Biophysical realism in neuromorphic electronics
Although primitive in their form, perceptrons still constitute the predecessor building blocks of contemporary ANNs that enabled a wide range of real-world applications. Nevertheless, it is now well recognized that ANNs based these simple neuronal models still face major challenges in approaching the biological level of intelligence and therefore neuroscience-driven development is essential for revisiting the computational primitives of the brain. Towards this approach, organic devices have shown the potential for biophysical realism in neuromorphic enginnering. As an illustration, biological aspects of homeostasis, functional connectivity and ionic/molecular recognition rise naturally in such neuromorphic devices with inherent sensing capabilities. The activties of this area of research concentrate of the reverse enginnering of information processing finctions, and biological computational primitives by leveraging the properties of organic materials.
D. Koutsouras, T. Prodromakis, G. G. Malliaras, P. W. M. Blom, P. Gkoupidenis, Functional connectivity of organic neuromorphic devices by global voltage oscillations, Adv. Intel. Sys. (2019).
D. A. Koutsouras, G. G. Malliaras, P. Gkoupidenis, Emulating Homeoplasticity Phenomena with Organic Electrochemical Devices, MRS Commun. 8, 493 (2018).
Y. van de Burgt, P. Gkoupidenis, Organic devices for brain-inspired computing: from artificial implementation to biophysical realism, MRS Bullet. 45, 8, 631 (2020).
Y. Tuchman, T. N. Mangoma, P. Gkoupidenis, Y. van De Burgt, R. A. John, N. Mathews, S. E Shaheen, R. Daly, G. G. Malliaras, A. Salleo, Organic neuromorphic devices: Past, present, and future challenges, MRS Bullet. 45, 8, 619 (2020).