Sensory-motor cortices shape functional connectivity dynamics in the human brain

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Large-scale biophysical circuit models offer insights into brain organization and spontaneous activity.
• Understanding the micro- and macro-scale properties shaping brain activity is crucial.

Purpose of the Study:

• To develop a spatially heterogeneous large-scale dynamical circuit model of the human cortex.
• To investigate how local circuit properties, informed by anatomical and functional gradients, influence resting-state functional connectivity (FC).
• To explore the drivers and potential mechanisms of multi-stability in FC dynamics.

Main Methods:

• Developed a spatially heterogeneous large-scale dynamical circuit model with regional variations in synaptic properties.
• Parameterized local circuit properties using anatomical and functional gradients.
• Analyzed static and dynamic resting-state functional connectivity (FC).
• Performed causal manipulation of the model and compared simulated FC dynamics with empirical data.
• Investigated the relationship between gene expression gradients and model drivers.

Main Results:

• Parameterizing the model with anatomical and functional gradients yielded more realistic static and dynamic FC.
• Simulated and empirical FC dynamics exhibited similar sharp transitions, suggesting multi-stability.
• Time-varying regional fMRI amplitude may correlate with FC multi-stability.
• Causal manipulation identified sensory-motor regions as key drivers of FC dynamics.
• The spatial distribution of these drivers aligns with gene expression gradients, implicating excitation-inhibition balance.

Conclusions:

• Spatially heterogeneous brain circuit models incorporating anatomical and functional gradients enhance the realism of simulated resting-state FC.
• The human brain exhibits multi-stability in FC dynamics, potentially driven by sensory-motor regions.
• Heterogeneity in the excitation-inhibition balance, reflected in gene expression patterns, may underlie FC multi-stability.