Neuro2023BMIサテライト企画＠仙台

The Chen lab develops high-channel-count, chronically implantable devices to record from and stimulate the brain. We harness cutting-edge developments in electrode fabrication and microelectronics to improve probe durability and biocompatibility, generating fundamental neuroscientific knowledge and translating results from the lab to the clinic. Our applications include the restoration of life-enhancing vision in the blind. Blindness affects 40 million people worldwide, with a wide variety of causes, including injury to or degeneration of the retina and optic nerve. Brain implants interface directly with visual regions in the brain, bypassing the retina and optic nerve to produce artificially generated percepts without input from the eye. We use devices with >1000 channels to interface with large areas of the visual cortex, delivering tiny electrical currents to elicit the perception of dots of light (known as ‘phosphenes’). We deliver stimulation across multiple electrodes simultaneously, inducing percepts composed of multiple phosphenes, and causing our subjects to see movement, and simple shapes such as letters.

His current research field is decoding speech from neural activity to restore communication to patients with paralysis. With his team, he demonstrated that speech could be decoded from the neural activity of a person with paralysis who had not spoken in over 15 years. This work was featured on the front page of the New York Times. Since then he has worked to improve the accuracy and expressivity possible with these derides. (Metzger et al., Nat. Comm. 2022)

Her lab’s main focus is the development of Brain-Machine Interfaces for people suffering from tetraplegia due to spinal cord injuries, strokes or diseases. Researched how grasp, speech and internal speech are represented in individual neurons in the posterior parietal cortex (supramarginal gyrus and anterior intraparietal cortex), ventral premotor cortex, motor cortex, and somatosensory cortex. Evaluated their suitability for BMI applications using chronically implantable microelectrode arrays. Built the first internal speech Brain-Machine interface. （Wandelt et al., Neuron, 2022）