Experimental verification of an opto-chemical “neurocomputer”

Proskurkin, Ivan S.; Smelov, Pavel S.; Vanag, Vladimir K.

doi:10.1039/d0cp01858a

Cited by 21 publications

(18 citation statements)

References 23 publications

(48 reference statements)

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“…Another similar concept is that of volume transmission and intercellular communication via diffusing signaling molecules secreted by excitable cells (Sykova and Nicholson, 2008). There also appears to be an interesting connection between the self-organizing Ca 2+ signaling in coupled astrocytes and the concept of "reaction-diffusion computing" or "chemical computing" based on oscillatory chemical (e.g., Belousov-Zhabotinsky) systems in coupled reactor volumes, e.g., microemulsions (Adamatzky et al, 2005;Epstein et al, 2012;Showalter and Epstein, 2015;Torbensen et al, 2017;Vanag, 2019;Proskurkin et al, 2020). It is conceivable that astrocytes can provide a substrate for such Ca 2+ -based reaction-diffusion computing in parallel to, and organizing sparse network-based neuronal connectivity.…”

Section: Discussionmentioning

confidence: 99%

Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics

Verisokin

Verveyko

Postnov

et al. 2021

Front. Cell. Neurosci.

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Neuronal firing and neuron-to-neuron synaptic wiring are currently widely described as orchestrated by astrocytes—elaborately ramified glial cells tiling the cortical and hippocampal space into non-overlapping domains, each covering hundreds of individual dendrites and hundreds thousands synapses. A key component to astrocytic signaling is the dynamics of cytosolic Ca2+ which displays multiscale spatiotemporal patterns from short confined elemental Ca2+ events (puffs) to Ca2+ waves expanding through many cells. Here, we synthesize the current understanding of astrocyte morphology, coupling local synaptic activity to astrocytic Ca2+ in perisynaptic astrocytic processes and morphology-defined mechanisms of Ca2+ regulation in a distributed model. To this end, we build simplified realistic data-driven spatial network templates and compile model equations as defined by local cell morphology. The input to the model is spatially uncorrelated stochastic synaptic activity. The proposed modeling approach is validated by statistics of simulated Ca2+ transients at a single cell level. In multicellular templates we observe regular sequences of cell entrainment in Ca2+ waves, as a result of interplay between stochastic input and morphology variability between individual astrocytes. Our approach adds spatial dimension to the existing astrocyte models by employment of realistic morphology while retaining enough flexibility and scalability to be embedded in multiscale heterocellular models of neural tissue. We conclude that the proposed approach provides a useful description of neuron-driven Ca2+-activity in the astrocyte syncytium.

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Section: Discussionmentioning

confidence: 99%

Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics

Verisokin

Verveyko

Postnov

et al. 2021

Front. Cell. Neurosci.

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“…On the other hand, fast oscillations are promising because they speed up of information processing. To compare with existing systems, optochemical neurocomputer [27] using BZ droplets in rubber tubings and light coupling has one of the natural pulses generator 75 s and 82 s, the rest of the droplets are susceptible to forced period of pulses. The working cycle of the optochemical neurocomputer is over an hour [27].…”

Section: Discussionmentioning

confidence: 99%

“…To compare with existing systems, optochemical neurocomputer [27] using BZ droplets in rubber tubings and light coupling has one of the natural pulses generator 75 s and 82 s, the rest of the droplets are susceptible to forced period of pulses. The working cycle of the optochemical neurocomputer is over an hour [27]. Another system is programmable chemical computer for pattern recognition, which works with periods 30 s to 60 s in an array of BZ droplets [3].…”

Section: Discussionmentioning

confidence: 99%

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Identification of the best medium for experiments on chemical computation with Belousov–Zhabotinsky reaction and ferroin-loaded Dowex beads

