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Threshold logic gates (TLGs) based on resonant tunneling diodes (RTDs) allow the implementation of simple McCulloch-Pitts (MCP) neuron models. Whilst they have been demonstrated implementing a wide range of binary logic circuits the gates are also theoretically capable of implementing artificial neural networks. The conventional operation of RTD based logic circuits with many cascaded stages has inherent disadvantages associated with the requirement of an evaluation period at each stage and the resultant use of multiple clocks. The authors propose that highly parallel structures similar to those found in artificial neural networks are better suited to RTD based TLGs and offer the way forward for future large scale designs.