brain machine interfaces
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Feedback control in the nervous system: from cells and circuits to behaviour
The nervous system is fundamentally a closed loop control device: the output of actions continually influences the internal state and subsequent actions. This is true at the single cell and even the molecular level, where “actions” take the form of signals that are fed back to achieve a variety of functions, including homeostasis, excitability and various kinds of multistability that allow switching and storage of memory. It is also true at the behavioural level, where an animal’s motor actions directly influence sensory input on short timescales, and higher level information about goals and intended actions are continually updated on the basis of current and past actions. Studying the brain in a closed loop setting requires a multidisciplinary approach, leveraging engineering and theory as well as advances in measuring and manipulating the nervous system. I will describe our recent attempts to achieve this fusion of approaches at multiple levels in the nervous system, from synaptic signalling to closed loop brain machine interfaces.
Genetic-based brain machine interfaces for visual restoration
Visual restoration is certainly the greatest challenge for brain-machine interfaces with the high pixel number and high refreshing rate. In the recent year, we brought retinal prostheses and optogenetic therapy up to successful clinical trials. Concerning visual restoration at the cortical level, prostheses have shown efficacy for limited periods of time and limited pixel numbers. We are investigating the potential of sonogenetics to develop a non-contact brain machine interface allowing long-lasting activation of the visual cortex. The presentation will introduce our genetic-based brain machine interfaces for visual restoration at the retinal and cortical levels.
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Explore how brain machine interfaces research is advancing inside Neuro.
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