Cost-efficiency trade-off in neural activity
The brain is highly energy consuming, therefore is under strong selective pressure to achieve cost-efficiency in both cortical connectivity and activity. However, cost-efficiency as a design principle for cortical activities has been rarely studied. Especially it is not clear how cost-efficiency is related to ubiquitously observed multi-scale properties: irregular firing,oscillations and neuronal avalanches. Here we demonstrate that these prominent properties can be simultaneously observed in a generic, biologically plausible neural circuit model that captures excitation-inhibition balance and realistic dynamics of synaptic conductance. Their co-emergence achieves minimal energy cost as well as maximal energy efficiency on information capacity, when neuronal firings are coordinated and shaped by moderate synchrony to reduce otherwise redundant spikes, and the dynamical clustering are maintained in the form of neuronal avalanches. Such cost-efficient neural dynamics can be employed as a foundation for further efficient information processing under energy constraint.