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

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. 

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

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. 

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

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.

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

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. 

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

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. 

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.

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:

• Dr Hannah Maslen, Deputy Director, Oxford Uehiro Centre for Practical Ethics, University of Oxford
• Prof. Eric Racine, Director, Pragmatic Health Ethics Research Unity, Montreal Institute of Clinical Research
• Prof Jeffrey Rosenfeld, Director, Monash Institute of Medical Engineering, Monash University
• Dr Isabell Kiral-Kornek, AI and Life Sciences Researcher, IBM Research
• A/Prof Adrian Carter, Neuroethics Program Coordinator, ARC Centre of Excellence for Integrative Brain Function

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.

This module covers a brief history of the neurotechnology industry, bringing the history of brain-computer interfacing to life through engaging skits and stories. 

This module covers many types of invasive neurotechnology devices/interfaces for the central and peripheral nervous systems. Invasive neurotech devices are crucial, as they often provide the greatest accuracy and long-term use applicability.

This module covers many of the types of non-invasive neurotech and neuroimaging devices including electroencephalography (EEG), electromyography (EMG), electroneurography (ENG), magnetoencephalography (MEG), and more.