Neuroinformatics is a research field concerned with the organization of neuroscience data by the application of computational models and analytical tools. These areas of research are important for the integration and analysis of increasingly large-volume, high-dimensional, and fine-grain experimental data.

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### Lectures

This opening lecture from INCF's Short Course in Neuroinformatics provides an overview of the field of neuroinformatics itself, as well as laying…

This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.

This lecture gives an introduction to simulation, models, and the neural simulation tool NEST.

This lecture covers modeling the neuron in silicon, modeling vision and audition, and sensory fusion using a deep network.

This lecture covers an introduction to connectomics, as well as image processing tools for the study of connectomics.

This lecture covers the description and characterization of an input-output relationship in a information-theoretic context.

This lecture covers structured data, databases, federating neuroscience-relevant databases, and ontologies.

This lecture provides a history of data management, recent developments data management, and a brief description of scientific data management.…

This lecture provides an introductory overview of some of the most important concepts in software engineering.

This lecture focuses on computational complexity, a concept which lies at the heart of computer science thinking. In short, it is a way to quickly…

This lecture will addresses what it means for a problem to have a computable solution, methods for combining computability results to analyse more…

In this lecture, you will learn about current methods, approaches, and challenges to studying human neuroanatomy, particularly through the lense…

This lesson provides a thorough description of neuroimaging development over time, both conceptually and technologically. You will learn about the…

This lesson contains the first part of the lecture *Data Science and Reproducibility*. You will learn about the development of data science…

In this second part of the lecture *Data Science and Reproducibility*, you will learn how to apply the awareness of the intersection…

This lecture aims to help researchers, students, and health care professionals understand the place for neuroinformatics in the patient journey…

This lesson provides an overview of the current status in the field of neuroscientific ontologies, presenting examples of data organization and…

This lesson continues from part one of the lecture *Ontologies, Databases, and Standards*, diving deeper into a description of ontologies…

This lesson aims to define computational neuroscience in general terms, while providing specific examples of highly successful computational…

In this lesson, you will learn how to understand data management plans and why data sharing is important.

This lecture gives a tour of what neuroethics is and how it applies to neuroscience and neurotechnology, while also addressing justice concerns…

This lecture covers a wide range of aspects regarding neuroinformatics and data governance, describing both their historical developments and…

This lesson gives an in-depth description of scientific workflows, from study inception and planning to dissemination of results.

This lecture describes how to build research workflows, including a demonstrate using DataJoint Elements to build data pipelines.

In this final lecture of the *INCF Short Course: Introduction to Neuroinformatics*, you will hear about new advances in the application of…

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### Courses

The emergence of data-intensive science creates a demand for neuroscience educators worldwide to deliver better neuroinformatics education and…

“Computational Thinking“ refers to a mindset or set of tools used by computational or ICT specialists to describe their work. This course is…

Future computing systems will capitalize on our increased understanding of the brain through the use of similar architectures and computational…

Most who enter the field of computational neuroscience have a prior background in either mathematics, physics, computer science, or (neuro)biology…

Data science relies on several important aspects of mathematics. In this course, you'll learn what forms of mathematics are most useful for data…

Presented by the Neuroscience Information Framework (NIF), this series consists of several lectures characterizing cutting-edge, open-source…