Alexander A. Borbély’s research while affiliated with University of Zurich and other places

The two-process model of sleep regulation has served as a conceptual framework in the last four decades for understanding sleep physiology. In the 1970s, long-term recordings of sleep in rats were obtained thanks to EEG telemetry. NonREM sleep and REM sleep were found to differ in their time course and response to light-dark protocols. There were indications for their coupling to the circadian system, in particular the light-dark and the dark-light transitions. With the advent of quantitative EEG analysis, slow-wave activity in nonREM sleep was recognized as a sleep-wake-dependent variable. The term “sleep homeostasis” was coined to specify the regulated balance between sleep and waking. The regulatory homeostatic process was designated as “Process S”. In the two-process model, its interaction with the circadian pacemaker “Process C” can account for sleep duration under various experimental protocols. Local, use-dependent slow-wave activity changes were demonstrated in both humans and rats by the selective, unilateral activation of a cortical region prior to sleep. Finding that rest in invertebrates has sleep-like regulatory properties opened a new realm of animal studies. Comparative sleep studies in a broad variety of animal species confirmed the validity of the basic concepts of the two-process model. Recent studies have addressed sleep-related changes of brain temperature as an indicator of brain metabolism; the application of the model to Drosophila; the divergence of cortical and subcortical states; and sleep in an increasing number of species and taxa.

The two-process model serves as a major conceptual framework in sleep science. Although dating back more than four decades, it has not lost its relevance for research today. Retracing its origins, I describe how animal experiments aimed at exploring the oscillators driving the circadian sleep-wake rhythm led to the recognition of gradients of sleep states within the daily sleep period. Advances in signal analysis revealed that the level of slow-wave activity in non-rapid eye movement sleep electroencephalogram is high at the beginning of the 12-light period and then declines. After sleep deprivation, the level of slow-wave activity is enhanced. By scheduling recovery sleep to the animal's activity period, the conflict between the sleep-wake-dependent and the circadian influence resulted in a two-stage recovery pattern. These experiments provided the basis for the first version of the two-process model. Sleep deprivation experiments in humans showed that the decline of slow-wave activity during sleep is exponential. The two-process model posits that a sleep-wake-dependent homeostatic process (Process S) interacts with a process controlled by the circadian pacemaker (Process C). At present, homeostatic and circadian facets of sleep regulation are being investigated at the synaptic level as well as in the transcriptome and proteome domains. The notion of sleep has been extended from a global phenomenon to local representations, while the master circadian pacemaker has been supplemented by multiple peripheral oscillators. The original interpretation that the emergence of sleep may be viewed as an escape from the rigid control imposed by the circadian pacemaker is still upheld.

In 2016 we reported evidence for associative learning in plants (Gagliano et al., 2016). In view of the far-reaching implications of this finding we welcome the attempt made by Markel to replicate our study (Markel, 2020). However, as we discuss here, the protocol employed by Markel was unsuitable for testing for associative learning.

Motor activity recording by a wrist-worn device is a common method to monitor the rest-activity cycle. The first author wore an actimeter continuously for more than three decades, starting in 1982 at the age of 43.5 years. Until November 2006 analysis was performed on a 15-min time base, and subsequently on a 2-min time base. The timing of night-time sleep was determined from the cessation and re-occurrence of daytime-level activity. Sleep duration declined from an initial 6.8 to 6 h in 2004. The declining trend was reversed upon retirement, whereas the variance of sleep duration declined throughout the recording period. Before retirement, a dominant 7-day rhythm of sleep duration as well as an annual periodicity was revealed by spectral analysis. These variations were attenuated or vanished during the years after retirement. We demonstrate the feasibility of continuous long-term motor activity recordings to study age-related variations of the rest-activity cycle. Here we show that the embeddedness in a professional environment imparts a temporal structure to sleep duration.

In complex and ever-changing environments, resources such as food are often scarce and unevenly distributed in space and time. Therefore, utilizing external cues to locate and remember high-quality sources allows more efficient foraging, thus increasing chances for survival. Associations between environmental cues and food are readily formed because of the tangible benefits they confer. While examples of the key role they play in shaping foraging behaviours are widespread in the animal world, the possibility that plants are also able to acquire learned associations to guide their foraging behaviour has never been demonstrated. Here we show that this type of learning occurs in the garden pea, Pisum sativum. By using a Y-maze task, we show that the position of a neutral cue, predicting the location of a light source, affected the direction of plant growth. This learned behaviour prevailed over innate phototropism. Notably, learning was successful only when it occurred during the subjective day, suggesting that behavioural performance is regulated by metabolic demands. Our results show that associative learning is an essential component of plant behaviour. We conclude that associative learning represents a universal adaptive mechanism shared by both animals and plants.