‘Neuroplasticity’ is the capability to change and reconfigure the networked connections in the brain which accounts for the remarkable complexity and adaptability of the mammalian brain. Synaptic neuroplasticity refers to the brain's extraordinary ability to change the strength and structure of the connections between neurons, which is essential for information transfer. This has inspired the design and training of artificial neural networks (ANN), allowing them to learn and improve their performance over time. In the trend to implement ANN in hardware, a particular challenge has been the implementation of plasticity in the artificial synapses. Here we present a concept and mechanism to incorporate plasticity into a system using electrochemical metallization (ECM) in a liquid matrix, dimethyl sulfoxide (DMSO).

A brain inspired liquid matrix has been employed to enable an ‘ionotronic’ system. These brain-inspired, dynamic and reconfigurable electronic connections are robust in DMSO while still being susceptible to manipulation upon applied external stimuli. These connections are wires that grow as dendrites due to the redox reaction taking place at the electrodes. The thickness and the growth conditions of these wires influence their electrical properties, which could be altered by varying the initial experimental conditions such as the applied voltage. The manipulation of these wires could be done during the growth of the wire between two nodes or more simultaneously. Furthermore, after the growth of a single wire, the filament could be manipulated to induce a breakage which resembles a synaptic property. The growth and manipulation of single 2D and 3D connections and in extension, networked connections, using external stimuli will be demonstrated along with electrical characterization of these filaments and possible applications. In essence, the foundation laid in the field of dynamic filament growth within a liquid matrix has the potential to transform the landscape of technological advancement. This innovation, with its capacity for synaptic mimicry, flexible growth, and 3-dimentionality, is expected to open up new avenues for research and development in fields as diverse as neuromorphic computing, cognitive sciences, and advanced artificial intelligence.