectures on neural coding & population dynamics (Spring 2019)

AMATH 383 Continuous mathematical modeling

• • UW students: vist Canvas for course webpage.

  • Syllabus (v2.0)

  • Lecture schedule

  • Homework 0 (review of differential equations, not graded)

  • Lecture on dynamic models of segregation (based on this playable post simulation, in turn based on this paper)

  • Lecture on zombie epidemic modeling (based on this paper (arxiv version))

AMATH 351 Introduction to ordinary differential equations (UW students: vist Canvas for course webpage).

• • Syllabus (v2.0)

  • Homework 0 (review of calculus, not graded)

Other teaching

• Renormalization group analysis of the period-doubling bifurcation (video), substitute lecture for Joel Zylberberg, AMATH 402/502

  • Slides (slightly updated for Hannah Choi's AMATH 402/502 class, winter 2017)