There is a growing recognition and adoption of open and FAIR science practices in neuroscience research. This is predominately regarded as scientific progress and has enabled significant opportunities for large, collaborative, team science. The efforts and practical work that go into creating an open and FAIR landscape extend far beyond just the science.

This course, consisting of one lecture and two workshops, is presented by the Computational Genomics Lab at the Centre for Addiction and Mental Health and University of Toronto. The lecture deals with single-cell and bulk level transciptomics, while the two hands-on workshops introduce users to transcriptomic data types (e.g., RNAseq) and how to perform analyses in specific use cases (e.g., cellular changes in major depression). 

This course consists of a three-part session from the second day of INCF's Neuroinformatics Assembly 2023. The lessons describe various on-going efforts within the fields of neuroinformatics and clinical neuroscience to adjust to the increasingly vast volumes of brain data being collected and stored.

Sessions from the INCF Neuroinformatics Assembly 2022 day 2. 

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In this course, you will learn how computational neuroscientists use mathematical models and computer simulations to study different plasticity phenomena in the brain. During the course, you will program your own neuron model, a so-called leaky-integrate-and-fire (LIF) neuron model, and simulate it with a computer. You will also learn how to add various neuronal properties and plasticity mechanisms to the model and study how they operate.

The Neurodata Without Borders: Neurophysiology project (NWB, https://www.nwb.org/) is an effort to standardize the description and storage of neurophysiology data and metadata. NWB enables data sharing and reuse and reduces the energy-barrier to applying data analytics both within and across labs. Several laboratories, including the Allen Institute for Brain Science, have wholeheartedly adopted NWB.

These courses give introductions and overviews of some of the major statistics software packages currently used in neuroscience research.

A virtual workshop with lectures and hands-on tutorials that will teach participants how to use open-source Miniscopes for in vivo calcium imaging. This workshop is designed to introduce all aspects of using Miniscopes, including basic principles of Miniscope design and imaging, how to build and attach a Miniscope, how to implant a GRIN lens for imaging deep structures, and how to analyze imaging data.

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

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. 

Future computing systems will capitalize on our increased understanding of the brain through the use of similar architectures and computational principles. During this workshop, we bring together recent developments in this rapidly developing field of neuromorphic computing systems, and also discuss challenges ahead.

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.

Sessions from the INCF Neuroinformatics Assembly 2022 Day 3. 

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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.

This course, consisting of one lecture and two workshops, is presented by the Computational Genomics Lab at the Centre for Addiction and Mental Health and University of Toronto. The lecture deals with single-cell and bulk level transciptomics, while the two hands-on workshops introduce users to transcriptomic data types (e.g., RNAseq) and how to perform analyses in specific use cases (e.g., cellular changes in major depression). 

Sessions from the INCF Neuroinformatics Assembly 2022 day 1. 

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Presented by the Neuroscience Information Framework (NIF), this series consists of several lectures characterizing cutting-edge, open-source software platforms and computational tools for neuroscientists. This course offers detailed descriptions of various neuroinformatic resources such as cloud-computing services, web-based annotation tools, genome browsers, and platforms for designing and building biophysically detailed models of neurons and neural ensembles.

This introductory-level course provide learners with an introduction to the field of neuroethics and spans the ethics of neuroscience to the neuroscience of ethics. The ethics of neuroscience lectures cover the ethical issues that arise in device/drug enhancement, imaging/monitoring, and social uses of neuroscience in the legal/justice system. The neuroscience of ethics lectures cover the origin of ethics (neural mechanisms and evolutionary origin).

This couse is the opening module for the University of Toronto's Krembil Centre for Neuroinformatics' virtual learning series Solving Problems in Mental Health Using Multi-Scale Computational Neuroscience. Lessons in this course introduce participants to the study of brain disorders, starting from elemental units like genes and neurons, eventually building up to whole-brain modelling and global activity patterns.

Given the extreme interconnectedness of the human brain, studying any one cerebral area in isolation may lead to spurious results or incomplete, if not problematic, interpretations. This course introduces participants to the various spatial scales of neuroscience and the fundamentals of whole-brain modelling, used to generate a more thorough picture of brain activity.