Brain circuits display modular architecture at different scales of organi- zation [5]. Such neural assemblies are typically associated to functional specialization but the mechanisms leading to their emergence and con- solidation still remain elusive. In addition, it has been shown that inhibitory plasticity has a decisive impact on long-term maintaining of memory [4]. In this study [1], we investigate how inputs can be learned to shape modular structures and how to maintain this structure in the long term emphasizing the role of inhibition in this maintenance. In particular, we focus on the role of partially synchronized dynamics for the creation and maintenance of structural modules in neural circuits by considering a network of excitatory and inhibitory θ-neurons [3] with plastic Hebbian synapses. The learning process consists of an entrainment to temporally alternating stimuli that are applied to sep- arate regions of the network. This entrainment leads to the emergence of modular structures. Then after the learning phase, the network dynamics is analysed during resting state (i.e. spontaneous activity without external stimulation). Contrary to common practice in artifi- cial neural networks - where the acquired weights are typically frozen after the learning session - we allow for synaptic adaptation even after the learning phase. We find that the presence of inhibitory neurons in the network is crucial for the emergence and the post-learning con- solidation of the modular structures. Indeed networks made of purely excitatory neurons or of neurons not respecting Dale’s principle [2] are unable to maintain the modular architecture induced by the entrained stimuli. We also demonstrate that the number of inhibitory neurons in the network is directly related to the maximal number of neural as- semblies that can be consolidated, supporting the idea that inhibition has a direct impact on the memory capacity of the neural network. Preliminary analysis of spiking neural networks with STDP show that inhibition favours spontaneous recalls of stored items promoting their consolidation. References: [1] Rapha ̈el Bergoin, Alessandro Torcini, Gustavo Deco, Mathias Quoy, and Gorka Zamora-Lo ́pez, under publication, 2023. [2] H Dale. Br Med J, 2:11611163, 1934. [3] G Bard Ermentrout and Nancy Kopell. SIAM journal on applied mathematics, 46(2):233-253, 1986. [4] Gianluigi Mongillo, Simon Rumpel, and Yonatan Loewenstein. Na- ture neuroscience, 21(10):1463-1470, 2018. [5] Gorka Zamora-Lo ́pez, Changsong Zhou, and Ju ̈rgen Kurths. Fron- tiers in neuroscience 5:83, 2011.