Criticality and universality in neuronal cultures during 'up' and 'down' states

Abstract

The brain can be seen as a self-organized dynamical system that optimizes information processing and storage capabilities. This is supported by studies across scales, from small neuronal assemblies to the whole brain, where neuronal activity exhibits features typically associated with phase transitions in statistical physics. Such a critical state is characterized by the emergence of scale-free statistics as captured, for example, by the sizes and durations of activity avalanches corresponding to a cascading process of information flow. Another phenomenon observed during sleep, under anesthesia, and in in vitro cultures, is that cortical and hippocampal neuronal networks alternate between "up" and "down" states characterized by very distinct firing rates. Previous theoretical work has been able to relate these two concepts and proposed that only up states are critical whereas down states are subcritical, also indicating that the brain spontaneously transitions between the two. Using high-speed high-resolution calcium imaging recordings of neuronal cultures, we test this hypothesis here by analyzing the neuronal avalanche statistics in populations of thousands of neurons during "up" and "down" states separately. We find that both "up" and "down" states can exhibit scale-free behavior when taking into account their intrinsic time scales. In particular, the statistical signature of "down" states is indistinguishable from those observed previously in cultures without "up" states. We show that such behavior can not be explained by network models of non-conservative leaky integrate-and-fire neurons with short-term synaptic depression, even when realistic noise levels, spatial network embeddings, and heterogeneous populations are taken into account, which instead exhibits behavior consistent with previous theoretical models. Similar differences were also observed when taking into consideration finite-size scaling effects, suggesting that the intrinsic dynamics and self-organization mechanisms of these cultures might be more complex than previously thought. In particular, our findings point to the existence of different mechanisms of neuronal communication, with different time scales, acting during either highactivity or low-activity states, potentially requiring different plasticity mechanisms. Author summaryUp and down states, where populations of neurons transition between periods of high and low-frequency activity, are ubiquitous in the brain. They are present during development, sleep, and anesthesia, and have been associated with memory consolidation and the regulation of homeostatic processes. Using large-scale high-speed calcium imaging recordings of neuronal cultures, we show that self-similar behavior can appear during both up and down states, but with different characteristic timescales. Detailed simulations of neuronal cultures are only able to capture the statistics during up states, suggesting that a different mechanism might be governing the dynamics of the down states. The presence of scale-free statistics with switching time scales points to novel self-organization mechanisms in neuronal systems.