Synthetic Neurons and Artificial Photoactivated Synapses

Introduction

The brain is a complex network of inter-connected neurons that communicate through synapses. SYNAPS aims to for the first time mimic such synapses using liposomes as artificial cells, and visible light to trigger a signal from a ‘sender’- to a ‘receiver’-liposome.

Objectives

Mimicking such communication processes will help with understanding how complex natural emergent properties arise, and could ultimately allow for the construction of a chemical computer.

Innovations

SYNAPS will excel beyond the state-of-the-art by:

• Maintaining chemical isolation between liposome interiors.
• Ensuring local, time-bound communication between connected liposomes.
• Using light as an external stimulus and fuel.

These concepts are essential to construct artificial tissues that can communicate on an individual liposome-to-liposome basis, in contrast to the state-of-the-art where communication generally occurs with the bulk solution.

Methodology

To achieve this, a messenger compound will be locally photosynthesized through transmembrane electron transfer by porphyrin dimers that portray a charge-transfer excited state.

Organization of Liposomes

The liposomes will be organized into a synaptic cleft through the use of synthetic complementary clustering compounds that provide stable adhesion between sender and receiver liposomes.

Signal Recognition

The messenger compound will be recognized by reversible and selective membrane-spanning receptors in the receiver liposome, which will output the signal through fluorescence.

Reaction Cascade Network

In addition, a reaction cascade network will be constructed involving the messenger to produce an artificial action potential, that is, a transient peak in the concentration of the messenger, ensuring a time-bound dissipative signal.

Conclusion

Altogether, SYNAPS will provide advances in systems chemistry by offering a nanoscale platform for communication between chemically isolated systems. Additionally, it will yield results that are useful for applications such as light-to-chemical energy conversion, chemical sensing, and smart drug delivery.