Machine learning and sleep:Detecting neural replay in sleep with EEG classifiers at Cardiff University on FindAPhD.com

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Prof Penny Lewis No more applications being accepted Funded PhD Project (Students Worldwide)

About the Project

Memories are spontaneously replayed in sleep, and this replay is critical for their consolidation (strengthening and integration with pre-existing knowledge). Until recently, it has been impossible to detect these replays in humans, but work from our laboratory has devised a method to achieve this using machine learning to analyse EEG data. In this PhD, we will seek to extend this work by improving the detection method and using it to examine many additional aspects of memory replay such as how long it lasts, which phases of sleep it occurs in, and how it impacts on neuroplasticity.

We will first use common machine learning algorithms such as SVM, Logistic Regression, KNN with emphasis in feature extraction and selection. As this is a challenging problem we aim to explore and combine techniques from areas such as time series analysis (dynamic time warping), neuroimaging (representation similarity analysis) and deep learning (LSTM, convolutional NN). We seek a computer science or engineering student with a good background in machine learning and signal processing to take this work forward.

Funding Notes

The studentship will commence in October 2018 (there is potential for an earlier start date) and will cover your tuition fees (at UK/EU level) as well as a maintenance grant. In 2017-18 the maintenance grant for full-time students was £14,553 per annum. As well as tuition fees and a maintenance grant, all School of Psychology students receive conference and participant money (approx. £2250 for the duration of the studentship).They also receive a computer and office space, additional funding for their research, and access to courses offered by the University’s Doctoral Academy and become members of the University Doctoral Academy.

References

Full awards (fees plus maintenance stipend) are open to UK Nationals, and EU students who can satisfy UK residency requirements. To be eligible for the full award, EU Nationals must have been in the UK for at least 3 years prior to the start of the course for which they are seeking funding, including for the purposes of full-time education.

As only one studentship is available and a very high standard of applications is typically received, the successful applicant is likely to have a very good first degree (a First or Upper Second class BSc Honours or equivalent) and/or be distinguished by having relevant research experience.

The School of Psychology is one of the largest and most successful in the UK (http://www.cf.ac.uk/psych/). The School’s excellent standard of research and teaching has been recognised in every Research Assessment Exercise. It has its own brain-imaging centre (http://www.cf.ac.uk/psych/cubric/), enhancing the international-leading research in behavioural neuroscience, cognitive ergonomics, forensic, social and developmental psychology.

The Neuroscience and Psychology of Sleep (Naps) lab is a thriving community of computer scientists and sleep researchers studying all aspects of how sleep impacts on cognition (see our nascent web pages: http://sites.cardiff.ac.uk/cubric/research-2-2/neuroscience-and-psychology-lab-naps/)

Cardiff University’s Brain Research Imaging Centre (CUBRIC) opened in Spring 2016, housing a unique combination of facilities and expertise that will further its world-leading research in Neuroimaging, Cognitive Neuroscience and Biological Psychiatry. Further details of CUBRIC can be found on our web-page: http://sites.cardiff.ac.uk/cubric

Where will I study?

Cardiff University

At the heart of our vibrant research culture is a welcoming community of students and staff, who share a single ambition: to tackle the grand challenges of our time and make a positive impact around the world.

Machine learning and sleep:Detecting neural replay in sleep with EEG classifiers

Cardiff University Cardiff School of Psychology