Sleep is critical for both health and cognition. Our lab is developing ways to manipulate sleep to maximise its beneficial properties.
Specifically, we are developing ways to actively manipulate the neural processing that occurs during sleep to enhance health and cognition. We are piloting methods that will help people enhance memory, disarm negative emotions, and combat cognitive decline through ageing while they sleep.
Our research also investigates brain plasticity, focusing specifically on the changes in behaviour neural structure and activity which occur after initial learning. This can be done either by directly influencing the neural oscillations in sleep (enhancing some and suppressing others) or by influencing which memories are replayed in sleep.
In both cases, the manipulations are usually achieved through the soft presentation of sounds during sleep. Over the last few years, we have coined the term ‘sleep engineering’ to capture the spirit of what we are doing.
Aims
- Understand how neural oscillations in sleep benefit cognition and general health
- Develop ways to enhance these neural oscillations
- Investigate the differences between memory replay in REM and SWS
- Develop machine learning methods to identify neural replay during sleep
- Understand how memory replay in sleep influences consolidation, and specifically determine how memory replay:
- enhances integration processes
- can be used to enhance creativity
- impacts on emotional content
Internships
We are always looking for interns who can dedicate at least five months. We can often pay a small stipend to cover living costs.
PhDs
We are always looking for PhD candidates who are interested in our research area. Please send a CV if you are interested.
Projects
Restorative Neural Dynamics (MRC Centre of Research Excellence (CoRE)
In collaboration with University of Oxford, Cardiff University, Great Ormond Street Hospital, Imperial College London and Newcastle University, the centre will investigate 'neural dynamics', the complex and changing patterns of activity across networks of nerve cells in the brain that underlie behaviour.
Together, we will develop technology novel devices, ranging from brain implants to non-invasive and wearable device, that could improve how the brain and body functions.
The researchers will study neural dynamics in mouse models, with computational modelling, and using human data, integrating these activities with device hardware and software development.
Overnight Therapy (Wellcome Trust Grant)
In this Wellcome Trust funded project, we are developing an early intervention to combat burgeoning depression and PTSD through manipulation of brain activity in sleep.
Memories reactivate spontaneously during sleep, and this alters neural representations. Such reactivation can be controlled via ‘targeted memory reactivation’ (TMR), in which a sound is linked to a target memory during wake, then used to trigger reactivation in sleep. TMR of negative memories during rapid eye movement sleep (REM) leads them to be rated as less upsetting, and to elicit reduced responses in the brain’s arousal system. TMR in non-rapid eye movement sleep (NREM) reliably strengthens memories.
We will therefore use negative REM TMR to disarm toxic autobiographical memories and positive NREM TMR to disrupt depressive rumination and improve mood. We will first optimise these two interventions in healthy controls, determining the ideal circadian phase for stimulation and characterising any impact it has on mood and on brain structure or function. We will then work with lived-experience experts to bring our interventions to people recently diagnosed with PTSD or depression in proof of concept and feasibility trials. To ensure these interventions will work irrespective of societal factors we will work hand in hand with colleagues in Colombia.
SolutionSleep (ERC grant on sleep and creativity)
Innovative problem-solving is critical for all spheres of organised endeavour, including science and industry, and thus forms the cornerstone of a successful society. Such creative thinking often requires the suppression of preconceptions and the restructuring of existing knowledge.
Pioneering work has shown that sleep facilitates problem-solving, but exactly how, and which sleep characteristics are important, remain to be determined. We know that recent experiences are replayed in sleep and that in Slow Wave Sleep (SWS) this replay integrates new knowledge with old.
The role of such replay in Rapid Eye Movement (REM) sleep, a stage which is strongly linked to creativity, is unknown. We have proposed BiOtA, a model which combines physiology, behavioural studies, and computational modelling to make testable predictions about the complementary contributions of memory replay in REM and SWS to problem-solving. We are testing this model through explicit manipulation of memory replay in sleep.
