Cochlear implants are the first and currently most successful sensory rehabilitation strategy, and equip thousands of hearing impaired patients. However, they suffer from strong information throughput limitations, making music perception and speech intelligibility in noise impossible, extremely detrimental to implanted patients. In this project, we propose to establish a clear proof of concept for a radically new auditory rehabilitation strategy by direct stimulation of the main sound processing center in the brain, the auditory cortex. The auditory cortex not only offers one order of magnitude more interfacing surface, to boost information throughput, but it is also a plastic structure, adaptable to complex auditory codes, which could benefit from acoustic information preprocessing by modern artificial intelligence algorithms. To demonstrate that cortical implants are feasible and outperform cochlear implants, artificial sound perceptions will be optogenetically generated via an LED display placed over the full extent of auditory cortex in behaving mice. Perceptual precision for a wide range of acoustic features will be precisely benchmarked against cochlear implant thanks to a range of psychophysical assays available in this animal model. The benefits of sound preprocessing by machine learning algorithms (deep learning networks) will be tested, and we will develop a new generation of ultrathin, flexible, biocompatible LED displays, that could be placed on the convoluted surface of human auditory cortex to activate precise and rich perceptions. Together, these brain-interfacing and bioelectronics innovations will enable a new implant strategy in that promises to be a major changer for hearing restoration quality in deaf patients, and pave the way for improvement of other sensory restoration strategies.
