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This lesson consists of lecture and tutorial components, focusing on resources and tools which facilitate multi-scale brain modeling and simulation. 

Difficulty level: Beginner
Duration: 3:46:21

In this talk, challenges of handling complex neuroscientific data are discussed, as well as tools and services for the annotation, organization, storage, and sharing of these data. 

Difficulty level: Beginner
Duration: 21:49
Speaker: : Thomas Wachtler

This lecture describes the neuroscience data respository G-Node Infrastructure (GIN), which provides platform independent data access and enables easy data publishing. 

Difficulty level: Beginner
Duration: 22:23
Speaker: : Michael Sonntag

This lesson provides an introduction to the course Neuroscience Data Integration Through Use of Digital Brain Atlases, during which attendees will learn about concepts for integration of research data, approaches and resources for assigning anatomical location to brain data, and infrastructure for sharing experimental brain research data. 

Difficulty level: Beginner
Duration: 14:02
Speaker: : Trygve Leergard

This talk covers the various concepts, motivations, and trends within the neuroscientific community related to the sharing and integration of brain research data. 

Difficulty level: Beginner
Duration: 30:39
Speaker: : Jan G. Bjaalie

This lesson focuses on the neuroanatomy of the human brain, delving into macrostructures like cortices, lobes, and hemispheres, and microstructures like neurons and cortical laminae.

Difficulty level: Beginner
Duration: 51:30

This lesson provides an introduction to the European open research infrastructure EBRAINS and its digital brain atlas resources.

Difficulty level: Beginner
Duration: 27:45
Speaker: : Trygve Leergard

In this lesson, attendees will learn about the challenges in assigning experimental brain data to specific locations, as well as the advantages and shortcomings of current location assignment procedures. 

Difficulty level: Beginner
Duration: 32:18

This lesson covers the inherent difficulties associated with integrating neuroscientific data, as well as the current methods and approaches to do so. 

Difficulty level: Beginner
Duration: 25:41
Speaker: : Trygve Leergard

Attendees of this talk will learn about QuickNII, a tool for user-guided affine registration of 2D experimental image data to 3D atlas reference spaces, which also facilitates data integration through standardized coordinate systems. 

Difficulty level: Beginner
Duration: 21:08
Speaker: : Maja Puchades

This lesson provides an overview of DeepSlice, a Python package which aligns histology to the Allen Brain Atlas and Waxholm Rat Atlas using deep learning.

Difficulty level: Beginner
Duration: 17:30
Speaker: : Harry Carey

This lesson provides an introduction to biologically detailed computational modelling of neural dynamics, including neuron membrane potential simulation and F-I curves. 

Difficulty level: Intermediate
Duration: 8:21
Speaker: : Mike X. Cohen

In this lesson, users learn how to use MATLAB to build an adaptive exponential integrate and fire (AdEx) neuron model. 

Difficulty level: Intermediate
Duration: 22:01
Speaker: : Mike X. Cohen

In this lesson, users learn about the practical differences between MATLAB scripts and functions, as well as how to embed their neuronal simulation into a callable function.  

Difficulty level: Intermediate
Duration: 11:20
Speaker: : Mike X. Cohen

This lesson teaches users how to generate a frequency-current (F-I) curve, which describes the function that relates the net synaptic current (I) flowing into a neuron to its firing rate (F). 

Difficulty level: Intermediate
Duration: 20:39
Speaker: : Mike X. Cohen

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 brief talk goes into work being done at The Alan Turing Institute to solve real-world challenges and democratize computer vision methods to support interdisciplinary and international researchers. 

Difficulty level: Beginner
Duration: 7:10

This lesson aims to define computational neuroscience in general terms, while providing specific examples of highly successful computational neuroscience projects. 

Difficulty level: Beginner
Duration: 59:21
Speaker: : Alla Borisyuk

This lesson delves into the the structure of one of the brain's most elemental computational units, the neuron, and how said structure influences computational neural network models. 

Difficulty level: Intermediate
Duration: 6:33
Speaker: : Marcus Ghosh

In this lesson you will learn how machine learners and neuroscientists construct abstract computational models based on various neurophysiological signalling properties. 

Difficulty level: Intermediate
Duration: 10:52
Speaker: : Dan Goodman