We are using a very recently developed technique to explicitly trigger memory replay, a pioneering method for quantifying this replay, and cutting-edge approaches for the manipulation of neural oscillations during sleep. We expect two key results: first, we will uncover the principles of how memory replay in REM and SWS combines with specific neural oscillations to promote both long-term memory and creative problem-solving.
This will involve the development of a computational model which will enable optimised experimental design, paving the way for efficient future investigation of how to enhance innovation through the manipulation of sleep. Second, we will develop methods for boosting key sleep processes in a selective, targeted manner. Immediate consequences will include a translational project to facilitate everyday problem-solving.
Humanlike Computing (EPSRC grant on AI and sleep)
The media have lately been full of excitement about progress in Artificial Intelligence. Not only can computers now beat humans at Go and detect cats in YouTube videos, but soon we will have robots in the house, self-driving cars, and many jobs might become automated. Apart from the societal challenges that this revolution will bring, many hurdles are still to be overcome before Artificial Intelligence will obtain truly human-like capabilities.
In particular, current artificial systems might be very good at specific tasks, but they cannot easily apply their processing power to other problems. Moreover, to become experts in a certain problem these machines often need millions of training examples.
Current AI systems follow a strategy very different from humans and obtain their strength from brute computing power and massive amounts of data rather than by cleverness. This is also the reason why it is hard to communicate with these machines, understand their decisions and instruct them.
The fact that computers use an approach that is so different from that used by humans seriously hinders the application of AI to real-world applications. The research community is well aware of these issues, and it is generally believed that the problem arises because machines don't construct a higher level understanding of the problems that they are solving. How this should be addressed is however not clear.
In humans and animals sleep plays an important role in creating high-level representations. During sleep, the brain consolidates information, rearranges it, finds links between different types of knowledge, reformulates problems, and comes up with creative solutions. Most people have experienced this at some point - as they feel better able to solve a problem after a good night of sleep.
It is only very recently that researchers have become able to manipulate the processes that go on during sleep, and thereby pick apart the roles the various sleep phases play and the reason why the sleep phases are ordered in a particular way.
In this project, we are examining how processes occurring during sleep can be mimicked in computational models, and thereby open the possibility to build more human-like artificial systems.
Lead researcher
Current Staff & Students
Previous Staff & Students
Previous postdocs
- Matthias Treder studied the detection of neural replay in sleep with EEG classifiers and is now a lecturer in Computer Science at Cardiff University.
- Suliman Belal studied the application of multivariate classifiers to sleep EEG data.
- Alexia Zoumpoulaki studied the detection of neural replay in sleep with EEG classifiers and is now a lecturer in Computer Science at Cardiff University.
- Simon Durrant studied the importance of SWS for gist abstraction and integration of new learning into schemas and is now a Lecturer at the University of Lincoln.
- Jakke Tamminen studied the importance of sleep for the integration of new learning into existing knowledge and is now a postdoc at Royal Holloway.
- Sofia Isabel Ribeiro Pereira studied how Targeted Memory Replay in SWS and REM contributes to abstraction.
- Miguel Navarrete focused on closed-loop auditory stimulation of both SWS and REM.
- Lorena Santamaria examined the impacts of Targeted Memory Reactivation on the transitive inference task.
- Yihe Lu developed computational models of what different types of replay do for memory.
Previous students
- Jules Schneider did a PhD on the potential of auditory closed-loop stimulation to enhance sleep oscillations and overnight memory consolidation.
- Hikaru Tsujimura did a PhD exploring the impact of sleep on the generalisation of facial representations and competition between different identities.
- Isabel Hutchison did a PhD on the impact of direct current stimulation on sleep and memory.
- Nora Hennies did a PhD on the impact of sleep on the formation of new semantic memories.
- James Cousins did a PhD on the impact of triggered replay during sleep upon overnight memory consolidation.
- Scott Cairney did a PhD on sleep and emotional memory and is now a postdoc at York.
