This lecture talks about the usage of knowledge graphs in hospitals and related challenges of semantic interoperability.
The state of the field regarding the diagnosis and treatment of major depressive disorder (MDD) is discussed. Current challenges and opportunities facing the research and clinical communities are outlined, including appropriate quantitative and qualitative analyses of the heterogeneity of biological, social, and psychiatric factors which may contribute to MDD.
This lesson gives a description of the BrainHealth Databank, a repository of many types of health-related data, whose aim is to accelerate research, improve care, and to help better understand and diagnose mental illness, as well as develop new treatments and prevention strategies.
This lesson corresponds to slides 46-78 of the PDF below.
This lesson describes not only the need for precision medicine, but also the current state of the methods, pharmacogenetic approaches, utility and implementation of such care today.
This lesson corresponds to slides 1-50 of the PowerPoint below.
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.
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.
This lecture covers the history of behaviorism and the ultimate challenge to behaviorism.
In this lesson, you will learn how to utilize various features and tools included in the EBRAINS platform, particularly focusing on rodent brain atlases and how to incorporate them into your analyses.
This talk describes how to use DataLad for your data management and curation techniques when dealing with animal datasets, which often contain several disparate types of data, including MRI, microscopy, histology, electrocorticography, and behavioral measurements.
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 lesson, you will learn about the connectome, the collective system of neural pathways in an organism, with a closer look at the neurons, synapses, and connections of particular species.
This lesson introduces the practical exercises which accompany the previous lessons on animal and human connectomes in the brain and nervous system.
In this lecture, attendees will learn how Mutant Mouse Resource and Research Center (MMRRC) archives, cryopreserves, and distributes scientifically valuable genetically engineered mouse strains and mouse ES cell lines for the genetics and biomedical research community.
This lecture discusses how to standardize electrophysiology data organization to move towards being more FAIR.
This lecture covers the emergence of cognitive science after the Second World War as an interdisciplinary field for studying the mind, with influences from anthropology, cybernetics, and artificial intelligence.