Turing Complete Neural Computation Based on Synaptic Plasticity
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F19%3A00510528" target="_blank" >RIV/67985807:_____/19:00510528 - isvavai.cz</a>
Result on the web
<a href="http://hdl.handle.net/11104/0300985" target="_blank" >http://hdl.handle.net/11104/0300985</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1371/journal.pone.0223451" target="_blank" >10.1371/journal.pone.0223451</a>
Alternative languages
Result language
angličtina
Original language name
Turing Complete Neural Computation Based on Synaptic Plasticity
Original language description
In neural computation, the essential information is generally encoded into the neurons via their spiking configurations, activation values or (attractor) dynamics. The synapses and their associated plasticity mechanisms are, by contrast, mainly used to process this information and implement the crucial learning features. Here, we propose a novel Turing complete paradigm of neural computation where the essential information is encoded into discrete synaptic states, and the updating of this information achieved via synaptic plasticity mechanisms. More specifically, we prove that any 2-counter machine—and hence any Turing machine—can be simulated by a rational-weighted recurrent neural network employing spike-timing-dependent plasticity (STDP) rules. The computational states and counter values of the machine are encoded into discrete synaptic strengths. The transitions between those synaptic weights are then achieved via STDP. These considerations show that a Turing complete synaptic-based paradigm of neural computation is theoretically possible and potentially exploitable. They support the idea that synapses are not only crucially involved in information processing and learning features, but also in the encoding of essential information. This approach represents a paradigm shift in the field of neural computation.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA19-05704S" target="_blank" >GA19-05704S: FoNeCo: Analytical Foundations of Neurocomputing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
PLoS ONE
ISSN
1932-6203
e-ISSN
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Volume of the periodical
14
Issue of the periodical within the volume
10
Country of publishing house
US - UNITED STATES
Number of pages
34
Pages from-to
e0223451
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85073468063