- Tia Tsimpanouli did a PhD on sleep, emotional memory and depression.
- Martyna Rakowska did a PhD in long-term brain and behavioural plasticity as a result of Targeted Memory Reactivation.
- Holly Kings did a PhD in brain plasticity as a result of long-term closed-loop auditory stimulation.
- Mahmoud Eid Abdelhafez Abdellahi did a PhD on the detection of replay in sleep using EEG classifiers.
- Anne Koopman did a PhD focusing on sleep and creativity, with special emphasis on indirect associations.
Publications
- Abdellahi, M. et al. 2023. Targeted memory reactivation in human REM sleep elicits detectable reactivation. eLife 12 e84324. (10.7554/elife.84324)
- Abdellahi, M. E. A. et al. 2023. Targeting targeted memory reactivation: characteristics of cued reactivation in sleep. NeuroImage 266 119820. (10.1016/j.neuroimage.2022.119820)
- Belal, S. et al. 2018. Identification of memory reactivation during sleep by EEG classification. NeuroImage 176 , pp.203-214. (10.1016/j.neuroimage.2018.04.029)
- Cairney, S. A. et al., 2014. Targeted memory reactivation during slow wave sleep facilitates emotional memory consolidation. Sleep 37 (4), pp.701-707. (10.5665/sleep.3572)
- Cairney, S. A. et al., 2014. Sleep spindles provide indirect support to the consolidation of emotional encoding contexts. Neuropsychologia 63 , pp.285-292. (10.1016/j.neuropsychologia.2014.09.016)
- Cairney, S. A. et al., 2011. Sleep and environmental context: interactive effects for memory. Experimental Brain Research 214 , pp.83-92. (10.1007/s00221-011-2808-7)
- Cairney, S. A. et al., 2015. Complementary roles of slow-wave sleep and rapid eye movement sleep in emotional memory consolidation. Cerebral Cortex 25 (6), pp.1565-1575. (10.1093/cercor/bht349)
- Cousins, J. M. et al., 2014. Cued memory reactivation during slow-wave sleep promotes explicit knowledge of a motor sequence. Journal of Neuroscience 34 (48), pp.15870-15876. (10.1523/JNEUROSCI.1011-14.2014)
- Cousins, J. N. et al., 2016. Cued reactivation of motor learning during sleep leads to overnight changes in functional brain activity and connectivity. Plos Biology 14 (5) e1002451. (10.1371/journal.pbio.1002451)
- Critchley, H. D. et al., 2007. Vagus nerve stimulation for treatment-resistant depression: behavioral and neural effects on encoding negative material. Psychosomatic Medicine -Washington- 69 (1), pp.17-22. (10.1097/PSY.0b013e31802e106d)
- Debellemanière, E. et al., 2022. Optimising sounds for the driving of sleep oscillations by closed‐loop auditory stimulation. Journal of Sleep Research (10.1111/jsr.13676)
- Durrant, S. and Lewis, P. A. 2009. Memory consolidation: tracking transfer with functional connectivity. Current Biology 19 (18), pp.R860-R862. (10.1016/j.cub.2009.08.019)
- Durrant, S. J. , Cairney, S. A. and Lewis, P. A. 2016. Cross-modal transfer of statistical information benefits from sleep.. Cortex 78 , pp.85-99. (10.1016/j.cortex.2016.02.011)
- Durrant, S. J. , Cairney, S. A. and Lewis, P. A. 2012. Overnight consolidation aids the transfer of statistical knowledge from the medial temporal lobe to the striatum. Cerebral Cortex -New York- Oxford University Press- 23 (10), pp.2467-2478. (10.1093/cercor/bhs244)
- Durrant, S. J. et al., 2015. Schema-conformant memories are preferentially consolidated during REM sleep. Neurobiology of Learning and Memory 122 , pp.41-50. (10.1016/j.nlm.2015.02.011)
