Modeling neuromodulatory-mediated modifications of calcium-based plasticity rules that prevent homeostatic reset during switches in firing activity

Synaptic plasticity refers to the ability of neurons to change their connections based on the correlation level in the activity of neighboring neurons. In parallel, neuron activity is affected by brain states. For example, during wake-sleep cycles, neurons switch from tonic to bursting activity. This firing pattern fluctuation is organized by neuromodulators – signaling molecules that induce reversible changes in functional properties of neurons or synapses.

In our previous work, we have shown that synaptic plasticity rules such as triplet [Pfister,2006] and calcium-dependent models [Graupner,2016; Shouval,2002] are not compatible with switches in firing patterns. Using a conductance-based model robust to neuromodulation and synaptic plasticity [Jacquerie,2021], we built a cortical network to study the evolution of synaptic weights during switches in firing activity. We reproduced experimental plasticity protocol validated in wakefulness [Sjostrom,2001]. Then, switching the network from tonic to burst without any modification of the synaptic rule leads to a homeostatic reset. All synaptic weights converge towards the same basal value whatever the rule due to neuromodulation of neuronal activity.

This reset is overcome in the triplet model thanks to neuromodulators that alter the shape of the spike-time dependent curve as demonstrated in [Gonzalez-Ruedas,2018]. To uncover the biological mechanisms of this change, we translated this modification in calcium-based rules by neuromodulating the calcium thresholds, potentiation and depression levels, as well as the learning rates. Our model is a powerful tool that leads the way to unravel biological explanations of the bursting activity role during sleep and its support on the down-selection mechanism.