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.
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.
This video provides a very quick introduction to some of the neuromorphic sensing devices, and how they offer unique, low-power applications.
This lecture covers modeling the neuron in silicon, modeling vision and audition, and sensory fusion using a deep network.
This lesson presents a simulation software for spatial model neurons and their networks designed primarily for GPUs.
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.
Presentation of the Brian neural simulator, where models are defined directly by their mathematical equations and code is automatically generated for each specific target.
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.
This lesson gives a description of the BrainHealth Databank, a repository of many types of health-related data, whose aim is to accelerate research, improve care, and to help better understand and diagnose mental illness, as well as develop new treatments and prevention strategies.
This lesson corresponds to slides 46-78 of the PDF below.
This lesson describes not only the need for precision medicine, but also the current state of the methods, pharmacogenetic approaches, utility and implementation of such care today.
This lesson corresponds to slides 1-50 of the PowerPoint below.
This lecture covers the needs and challenges involved in creating a FAIR ecosystem for neuroimaging research.
This lecture covers how to make modeling workflows FAIR by working through a practical example, dissecting the steps within the workflow, and detailing the tools and resources used at each step.
This lecture focuses on the structured validation process within computational neuroscience, including the tools, services, and methods involved in simulation and analysis.
This session provides users with an introduction to tools and resources that facilitate the implementation of FAIR in their research.
This lesson describes the current state of brain-computer interface (BCI) standards, including the present obstacles hindering the forward movement of BCI standardization as well as future steps aimed at solving this problem.
This lecture covers the ethical implications of the use of brain-computer interfaces, brain-machine interfaces, and deep brain stimulation to enhance brain functions and was part of the Neuro Day Workshop held by the NeuroSchool of Aix Marseille University.
Panel discussion by leading scientists, engineers and philosophers discuss what brain-computer interfaces are and the unique scientific and ethical challenges they pose. hosted by Lynne Malcolm from ABC Radio National's All in the Mind program and features:
In this module you will learn the basics of Brain Computer Interface (BCI). You will read an introduction to the different technologies available, the main components and steps required for BCI, associated safety and ethical issues, as well as an overview about the future of the field.
In this module, users will learn about the different types of neurotechnology and how each of them works. This will be done through the metaphor of going to a symphony... in your brain. Like a symphony, brain processes emerge from collections of neural activity. This video encourages us to imagine ourselves moving to different areas in the concert hall to understand where different technologies interface. Once the concert ends, we talk about underlying neural mechanisms and technology that allow researchers and innovators to interact with the brain.
This module addresses how neurotechnology is currently used for medical and non-medical applications, and how it might advance in the future.