Sleep Science Friday Series

Psychedelic 5-MeO-DMT induces slow waves in the brain of awake mice

In this edition of Sleep Science Friday, Dr. Lyudmila Korostovtseva (Chair of the ESRS Digital and Communication Committee) speaks with Dr. Benjamin Bréant about his recent study investigating the effects of the psychedelic compound 5-MeO-DMT on brain activity and behaviour in mice.  The study reports the emergence of slow-wave activity typically associated with NREM sleep during behavioural wakefulness, alongside neuronal off-periods and suppression of theta rhythm. The findings indicate a dissociated brain state combining electrophysiological features of sleep with behavioural features of wakefulness.  The study also examines effects on sleep homeostasis, including changes in slow-wave activity following sleep deprivation, as well as the involvement of serotonergic mechanisms, particularly 5-HT1A receptors.

AI in REM sleep behaviour disorder (RBD) research

This week, Dr Matias Rusane interviews Dr Matteo Cesari, a leading expert in the application of artificial intelligence to REM sleep behaviour disorder (RBD). Following the current theme “Sleep in the age of technology” of the ECN committee, they discussed the impact of AI on RBD research. RBD is a parasomnia characterised by abnormal muscle activity and dream enactment during REM sleep. The isolated form of the disorder [https://doi.org/10.1186/s13024-025-00809-0] (iRBD) is now widely recognised as an early stage of alpha-synuclein-related neurodegenerative diseases, such as Parkinson’s disease. Studies [https://doi.org/10.1016/j.smrv.2018.09.008] demonstrate that 80–90% of individuals diagnosed with iRBD develop neurodegenerative symptoms within 10-15 years. As such, this population represents an ideal cohort for clinical trials aimed at testing disease-modifying therapies. Recent advances suggest that AI could play a transformative role in several key areas of RBD research and clinical management: - Diagnosis: Current diagnostic guidelines rely on labour-intensive manual and visual analysis of polysomnographic data to detect abnormal muscle tone and behaviours during REM sleep. AI offers a promising alternative by enabling faster, automated, and objective assessment, thereby supporting clinicians in making more efficient and accurate diagnoses. - Screening: At present, RBD diagnosis is limited to specialised neurological sleep laboratories, contributing to widespread underdiagnosis. However, the integration of AI with emerging wearable technologies could enable large-scale screening in the general population. This capability will become increasingly important as disease-modifying treatments become available, highlighting the need for early detection. - Prognosis: AI is also being explored for its ability to detect complex patterns across sleep recordings, brain imaging, and biomarker data. These insights may help predict the timeline for progression from iRBD to overt alpha-synucleinopathies. In turn, this predictive power could allow for more personalised treatment planning and early intervention strategies. In conclusion, advancements in AI hold great promise for transforming RBD research and clinical care. Through collaborative efforts across institutions and disciplines, the field is well-positioned to develop innovative tools that enhance diagnosis, enable large-scale screening, and improve prognostic accuracy. These developments have the potential to significantly impact clinical practice and patient care. In the interview, Dr. Cesari also shares his advice for early career professionals who want to work with AI in sleep.

Sleep, Biological Sex Differences, and Alzheimer's Disease

In this edition of Sleep Science Friday, Dr. Adriana Michalak is joined by Dr. Claudia Barth and Dr. Laura Stankeviciute to explore two often underestimated yet critical dimensions of Alzheimer’s Disease: biological sex differences and sleep.  Understanding Alzheimer's Disease AD is the most common type of dementia, affecting an estimated 7 million people in Europe alone as of 2025 (European Brain Council [https://www.braincouncil.eu/projects/rethinking-alzheimers-disease/]). The disease leads to degeneration of nerve cells and neuroinflammation due to accumulation of toxic extracellular amyloid plaques (Aβ), intracellular neurofibrillary tangles, and abnormal activation of microglia. These alterations result in neuronal death, brain tissue damage, and progressive brain atrophy, leading to cognitive decline and other behavioural alterations. Alzheimer's is influenced by both modifiable risk factors—such as diabetes, high blood pressure, physical activity, diet, and sleep—and non-modifiable ones like age, genetics, and biological sex. Sex-Specific Vulnerability: A Research Gap Women account for nearly two-thirds of AD cases, yet the impact of hormonal changes remains poorly understood (Barth et al., 2023 [https://www.thelancet.com/journals/landia/article/PIIS2213-8587(23)00224-3/abstract]). Major hormonal transitions such as pregnancy and menopause may represent critical windows of vulnerability in developing AD—a topic we discussed extensively with neuroscientist Dr. Claudia Barth. The Sleep-AD Connection As Dr. Laura Stankeviciute stated, sleep is not a lifestyle choice but a biological necessity that must be prioritised and protected. Sleep disruption is both a symptom and driver of AD progression, illustrating a two-way interaction between brain degeneration, cognitive decline, and disturbed sleep (Ju et al., 2013 [https://pubmed.ncbi.nlm.nih.gov/24366271/]; Bubu et al., 2017 [https://academic.oup.com/sleep/article-abstract/40/1/zsw032/2661823?redirectedFrom=fulltext]). These disturbances affect quality of life for patients and caregivers and often hasten patients' institutionalisation (Petit et al., 2017 [https://www.sciencedirect.com/science/article/abs/pii/B9780323242882000969]). The connection becomes particularly relevant during hormonal transitions related to menopause. During menopause, the number of women reporting sleep problems nearly doubles. Difficulties include falling and staying asleep, frequent awakenings, and daytime fatigue, often intensified by hot flushes and mood disturbances, such as depression (Baker et al., 2019 [https://pmc.ncbi.nlm.nih.gov/articles/PMC6092036/]). Technology and Future Directions During the interview, we also emphasised incorporating wearable rest-activity pattern measures alongside traditional sleep studies, as sleep unfolds over time, and a single-night polysomnographic recording in the sleep laboratory fails to account for menstrual or seasonal changes. This longitudinal recording is particularly valuable in preclinical AD, as capturing early sleep and circadian disturbances could offer windows for timely, protective interventions. Co-Creation in Dementia Research We discussed the vulnerability of caregivers (predominantly women), noting the striking pattern that women are significantly more willing to participate as study volunteers in dementia research, and the importance of engaging participants as partners in science co-creation. As scientists, we are trusted sources of knowledge, but our participants' insights are invaluable in making science meaningful for all.