Prof. Martin Dresler on Sleep – exploring a fascinating mystery
Martin Dresler is an associate professor of cognitive neuroscience at the Donders Institute / Radboud University Medical Center.
Trained in biopsychology, philosophy, and mathematics, he completed his PhD and postdoc on cognitive neuroscience at the Max Planck Institute of Psychiatry, Oxford University and Stanford University, before establishing his lab at the Donders Institute.
The research of his group centers on the cognitive neuroscience of sleep, including cognitive processes occurring during sleep and the role of sleep for memory processes, neuroplasticity and general cognitive functioning.
Principal investigator - Donders Institute for Brain, Cognition and Behaviour
Dr M. Dresler (Martin) - Radboud Universiteit
Dr Elisabetta Burchi
Since the dawn of civilization, sleep has fascinated and inspired scholars, poets, and philosophers.
It wasn’t until the 20s of the last century with the documentation of electroencephalographic (EEG) activity from the surface of the skull that we had a scientific framework for sleep research.
The description of sleep staging based on EEG changes, followed by the discovery of rapid eye movement (REM) sleep consequently propelled sleep research to the forefront of neuroscience.
At the Donders Institute, in the Netherlands, Prof Dresler leads the “Sleep & Memory lab”, focused on unveiling the secrets around sleep and the role of sleep for cognitive functioning.
Dear Prof Dresler, assuming an evolutionary perspective, sleep must serve several vital functions to overcompensate for compelling the individual in a non-responsive state.
Beyond the pleasure associated, what are the biological functions of what is perceived as a good night of sleep?
We know that sleep serves several functions, ranging from very basic biological to higher cognitive ones.
A good night’s sleep contributes to memory consolidation, emotional processing, and metabolic clearance in the brain, but it has also impact on endocrine regulation, energy metabolism, and even immunological memory and responses to vaccines.
That is fascinating!
We have mentioned the “quality” of sleep, and this is generally reduced to a time consideration.
Beyond time, are there any other objective parameters that can help defining the quality of sleep n terms of effective regulation of the functions you mentioned before?
Good point! Given the breadth of its scope, making sure that we have a good quality of sleep is pretty relevant.
However, there is no good correlation between subjective and objective evaluation regarding quality of sleep.
For instance, there are often discrepancies between self-reported hours of sleep and polysomnographic measures.
Some electrophysiological parameters have been instead found to be good markers of poor subjective sleep quality, for example fragmentation of REM sleep.
A parameter that is often used as a simple objective indicator of sleep quality is sleep efficiency, i.e. the percentage of time spent asleep from lights-off in the evening to lights-on in the morning.
A good sleep efficiency is considered to be between 85% and 95%; if it is higher, it may indicate a state of sleep deprivation; if it is lower, it may indicate pathological processes.
If you are not a sleep scientist, you shouldn’t worry too much about precise numbers though: the best indicator for sufficient and healthy sleep is simply to feel fresh and vigilant during the day, whereas obsessing too much with supposed ideal sleep timing may result in developing sleep disorders.
We cannot neglect the most mysterious of the topics – dreams.
The content and function of dreams have been topics of scientific, philosophical, and religious interest throughout recorder history: what did the neurosciences discover about dreams and their functions?
Dreams are indeed both fascinating and difficult to study in neuroscience, as we have to somehow bring objective measures of neurophysiology together with the subjectivity and unreliability of dream reports.
A very helpful tool – and fascinating phenomenon in itself – that we are increasingly making use of is lucid dreaming: when a dreamer realizes to be in a dream during ongoing sleep.
This skill can be used to ask research participants to intentionally perform certain tasks during their sleep, which allows us to study dream content in a much more systematic fashion.
Even more mysterious – and difficult to study – than dream neurophysiology is the possible function of dreaming.
A widely discussed theory that I find very convincing is that dreaming serves as a simulation of reality: a virtual training ground in which new behaviors can be learned and trained, in particular new skills to cope with threats or social situations.
What’s the most exciting project you are currently working on? What are the gaps that you see in sleep science and how could we address them?
A major problem of sleep research is that requires a considerable time investment to study even single nights in the sleep laboratory, which typically leads to small studies with only a few dozen participants at best.
We are therefore increasingly using wearable sleep EEG systems to study sleep in multiple consecutive nights in larger groups of participants in more naturalistic home settings.
We are planning to expand this research line towards citizen science approaches, working together with groups of sleep and dream enthusiasts to conduct larger studies, and tap into the expertise of sleep hacking and dream communities.
Such private experimentation with different strategies of sleep monitoring and modulation can deliver interesting insights that would be difficult to acquire to a similar extend in the laboratory: from self-quantifiers who record their sleep over months or years, or polyphasic sleepers who try to reduce their total sleep time by adopting different sleep schedules, to lucid dreamers who develop and train different strategies to increase their awareness during sleep and dreaming.
It is exciting to see that wearable technology has the potential to become a flywheel in sleep research as well as, more broadly, in healthcare– not only helping to capture continuous physiological data, but also to potentially modulate physiological functions in a personalized fashion.
In this regard, it may be interesting to investigate the potential of tVNS in the promotion of good sleep and cognitive enhancement.
Thanks again Martin!