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

This lesson provides an introduction to the Symposium on Science Management at the Canadian Association for Neuroscience 2019 Meeting.

This lesson gives a primer to project management in a scientific context, with a particular neuroinformatic case study. 

In this lesson, you will hear about the current challenges regarding data management, as well as policies and resources aimed to address them. 

This lesson covers "Knowledge Translation", the activities involved in moving research from the laboratory, the research journal, and the academic conference into the hands of people and organizations who can put it to practical use.

In this lesson, you will hear about the various methods developed and employed in managing performance. 

This lesson provides an overview of how to manage relationships in a research context, while highlighting the need for effective communication at various levels.

In this lesson you will hear a panel discussion which hosts experts in the field whom have extensive experience with management in a science setting.

This is a tutorial on how to simulate neuronal spiking in brain microcircuit models, as well as how to analyze, plot, and visualize the corresponding data. 

This video will document the process of running an app on brainlife, from data staging to archiving of the final data outputs.

This quick video presents some of the various visualizers available on brainlife.io

This short video shows how a brainlife.io publication can be opened from the Data Deposition page of the journal Nature Scientific Data.

An introduction to data management, manipulation, visualization, and analysis for neuroscience. Students will learn scientific programming in Python, and use this to work with example data from areas such as cognitive-behavioral research, single-cell recording, EEG, and structural and functional MRI. Basic signal processing techniques including filtering are covered. The course includes a Jupyter Notebook and video tutorials.

This lecture covers visualizing extracellular neurotransmitter dynamics