Summary
Understanding and modulating neural networks requires high-resolution acquisition of neural activity over time, real-time analysis, and minimally invasive stimulation methods with high specificity. Such procedures are particularly needed for treatment of sensory disfunction (e.g. hearing loss), and certain neurological diseases (e.g. epilepsy). The lack of soft, biocompatible, hybrid and smart neural interfaces hinders our capacity to study complex neural dynamics and efficiently apply responsive neuro-modulation therapy. Here, the overall objective is to exploit novel ion gated transistors (IGTs) and organic light emitting diodes (OLEDs) to establish the first fully implantable, biocompatible, and soft responsive electro-optical neurostimulation system in an animal model. I hypothesize that organic electronics can create all the required building blocks, from an IGT-based application-specific integrated circuit that will improve the efficiency of neural signal acquisition and permit local processing, to OLED-based optogenetics, through a conformable self-contained package. Such a system will increase signal-to-noise ratio (>25dB), resolution (>1500 interfaces/cm2), and spatial specificity (con-formable OLEDs for optogenetics) compared to existing state-of-the-art neurostimulation devices such as cochlear implants. To achieve that, we will have to design smart fabrication routes that allow the development of both devices into a single front-end probe, overcome stability issues, and create efficient and fast IGTs for both front-end interfaces and circuits. We will do that by tuning materials composition, engineering improved designs and better understand the mechanisms of interaction with the physiological environment. This research will enable a new generation of neural interfaces and a deeper understanding of auditory neural networks, and the electro-optical stimulation effects upon them.
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| Web resources: | https://cordis.europa.eu/project/id/101078225 |
| Start date: | 01-11-2023 |
| End date: | 31-10-2028 |
| Total budget - Public funding: | 1 499 213,00 Euro - 1 499 213,00 Euro |
Cordis data
Original description
Understanding and modulating neural networks requires high-resolution acquisition of neural activity over time, real-time analysis, and minimally invasive stimulation methods with high specificity. Such procedures are particularly needed for treatment of sensory disfunction (e.g. hearing loss), and certain neurological diseases (e.g. epilepsy). The lack of soft, biocompatible, hybrid and smart neural interfaces hinders our capacity to study complex neural dynamics and efficiently apply responsive neuro-modulation therapy. Here, the overall objective is to exploit novel ion gated transistors (IGTs) and organic light emitting diodes (OLEDs) to establish the first fully implantable, biocompatible, and soft responsive electro-optical neurostimulation system in an animal model. I hypothesize that organic electronics can create all the required building blocks, from an IGT-based application-specific integrated circuit that will improve the efficiency of neural signal acquisition and permit local processing, to OLED-based optogenetics, through a conformable self-contained package. Such a system will increase signal-to-noise ratio (>25dB), resolution (>1500 interfaces/cm2), and spatial specificity (con-formable OLEDs for optogenetics) compared to existing state-of-the-art neurostimulation devices such as cochlear implants. To achieve that, we will have to design smart fabrication routes that allow the development of both devices into a single front-end probe, overcome stability issues, and create efficient and fast IGTs for both front-end interfaces and circuits. We will do that by tuning materials composition, engineering improved designs and better understand the mechanisms of interaction with the physiological environment. This research will enable a new generation of neural interfaces and a deeper understanding of auditory neural networks, and the electro-optical stimulation effects upon them.Status
SIGNEDCall topic
ERC-2022-STGUpdate Date
31-07-2023
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