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Biophysical mechanisms of default mode network function and dysfunction

Trang-Anh E. Nghiem, Vinod Menon

preprint DOI: 10.1101/2025.04.16.649208 (opens in new tab)

Summary

AI-generated from the abstract

Stimulating the insula node of the salience network suppresses default mode network (DMN) activity in computational simulations, while cingulate cortex stimulation enhances retrosplenial cortex activity. Prelimbic cortex stimulation partially replicates insula-mediated suppression but fails to suppress cingulate regions, suggesting it acts as a functional bridge between networks. DMN emergence as a functionally segregated network is robust across wide ranges of excitatory-inhibitory balance and cholinergic modulation, but outside these boundaries, integrity breaks down through three failure modes: loss of responsiveness, reversal of suppression to enhancement, and network fragmentation.

Study at a glance

Characteristics Computational modeling study
Key finding Stimulation of the insula node of the salience network suppresses DMN activity, while cingulate cortex stimulation enhances retrosplenial cortex activity, and DMN integrity breaks down through three distinct failure modes when excitatory-inhibitory balance or cholinergic modulation exceed certain boundaries.

Abstract

Abstract The default mode network (DMN) plays a fundamental role in internally focused cognition, and its disruption is implicated in numerous brain disorders. While neuroimaging has revealed DMN suppression by salient stimuli, the cellular mechanisms orchestrating this process remain unknown. Using whole-brain computational modeling informed by neuronal biophysics and retrograde tracer-derived directional mouse brain connectomics, we demonstrate that stimulation of the insula node of the salience network suppresses DMN activity, whereas cingulate cortex stimulation produces antagonistic effects, enhancing retrosplenial cortex activity. Prelimbic cortex stimulation showed intermediate patterns, partially replicating insula-mediated suppression while failing to suppress cingulate regions, suggesting its role as a functional bridge between networks. Systematic brain-wide analysis confirmed the insula’s unique pattern of simulated DMN suppression. Comprehensive parameter space exploration demonstrated that DMN emergence as a functionally segregated network is robust across wide ranges of excitatory-inhibitory balance regimes and cholinergic modulation. However, outside these boundaries, DMN integrity breaks down through three distinct failure modes: loss of responsiveness, reversal of suppression to enhancement, and network fragmentation. The retrosplenial cortex emerged as a particularly vulnerable regulatory hub whose excitatory-inhibitory disruption reversed normal suppression patterns across the DMN, while prelimbic cortex demonstrated remarkable robustness. Brain-wide analysis also identified a functionally segregated frontal network displaying antagonistic dynamics with the DMN. Our findings provide mechanistic insights into DMN robustness and vulnerability, establishing a framework that links cellular excitatory-inhibitory balance to large-scale network dynamics. This model could explain how region-specific disruptions can produce the heterogeneous patterns of DMN dysfunction observed across brain disorders. Significance Statement To respond to important external events, the brain must suppress internal thought processes implicating the default mode network. This suppression fails in psychiatric conditions, that also involve imbalances between excitatory and inhibitory neurons. However, the connection between cellular imbalances and default-mode-network dysfunction has remained unclear. We used brain-wide computer simulations incorporating neuronal properties to understand how imbalance at the cellular scale disrupts network function. Our simulations reveal the precise excitatory-inhibitory balance needed for normal suppression. Additionally, we identified distinct failure modes and discovered that certain brain hubs are more vulnerable than others to disruption. Our findings reveal how cellular alterations scale up to cause network-level dysfunction, potentially guiding treatments targeting specific brain regions in individual patients.

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