Dr. Paschalis Gkoupidenis 'Organic neuromorphic electronics'

Harnessing the exceptional efficiency of the brain in information processing at the technological level can be condensed in the terms “artificial intelligence” and “neuromorphic computing”. A popular approach in artificial intelligence is the representation of information processing aspects found in biological systems with artificial neural networks (ANNs). This approach is based on executing algorithms, that loosely represent the function of the nervous system, on traditional computer architectures. Over the last decade, the field of artificial intelligence (AI) has demonstrated an enormous potential for complex processing and efficient computing. However, concepts of AI are mainly based on digital operating principles, while being part of an analogue world with great diversity in signaling. Moreover, AI still lacks the efficiency and computing capacity of biological systems. Alternatively, neural functions can be directly emulated with non-conventional devices, circuits and architectures. This hardware-based paradigm of brain-inspired processing is known as neuromorphic electronics. In this talk, various neuromorphic devices will be presented that are based on organic mixed conductors, materials that are traditionally used in bioelectronics. A prominent example of a device in bioelectronics that exploits mixed ionic-electronic conductivity phenomena is the organic electrochemical transistor (OECT). Organic neuromorphic electronics based on OECTs have the ability to emulate efficiently and with fidelity a wide range of bio-inspired functions including synaptic plasticity and neuronal dynamics. Their operation in common electrolytes permits the definition of spatially distributed multiple inputs at a single device level. The presence of a global electrolyte in an array of devices also allows for the homeostatic or global control of the array. Global electrical oscillations can be used as global clocks that phase-lock the local activity of individual devices in analogy to the global oscillations in the brain. Moreover, “soft” interconnectivity through the electrolyte can be defined, a feature that paves the way for parallel interconnections between devices with minimal hard-wired connections. Finally, practical demonstrations will be shown, highlighting the potential of organic materials in robotics, neuromorphic sensing and biointerfacing.