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 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.
This lecture covers the history of behaviorism and the ultimate challenge to behaviorism.
This lecture covers various learning theories.
This lesson characterizes different types of learning in a neuroscientific and cellular context, and various models employed by researchers to investigate the mechanisms involved.
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.
How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.
This tutorial introduces pipelines and methods to compute brain connectomes from fMRI data. With corresponding code and repositories, participants can follow along and learn how to programmatically preprocess, curate, and analyze functional and structural brain data to produce connectivity matrices.
In this lightning talk, you will learn about BrainGlobe, an initiative which exists to facilitate the development of interoperable Python-based tools for computational neuroanatomy.
In this short talk you will learn about The Neural System Laboratory, which aims to develop and implement new technologies for analysis of brain architecture, connectivity, and brain-wide gene and molecular level organization.
In this lecture, you will learn about current methods, approaches, and challenges to studying human neuroanatomy, particularly through the lense of neuroimaging data such as fMRI and diffusion tensor imaging (DTI).
This video demonstrates each required step for preprocessing T1w anatomical data in brainlife.io.
This lesson delves into the human nervous system and the immense cellular, connectomic, and functional sophistication therein.