Acerca de este Curso
4.6
432 calificaciones
90 revisiones
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....
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Cursos 100 % en línea

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Fechas límite flexibles

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Beginner Level

Nivel principiante

Clock

Approx. 29 hours to complete

Sugerido: 5 hours/week...
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English

Subtítulos: English...

Habilidades que obtendrás

Computational NeuroscienceArtificial Neural NetworkReinforcement LearningBiological Neuron Model
Globe

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Calendar

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Beginner Level

Nivel principiante

Clock

Approx. 29 hours to complete

Sugerido: 5 hours/week...
Comment Dots

English

Subtítulos: English...

Programa - Qué aprenderás en este curso

Week
1
Clock
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
Week
2
Clock
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
Week
3
Clock
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
Week
4
Clock
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

Principales revisiones

por JRApr 8th 2018

Extremely enlightening course on how Neuron's work and the science of computational neuroscience. Even if you don't want to get into the complex mathematics you can get a lot out of the course

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.

Instructores

Rajesh P. N. Rao

Professor
Computer Science & Engineering

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

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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