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This lecture covers a lot of post-war developments in the science of the mind, focusing first on the cognitive revolution, and concluding with living machines.

Difficulty level: Beginner
Duration: 2:24:35

This lecture focuses on how the immune system can target and attack the nervous system to produce autoimmune responses that may result in diseases such as multiple sclerosis, neuromyelitis, and lupus cerebritis manifested by motor, sensory, and cognitive impairments. Despite the fact that the brain is an immune-privileged site, autoreactive lymphocytes producing proinflammatory cytokines can cause active brain inflammation, leading to myelin and axonal loss.

Difficulty level: Beginner
Duration: 37:36
Speaker: : Anat Achiron

This lesson gives an introduction to simple spiking neuron models.

Difficulty level: Beginner
Duration: 48 Slides
Speaker: : Zubin Bhuyan

This lesson provides an introduction to simple spiking neuron models.

Difficulty level: Beginner
Duration: 48 Slides
Speaker: : Zubin Bhuyan

This lesson gives an introductory presentation on how data science can help with scientific reproducibility.

Difficulty level: Beginner
Duration:
Speaker: : Michel Dumontier

This presentation accompanies the paper entitled: An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data (see link below to download publication). 

Difficulty level: Beginner
Duration: 4:56

This lesson provides an introduction to the lifecycle of EEG/ERP data, describing the various phases through which these data pass, from collection to publication.

Difficulty level: Beginner
Duration: 35:30

In this lesson you will learn about experimental design for EEG acquisition, as well as the first phases of the EEG/ERP data lifecycle. 

Difficulty level: Beginner
Duration: 30:04

This lesson provides an overview of the current regulatory measures in place regarding experimental data security and privacy. 

Difficulty level: Beginner
Duration: 31:00

In this lesson, you will learn the appropriate methods for collection of both data and associated metadata during EEG experiments.

Difficulty level: Beginner
Duration: 29:14

This lesson goes over methods for managing EEG/ERP data after it has been collected, from annotation to publication. 

Difficulty level: Beginner
Duration: 39:25

In this final lesson of the course, you will learn broadly about EEG signal processing, as well as specific applications which make this kind of brain signal valuable to researchers and clinicians. 

Difficulty level: Beginner
Duration: 34:51

This lecture on model types introduces the advantages of modeling, provide examples of different model types, and explain what modeling is all about. 

Difficulty level: Beginner
Duration: 27:48
Speaker: : Gunnar Blohm

This lecture focuses on how to get from a scientific question to a model using concrete examples. We will present a 10-step practical guide on how to succeed in modeling. This lecture contains links to 2 tutorials, lecture/tutorial slides, suggested reading list, and 3 recorded Q&A sessions.

Difficulty level: Beginner
Duration: 29:52
Speaker: : Megan Peters

This lecture formalizes modeling as a decision process that is constrained by a precise problem statement and specific model goals. We provide real-life examples on how model building is usually less linear than presented in Modeling Practice I

Difficulty level: Beginner
Duration: 22:51
Speaker: : Gunnar Blohm

This lecture focuses on the purpose of model fitting, approaches to model fitting, model fitting for linear models, and how to assess the quality and compare model fits. We will present a 10-step practical guide on how to succeed in modeling. 

Difficulty level: Beginner
Duration: 26:46
Speaker: : Jan Drugowitsch

This lecture summarizes the concepts introduced in Model Fitting I and adds two additional concepts: 1) MLE is a frequentist way of looking at the data and the model, with its own limitations. 2) Side-by-side comparisons of bootstrapping and cross-validation.

Difficulty level: Beginner
Duration: 38.17
Speaker: : Kunlin Wei

This lecture provides an overview of the generalized linear models (GLM) course, originally a part of the Neuromatch Academy (NMA), an interactive online summer school held in 2020. NMA provided participants with experiences spanning from hands-on modeling experience to meta-science interpretation skills across just about everything that could reasonably be included in the label "computational neuroscience". 

Difficulty level: Beginner
Duration: 33:58
Speaker: : Cristina Savin

This lecture further develops the concepts introduced in Machine Learning I. This lecture is part of the Neuromatch Academy (NMA), an interactive online computational neuroscience summer school held in 2020.

Difficulty level: Beginner
Duration: 29:30
Speaker: : I. Memming Park

This lecture introduces the core concepts of dimensionality reduction.

Difficulty level: Beginner
Duration: 31:43
Speaker: : Byron Yu