Patterns of neuronal synchrony in higher-order networks

Area of Science:

• Neuroscience
• Computational Neuroscience
• Complex Systems

Background:

• Neuronal synchrony is vital for cognition and motor control.
• Traditional focus on pairwise neuronal interactions is expanding to include higher-order interactions.
• Complex synchronous patterns, like chimera states, are observed in neuronal networks and linked to neurological disorders.

Purpose of the Study:

• To review how pairwise and higher-order interactions influence synchrony patterns in neuronal networks.
• To provide a comprehensive overview of connectivity mechanisms driving neuronal synchrony.
• To highlight the significance of synchronous states in neurological systems.

Main Methods:

• Review of existing literature on neuronal synchrony.
• Exploration of various connectivity mechanisms (e.g., temporal interactions, time-delayed coupling, adaptive communication).
• Analysis of key neuronal models (Hindmarsh-Rose, Hodgkin-Huxley, Sherman, FitzHugh-Nagumo).

Main Results:

• Both pairwise and higher-order interactions generate complex synchronous spatiotemporal patterns.
• Chimera states, characterized by coexisting synchronized and desynchronized activity, emerge from these interactions.
• Network structure and neuronal dynamics significantly influence the emergence and stability of synchrony patterns.

Conclusions:

• Understanding diverse synchrony patterns is crucial for neurological research.
• Higher-order interactions play a significant role in shaping network dynamics.
• Further research into neuronal synchrony can inform treatments for neurological disorders.