Neuromorphic Organic Devices as Building Blocks for Neuroelectronics

Organic electronic neuromorphic components and devices operated in electrolyte are being investigated as powerful tools for bio-sensing, since their response is quantitatively determined by the composition of operational electrolyte,¹ or as signal processing units, thanks to their selective response to frequency which enables low-power computation at the hardware level.^2,3<br/>Given the inherent match between the timescales, the chemical identity of the charge carriers and the signal processing logic paradigms in the brain and in organic neuromorphic devices, the latter are - ideally - the natural choice when tackling the convoluted task of efficiently interfacing neural tissue, establishing bidirectional exchange of information. Nonetheless, the implementation of neuromorphic devices and concepts in neuroelectronic interfaces designed specifically for clinical applications comes with a number of practical and conceptual hurdles which should be addressed, from both sides of the biotic/abiotic interface.<br/>Scope of this presentation is to discuss some of these critical issues, which have so far impaired translation of neuromorphism in clinical scenarios, and to present strategies for overcoming them, with a focus on connection schemes and characterization strategies as well as on device geometry and material processing, hoping to trace a useful <i>vademecum</i> for Organic Neuromorphic Neuroelectronics development.<br/> <br/> <br/><b>References</b><br/> <br/>Giordani M, Sensi M, Berto M, et al. Neuromorphic Organic Devices that Specifically Discriminate Dopamine from Its Metabolites by Nonspecific Interactions. <i>Adv Funct Mater</i>. 2020;30(28):1-13. doi:10.1002/adfm.202002141<br/>De Salvo A, Rondelli F, Di Lauro M <i>et al.</i> <i>Organic electronics circuitry for in situ real-time processing of electrophysiological signals</i>. https://www.researchsquare.com/article/rs-2775813/v1 (2023) doi:10.21203/rs.3.rs-2775813/v1.<br/>Keene, S. T., Gkoupidenis, P. & Burgt, Y. van de. Neuromorphic computing systems based on flexible organic electronics. in <i>Organic Flexible Electronics</i> 531–574 (Elsevier, 2021). doi:10.1016/B978-0-12-818890-3.00018-7.