Muzika

Górecki

2022

Reac Kinet Mech Cat

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Our study is focused on identification of the best medium for future experiments on information processing with Belousov–Zhabotinsky reaction proceeding in Dowex beads with immobilized catalyst inside. The optimum medium should be characterized by long and stable nonlinear behavior, mechanical stability and should allow for control with electric potential. We considered different types of Dowex ion-exchange resins, bead distributions and various initial concentrations of substrates: malonic acid and 1,4-cyclohexanedione. The electric potential on platinum electrodes, stabilized by a potentiostat is used to control medium evolution. A negative electric potential generates activator species HBrO2 on the working electrode according to the reaction: BrO3− + 2e− + 3H+ → HBrO2 + H2O, while positive electric potential attracts inhibitor species Br− to the proximity of it. We study oscillation amplitude and period stability in systems with ferroin loaded Dowex 50W-X2 and Dowex 50W-X8 beads during experiments exceeding 16 h. It has been observed, that the above mentioned resins generate a smaller number of CO2 bubbles close to the beads than Dowex 50W-X4, which makes Dowex 50W-X2 and Dowex 50W-X8 more suitable for applications in chemical computing. We report amplitude stability, oscillation frequency, merging and annihilation of travelling waves in a lattice of Dowex 50W-X8 beads (mesh size 50–100) in over 19 h long experiments with equimolar solution of malonic acid and 1,4-cyclohexanedione. This system looks as a promising candidate for chemical computing devices that can operate for a day.

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“…Recent studies have demonstrated that an oscillating BZ-reaction can be efficiently applied for information processing Smelov and Vanag (2018) ; Vanag VK. (2019) ; Proskurkin et al (2020) ; Egbert, (2019) ; Duenas-Diez and Perez-Mercader (2019) ; Duenas-Diez and Perez-Mercader (2020) . For example, it has been shown that a network of interacting chemical oscillators can be trained to perform classification tasks with a reasonable accuracy Gruenert et al (2015) ; Gizynski and Gorecki (2017a) .…”

Section: Introductionmentioning

confidence: 99%

Computing With Networks of Chemical Oscillators and its Application for Schizophrenia Diagnosis

Bose

Górecki

2022

Front. Chem.

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Chemical reactions are responsible for information processing in living organisms, yet biomimetic computers are still at the early stage of development. The bottom-up design strategy commonly used to construct semiconductor information processing devices is not efficient for chemical computers because the lifetime of chemical logic gates is usually limited to hours. It has been demonstrated that chemical media can efficiently perform a specific function like labyrinth search or image processing if the medium operates in parallel. However, the number of parallel algorithms for chemical computers is very limited. Here we discuss top-down design of such algorithms for a network of chemical oscillators that are coupled by the exchange of reaction activators. The output information is extracted from the number of excitations observed on a selected oscillator. In our model of a computing network, we assume that there is an external factor that can suppress oscillations. This factor can be applied to control the nodes and introduce input information for processing by a network. We consider the relationship between the number of oscillation nodes and the network accuracy. Our analysis is based on computer simulations for a network of oscillators described by the Oregonator model of a chemical oscillator. As the example problem that can be solved with an oscillator network, we consider schizophrenia diagnosis on the basis of EEG signals recorded using electrodes located at the patient’s scalp. We demonstrated that a network formed of interacting chemical oscillators can process recorded signals and help to diagnose a patient. The parameters of considered networks were optimized using an evolutionary algorithm to achieve the best results on a small training dataset of EEG signals recorded from 45 ill and 39 healthy patients. For the optimized networks, we obtained over 82% accuracy of schizophrenia detection on the training dataset. The diagnostic accuracy can be increased to almost 87% if the majority rule is applied to answers of three networks with different number of nodes.

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Experimental verification of an opto-chemical “neurocomputer”

Abstract: A hierarchical network of pulse coupled chemical micro-oscillators and excitable cells demonstrates intelligent behavior.

Cited by 21 publications

References 23 publications

Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics

Modeling of Astrocyte Networks: Toward Realistic Topology and Dynamics

Identification of the best medium for experiments on chemical computation with Belousov–Zhabotinsky reaction and ferroin-loaded Dowex beads

Computing With Networks of Chemical Oscillators and its Application for Schizophrenia Diagnosis

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