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Computational Neuroscience and Neuroengineering (Jablonski)

Understanding how the nervous system works is a key question studied for decades. Despite many efforts it is challenging to investigate all these processes in in vivo or in vitro experiments. For this reason and for example to help with development of neuroprostheses, in silico approaches are desired which we employ in our group. Up to now, the electrical cochlear implant (eCI) is the most successful neuroprosthesis restoring hearing to around one million people worldwide. Despite that, hearing rehabilitation with eCIs is far from normal hearing due to limited spectral resolution. This limitation is set by a spread of electrical excitation from each electrical contact inside a cochlea that is filled with a conductive fluid leading to channel interaction. Although most of eCI users achieve fair open-set speech perception in quiet, performance in complex listening tasks (for example speech recognition in noisy and/or reverberant environments) and music appreciation may be limited. This makes optogenetic cochlear implant (oCI) a candidate to overcome spectral resolution limitation with the use of light that can be confined in space allowing for a greater number of non-interacting channels.

Currently the group focusses on investigating how the auditory system works with an emphasis on the periphery in order to develop next generation oCIs on a hardware and a software level. On a software level, it involves establishment of novel sound coding strategies that transfer sound into a stimulation of spiral ganglion neurons to enable hearing in deaf. An optical sound coding strategy that capitalizes on the new stimulation modality requires fine-grained, fast, and power-efficient real-time sound processing and control of multiple microscale optical emitters. Such algorithm in case of eCI would be tested in human patients. However, as a non-clinical concept oCI testing requires an in silico framework. For that we develop computational models constrained by experimental data obtained from close collaboration within the Institute for Auditory Neuroscience.

Selected Publications

  • En route to sound coding strategies for optical cochlear implants

    iScience, 2023, 26(10):107725 - DOI -
  • Model-based prediction of optogenetic sound encoding in the human cochlea by future optical cochlear implants

    CSBJ, 2022, 20:3621-3629 - DOI -
All Publications

Dr. Lukasz Jablonski Group Leader Auditory Neuroscience


Lakshay Khurana Scientist Auditory Neuroscience