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Area of Science:

  • Computational Neuroscience
  • Network Science
  • Complex Systems

Background:

  • Understanding the collective dynamics of the brain, particularly neuronal synchronization, is crucial.
  • The influence of temporal and higher-order interactions on these dynamics remains an area of interest.

Purpose of the Study:

  • To investigate how temporal higher-order interactions, modeled by simplicial complexes, affect neuronal synchronization.
  • To compare synchronization in temporal higher-order networks with temporal pairwise and static many-body interactions.

Main Methods:

  • Modeling neuronal ensembles with gap junction interactions using temporal higher-order networks (simplicial complexes).
  • Employing the master stability function approach to analyze the local stability of synchronous solutions.
  • Conducting numerical simulations to observe the emergence of complete neuronal synchronization.

Main Results:

  • The critical synaptic strength for synchronization is lower in temporal higher-order networks compared to temporal pairwise or static many-body interactions.
  • Neuronal synchronization can emerge solely from higher-order, time-varying interactions.
  • Enhanced synchronization in temporal higher-order structures correlates with the density of group interactions.

Conclusions:

  • Temporal higher-order interactions significantly facilitate neuronal synchronization.
  • The density of group interactions plays a key role in enhancing synchronization within these networks.
  • Analytical conditions derived from the master stability function align with numerical findings, validating the model.