This short talk addresses how to use VisuAlign to make nonlinear adjustments to 2D-to-3D registrations generated by QuickNII.
This talk aims to provide guidance regarding the myriad labelling methods for histological image data.
This lesson provides a cross-species comparison of neuron types in the rat and mouse brain.
This lecture concludes the course with an outline of future directions of the field of neuroscientific research data integration.
This lecture provides an introduction to the application of genetic testing in neurodevelopmental disorders.
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.
This lecture provides an introduction to Plato’s concept of rationality and Aristotle’s concept of empiricism, and the enduring discussion between rationalism and empiricism to this day.
This lecture covers different perspectives on the study of the mental, focusing on the difference between Mind and Brain.
This lecture covers the three big questions: What is the universe?, what is life?, and what is consciousness?
This lecture covers the history of behaviorism and the ultimate challenge to behaviorism.
This lecture covers various learning theories.
This lecture covers a lot of post-war developments in the science of the mind, focusing first on the cognitive revolution, and concluding with living machines.
This talk describes the relevance and power of using brain atlases as part of one's data integration pipeline.
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 brief talk goes into work being done at The Alan Turing Institute to solve real-world challenges and democratize computer vision methods to support interdisciplinary and international researchers.
This talk gives a brief overview of current efforts to collect and share the Brain Reference Architecture (BRA) data involved in the construction of a whole-brain architecture that assigns functions to major brain organs.
This lesson aims to define computational neuroscience in general terms, while providing specific examples of highly successful computational neuroscience projects.
This lecture gives an introduction to simulation, models, and the neural simulation tool NEST.
This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.
In this lesson, you will learn about how genetics can contribute to our understanding of psychiatric phenotypes.