Introduction to Neural Networks - Day 10 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Introduction to Convolutional Neural Networks - Day 11 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Initialization, Optimization, and Regularization - Day 12 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
U-Nets for medical Image-Segmentation - Day 13 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
Sequence Processing - Day 15 lecture of the Foundations of Machine Learning in Python course.
High-Performance Computing and Analytics Lab, University of Bonn
This lecture gives an introduction to the INCF Short Course: Introduction to Neuroinformatics.
Presented by the OHBM OpenScienceSIG, this lesson covers how containers can be useful for running the same software on different platforms and sharing analysis pipelines with other researchers.
This lesson breaks down the principles of Bayesian inference and how it relates to cognitive processes and functions like learning and perception. It is then explained how cognitive models can be built using Bayesian statistics in order to investigate how our brains interface with their environment.
This lesson corresponds to slides 1-64 in the PDF below.
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.
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 lecture provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.
This lesson is part 1 of 2 of a tutorial on statistical models for neural data.
What is the difference between attention and consciousness? This lecture describes the scientific meaning of consciousness, journeys on the search for neural correlates of visual consciousness, and explores the possibility of consciousness in other beings and even non-biological structures.
This talk gives an overview of the Human Brain Project, a 10-year endeavour putting in place a cutting-edge research infrastructure that will allow scientific and industrial researchers to advance our knowledge in the fields of neuroscience, computing, and brain-related medicine.
This lecture gives an introduction to the European Academy of Neurology, its recent achievements and ambitions.
This talk enumerates the challenges regarding data accessibility and reusability inherent in the current scientific publication system, and discusses novel approaches to these challenges, such as the EBRAINS Live Papers platform.
This lesson covers membrane potential of neurons, and how parameters around this potential have direct consequences on cellular communication at both the individual and population level.
In this lesson you will learn about neurons' ability to generate signals called action potentials, and biophysics of voltage-gated ion channels.
This lesson discusses voltage-gating kinetics of sodium and potassium channels.
In this lesson, you will learn about the ionic basis of the action potential, including the Hodgkin-Huxley model.