Introduction Progressive loss of synapses and neurons can reshape circuit activity before complete network failure. Yet it remains unclear why some spiking networks preserve weakly active, irregular dynamics under structural damage while others drift toward abnormal firing, variability or synchrony [1,2]. This problem is difficult because structural loss, baseline dynamics and excitatory-inhibitory organization interact. We address two questions: which factors support resilience during degeneration, and can activity changes be predicted from network structure?
Methods We simulated an empirical layer-4 cortical microcircuit [3] and matched synthetic networks: Erdős-Rényi, small-world, scale-free, and two inhibition-promoting variants. All networks were calibrated to comparable baseline spiking activity. Degeneration was applied in two families, synaptic and neuronal, each with five pruning rules spanning random, peripheral, central and broadcaster-targeted damage. For each network, we related firing rate, variability and synchrony to global and subpopulation-resolved weighted structural descriptors.
Results Inhibition-promoting architectures, including subpopulation-constrained and inhibitory-hub networks, resisted degeneration at moderate inhibitory strength, whereas generic synthetic networks drifted more strongly. Stronger inhibition could stabilize all network classes, showing that architecture changes the inhibitory gain required for resilience rather than defining an absolute resilient category. Effective synaptic weight organized within-class activity trends, while weight-aware E/I interaction features captured cross-architecture differences and predicted activity changes.
Discussion These results suggest that circuits may be especially vulnerable when degeneration weakens inhibitory control or disrupts where inhibition is positioned. They also offer a possible interpretation of maladaptive sprouting: adding connections semi-randomly may restore connection number while blurring the fine inhibitory organization needed for stability. Conversely, therapies that boost inhibition or improve its recruitment could help stabilize activity under structural loss.
References [1] van Vreeswijk C, Sompolinsky H. Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science. 1996.
[2] Brunel N. Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. Journal of Computational Neuroscience. 2000. [3] Landau ID, Egger R, Dercksen VJ, Oberlaender M, Sompolinsky H. The impact of structural heterogeneity on excitation-inhibition balance in cortical networks. Neuron. 2016.
Acknowledgement This work was supported by the PEPR Sant´e Num´erique program (France 2030), project “Brain Health Trajectories (BHT)”, implemented by the Agence Nationale de la Recherche (ANR) under grant number ANR-22-PESN-0012-BHT.
