26.11.2015: Gianluigi Mongillo

Inhibitory plasticity defines the realm of excitatory plasticity.

The neocortical network is largely excitatory as most neurons and most synapses are excitatory. Accordingly, it is widely held that cortical dynamics and computation are primarily determined by the pattern of excitatory synaptic connections. However, there is strong experimental evidence that excitatory connectivity is constantly re-organizing, even in the absence of explicit learning. This raises the question of how functionality is maintained over time in volatile networks. Here, we quantified spontaneous synaptic re-organization by chronically imaging thousands of dendritic spines in the mouse auditory cortex, and investigated its consequences in a balanced network model of a cortical region. Surprisingly, we found that the firing rates of individual neurons are stably maintained despite massive excitatory plasticity. By contrast, they are exquisitely sensitive to changes in the pattern of inhibitory synaptic connections. We show that this is a direct consequence of the different distributions of firing rates of the excitatory and inhibitory neurons. Computationally, these results indicate that inhibitory plasticity – but not excitatory plasticity – is both necessary and sufficient for large scale changes in the patterns of network's spiking activity. Taken together, our findings show that inhibition can maintain functional stability in a volatile network by bounding the impact of excitatory synaptic re-organization.