Parametric resonance brain model.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
21 Oct 2024
21 Oct 2024
Historique:
received:
06
06
2024
accepted:
15
10
2024
medline:
21
10
2024
pubmed:
21
10
2024
entrez:
20
10
2024
Statut:
epublish
Résumé
The paper introduces a parametric resonance model for characterizing some features of the brain's electrical activity. This activity is assumed to be a fundamental aspect of brain functionality underpinning functions from basic sensory processing to complex cognitive operations such as memory, reasoning, and emotion. A pivotal element of the proposed parametric model is neuron synchronization which is crucial for generating detectable brain waves. The analysis of the frequency content of brain waves, categorized as delta (0÷4 Hz), theta (4÷7 Hz), alpha (8÷12 Hz), beta (13÷30 Hz), and gamma (30÷100 Hz) reveals, notably, that the mean frequency of each of these brain wave classes is, in sequence, approximately the double of that of the previous one. Based on this observation, the proposed parametric resonance model suggests a cascade of amplification effects. Following the proposed model, in the transition from wakefulness to sleep, the brain wave bands are energized at double frequency by higher frequency neighboring bands; on the contrary, in the sleep to awake transition, brain waves are energized at a half frequency by their lower frequency neighbor waves. Finally, the trend of increasing amplitude values from higher to lower frequencies lends empirical support to the parametric resonant brain model validity.
Identifiants
pubmed: 39428435
doi: 10.1038/s41598-024-76610-8
pii: 10.1038/s41598-024-76610-8
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
24657Informations de copyright
© 2024. The Author(s).
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