Neuroscience and psychology of sleep lab (NaPS)

Sleep is critical for both health and cognition. Our lab is developing ways to manipulate sleep in order to maximise its beneficial properties.

We are working on ways to enhance memory, disarm negative emotions, and combat cognitive decline through ageing.

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.

Positions available

Please contact Professor Penny Lewis (preferably attaching a CV) if you are interested in applying for a position in the group.

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.

Project: Computational modelling of memory processing in sleep
Supervisor: Professor Penny Lewis
Start date: Flexible from 1 January 2019 to 1 October 2019

ProjectMachine learning and sleep: Detecting neural replay in sleep with EEG classifiers
Supervisor: Professor Penny Lewis
Start date: Flexible from 1 January 2019 to 1 October 2019

Postdocs

We will be advertising several postdocs in the next year. Topics include sleep engineering, EEG analysis, machine learning, and computational modelling.

We are primarily interested in offline learning during sleep and wakefulness: Our research investigates brain plasticity, focusing specifically on the changes in behavior and neural activity which occur after initial learning.

We are particularly interested in changes occurring while a memory is not being encoded, practised or recalled.

Over the last few years, we have coined the term ‘sleep engineering’ to capture the spirit of what we are doing.

Specifically, we are developing ways to actively manipulate the neural processing that occurs during sleep in order to enhance health and cognition.

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 quiet presentation of sounds during sleep.

Interns

  • Natalie Gunasekara
  • Duarte Pereira
  • Shi Wei Teo

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 integration of new learning into existing knowledge and is now a postdoc at Royal Holloway.

Previous students

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 upon 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.

Selected publications

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 suppression of preconceptions and 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 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 development of a computational model which will enable optimised experimental design, paving the way for efficient future investigation of how to enhance innovation through 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.

Check out the ERCcOMICS Blog which features the ERC SolutionSleep project.

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, they cannot easily apply their processing power to other problems. Moreover, in order 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 compute 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 application of AI to real world applications. The research community is well aware of these issues, and it generally believed that the problem arises because machines don't construct 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 of 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 to processes occurring during sleep can be mimicked in computational models, and thereby open the possibility to build more human-like artificial systems.

Lead researcher

Professor Penny Lewis

Professor Penny (Penelope) Lewis

Professor

Email:
lewisp8@cardiff.ac.uk
Telephone:
+44 (0)29 2087 0467

Academic staff

Miguel Navarrete

Miguel Navarrete

Research Associate

Email:
navarretem@cardiff.ac.uk
Telephone:
+44 (0)29 2087 0365

Postgraduate students

Martyna Rakowska

Research student

Email:
rakowskam@cardiff.ac.uk
Schneiderj2

Jules Schneider

Research student

Email:
schneiderj2@cardiff.ac.uk
Koopman

Anne Koopman

Research student

Email:
koopmanac@cardiff.ac.uk
Holly

Holly Kings

Research student

Email:
kingsho@cardiff.ac.uk
Imo

Imogen Birch

Research student

Email:
birchi@cardiff.ac.uk

Seminars

We hold a Journal Club on sleep and memory at 15:00 on Fridays.

Meetings

Guest lectures

Past guest lectures

  • 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

Features and talks

Books

Blogs

  • 'ERCcOMICS' Blog featuring the SolutionSleep ERC-funded project on sleep and creativity

Radio interviews

News and magazine articles

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.

Images