This module covers how neurotechnology is perceived in media today. We discuss a few specific films and talk about how the perception of neurotechnology changes with our media. Finally, we introduce a few interesting terms related to ethics and address some future issues the technology may cause.
What will happen to the mind and our personalities when we start modifying our brains and bodies with technology? What is the mind and how should we think about it? What is a cyborg and what makes them human? Where is the line between these? This video invites us to think about what the future of consciousness might look like.
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 aims to define computational neuroscience in general terms, while providing specific examples of highly successful computational neuroscience projects.
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.
This lesson delves into the specifics of how action potentials propagate through individual neurons.
This lesson discusses long-range inhibitory connections in the brain, with examples from three different systems.
An introduction to data management, manipulation, visualization, and analysis for neuroscience. Students will learn scientific programming in Python, and use this to work with example data from areas such as cognitive-behavioral research, single-cell recording, EEG, and structural and functional MRI. Basic signal processing techniques including filtering are covered. The course includes a Jupyter Notebook and video tutorials.