Skip to main content

This lesson describes the principles underlying functional magnetic resonance imaging (fMRI), diffusion-weighted imaging (DWI), tractography, and parcellation. These tools and concepts are explained in a broader context of neural connectivity and mental health. 

Difficulty level: Intermediate
Duration: 1:47:22

In this lecture, you will learn about current methods, approaches, and challenges to studying human neuroanatomy, particularly through the lense of neuroimaging data such as fMRI and diffusion tensor imaging (DTI). 

Difficulty level: Intermediate
Duration: 1:35:14
Speaker: : Matt Glasser

This lesson provides an overview of the current status in the field of neuroscientific ontologies, presenting examples of data organization and standards, particularly from neuroimaging and electrophysiology. 

Difficulty level: Intermediate
Duration: 33:41

In this final lecture of the INCF Short Course: Introduction to Neuroinformatics, you will hear about new advances in the application of machine learning methods to clinical neuroscience data. In particular, this talk discusses the performance of SynthSeg, an image segmentation tool for automated analysis of highly heterogeneous brain MRI clinical scans.

Difficulty level: Intermediate
Duration: 1:32:01

This lesson explores how researchers try to understand neural networks, particularly in the case of observing neural activity. 

Difficulty level: Intermediate
Duration: 8:20
Speaker: : Marcus Ghosh

This lecture provides an introduction to the Brain Imaging Data Structure (BIDS), a standard for organizing human neuroimaging datasets.

Difficulty level: Intermediate
Duration: 56:49

In this lesson, you will learn about the Python project Nipype, an open-source, community-developed initiative under the umbrella of NiPy. Nipype provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages within a single workflow.

Difficulty level: Intermediate
Duration: 1:25:05
Speaker: : Satrajit Ghosh

This lecture introduces you to the basics of the Amazon Web Services public cloud. It covers the fundamentals of cloud computing and goes through both the motivations and processes involved in moving your research computing to the cloud.

Difficulty level: Intermediate
Duration: 3:09:12

This lecture gives an overview of how to prepare and preprocess neuroimaging (EEG/MEG) data for use in TVB.  

Difficulty level: Intermediate
Duration: 1:40:52
Speaker: : Paul Triebkorn

This lesson continues from part one of the lecture Ontologies, Databases, and Standards, diving deeper into a description of ontologies and knowledg graphs. 

Difficulty level: Intermediate
Duration: 50:18
Speaker: : Jeff Grethe

This lecture focuses on ontologies for clinical neurosciences.

Difficulty level: Intermediate
Duration: 21:54

This lesson contains practical exercises which accompanies the first few lessons of the Neuroscience for Machine Learners (Neuro4ML) course. 

Difficulty level: Intermediate
Duration: 5:58
Speaker: : Dan Goodman

This video briefly goes over the exercises accompanying Week 6 of the Neuroscience for Machine Learners (Neuro4ML) course, Understanding Neural Networks.

Difficulty level: Intermediate
Duration: 2:43
Speaker: : Marcus Ghosh

This lesson provides an introduction to modeling single neurons, as well as stability analysis of neural models.

Difficulty level: Intermediate
Duration: 1:26:06
Speaker: : Bard Ermentrout

This lesson continues a thorough description of the concepts, theories, and methods involved in the modeling of single neurons. 

Difficulty level: Intermediate
Duration: 1:25:38
Speaker: : Bard Ermentrout

In this lesson you will learn about fundamental neural phenomena such as oscillations and bursting, and the effects these have on cortical networks. 

Difficulty level: Intermediate
Duration: 1:24:30
Speaker: : Bard Ermentrout

This lesson continues discussing properties of neural oscillations and networks. 

Difficulty level: Intermediate
Duration: 1:31:57
Speaker: : Bard Ermentrout

In this lecture, you will learn about rules governing coupled oscillators, neural synchrony in networks, and theoretical assumptions underlying current understanding.

Difficulty level: Intermediate
Duration: 1:26:02
Speaker: : Bard Ermentrout

This lesson provides a continued discussion and characterization of coupled oscillators. 

Difficulty level: Intermediate
Duration: 1:24:44
Speaker: : Bard Ermentrout

This lesson gives an overview of modeling neurons based on firing rate. 

Difficulty level: Intermediate
Duration: 1:26:42
Speaker: : Bard Ermentrout