Computational Neuroscience


Resource | v1 | created by coursera-bot |
Type Course
Created unavailable
Identifier unavailable

Description

This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning. We will make use of Matlab/Octave/Python demonstrations and exercises to gain a deeper understanding of concepts and methods introduced in the course. The course is primarily aimed at third- or fourth-year undergraduates and beginning graduate students, as well as professionals and distance learners interested in learning how the brain processes information.

Relations

Currently, no topics are attached.

supervised by University of Washington

Founded in 1861, the University of Washington is one of the oldest state-supported institutions of hi...

Currently, no resources are attached.


Edit resource New resource

0.0 /10
useless alright awesome
from 0 reviews
Write comment Rate resource Tip: Rating is anonymous unless you also write a comment.
Resource level 0.0 /10
beginner intermediate advanced
Resource clarity 0.0 /10
hardly clear sometimes unclear perfectly clear
Reviewer's background 0.0 /10
none basics intermediate advanced expert
Comments 0
Currently, there aren't any comments.