Inhibitory neurons control the consolidation of neural assemblies via adaptation to selective stimuli
Résumé
Brain circuits display modular architecture at different scales of organization [5]. Such neural assemblies are typically associated to functional specialization but the mechanisms leading to their emer- gence and consolidation 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 in- puts 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 dy- namics for the creation and maintenance of structural modules in neu- ral circuits by considering a network of excitatory and inhibitory θ- neurons [3] with plastic Hebbian synapses. The learning process con- sists of an entrainment to temporally alternating stimuli that are ap- plied to separate 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 artificial 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 consolidation 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 assemblies 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] Raphaël Bergoin, Alessandro Torcini, Gustavo Deco, Mathias Quoy, and Gorka Zamora-López. Inhibitory neurons control the consolidation of neural assemblies via adaptation to selective stimuli. 2023.
[2] H Dale. Pharmacology and nerve endings. Br Med J, 2:1161–1163, 1934.
[3] G Bard Ermentrout and Nancy Kopell. Parabolic bursting in an ex- citable system coupled with a slow oscillation. SIAM journal on applied mathematics, 46(2):233–253, 1986.
[4] Gianluigi Mongillo, Simon Rumpel, and Yonatan Loewenstein. Inhibitory connectivity defines the realm of excitatory plasticity. Nature neuro- science, 21(10):1463–1470, 2018.
[5] Gorka Zamora-López, Changsong Zhou, and Jürgen Kurths. Exploring brain function from anatomical connectivity. Frontiers in neuroscience, 5:83, 2011.
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