- Durrant, S. J. et al., 2011. Sleep-dependent consolidation of statistical learning. Neuropsychologia 49 (5), pp.1322-1331. (10.1016/j.neuropsychologia.2011.02.015)
- Eichenlaub, J. et al., 2018. Incorporation of recent waking-life experiences in dreams correlates with frontal theta activity in REM sleep. Social Cognitive and Affective Neuroscience 13 (6), pp.637-647. (10.1093/scan/nsy041)
- Eichenlaub, J. et al., 2019. The nature of delayed dream incorporation ('dream-lag effect'): personally significant events persist, but not major daily activities or concerns. Journal of Sleep Research 28 (1) e12697. (10.1111/jsr.12697)
- Foldes, T. , Santamaria, L. and Lewis, P. 2023. Sleep-related benefits to transitive inference are modulated by encoding strength and joint rank. Learning & Memory 30 (9), pp.201-211. (10.1101/lm.053787.123)
- Greco, V. et al. 2023. Wearing an eye mask during overnight sleep improves episodic learning and alertness. Sleep 46 (3) zsac305. (10.1093/sleep/zsac305)
- Hennies, N. et al., 2017. Cued memory reactivation during SWS abolishes the beneficial effect of sleep on abstraction. Sleep 40 (8)(10.1093/sleep/zsx102)
- Hennies, N. et al., 2016. Sleep spindle density predicts the effect of prior knowledge on memory consolidation. Journal of Neuroscience 36 (13), pp.3799-3810. (10.1523/JNEUROSCI.3162-15.2016)
- Hennies, N. et al., 2014. Time- but not sleep-dependent consolidation promotes the emergence of cross-modal conceptual representations. Neuropsychologia 63 , pp.1161-123. (10.1016/j.neuropsychologia.2014.08.021)
- Holland, P. and Lewis, P. A. 2007. Emotional memory: selective enhancement by sleep. Current Biology 17 (5), pp.R179-R181. (10.1016/j.cub.2006.12.033)
- Hutchinson, I. C. et al., 2021. Targeted memory reactivation in REM but not SWS selectively reduces arousal responses. Communications Biology 4 404. (10.1038/s42003-021-01854-3)
- Javardi, A. H. , Walsh, V. and Lewis, P. A. 2010. Offline consolidation of procedural skill learning is enhanced by negative emotional content. Experimental Brain Research 208 (4), pp.507-517. (10.1007/s00221-010-2497-7)
- Kavoosi, A. et al., 2024. MorpheusNet: Resource efficient sleep stage classifier for embedded on-line systems. Presented at: IEEE International Conference on Systems, Man, and Cybernetics (SMC) Honolulu, Oahu, HI, USA 01-04 October 2023. Proceedings IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE. , pp.2315-2320. (10.1109/SMC53992.2023.10394274)
- Leitner, C. et al., 2024. REM sleep and emotion dysregulation in the elderly: a TMR study. Presented at: 17th World Sleep Congress Rio de Janeiro, Brazil 20-25 October 2023. (10.1016/j.sleep.2023.11.147)
- Leitner, C. et al., 2025. Isolated REM sleep behavior disorder: A model to assess the overnight habituation of emotional reactivity. Clocks & Sleep 7 (1) 9. (10.3390/clockssleep7010009)
- Lewis, P. A. 2002. Finding the timer. Trends in Cognitive Sciences 6 (5), pp.195-196. (10.1016/S1364-6613(02)01906-X)
- Lewis, P. A. 2002. Musical Minds. Trends in Cognitive Sciences 6 (9), pp.364-366. (10.1016/S1364-6613(02)01955-1)
- Lewis, P. A. et al. 2017. Higher order intentionality tasks are cognitively more demanding. Social Cognitive and Affective Neuroscience 12 (7), pp.1063-1071. (10.1093/scan/nsx034)
- Lewis, P. A. et al. 2011. The impact of overnight consolidation upon memory for emotional and neutral encoding contexts. Neuropsychologia 49 (9), pp.2619-2629. (10.1016/j.neuropsychologia.2011.05.009)
