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Human-centred physical neuromorphics with visual brain-computer interfaces

Physics

Human-centred physical neuromorphics with visual brain-computer interfaces

G. Wang, G. Marcucci, et al.

This groundbreaking research by Gao Wang, Giulia Marcucci, Benjamin Peters, Maria Chiara Braidotti, Lars Muckli, and Daniele Faccio showcases the ability to transmit images to the brain via steady-state visual evoked potentials (SSVEPs) using advanced frequency division multiplexing techniques. This innovative approach opens avenues for neural interfaces and connectivity between multiple brains, revolutionizing human-machine interaction.

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Playback language: English
Abstract
This paper demonstrates the feasibility of encoding information in steady-state visual evoked potentials (SSVEPs) using high-density frequency division multiplexing (FDM), involving hundreds of frequencies to transmit images to the brain and implement photonic neural networks for classification tasks. The system shows promising scalability by connecting multiple brains in series, opening new possibilities for neural interfaces and human-machine interactions.
Publisher
Nature Communications
Published On
Jul 29, 2024
Authors
Gao Wang, Giulia Marcucci, Benjamin Peters, Maria Chiara Braidotti, Lars Muckli, Daniele Faccio
Tags
information encoding
steady-state visual evoked potentials
frequency division multiplexing
neural interfaces
photonic neural networks
human-machine interaction
classification tasks

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