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 provides an introductory overview of some of the most important concepts in software engineering.
In this lesson, you will learn in more detail about neuromorphic computing, that is, non-standard computational architectures that mimic some aspect of the way the brain works.
This video provides a very quick introduction to some of the neuromorphic sensing devices, and how they offer unique, low-power applications.
This talk describes the NIH-funded SPARC Data Structure, and how this project navigates ontology development while keeping in mind the FAIR science principles.
This lesson provides an overview of the current status in the field of neuroscientific ontologies, presenting examples of data organization and standards, particularly from neuroimaging and electrophysiology.
This lesson continues from part one of the lecture Ontologies, Databases, and Standards, diving deeper into a description of ontologies and knowledg graphs.
This lecture covers structured data, databases, federating neuroscience-relevant databases, and ontologies.
This lecture covers FAIR atlases, including their background and construction, as well as how they can be created in line with the FAIR principles.
This lecture focuses on ontologies for clinical neurosciences.
While the previous lesson in the Neuro4ML course dealt with the mechanisms involved in individual synapses, this lesson discusses how synapses and their neurons' firing patterns may change over time.
In this lesson, you will learn about how machine learners and computational neuroscientists design and build models of neuronal synapses.
How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.