- Lewis, P. A. , Couch, T. J. and Walker, M. P. 2010. Keeping time in your sleep: overnight consolidation of temporal rhythm. Neuropsychologia 49 (1), pp.115-123. (10.1016/j.neuropsychologia.2010.10.025)
- Lewis, P. A. et al. 2006. Neural correlates of processing valence and arousal in affective words. Cerebral Cortex -New York- Oxford University Press- 17 (3), pp.742-748. (10.1093/cercor/bhk024)
- Lewis, P. A. et al. 2005. Brain mechanisms for mood congruent memory facilitation. NeuroImage 25 (4), pp.1214-1223. (10.1016/j.neuroimage.2004.11.053)
- Lewis, P. A. and Critchley, H. D. 2003. Mood-dependent memory. Trends in Cognitive Sciences 7 (10), pp.431-433. (10.1016/j.tics.2003.08.005)
- Lewis, P. A. and Miall, R. C. 2006. A right hemispheric prefrontal system for cognitive time measurement. Behavioural Processes 71 (2-3), pp.226-234. (10.1016/j.beproc.2005.12.009)
- Lewis, P. A. and Miall, R. C. 2003. Brain activation patterns during measurement of sub- and supra-second intervals. Neuropsychologia 41 (12), pp.1583-1592. (10.1016/S0028-3932(03)00118-0)
- Lewis, P. A. and Miall, R. C. 2009. The precision of temporal judgement: milliseconds, many minutes, and beyond. Philosophical Transactions of the Royal Society B: Biological Sciences 364 (1525)(10.1098/rstb.2009.0020)
- Lewis, P. A. et al. 2003. Interval timing in mice does not rely upon the circadian pacemaker. Neuroscience Letters 348 (3), pp.131-134. (10.1016/S0304-3940(03)00521-4)
- Lewis, P. A. and Miall, R. C. 2002. Brain activity during non-automatic motor production of discrete multi-second intervals. Neuroreport -Oxford- 13 (4), pp.1731-1735.
- Lewis, P. A. and Miall, R. C. 2006. Remembering the time: a continuous clock. Trends in Cognitive Sciences 10 (9), pp.401-406. (10.1016/j.tics.2006.07.006)
- Lewis, P. A. and Miall, R. C. 2003. Distinct systems for automatic and cognitively controlled time measurement: evidence from neuroimaging. Current Opinion in Neurobiology 13 (2), pp.250-255. (10.1016/S0959-4388(03)00036-9)
- Lewis, P. A. et al. 2011. Ventromedial prefrontal volume predicts understanding of others and social network size. NeuroImage 57 (4), pp.1624-1629. (10.1016/j.neuroimage.2011.05.030)
- Lewis, P. A. and Walsh, V. 2002. Neuropsychology: Time Out of Mind. Current Biology 12 (1), pp.R9-R11. (10.1016/S0960-9822(01)00638-8)
- Lewis, P. A. and Walsh, V. 2005. Time perception: components of the brain’s clock. Current Biology 15 (10), pp.R389-R391. (10.1016/j.cub.2005.05.008)
- Lewis, P. A. et al. 2004. Brain activity correlates differentially with increasing temporal complexity of rhythms during initialisation, synchronisation, and continuation phases of paced finger tapping. Neuropsychologia 42 (10), pp.1301-1312. (10.1016/j.neuropsychologia.2004.03.001)
- Lewis, P. , Knoblich, G. and Poe, G. 2018. How memory replay in sleep boosts creative problem solving. Trends in Cognitive Sciences 22 (6), pp.491-503. (10.1016/j.tics.2018.03.009)
- Meshreky, K. and Lewis, P. 2025. Do eye movements in REM sleep play a role in overnight emotional processing?. Neuropsychologia 215 109169. (10.1016/j.neuropsychologia.2025.109169)
- Navarrete, M. et al. 2022. Ongoing neural oscillations predict the post-stimulus outcome of closed loop auditory stimulation during slow-wave sleep. NeuroImage 253 119055. (10.1016/j.neuroimage.2022.119055)
- Navarrete, M. et al. 2024. Auditory stimulation during REM sleep modulates REM electrophysiology and cognitive performance. Communications Biology 7 (1) 193. (10.1038/s42003-024-05825-2)
