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How to Use Allen Institute for Brain Science Resources

Allen Institute for Brain Science

This course features tutorials on how to use Allen atlases and digital brain atlasing tools, including operational and user features of the Allen Mouse Brain Atlas, as well as the Allen Institute's 3D viewing tool, Brain Explorer®.

 

INCF Assembly 2022 - Training Day 2

INCF

This course contains sessions from the second day of INCF's Neuroinformatics Assembly 2022.

 

Module 2: EEG

Mike X. Cohen

In this module, you will work with human EEG data recorded during a steady-state visual evoked potential study (SSVEP, aka flicker). You will learn about spectral analysis, alpha activity, and topographical mapping. The MATLAB code introduces functions, sorting, and correlation analysis.

 
INCF TrainingSpace

Session 1: A FAIR Roadmap for Knowledge Graphs and Ontologies

INCF

This course corresponds to the first session of talks given at INCF's Neuroinformatics Assembly 2023. The sessions consists of several lectures, focusing on using the principles of FAIR (findability, accessibility, interoperability, and reusability) to inform future directions in neuroscience and neuroinformatics. In particular, these talks deal with the development of knowledge graphs and ontologies. 

 

Reinforcement Learning

Neuromatch Academy

Neuromatch Academy aims to introduce traditional and emerging tools of computational neuroscience to trainees.

 
INCF TrainingSpace

UCSC Genome Browser Tutorial

University of California, Sanata Cruz (UCSC)

The UCSC Genome Browser is an online and downloadable genome browser hosted by the University of California, Santa Cruz (UCSC). It is an interactive website offering access to genome sequence data from a variety of vertebrate and invertebrate species and major model organisms, integrated with a large collection of aligned annotations.

 

Module 3: Computational Models

Mike X. Cohen

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and F-I curves. The MATLAB code introduces live scripts and functions.

 

Ethics and Governance

Ethical conduct of science, good governance of data, and accelerated translation to the clinic are key to high-calibre open neuroscience.  Everyday practitioners of science must be sensitized to a range of ethical considerations in their research, some having especially to do with open data-sharing. The lessons included in this course introduce a number of these topics and end with concrete guidance for participant consent and de-identification of data.

 

The Virtual Brain Node #10 Workshop: Personalized Multi-Scale Brain Simulation

The Virtual Brain

This workshop provides basic knowledge on personalized brain network modeling using the open-source simulation platform The Virtual Brain (TVB). Participants will gain theoretical knowledge and apply this knowledge to construct brain models, process multimodal neuroimaging data for reconstructing individual brains, run simulations, and use supporting neuroinformatics tools such as collaboratories, pipelines, workflows, and data repositories.

 

Data Science and Neuroinformatics

INCF

Much like neuroinformatics, data science uses techniques from computational science to derive meaningful results from large complex datasets. In this session, we will explore the relationship between neuroinformatics and data science, by emphasizing a range of data science approaches and activities, ranging from the development and application of statistical methods, through the establishment of communities and platforms, and through the implementation of open-source software tools.

 
INCF TrainingSpace

Biochemical Models

INCF

This course consists of introductory lectures on different aspects of biochemical models. By following this course, you will learn about the various forms plasticity can take at different levels in the brain, how to model chemical computation in the brain, as well as computationally demanding studies of synaptic plasticity on the molecular level. 

 

Open Data in Neuroscience: Data Sharing in EBRAINS

Maaike van Swieten, Ida Aasebø, the EBRAINS curation services and HBP-EBRAINS

There is a broad consensus among researchers, publishers, and funding bodies that open sharing of data is needed to address major reproducibility and transparency challenges that currently exist in all scientific disciplines. In addition to potentially increasing the utilization of shared data through re-analysis and integration with other data, data sharing is beneficial for individual researchers through data citation and increased exposure of research.

 

INCF Assembly 2022 - Training Day 2

INCF

This course contains sessions from the second day of INCF's Neuroinformatics Assembly 2022.

 
INCF TrainingSpace

Deep Learning: Graphs

NYU Center for Data Science

This module provides an introduction to the problem of speech recognition using neural models, emphasizing the CTC loss for training and inference when input and output sequences are of different lengths. It also covers beam search for use during inference, and how that procedure may be modeled at training time using a Graph Transformer Network.

 
INCF TrainingSpace

Introduction to EEGLAB

Swartz Center for Computational Neuroscience

EEGLAB is an interactive MATLAB toolbox for processing continuous and event-related EEG, MEG, and other electrophysiological data. In this course, you will learn about features incorporated into EEGLAB, including independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. EEGLAB runs under Linux, Unix, Windows, and Mac OS X.

 
INCF TrainingSpace

Session 6: Research Workflows for Collaborative Neuroscience

INCF

This course contains videos, lectures, and hands-on tutorials as part of INCF's Neuroinformatics Assembly 2023 workshop on developing robust and reproducible research workflows to foster greater collaborative efforts in neuroscience.

 

Reproducible Science (Including Git, Docker, and Binder)

Krembil Centre for Neuroinformatics

This course consists of two workshops which focus on the need for reproducibility in science, particularly under the umbrella roadmap of FAIR scienctific principles. The tutorials also provide an introduction to some of the most commonly used open-source scientific tools, including Git, GitHub, Google Colab, Binder, Docker, and the programming languages Python and R. 

 

INCF Assembly 2022 - Training Day 2

INCF

This course contains sessions from the second day of INCF's Neuroinformatics Assembly 2022.

 
INCF TrainingSpace

Session 9: Event Annotation in Neuroimaging Using HED: From Experiment to Analysis

INCF

This workshop delves into the need for, structure of, tools for, and use of hierarchical event descriptor (HED) annotation to prepare neuroimaging time series data for storing, sharing, and advanced analysis. HED are a controlled vocabulary of terms describing events in a machine-actionable form so that algorithms can use the information without manual recoding.

 

Digital Health for Mental Health

Krembil Centre for Neuroinformatics

As technological improvements continue to facilitate innovations in the mental health space, researchers and clinicians are faced with novel opportunities and challenges regarding study design, diagnoses, treatments, and follow-up care. This course includes a lecture outlining these new developments, as well as a workshop which introduces users to Synapse, an open-source platform for collaborative data analysis.