Fabian‐Xosé Fernandez

Decades of studies have shown that eliminating circadian rhythms of mammals does not compromise their health or longevity in the laboratory in any obvious way. These observations have raised questions about the functional significance of the mammalian circadian system, but have been difficult to address for lack of an appropriate animal model. Surgical ablation of the suprachiasmatic nucleus (SCN) and clock gene knockouts eliminate rhythms, but also damage adjacent brain regions or cause developmental effects that may impair cognitive or other physiological functions. We developed a method that avoids these problems and eliminates rhythms by noninvasive means in Siberian hamsters ( Phodopus sungorus ). The present study evaluated cognitive function in arrhythmic animals by using a hippocampal-dependent learning task. Control hamsters exhibited normal circadian modulation of performance in a delayed novel-object recognition task. By contrast, arrhythmic animals could not discriminate a novel object from a familiar one only 20 or 60 min after training. Memory performance was not related to prior sleep history as sleep manipulations had no effect on performance. The GABA antagonist pentylenetetrazol restored learning without restoring circadian rhythms. We conclude that the circadian system is involved in memory function in a manner that is independent of sleep. Circadian influence on learning may be exerted via cyclic GABA output from the SCN to target sites involved in learning. Arrhythmic hamsters may have failed to perform this task because of chronic inhibitory signaling from the SCN that interfered with the plastic mechanisms that encode learning in the hippocampus.

Sleep is entwined across many physiologic processes in the brain and periphery, thereby exerting tremendous influence on our well-being. Yet sleep exists in a social-environmental context. Contextualizing sleep health with respect to its determinants—from individual- to societal-level factors—would enable neuroscientists to more effectively translate sleep health into clinical practice. Key challenges and opportunities pertain to (i) recognizing and exploring sleep’s functional roles, (ii) clarifying causal mechanisms in relation to key outcomes, (iii) developing richer model systems, (iv) linking models to known contextual factors, and (v) leveraging advances in multisensory technology. Meeting these challenges and opportunities would help transcend disciplinary boundaries such that social-environmental considerations related to sleep would become an ever-greater presence in the clinic.