- Navarrete, M. et al. 2020. Examining the optimal timing for closed loop auditory stimulation of slow wave sleep in young and older adults. SLEEP 43 (6), pp.1-14. (10.1093/sleep/zsz315)
- Navarrete, M. , Valderrama, M. and Lewis, P. A. 2020. The role of slow-wave sleep rhythms in the corticalhippocampal loop for memory consolidation. Current Opinion in Behavioral Sciences 32 , pp.102-110. (10.1016/j.cobeha.2020.02.006)
- Pereira, S. I. R. and Lewis, P. A. 2020. Sleeping through brain excitation and inhibition. Nature Neuroscience 23 , pp.1037-1039. (10.1038/s41593-020-0697-4)
- Pereira, S. I. R. and Lewis, P. A. 2020. The differing roles of NREM and REM sleep in the slow enhancement of skills and schemas. Current Opinion in Physiology 15 , pp.82-88. (10.1016/j.cophys.2019.12.005)
- Pereira, S. I. R. et al. 2023. Rule abstraction is facilitated by auditory cueing in REM sleep. Journal of Neuroscience 43 (21), pp.3838-3848. (10.1523/JNEUROSCI.1966-21.2022)
- Pereira, S. I. R. et al. 2022. Cueing emotional memories during slow wave sleep modulates next-day activity in the orbitofrontal cortex and the amygdala. NeuroImage 253 119120. (10.1016/j.neuroimage.2022.119120)
- Powell, J. et al., 2012. Orbital prefrontal cortex volume predicts social network size: an imaging study of individual differences in humans. Proceedings of the Royal Society B: Biological Sciences 283 (1824)(10.1098/rspb.2011.2574)
- Powell, J. L. et al., 2010. Orbital prefrontal cortex volume correlates with social cognitive competence. Neuropsychologia 48 (12), pp.3554-3562. (10.1016/j.neuropsychologia.2010.08.004)
- Rakowska, M. et al. 2021. Long term effects of cueing procedural memory reactivation during NREM sleep. NeuroImage 244 118573. (10.1016/j.neuroimage.2021.118573)
- Santamaria, L. et al., 2024. Memory reactivation in slow wave sleep enhances relational learning in humans. Communications Biology 7 (1) 288. (10.1038/s42003-024-05947-7)
- Santamaria, L. et al., 2024. Effects of targeted memory reactivation on cortical networks. Brain Sciences 14 (2) 114. (10.3390/brainsci14020114)
- Schneider, J. et al., 2020. Susceptibility to auditory closed-loop stimulation of sleep slow oscillations changes with age. SLEEP 43 (12)(10.1093/sleep/zsaa111)
- Sommer, T. et al., 2022. The assimilation of novel information into schemata and its efficient consolidation. Journal of Neuroscience 42 (30), pp.5916-5929. (10.1523/jneurosci.2373-21.2022)
- Tamminen, J. , Lambon Ralph, M. A. and Lewis, P. 2017. Targeted memory reactivation of newly learned words during sleep triggers REM-mediated integration of new memories and existing knowledge.. Neurobiology of Learning and Memory 137 , pp.77-82. (10.1016/j.nlm.2016.11.012)
- Tamminen, J. , Lambon Ralph, M. A. and Lewis, P. A. 2013. The role of sleep spindles and slow-wave activity in integrating new information in semantic memory. Journal of Neuroscience 33 (39), pp.15376-15381. (10.1523/JNEUROSCI.5093-12.2013)
- van Rijn, E. et al., 2015. The dream-lag effect: selective processing of personally significant events during Rapid Eye Movement sleep, but not during Slow Wave Sleep. Neurobiology of Learning and Memory 122 , pp.98-109. (10.1016/j.nlm.2015.01.009)
- Wuerger, S. et al., 2012. Premotor cortex is sensitive to auditory–visual congruence for biological motion. Journal of Cognitive Neuroscience 24 (3), pp.575-587. (10.1162/jocn_a_00173)
Events
Seminars
We hold a Journal Club on sleep and memory at 10:00 on Wednesdays.
