Dynamic effective connectivity of inter-areal brain circuits

Area of Science:

• Computational neuroscience
• Systems neuroscience
• Network neuroscience

Background:

• Structural brain connectivity defines physical pathways but not causal information flow.
• Effective connectivity, or causal influence between brain areas, is dynamic and context-dependent.
• Understanding dynamic effective connectivity is crucial for deciphering brain function.

Purpose of the Study:

• To investigate how dynamic effective connectivity arises from neural activity.
• To explore the role of neural oscillations and network dynamics in information routing.
• To demonstrate the rapid, stimulus-triggered reconfiguration of brain communication pathways.

Main Methods:

• Simulations of large random networks of spiking neurons and rate units.
• Semi-analytic approaches to analyze mesoscale network motifs.
• Causal analysis of time-series data from simulated neural activity.
• Perturbation analysis to probe transitions in effective connectivity.

Main Results:

• Different dynamical states of the same structural network yield distinct effective connectivity motifs.
• Directionality in effective connectivity emerges from spontaneous symmetry breaking and entrainment of neural rhythms.
• Effective connectivity configurations can be rapidly switched by timed perturbations, independent of synaptic plasticity.
• Dynamic effective connectivity modulates the efficiency and directionality of information transfer between brain areas.

Conclusions:

• Dynamic effective connectivity is an emergent property of neural activity organization, not solely fixed structure.
• Interactions between brain rhythms provide a mechanism for self-organized control of communication-through-coherence.
• The brain can rapidly reconfigure information routing pathways on demand, enabling flexible cognitive function.