Lecture

Neural Signals and Signal Processing: Modeling and Simulation

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In course

NX-421: Neural signals and signal processing

Understanding, processing, and analysis of signals and images obtained from the central and peripheral nervous system ...

Description

This lecture covers the fundamentals of neural signals and signal processing, focusing on the modeling and simulation of neural systems. Topics include the importance of modeling, types of models, neural structures, and the organization of the cortex. The lecture also delves into the classification of nerve fibers, neuron morphology, and the spinal cord's structure. Furthermore, it explores the generation of physiological signals, action potential propagation, and the use of hybrid models in neuroengineering.

Instructors (2)

Dimitri Nestor Alice Van De Ville

Expertise Brain and spinal cord imaging, signal and image processing, network science, dynamic systems Teaching & PhD PhD Students Alexandre Cionca, Chun Hei Michael Chan, Flavia Petruso, Bassam El Rawas, Nikolaos Molochidis, Christophe Pascal Jérémie Chênes, Fabrice Jean Guibert, Alessio Siviglia, Ekansh Sareen, Beatrice Lugli Past EPFL PhD Students Djano Kandaswamy, Fikret Isik Karahanoglu, Nora Leonardi, Zafer Dogan, Jeffrey Adam Kasten, Naghmeh Ghazaleh, Rotem Roza Kopel, Daniela Maria Zöller, Thomas

Silvestro Micera

Short biographical sketch Silvestro Micera received the University degree (Laurea) in Electrical Engineering from the University of Pisa, in 1996, and the Ph.D. degree in Biomedical Engineering from the Scuola Superiore Sant'Anna, in 2000. From 2000 to 2009, he has been an Assistant Professor of BioRobotics at the Scuola Superiore Sant'Anna where he is now the Head of the Neural Engineering group. In 2007 he was a Visiting Scientist at the Massachusetts Institute of Technology, Cambridge, USA with a Fulbri

Official source

Ontological neighbourhood

Biology

Neuroscience: Computational neuroscience

Cell biology: Neurotransmission

Anatomy: Neuroanatomy

Related concepts (32)

Action potential

An action potential occurs when the membrane potential of a specific cell rapidly rises and falls. This depolarization then causes adjacent locations to similarly depolarize. Action potentials occur in several types of animal cells, called excitable cells, which include neurons, muscle cells, and in some plant cells. Certain endocrine cells such as pancreatic beta cells, and certain cells of the anterior pituitary gland are also excitable cells.

Taskbar

The Taskbar is a graphical user interface element that has been part of Microsoft Windows since Windows 95, displaying and facilitating switching between running programs. The Taskbar and the associated Start Menu were created and named in 1993 by Daniel Oran, a program manager at Microsoft who had previously collaborated on Great ape language research with the behavioral psychologist B.F. Skinner at Harvard. The Taskbar is an exemplar of a category of always-visible graphical user interface elements that provide access to fundamental operating system functions and information.

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The Windows shell is the graphical user interface for the Microsoft Windows operating system. Its readily identifiable elements consist of the desktop, the taskbar, the Start menu, the task switcher and the AutoPlay feature. On some versions of Windows, it also includes Flip 3D and the charms. In Windows 10, the Windows Shell Experience Host interface drives visuals like the Start Menu, Action Center, Taskbar, and Task View/Timeline.

Neural coding

Neural coding (or neural representation) is a neuroscience field concerned with characterising the hypothetical relationship between the stimulus and the individual or ensemble neuronal responses and the relationship among the electrical activity of the neurons in the ensemble. Based on the theory that sensory and other information is represented in the brain by networks of neurons, it is thought that neurons can encode both digital and analog information.

Models of neural computation

Models of neural computation are attempts to elucidate, in an abstract and mathematical fashion, the core principles that underlie information processing in biological nervous systems, or functional components thereof. This article aims to provide an overview of the most definitive models of neuro-biological computation as well as the tools commonly used to construct and analyze them.

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