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Optimal Control

Level
Beginner

Neuromatch Academy aims to introduce traditional and emerging tools of computational neuroscience to trainees. It is appropriate for student population ranging from undergraduates to faculty in academic settings and also includes industry professionals. In addition to teaching the technical details of computational methods, Neuromatch Academy also provide a curriculum centered on modern neuroscience concepts taught by leading professors along with explicit instruction on how and why to apply models.

 

This course provides an introduction of optimal control, describes open-loop and closed-loop control, and application to motor control.

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Course Features
Lectures
Interactive Tutorials
Suggested Reading
Recordings of question and answer sessions
Discussion Forum on Neurostars.org
Lessons of this Course
1
1
Duration:
36:23

This lecture provides an introduction to optimal control, describes open-loop and closed-loop control, and application to motor control.

2
2
Duration:
4:46
Speaker:

In this tutorial, you will perform a Sequential Probability Ratio Test between two hypotheses HL and HR by running simulations of a Drift Diffusion Model (DDM).

3
3
Duration:
10:02
Speaker:

In this tutorial, you will implement a continuous control task: you will design control inputs for a linear dynamical system to reach a target state. 

4
4
Duration:
28:48

This lecture covers the utility of action: vigor and neuroeconomics of movement and applications to foraging and the marginal value theorem.