SC7 Brain-Computer Interfaces to Probe Problem-Solving

Description

Session 1: Introduction to motor neurophysiology. Behavior, single-unit physiology and population dynamics.
Session 2: Introduction to machine learning. Brain-computer interfaces as a specific application of machine learning. New tools for analyzing neural population activity.
Session 3: Studying learning and problem-solving using the BCI framework
Session 4: Continuation of prior lectures, overview of the BCI field, and brainstorming discussion.

Objectives

Students will develop a working knowledge of brain-computer interfaces. This will include an ability to derive the fundamental equations, and an understanding of the tradeoffs choices inherent in BCI design. Students will be able to use modern tools of multineuronal data analysis. At very least, students will be equipped to read,
understand, and critically evaluate the emerging literature of brain-computer interfaces and multineuronal analysis.

Literature

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Course location

Lecture Room 3

Course requirements

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Instructor information.

Instructor

Aaron Batista

Website

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