Abstract
The brain is constantly challenged by severely destabilizing forces: proteins turn over rapidly, Hebbian modifications alter and introduce positive feedback into networks, and environments change over many timescales. Homeostatic plasticity mechanisms, which operate via negative feedback, are believed to compensate for these changes and constrain neuronal activity to a firing rate (FR) set point1,2,3. For decades, it has been widely assumed that activity in neural networks is robust as a direct result of the widespread expression of FR homeostasis1,4. Here we reveal that network dynamics are stabilized independent of excitatory FR homeostasis and that cortical networks actively self-organize around an ideal computational regime.
We continuously tracked network spiking activity in the visual cortex (V1) of freely behaving rats for nine days. We found that, under baseline conditions, networks of excitatory neurons are robustly organized around criticality, a regime known to maximize information capacity and dynamic range. Monocular deprivation (MD) revealed a dissociation of excitatory FRs and network dynamics. MD immediately and severely disrupted network organization, which returned precisely to criticality over 48h. In contrast, both the excitatory FR drop and the subsequent FR recovery trailed the timecourse of network changes by more than 30h. Model investigations suggest a role for inhibitory neurons in maintaining critical dynamics. Collectively, these results show that complex activity in cortical circuits is actively maintained near criticality and that this organization is not explained by previously identified mechanisms of pyramidal neuron FR homeostasis.
