Logical Gates Implemented by Solitons at the Junctions Between One-Dimensional Lattices

Siccardi, Stefano; Adamatzky, Andrew

doi:10.1142/s0218127416501078

Cited by 16 publications

(15 citation statements)

References 39 publications

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“…These states are updated in parallel in discrete time depending on states of two closest neighbours in the node chain and two closest neighbours in the complementary chain. In this way it is possible to represent the actin filaments as an automaton of finite states with transition rules that support traveling and mobile localizations [3], [24], [25]. Also, we can assume that states of nodes depends not only on the current states of neighbouring node but also on their past states so that we assess the effect of memory of past states on the dynamics of acting automata [1].…”

Section: Discussionmentioning

confidence: 99%

Decidable and undecidable arithmetic functions in actin filament networks

Schumann¹

2017

J. Phys. D: Appl. Phys.

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The plasmodium of Physarum polycephalum, called slime mould, is very sensitive to its environment and reacts to stimuli by its appropriate motions. The sensitive stage as well as the motor stage of these reactions are explained by actin filament networks. This paper is devoted to actin filament networks as a computation medium. The point is that actin filaments are sensitive to outer cellular stimuli (attractants as well as repellents) and they appear and disappear at different places of the cell to change the cell structure, e.g. its shape. Due to assembling and disassembling actin filaments, Physarum polycephalum as well as other unicellular organisms like Amoeba proteus can move in responses to different stimuli. As a result, these organisms can be considered a simple reversible logic gate, where outer cellular signals are its inputs and the motions are its outputs. In this way, we can implement different logic gate on the amoeboid behaviours. The actin filament networks have the same basic properties as neural networks: lateral inhibition; lateral activation; recurrent inhibition; recurrent excitation; feedforward inhibition; feedforward excitation; convergence/divergence. These networks can embody arithmetic functions defined recursively and corecursively within p-adic valued logic. Furthermore, within these networks we can define the so-called diagonalization for deducing undecidable arithmetic functions.

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Section: Discussionmentioning

confidence: 99%

Decidable and undecidable arithmetic functions in actin filament networks

Schumann¹

2017

J. Phys. D: Appl. Phys.

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“…We have shown that and , or and not gates can be implemented in such setups. These gates can be cascaded into hierarchical circuits, as we have shown on an example of nor 32 .…”

Section: Introductionmentioning

confidence: 99%

“…Computational studies discussed the feasibility of implementing Boolean gates on a single actin filament 31 and on an intersection of several actin filaments 32 via collisions between solitons. Further studies applied a reservoir-computing-like approach to discover functions on a single actin unit 33 as well as filament 34 .…”

Section: Introductionmentioning

confidence: 99%

“…Further studies applied a reservoir-computing-like approach to discover functions on a single actin unit 33 as well as filament 34 . In 2016, for instance, we demonstrated that it is possible to implement logical circuits by linking the protein chains 32 . In such a setup, Boolean values are represented by localisations travelling along the filaments and the computation is realised via collisions between localisations at the junctions between the chains.…”

Section: Introductionmentioning

confidence: 99%

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Computing on actin bundles network

Adamatzky

Huber

Schnauß

2019

Sci Rep

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Actin filaments are conductive to ionic currents, mechanical and voltage solitons. These travelling localisations can be utilised to generate computing circuits from actin networks. The propagation of localisations on a single actin filament is experimentally unfeasible to control. Therefore, we consider excitation waves propagating on bundles of actin filaments. In computational experiments with a two-dimensional slice of an actin bundle network we show that by using an arbitrary arrangement of electrodes, it is possible to implement two-inputs-one-output circuits.

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“…These models considered a unit (F-actin) of an actin filament as a single, discrete, entity which can take just two or three states, and carriers of information occupied one-two actin units. These were models of rather coarse-grained computation [19][20][21][22][23]. To take the paradigm of computation via interaction travelling localisations at the sub-molecular level we must understand how information, presented by a perturbation of some part of an F-actin unit from its resting state, propagates in the F-actin unit.…”

Section: Introductionmentioning

confidence: 99%

On the Dynamics of Excitation and Information Processing in F-actin: Automaton Model

Adamatzky¹,

Lab²

2017

ComplexSystems

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We represent a filamentous actin molecule as a graph of finite-state machines (F-actin automaton). Each node in the graph takes three states -resting, excited, refractory. All nodes update their states simultaneously and by the same rule, in discrete time steps. Two rules are considered: threshold rule -a resting node is excited if it has at least one excited neighbour and narrow excitation interval rule -a resting node is excited if it has exactly one excited neighbour. We analyse distributions of transient periods and lengths of limit cycles in evolution of F-actin automaton, propose mechanisms for formation of limit cycles and evaluate density of information storage in F-actin automata.

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Logical Gates Implemented by Solitons at the Junctions Between One-Dimensional Lattices

Cited by 16 publications

References 39 publications

Decidable and undecidable arithmetic functions in actin filament networks

Decidable and undecidable arithmetic functions in actin filament networks

Computing on actin bundles network

On the Dynamics of Excitation and Information Processing in F-actin: Automaton Model

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