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

Difficulty level: Intermediate
Duration: 47:00
Speaker: : Dimitri Yatsenko

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

Difficulty level: Beginner
Duration: 9:52
Speaker: : Randy McIntosh

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

Difficulty level: Beginner
Duration: 19:06
Speaker: : Kelly Shen

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

Difficulty level: Beginner
Duration: 18:13
Speaker: : Mojib Javadi

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.

Difficulty level: Beginner
Duration: 15:05
Speaker: : Jordan Antflick

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

Difficulty level: Beginner
Duration: 12:57

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

Difficulty level: Beginner
Duration:
Speaker: : Helena Ledmyr

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.

Difficulty level: Beginner
Duration: 54:38
Speaker: :

This lecture gives an introduction to the types of glial cells, homeostasis (influence of cerebral blood flow and influence on neurons), insulation and protection of axons (myelin sheath; nodes of Ranvier), microglia and reactions of the CNS to injury.

Difficulty level: Beginner
Duration: 40:32

This lecture covers the history of behaviorism and the ultimate challenge to behaviorism. 

Difficulty level: Beginner
Duration: 1:19:08

This lecture covers various learning theories.

Difficulty level: Beginner
Duration: 1:00:42

This lesson characterizes different types of learning in a neuroscientific and cellular context, and various models employed by researchers to investigate the mechanisms involved. 

Difficulty level: Intermediate
Duration: 3:54
Speaker: : Dan Goodman

In this lesson, you will learn about different approaches to modeling learning in neural networks, particularly focusing on system parameters such as firing rates and synaptic weights impact a network. 

Difficulty level: Intermediate
Duration: 9:40
Speaker: : Dan Goodman

How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.

Difficulty level: Beginner
Duration: 1:08:45
Speaker: : Clay Reid

This lesson contains both a lecture and a tutorial component. The lecture (0:00-20:03 of YouTube video) discusses both the need for intersectional approaches in healthcare as well as the impact of neglecting intersectionality in patient populations. The lecture is followed by a practical tutorial in both Python and R on how to assess intersectional bias in datasets. Links to relevant code and data are found below. 

Difficulty level: Beginner
Duration: 52:26

This is an introductory lecture on whole-brain modelling, delving into the various spatial scales of neuroscience, neural population models, and whole-brain modelling. Additionally, the clinical applications of building and testing such models are characterized. 

Difficulty level: Intermediate
Duration: 1:24:44
Speaker: : John Griffiths

This is a tutorial on designing a Bayesian inference model to map belief trajectories, with emphasis on gaining familiarity with Hierarchical Gaussian Filters (HGFs).

 

This lesson corresponds to slides 65-90 of the PDF below. 

Difficulty level: Intermediate
Duration: 1:15:04
Speaker: : Daniel Hauke

This lecture discusses what defines an integrative approach regarding research and methods, including various study designs and models which are appropriate choices when attempting to bridge data domains; a necessity when whole-person modelling. 

Difficulty level: Beginner
Duration: 1:28:14
Speaker: : Dan Felsky

Similarity Network Fusion (SNF) is a computational method for data integration across various kinds of measurements, aimed at taking advantage of the common as well as complementary information in different data types. This workshop walks participants through running SNF on EEG and genomic data using RStudio.

Difficulty level: Intermediate
Duration: 1:21:38
Speaker: : Dan Felsky

In this lesson, you will learn about one particular aspect of decision making: reaction times. In other words, how long does it take to take a decision based on a stream of information arriving continuously over time?

Difficulty level: Intermediate
Duration: 6:01
Speaker: : Dan Goodman