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This video gives a brief introduction to Neuro4ML's lessons on neuromorphic computing - the use of specialized hardware which either directly mimics brain function or is inspired by some aspect of the way the brain computes. 

Difficulty level: Intermediate
Duration: 3:56
Speaker: : Dan Goodman

In this lesson, you will learn in more detail about neuromorphic computing, that is, non-standard computational architectures that mimic some aspect of the way the brain works. 

Difficulty level: Intermediate
Duration: 10:08
Speaker: : Dan Goodman

This video provides a very quick introduction to some of the neuromorphic sensing devices, and how they offer unique, low-power applications.

Difficulty level: Intermediate
Duration: 2:37
Speaker: : Dan Goodman
Course:

This lecture covers modeling the neuron in silicon, modeling vision and audition, and sensory fusion using a deep network. 

Difficulty level: Beginner
Duration: 1:32:17
Speaker: : Shih-Chii Liu

This lesson presents a simulation software for spatial model neurons and their networks designed primarily for GPUs.

Difficulty level: Intermediate
Duration: 21:15
Speaker: : Tadashi Yamazaki

This lesson gives an overview of past and present neurocomputing approaches and hybrid analog/digital circuits that directly emulate the properties of neurons and synapses.

Difficulty level: Beginner
Duration: 41:57
Speaker: : Giacomo Indiveri

Presentation of the Brian neural simulator, where models are defined directly by their mathematical equations and code is automatically generated for each specific target.

Difficulty level: Beginner
Duration: 20:39
Speaker: : Giacomo Indiveri

The lecture covers a brief introduction to neuromorphic engineering, some of the neuromorphic networks that the speaker has developed, and their potential applications, particularly in machine learning.

Difficulty level: Intermediate
Duration: 19:57

This lesson breaks down the principles of Bayesian inference and how it relates to cognitive processes and functions like learning and perception. It is then explained how cognitive models can be built using Bayesian statistics in order to investigate how our brains interface with their environment. 

This lesson corresponds to slides 1-64 in the PDF below. 

Difficulty level: Intermediate
Duration: 1:28:14

This is a tutorial on designing a Bayesian inference model to map belief trajectories, with emphasis on gaining familiarity with Hierarchical Gaussian Filters (HGFs).

 

This lesson corresponds to slides 65-90 of the PDF below. 

Difficulty level: Intermediate
Duration: 1:15:04
Speaker: : Daniel Hauke

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 provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.

Difficulty level: Beginner
Duration: 37:51

This lesson is part 1 of 2 of a tutorial on statistical models for neural data.

Difficulty level: Beginner
Duration: 1:45:48
Speaker: : Jonathan Pillow

What is the difference between attention and consciousness? This lecture describes the scientific meaning of consciousness, journeys on the search for neural correlates of visual consciousness, and explores the possibility of consciousness in other beings and even non-biological structures.

Difficulty level: Beginner
Duration: 1:10:01
Speaker: : Christof Koch

This lecture gives an introduction to the types of glial cells, homeostasis (influence of cerebral blood flow and influence on neurons), insulation and protection of axons (myelin sheath; nodes of Ranvier), microglia and reactions of the CNS to injury.

Difficulty level: Beginner
Duration: 40:32

This tutorial introduces pipelines and methods to compute brain connectomes from fMRI data. With corresponding code and repositories, participants can follow along and learn how to programmatically preprocess, curate, and analyze functional and structural brain data to produce connectivity matrices. 

Difficulty level: Intermediate
Duration: 1:39:04

In this lightning talk, you will learn about BrainGlobe, an initiative which exists to facilitate the development of interoperable Python-based tools for computational neuroanatomy.

Difficulty level: Beginner
Duration: 3:33

In this short talk you will learn about The Neural System Laboratory, which aims to develop and implement new technologies for analysis of brain architecture, connectivity, and brain-wide gene and molecular level organization.

Difficulty level: Beginner
Duration: 8:38
Speaker: : Trygve Leergard

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 video demonstrates each required step for preprocessing T1w anatomical data in brainlife.io.

Difficulty level: Beginner
Duration: 3:28
Speaker: :