Acerca de este Curso
4.6
448 calificaciones
97 revisiones
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Nivel principiante

Nivel principiante

Horas para completar

Aprox. 31 horas para completar

Sugerido: 5 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English)

Habilidades que obtendrás

Computational NeuroscienceArtificial Neural NetworkReinforcement LearningBiological Neuron Model
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Nivel principiante

Nivel principiante

Horas para completar

Aprox. 31 horas para completar

Sugerido: 5 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
Horas para completar
4 horas para completar

Introduction & Basic Neurobiology (Rajesh Rao)

This module includes an Introduction to Computational Neuroscience, along with a primer on Basic Neurobiology. ...
Reading
6 videos (Total 89 min), 6 readings, 2 quizzes
Video6 videos
1.2 Computational Neuroscience: Descriptive Models11m
1.3 Computational Neuroscience: Mechanistic and Interpretive Models12m
1.4 The Electrical Personality of Neurons23m
1.5 Making Connections: Synapses20m
1.6 Time to Network: Brain Areas and their Function17m
Reading6 lecturas
Welcome Message & Course Logistics10m
About the Course Staff10m
Syllabus and Schedule10m
Matlab & Octave Information and Tutorials10m
Python Information and Tutorials10m
Week 1 Lecture Notes10m
Quiz2 ejercicios de práctica
Matlab/Octave Programmingm
Python Programmingm
Semana
2
Horas para completar
4 horas para completar

What do Neurons Encode? Neural Encoding Models (Adrienne Fairhall)

This module introduces you to the captivating world of neural information coding. You will learn about the technologies that are used to record brain activity. We will then develop some mathematical formulations that allow us to characterize spikes from neurons as a code, at increasing levels of detail. Finally we investigate variability and noise in the brain, and how our models can accommodate them....
Reading
8 videos (Total 167 min), 3 readings, 1 quiz
Video8 videos
2.2 Neural Encoding: Simple Models12m
2.3 Neural Encoding: Feature Selection22m
2.4 Neural Encoding: Variability23m
Vectors and Functions (by Rich Pang)30m
Convolutions and Linear Systems (by Rich Pang)16m
Change of Basis and PCA (by Rich Pang)18m
Welcome to the Eigenworld! (by Rich Pang)24m
Reading3 lecturas
Welcome Message10m
Week 2 Lecture Notes and Tutorials10m
IMPORTANT: Quiz Instructions10m
Quiz1 ejercicio de práctica
Spike Triggered Averages: A Glimpse Into Neural Encodingm
Semana
3
Horas para completar
3 horas para completar

Extracting Information from Neurons: Neural Decoding (Adrienne Fairhall)

In this module, we turn the question of neural encoding around and ask: can we estimate what the brain is seeing, intending, or experiencing just from its neural activity? This is the problem of neural decoding and it is playing an increasingly important role in applications such as neuroprosthetics and brain-computer interfaces, where the interface must decode a person's movement intentions from neural activity. As a bonus for this module, you get to enjoy a guest lecture by well-known computational neuroscientist Fred Rieke. ...
Reading
6 videos (Total 114 min), 2 readings, 1 quiz
Video6 videos
3.2 Population Coding and Bayesian Estimation24m
3.3 Reading Minds: Stimulus Reconstruction11m
Fred Rieke on Visual Processing in the Retina14m
Gaussians in One Dimension (by Rich Pang)30m
Probability distributions in 2D and Bayes' Rule (by Rich Pang)13m
Reading2 lecturas
Welcome Message10m
Week 3 Lecture Notes and Supplementary Material10m
Quiz1 ejercicio de práctica
Neural Decoding30m
Semana
4
Horas para completar
3 horas para completar

Information Theory & Neural Coding (Adrienne Fairhall)

This module will unravel the intimate connections between the venerable field of information theory and that equally venerable object called our brain....
Reading
5 videos (Total 98 min), 2 readings, 1 quiz
Video5 videos
4.2 Calculating Information in Spike Trains17m
4.3 Coding Principles19m
What's up with entropy? (by Rich Pang)25m
Information theory? That's crazy! (by Rich Pang)16m
Reading2 lecturas
Welcome Message10m
Week 4 Lecture Notes and Supplementary Material10m
Quiz1 ejercicio de práctica
Information Theory & Neural Codingm
4.6
97 revisionesChevron Right

Principales revisiones

por CMJun 15th 2017

This course is an excellent introduction to the field of computational neuroscience, with engaging lectures and interesting assignments that make learning the material easy.

por ATMay 27th 2018

This is a wonderful start for a biologist , to get idea of concepts of learning . An advanced course focused more on brain circuitry is suggested.\n\nThanks a lot

Instructores

Avatar

Rajesh P. N. Rao

Professor
Computer Science & Engineering
Avatar

Adrienne Fairhall

Associate Professor
Physiology and Biophysics

Acerca de University of Washington

Founded in 1861, the University of Washington is one of the oldest state-supported institutions of higher education on the West Coast and is one of the preeminent research universities in the world....

Preguntas Frecuentes

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