Sleep exerts many effects on mammalian forebrain networks, including homeostatic effects on both synaptic strengths and firing rates. We used large-scale recordings to examine the activity of neurons in the frontal cortex of rats and firstly observed that the distribution of pyramidal cell firing rates was wide and strongly skewed towards high firing rates. Moreover, neurons from different parts of that distribution were differentially modulated by sleep sub-states. Periods of nonREM sleep reduced the activity of high firing rate neurons and tended to upregulate firing of slow firing neurons. By contrast, the effect of REM was to reduce firing rates across the entire rate spectrum. Microarousals, interspersed within nonREM epochs, increased firing rates of slow firing neurons. The net result of sleep was to homogenize the firing rate distribution. These findings are at variance with current homeostatic models and provide a novel view of sleep in adjusting network excitability.

g-Aminobutyric acid (GABA)ergic inputs are strategically positioned to gate synaptic integration along the dendritic arbor of pyramidal cells. However, their spatiotemporal dynamics during behavior are poorly understood. Using an optical-tagging electrophysiological approach to record and label somatostatin-expressing (Sst) interneurons (GABAergic neurons specialized for dendritic inhibition), we discovered a layer-specific modulation of their activity in behaving mice. Sst interneuron subtypes, residing in different cortical layers and innervating complementary laminar domains, exhibited opposite activity changes during transitions to active wakefulness. The relative weight of vasoactive intestinal peptide-expressing (Vip) interneuron-mediated inhibition of distinct Sst interneurons and cholinergic modulation determined their in vivo activity. These results reveal a state-dependent laminar influence of Sst interneuronmediated inhibition, with implications for the compartmentalized regulation of dendritic signaling in the mammalian neocortex.

During non-rapid eye movement (NREM) sleep, neuronal populations in the mammalian forebrain alternate between periods of spiking and inactivity. Termed the slow oscillation in the neocortex and sharp wave-ripples in the hippocampus, these alternations are often considered separately but are both crucial for NREM functions. By directly comparing experimental observations of naturally-sleeping rats with a mean field model of an adapting, recurrent neuronal population, we find that the neocortical alternations reflect a dynamical regime in which a stable active state is interrupted by transient inactive states (slow waves) while the hippocampal alternations reflect a stable inactive state interrupted by transient active states (sharp waves). We propose that during NREM sleep in the rodent, hippocampal and neocortical populations are excitable: each in a stable state from which internal fluctuations or external perturbation can evoke the stereotyped population events that mediate NREM functions.

Sleep is thought to mediate mnemonic and homeostatic functions. However, the mechanism by which this brain state can implement both the “selective” plasticity needed to consolidate novel memory traces as well as the “general” plasticity necessary to maintain a well-functioning neuronal system is unclear. Recent findings show that both of these functions differentially affect neurons based on their intrinsic firing rate, a ubiquitous neuronal heterogeneity. Furthermore, they are both implemented by the NREM slow oscillation, which also distinguishes neurons based on firing rate during sequential activity at the DOWN->UP transition. These findings suggest a mechanism by which spiking activity during the slow oscillation acts to maintain network statistics that promote a skewed distribution of neuronal firing rates, and “perturbation” of that activity by hippocampal replay acts to integrate new memory traces into the existing cortical network.