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.
Overview of the content for Day 1 of this course.
Overview of Day 2 of this course.
Best practices: the tips and tricks on how to get your Miniscope to work and how to get your experiments off the ground.
This talk compares various sensors and resolutions for in vivo neural recordings.
This talk delves into challenges and opportunities of Miniscope design, seeking the optimal balance between scale and function.
Attendees of this talk will learn aobut computational imaging systems and associated pipelines, as well as open-source software solutions supporting miniscope use.
This lecture introduces neuroscience concepts and methods such as fMRI, visual respones in BOLD data, and the eccentricity of visual receptive fields.
This tutorial walks users through the creation and visualization of activation flat maps from fMRI datasets.
This talk covers the present state and future directions of calcium imaging data analysis, particularly in the context of one-photon vs two-photon approaches.