Topic: auditory nerve

The auditory nerve encodes sound with spike-timing that is phase locked to the fine-grained temporal structure of sound. The precision of this coding substantially exceeds that of any other sensory modality, but its role in hearing remains controversial because physiological mechanisms for extracting information from the spike timing have proven elusive. We investigated the perceptual role of auditory nerve phase locking using deep artificial neural networks in the spirit of ideal observer analysis. Neural networks took input from a simulated cochlea and were optimized for natural tasks. We ex

Cochlear implants (CI) are neuroprostheses that restore hearing for deaf humans by delivering patterned pulses of current to the auditory nerve, bypassing the damaged sensory epithelium of the inner ear. Almost all CI users require adaptation periods to attain speech comprehension, which improves most rapidly in the first weeks to 6 months following CI activation [1]. In CI studies of deafened animals, training induces cortical map plasticity in primary auditory cortex (A1) of task-relevant stimuli [2, 3]. It remains unclear whether observed CI training-induced cortical plasticity in animal mo

In cases of profound cochlear dysfunction, electrical cochlear implants (eCIs) offer partial restoration of hearing. Nevertheless, the auditory experience with eCIs remains imperfect due to the broad excitation of auditory nerve neurons by electrical signals that limits the perceptual channels available to users. Optogenetics offers a breakthrough by enabling the stimulation of the auditory nerve by an optical cochlear implant (oCI). Light, unlike electrical signals, can be precisely confined in space, resulting in reduced spread of excitation and improved frequency selectivity. However, optog

Numerous computational models of the cochlea have been developed that faithfully capture the transformation of incoming sound into basilar membrane motion and auditory nerve spike patterns, with widespread uptake across academia and industry. Models of sensory processing in the brain, however, are generally much less accurate, with even the best failing to explain most of the variance in sub-cortical and cortical neural activity.Here, we used large-scale neural recordings from measurement sites spanning the inferior colliculus (IC) of normal-hearing gerbils to develop a deep learning model of