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Language of fungi derived from their electrical spiking activity
1Unconventional Computing Laboratory, UWE, Bristol, UK.
Abstract:
Fungi exhibit oscillations of extracellular electrical potential recorded via differential electrodes inserted into a substrate colonized by mycelium or directly into sporocarps. We analysed electrical activity of ghost fungi (Omphalotus nidiformis), Enoki fungi (Flammulina velutipes), split gill fungi (Schizophyllum commune) and caterpillar fungi (Cordyceps militaris). The spiking characteristics are species specific: a spike duration varies from 1 to 21 h and an amplitude from 0.03 to 2.1 mV. We found that spikes are often clustered into trains. Assuming that spikes of electrical activity are used by fungi to communicate and process information in mycelium networks, we group spikes into words and provide a linguistic and information complexity analysis of the fungal spiking activity. We demonstrate that distributions of fungal word lengths match that of human languages. We also construct algorithmic and Liz-Zempel complexity hierarchies of fungal sentences and show that species S. commune generate the most complex sentences.
Insights
Fungi communicate using electrical signals, with distinct species-specific patterns. Analysis reveals fungal "language" complexity comparable to human languages, with split gill fungi exhibiting the most intricate communication.
Area of Science:
- Mycology
- Neurobiology
- Bioelectricity
Background:
- Fungi generate electrical potential oscillations.
- Extracellular electrical activity is measurable in fungal mycelium and sporocarps.
Purpose of the Study:
- To analyze the species-specific electrical activity in four fungi species.
- To investigate the potential for fungal electrical activity as a communication system.
- To compare the linguistic complexity of fungal electrical signals with human language.
Main Methods:
- Recording extracellular electrical potential using differential electrodes.
- Analyzing spike duration, amplitude, and clustering.
- Applying linguistic and information complexity analysis to fungal electrical activity patterns.
Main Results:
- Electrical spiking characteristics are unique to each fungal species, with variations in spike duration (1-21 h) and amplitude (0.03-2.1 mV).
- Fungal electrical spikes often form trains, suggesting structured communication.
- Distributions of fungal "word" lengths align with human language patterns.
- Split gill fungi (S. commune) produce the most complex fungal "sentences" based on algorithmic and Liz-Zempel complexity.
Conclusions:
- Fungal electrical activity exhibits species-specific patterns that may represent a form of communication.
- The complexity of fungal electrical signaling shows parallels with human linguistic structures.
- Further research into fungal bioelectricity could reveal insights into mycelial network information processing.
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