Variations of the spontaneous electrical activities of the neuronal networks imposed by the exposure of electromagnetic radiations using computational map-based modeling.

Journal of computational neuroscience · 2023 · Mixed · Insufficient evidence

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MixedInsufficient evidencePaper 5716

Study snapshot

PublicationJournal of computational neuroscience · 2023

Study typeother

Reported directionMixed

Evidence ratingInsufficient

Abstract

The interaction between neurons in a neuronal network develops spontaneous electrical activities. But the effects of electromagnetic radiation on these activities have not yet been well explored. In this study, a ring of three coupled 1-dimensional Rulkov neurons and the generated electromagnetic field (EMF) are considered to investigate how the spontaneous activities might change regarding the EMF exposure. By employing the bifurcation analysis and time series, a comprehensive view of neuronal behavioral changes due to electromagnetic inductions is provided. The main findings of this study are as follows: 1) When a neuronal network is showing a spontaneous chaotic firing manner (without any external stimuli), a generated magnetic field inhibits this type of behavior. In fact, EMF completely eliminated the chaotic intrinsic behaviors of the neuronal loop. 2) When the network is exhibiting regular period-3 spiking patterns, the generated magnetic field changes its firing pattern to chaotic spiking, which is similar to epileptic seizures. 3) With weak synaptic connections, electromagnetic radiation inhibits and suppresses neuronal activities. 4) If the external magnetic flux has a high amplitude, it can change the shape of the induction current according to its shape 5) when there are weak synaptic connections in the network, a high-frequency external magnetic flux engenders high-frequency fluctuations in the membrane voltages. On the whole, electromagnetic radiation changes the pattern of the spontaneous activities of neuronal networks in the brain according to synaptic strengths and initial states of the neurons.

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AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typeother

Effect directionmixed

PopulationNot supplied

Sample sizeNot supplied

ExposureNot supplied

Evidence strengthInsufficientConfidence: 74% · Peer reviewed: yes

Main findings

Using a computational ring network of three coupled 1D Rulkov neurons with a generated electromagnetic field, the study reports that electromagnetic induction can eliminate spontaneous chaotic firing in the modeled loop, can convert regular period-3 spiking into chaotic spiking, and can inhibit/suppress activity when synaptic connections are weak. It also reports that high-amplitude external magnetic flux can alter the induction current shape and that high-frequency external magnetic flux can induce high-frequency membrane-voltage fluctuations when synaptic connections are weak.

Outcomes measured

Spontaneous electrical activity patterns in a modeled neuronal network (e.g., chaotic firing, period-3 spiking, suppression of activity, membrane voltage fluctuations)
Induction current shape changes under high-amplitude external magnetic flux

Limitations

Computational/map-based modeling study (no empirical human/animal/in vitro exposure described)
Modeled network consists of three coupled 1-dimensional Rulkov neurons in a ring (highly simplified representation)
Exposure characteristics (e.g., real-world source, frequency values, dosimetry/SAR, duration) are not specified in the abstract

View raw extracted JSON

{
  "study_type": "other",
  "exposure": {
    "band": null,
    "source": null,
    "frequency_mhz": null,
    "sar_wkg": null,
    "duration": null
  },
  "population": null,
  "sample_size": null,
  "outcomes": [
    "Spontaneous electrical activity patterns in a modeled neuronal network (e.g., chaotic firing, period-3 spiking, suppression of activity, membrane voltage fluctuations)",
    "Induction current shape changes under high-amplitude external magnetic flux"
  ],
  "main_findings": "Using a computational ring network of three coupled 1D Rulkov neurons with a generated electromagnetic field, the study reports that electromagnetic induction can eliminate spontaneous chaotic firing in the modeled loop, can convert regular period-3 spiking into chaotic spiking, and can inhibit/suppress activity when synaptic connections are weak. It also reports that high-amplitude external magnetic flux can alter the induction current shape and that high-frequency external magnetic flux can induce high-frequency membrane-voltage fluctuations when synaptic connections are weak.",
  "effect_direction": "mixed",
  "limitations": [
    "Computational/map-based modeling study (no empirical human/animal/in vitro exposure described)",
    "Modeled network consists of three coupled 1-dimensional Rulkov neurons in a ring (highly simplified representation)",
    "Exposure characteristics (e.g., real-world source, frequency values, dosimetry/SAR, duration) are not specified in the abstract"
  ],
  "evidence_strength": "insufficient",
  "confidence": 0.74,
  "peer_reviewed_likely": "yes",
  "keywords": [
    "computational modeling",
    "Rulkov neuron",
    "neuronal network",
    "spontaneous activity",
    "bifurcation analysis",
    "time series",
    "electromagnetic field",
    "magnetic flux",
    "electromagnetic induction",
    "chaos",
    "spiking",
    "synaptic strength",
    "membrane voltage"
  ],
  "suggested_hubs": []
}

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AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.1007/s10827-022-00842-8
PubMed: 36539556

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