Meetings
Past meetings
- Replay@CUBRIC-25, May 2025, Cardiff
- World Sleep Day, 14 March 2025, Cardiff
- Cardiff Sleep Network Day of Sleep (22 July 2019, Cardiff)
- Replay@CUBRIC 2018 (13-14 September 2018, Cardiff)
- World Sleep Day Celebration (8 March 2018, Cardiff)
- Creative Minds Summer School (July 2017, Budapest)
- Replay@CUBRIC 2017 (8 May 2017, Cardiff)
Guest lectures
Past guest lectures
- Eitan Schechtman: ‘Reactivation of interacting memory traces in the sleeping brain’, September 2024
- Francesca Siclari: ‘The EEG correlates of dream consciousness’, August 2018
- Michele Bellesi: ‘Enhancing sleep slow waves using acoustic stimuli’, April 2018
- Nicolai Axmacher: ‘Engram patterns in intracranial EEG and fMRI’, October 2017
- Hong-Viet Ngo: ‘Brain stimulation during sleep: Targeting EEG oscillations to investigate the memory function of sleep’, July 2017
- Lucia Talamini: ‘Closed-loop stimulation of sleep’, May 2017
- Martin Willis: 'Sleeping before the Neurosciences: Science, Medicine and Culture’, April 2017
- Gordon Feld: ‘Neurochemical mechanisms of sleep’s beneficial effect on memory processes’, 6 February 2017
Media coverage
Podcasts
Features and talks
- BBC Reel feature on sleep art
- BBC feature on our work
- TEDx talk on Sleep Engineering (over a million views)
Books
- The Secret World of Sleep: The Surprising Science of the Mind at Rest
- Spindles: Stories from the Science of Sleep
Blogs
- 'ERCcOMICS' Blog featuring the SolutionSleep ERC-funded project on sleep and creativity
- BBC Idea: The extraordinary human brain: Can we manipulate our sleep?
Radio interviews
- BBC CrowdScience: Why can’t I sleep?
- Radio New Zealand: The Secret World of Sleep
- Brain Science Podcast: Sleep Science with Penny Lewis
- Australian Broadcasting Corporation: All in the Mind – the mind at rest
- Constant Wonder: Engineering Sleep, Flea Circus, Ghost Town, Ice King
- BBC Radio 4: Science of Dreaming
News and magazine articles
- iNews: Sleep study discovery could hold key to tackling PTSD and other anxiety disorders
- BBC: Sleep engineering 'could help treat PTSD'
- Donna Moderna (Italian-language magazine): Dormi e sarai più creativa
- Financial Times: Why we dream
- The Atlantic: A New Theory Linking Sleep and Creativity by Ed Yong
- Parade: 5 things you didn’t know about sleep
- Daily Telegraph: Top tips for better sleep
- Top Sante: Ask the sleep expert
- BBC Focus: How sleep can make you smarter
- Candis: The secrets of sleep
- Huffington Post: Advice on how to get more rest
Clinical unit and sleep labs
Our research sleep lab includes a two-bedroom suite, a nurses' station, and a control room, which is arranged for EEG application and overnight researcher observation.
Schools
Next steps
Research that matters
Our research makes a difference to people’s lives as we work across disciplines to tackle major challenges facing society, the economy and our environment.
Postgraduate research
Our research degrees give the opportunity to investigate a specific topic in depth among field-leading researchers.
Our research impact
Our research case studies highlight some of the areas where we deliver positive research impact.