Taxonomic Distribution and Evolutionary Advantages
Action potentials are found throughout multicellular organisms, including plants, invertebrates such as insects, and vertebrates such as reptiles and mammals. Sponges seem to be the main phylum of multicellular eukaryotes that does not transmit action potentials, although some studies have suggested that these organisms have a form of electrical signaling, too. The resting potential, as well as the size and duration of the action potential, have not varied much with evolution, although the conduction velocity does vary dramatically with axonal diameter and myelination.
Animal | Cell type | Resting potential (mV) | AP increase (mV) | AP duration (ms) | Conduction speed (m/s) |
---|---|---|---|---|---|
Squid (Loligo) | Giant axon | −60 | 120 | 0.75 | 35 |
Earthworm (Lumbricus) | Median giant fiber | −70 | 100 | 1.0 | 30 |
Cockroach (Periplaneta) | Giant fiber | −70 | 80–104 | 0.4 | 10 |
Frog (Rana) | Sciatic nerve axon | −60 to −80 | 110–130 | 1.0 | 7–30 |
Cat (Felis) | Spinal motor neuron | −55 to −80 | 80–110 | 1–1.5 | 30–120 |
Given its conservation throughout evolution, the action potential seems to confer evolutionary advantages. One function of action potentials is rapid, long-range signaling within the organism; the conduction velocity can exceed 110 m/s, which is one-third the speed of sound. For comparison, a hormone molecule carried in the bloodstream moves at roughly 8 m/s in large arteries. Part of this function is the tight coordination of mechanical events, such as the contraction of the heart. A second function is the computation associated with its generation. Being an all-or-none signal that does not decay with transmission distance, the action potential has similar advantages to digital electronics. The integration of various dendritic signals at the axon hillock and its thresholding to form a complex train of action potentials is another form of computation, one that has been exploited biologically to form central pattern generators and mimicked in artificial neural networks.
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