Metastable Dynamics Emerge from Local Excitatory-Inhibitory Homeostasis in the Cortex at Rest
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The human cortex displays highly metastable dynamics at rest, underlying the spontaneous exploration of large-scale network states. This metastability depends on edge-of-bifurcation dynamics at the circuit level, which emerge due to the local control of firing rates through multiple mechanisms of excitatory-inhibitory (E-I) homeostasis. However, it is unclear how the distinct forms of homeostasis contribute to the metastability of large-scale cortical networks. Here, we propose that individual mechanisms of E-I homeostasis contribute uniquely to the emergence of metastable dynamics and resting-state functional networks and test that hypothesis in a large-scale model of the human cortex. We show that empirical networks and dynamics can only be reproduced when accounting for multiple mechanisms of E-I homeostasis. More specifically, while the homeostasis of excitation and inhibition enhances metastability, the complementary regulation of intrinsic excitability ensures moderate levels of synchrony, maximizing the complexity of functional networks. Furthermore, the modulation of distance-to-bifurcation by the homeostasis of excitation and intrinsic excitability supports collective dynamics by compensating for strong input fluctuations in strongly connected areas. Altogether, our results show that cortical networks self-organize toward maximal metastability through the multi-factor homeostatic regulation of E-I balance, which controls local edge-of-bifurcation dynamics. Therefore, the functional benefits of combining multiple homeostatic mechanisms transcend the circuit level, supporting the rich spontaneous dynamics of large-scale cortical networks.
Experimental studies have consistently shown that cortical circuits maintain a precise homeostasis of excitatory-inhibitory (E-I) balance, thereby optimizing local dynamics. While it is well-established that multiple homeostatic mechanisms are involved in this local regulation, it remains unclear how each contributes to the large-scale dynamics of cortical networks. This study presents evidence that, through E-I homeostasis, the cortex can self-organize towards a regime of highly complex and metastable spontaneous dynamics. Crucially, we demonstrate that this results from the synergistic action of multiple homeostatic mechanisms. Our findings advance our understanding of E-I homeostasis as a process of self-organization, demonstrating its key role in the maintenance of metastable dynamics in large-scale cortical networks.
