Structure-function discrepancy: inhomogeneity and delays in synchronized neural networks.

Area of Science:

• Computational Neuroscience
• Network Science
• Systems Biology

Background:

• Understanding brain function requires mapping structural and functional neural connectivity.
• Discrepancies between structural and functional connectivity pose a significant challenge.
• Neural mass models are used to study large-scale brain dynamics.

Purpose of the Study:

• To investigate how inhomogeneity in coupling structure and delays affects synchronization in neural networks.
• To derive a direct relationship between structural and functional connectivity.
• To explain the observed resemblance between structural and functional connectivity.

Main Methods:

• Derivation of phase dynamics for generic networks of oscillatory neural masses.
• Analysis of synchronization behavior under homogeneous and distributed delay conditions.
• Comparison of phase coupling patterns resulting from structural inhomogeneity versus distributed delays.
• Illustration using resting-state activity and anatomical connectivity data.

Main Results:

• Homogeneous delays preserve structural coupling, leading to clustered phase distributions and few synchronized groups.
• Distributed delays introduce phase coupling inhomogeneity, eliminating clustered distributions and mimicking structural inhomogeneity.
• Phase (de-)synchronization patterns from inhomogeneous coupling and distributed delays are indistinguishable.
• An analytical expression for effective phase coupling as a function of structural coupling was derived.

Conclusions:

• Structural connectivity constrains network synchronizability, which is modulated by delay distribution.
• Distributed delays can functionally mimic structural inhomogeneity in neural networks.
• The derived relationship explains the resemblance but not the one-to-one correspondence between structural and functional connectivity.