The human brain contains about 86 billion neurons, forming approximately 100 trillion molecular-level connections known as, synapses. A synapse is about 20 nm gap separating two neurons. It is well accepted that biological memory and learning are the result of synaptic plasticity, a capability to adapt to a change, and governed by classes of phenomena such as long-term potentiation (LTP) and short-term plasticity (STP). At the molecular level, lipid bilayers are the underlying structures of neurons and their synapses, where the electrical signals are facilitated by ion diffusion. Therefore, it is not surprising that lipids and their intermediates are crucial to normal brain function. Using the droplet interface bilayer (DIBs) platform to model artificial neurons and electrical stimulation protocols, we show that DIBs displaying memcapacitive properties can exhibit persistent synaptic plasticity in the form of long-term potentiation (LTP) associated with capacitive energy storage in the phospholipid bilayer over long time scales (min – hrs). Furthermore, by incorporating Gramicidin-A (gA) ion channels within the bilayer, we also demonstrate paired-pulse facilitation and depression (PPF and PPD) in the form of short-term synaptic plasticity (STP), emulating the brain’s efficiency and flexible cognitive capabilities on short time scales (msec – min). The observed STP behavior arises from reversible physical changes of the bilayer which regulate ion channel conductance efficiency. In DIBs containing gA ion channels, we’ve demonstrated that the extent of STP is influenced by the presence of dissolved cationic species—K⁺and Na⁺ promote STP, while Li⁺ and Tm³⁺ suppress STP. Although short- and long-lasting forms of synaptic plasticity including LTP and STP have been extensively used as cellular models for learning, memory, and processing in animals, neuroplasticity and memory encoding by phospholipid membranes has yet to be seriously explored. Demonstration of such behaviors presents us with a model system aimed at understanding the molecular basis of biological memory and can serve as a foundation for developing soft-matter-based neuromorphic computers.

Dima Bolmatov

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