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Slime mould logic gates based on frequency changes of electrical potential oscillation

Whiting, James G. H.; de Lacy Costello, Ben P. J.; Adamatzky, Andrew

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James Whiting
Occasional Associate Lecturer - CATE - ENG


Physarum polycephalum is a large single amoeba cell, which in its plasmodial phase, forages and connects nearby food sources with protoplasmic tubes. The organism forages for food by growing these tubes towards detected foodstuff, this foraging behaviour is governed by simple rules of photoavoidance and chemotaxis. The electrical activity of the tubes oscillates, creating a peristaltic like action within the tubes, forcing cytoplasm along the lumen; the frequency of this oscillation controls the speed and direction of growth. External stimuli such as light and food cause changes in the oscillation frequency. We demonstrate that using these stimuli as logical inputs we can approximate logic gates using these tubes and derive combinational logic circuits by cascading the gates, with software analysis providing the output of each gate and determining the input of the following gate. Basic gates OR, AND and NOT were correct 90%, 77.8% and 91.7% of the time respectively. Derived logic circuits XOR, half adder and full adder were 70.8%, 65% and 58.8% accurate respectively. Accuracy of the combinational logic decreases as the number of gates is increased, however they are at least as accurate as previous logic approximations using spatial growth of P. polycephalum and up to 30 times as fast at computing the logical output. The results shown here demonstrate a significant advancement in organism-based computing, providing a solid basis for hybrid computers of the future. © 2014 Elsevier Ireland Ltd.


Whiting, J. G. H., de Lacy Costello, B. P. J., & Adamatzky, A. (2014). Slime mould logic gates based on frequency changes of electrical potential oscillation. BioSystems, 124, 21-25.

Journal Article Type Article
Acceptance Date Oct 31, 2014
Publication Date Jan 1, 2014
Deposit Date Sep 23, 2016
Publicly Available Date Sep 23, 2016
Journal BioSystems
Print ISSN 0303-2647
Electronic ISSN 1872-8324
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 124
Pages 21-25
Keywords physarum polycephalum, Boolean logic, biological computing
Public URL
Publisher URL
Additional Information Additional Information : The final publication is available at


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