Functional Connectivity of Organic Neuromorphic Devices by Global Voltage Oscillations. (8th May 2019)

• Record Type: Journal Article
• Authors: Koutsouras, Dimitrios A.; Prodromakis, Themis; Malliaras, George G.; Blom, Paul W. M.; Gkoupidenis, Paschalis
• Is Part Of: Advanced intelligent systems. Volume 1:Number 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-05-08
• Subjects: electrolytes -- functional connectivity -- neuromorphic devices -- organic electrochemical transistors -- PEDOT:PSS; Artificial intelligence -- Periodicals; Robotics -- Periodicals; Control theory -- Periodicals; 006.3
• DOI: 10.1002/aisy.201900013
• Languages: English
• ISSNs: 2640-4567

Abstract

Abstract : Global oscillations in the brain synchronize neural populations and lead to dynamic binding between different regions. This functional connectivity reconfigures as needed for the architecture of the neural network, thereby transcending the limitations of its hardwired structure. Despite the fact that it underlies the versatility of biological computational systems, this concept is not captured in current neuromorphic device architectures. Herein, functional connectivity in an array of organic neuromorphic devices connected through an electrolyte is demonstrated. The output of these devices is shown to be synchronized by a global oscillatory input despite the fact that individual inputs are stochastic and independent. This temporal coupling is induced at a specific phase of the global oscillation in a way that is reminiscent of phase locking of neurons to brain oscillations. This demonstration provides a pathway toward new neuromorphic architectural paradigms, where dynamic binding transcends the limitations of structural connectivity, and could enable architectural concepts of hierarchical information flow. Abstract : An array of organic neuromorphic devices immersed in a common electrolyte is synchronized by global voltage oscillations. This functional connectivity between devices is inspired by the macroscopic electrical oscillations in biological neural networks, and its implementation leads to more biologically plausible mechanisms in neuromorphic devices beyond the current mainstream approach of structural connectivity.