A course in which selected students conduct original research under the direction of a faculty member.

Doctoral research

Special Topics in Neuroscience: Applied Statistics in Neuroscience

The course is focused on understanding how information about brain and nervous system function can be determined from a wide range of experimental and data analysis techniques.

Independent research conducted under the guidance of a faculty member.

An introduction to teaching neuroscience for undergraduate teaching assistants, with a focus on effective teaching, active engagement of students, and development of innovative classroom activities. May be used as NEUR elective credit for NEUR majors.

This class offers an introduction to the world of building mathematical and computational models to understand cognitive and neural processes. The philosophy of this course is to have you actually build these models and engage with the data to (re)discover the theories for yourself. To this end you will be deriving mathematical expressions for behaviors in different experiments, building computational models to simulate neural firing, and analyzing real behavioral and neural data. In addition, you’ll have the opportunity to build your own models and experiments in a project that takes the place of the final. While computational methods can be applied to understand any aspect of Cognition, in this course we will focus on the computational modeling of decision making. By focusing on a single topic, the goal is to go deep down the modeling rabbit hole to really see how models are built, tested, and improved upon over time. 

Special Topics in Neuroscience