"Neural Engineering: Restoring, Replacing, and…" Dr. Moritz Grosse-Wentrup (NEUROTECHNIX 2017)
Title: Neural Engineering: Restoring, Replacing, and Extending Cognition
Keynote Lecturer: Moritz Grosse-Wentrup
Presented on: 31/10/2017, Funchal, Madeira, Portugal
Abstract: Neural engineering restores, replaces, or extends cognitive functions by establishing bi-directional interfaces to the brain. These interfaces require sensors to record neural activity, machine learning algorithms to decode cognitive states from neural signals in real-time, and actuators to steer neural activity towards desired target states. In this talk, I give an overview of the primary challenges for neural engineering and highlight solutions developed in my group. On the algorithmic side, I focus on two key problems: How can we build brain decoding models that generalise across heterogeneous subjects, and how can we use these models to predict how neural activity should be altered, e.g., by transcranial electrical stimulation, to achieve a desired cognitive state? On the hardware side, I present a low-cost system that enables high-quality EEG recordings outside of laboratory environments, and introduce a brain-robot interface that combines real-time brain decoding with haptic feedback. I demonstrate the impact of our work on two translational projects in the domain of personalisedmedicine: A brain-computer interface for communication with severely paralysed patients in late-stages of amyotrophic lateral sclerosis, and a brain-robot interface for post-stroke motor rehabilitation. I conclude by outlining my vision for translating neural engineering into everyday applications that benefit patient populations as well as healthy users.
Event's Website: http://www.neurotechnix.org/
Presented at the following Event: NEUROTECHNIX, 5th International Congress on Neurotechnology, Electronics and Informatics
Title: Neural Engineering: Restoring, Replacing, and Extending Cognition
Keynote Lecturer: Moritz Grosse-Wentrup
Presented on: 31/10/2017, Funchal, Madeira, Portugal
Abstract: Neural engineering restores, replaces, or extends cognitive functions by establishing bi-directional interfaces to the brain. These interfaces require sensors to record neural activity, machine learning algorithms to decode cognitive states from neural signals in real-time, and actuators to steer neural activity towards desired target states. In this talk, I give an overview of the primary challenges for neural engineering and highlight solutions developed in my group. On the algorithmic side, I focus on two key problems: How can we build brain decoding models that generalise across heterogeneous subjects, and how can we use these models to predict how neural activity should be altered, e.g., by transcranial electrical stimulation, to achieve a desired cognitive state? On the hardware side, I present a low-cost system that enables high-quality EEG recordings outside of laboratory environments, and introduce a brain-robot interface that combines real-time brain decoding with haptic feedback. I demonstrate the impact of our work on two translational projects in the domain of personalisedmedicine: A brain-computer interface for communication with severely paralysed patients in late-stages of amyotrophic lateral sclerosis, and a brain-robot interface for post-stroke motor rehabilitation. I conclude by outlining my vision for translating neural engineering into everyday applications that benefit patient populations as well as healthy users.
Event’s Website: http://www.neurotechnix.org/
Presented at the following Event: NEUROTECHNIX, 5th International Congress on Neurotechnology, Electronics and Informatics
