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Lecture

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In course

NX-422: Neural interfaces

Neural interfaces (NI) are bioelectronic systems that interface the nervous system to digital technologies. This course presents their main building blocks (transducers, instrumentation & communication), reviews current and upcoming materials and technolog ...

Instructors (2)

Stéphanie Lacour

Stéphanie P. Lacour holds the Bertarelli Foundation Chair in Neuroprosthetic Technology in the School of Engineering at EPFL and leads the Laboratory for Soft Bioelectronic Interfaces. She received her PhD in Electrical Engineering from INSA de Lyon, France, and completed postdoctoral research at Princeton University and the University of Cambridge. She is the recipient of the 2006 MIT TR35, a University Research Fellowship of the Royal Society, European Research Council ERC Starting and POC Grants, and a SNSF-ERC Consolidator Grant. She was elected a 2015 Young Global Leader by the World Economic Forum.

Mahsa Shoaran

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Related concepts (2)

Artificial neural network

Artificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.

Neural oscillation

Neural oscillations, or brainwaves, are rhythmic or repetitive patterns of neural activity in the central nervous system. Neural tissue can generate oscillatory activity in many ways, driven either by mechanisms within individual neurons or by interactions between neurons. In individual neurons, oscillations can appear either as oscillations in membrane potential or as rhythmic patterns of action potentials, which then produce oscillatory activation of post-synaptic neurons.