prof. Peter Achermann!
prof. Peter Achermann is Emeritus Professor at the University of Zurich. In his research he focuses on basic and clinical aspects of sleep regulation and analysis of EEG signals, and over the past decade, mainly on the trait aspects in sleep and wake EEG, brain connectivity and cerebral blood flow during sleep and the process of sleep onset and the borderland between wakefulness and sleep. He's considered as a top sleep EEG expert and is internationally recognized for his contribution to sleep EEG analysis, modelling od sleep regulation and circadian rhytms.
Title: Cortical neuronal activity and sleep homeostasis
According to traditional theory, the need for sleep accumulates during wakefulness and dissipates during sleep. A key notion is that sleep-wake history determines the levels of homeostatic sleep pressure, referred to as Process S which is reflected in electroencephalogram (EEG) slow wave activity (SWA, EEG power in 0.5–4 Hz range) during sleep. It has been widely used to obtain insights into sleep regulatory mechanisms. The notion of sleep as a local, activity-dependent process suggests that neuronal activity history must be integrated to determine the dynamics of global Process S. We developed novel mathematical models of Process S based on cortical activity recorded in freely behaving mice, describing the local Process S as a function of the deviation of neuronal firing rates from a locally defined set-point, independent of the global sleep-wake state. Averaging locally derived Processes S and their rate parameters yielded values resembling those obtained from EEG SWA and global vigilance states. Although time awake is considered to be the main variable affecting sleep need, investigating the role of additional extrinsic influences on the dynamics of Process S remains essential to understand its neurophysiological substrates. Surprisingly, a combination of experimental and modeling approaches to investigate the influence of waking behavior and time of day on sleep homeostasis revealed that the mechanisms underlying Process S dynamics are mostly resilient to external factors.