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Short-Term Variability in Cognitive Function as a Potential Stroke Recovery Biomarker

   Faculty of Biology, Medicine and Health

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  Dr Laura Brown, Prof Craig Smith, Prof Stuart Allan, Dr Matthew Machin  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Our cognitive function naturally varies over periods of hours or days. For instance, even healthy individuals show predictable changes in cognitive ability over the course of the day that correspond to natural circadian rhythms (Schmidt et al., 2007). The extent of this variability increases in the presence of neuropathology (Paradee et al., 2005), and correlates with functional performance (Gamaldo & Allaire, 2015). Together, this suggests that short-term variability in cognition could be a meaningful marker of underlying system integrity in people with neurological conditions, such as stroke.

Until recently, variability in cognitive function has been difficult to measure due to the practical challenges of repeated cognitive testing. However, there are now brief computerised tests of cognitive function that can be administered without a researcher being present (Brown et al., 2016), through mobile smartphone platforms (Fox et al., 2022). The aim of this PhD would be to determine the feasibility and validity of using these cognitive tests in a post-stroke population to measure indices of cognitive variability that predict future prognosis or functional status.

This PhD would primarily involve recruiting stroke patients to complete a series of brief cognitive tests, administered through a mobile phone app. These cognitive data would be supplemented with measures of patients’ clinical characteristics and functional status, as well as qualitative and quantitative data relating to the acceptability, usability, and patient experience of the app. Additional methods of investigation may include co-design with patients and other stakeholders, as well as systematic reviews of existing evidence relating to cognitive variability and/or predictors of stroke recovery.

The PhD would be supervised by a multidisciplinary team comprising expertise in psychology, neuroscience, stroke medicine, and software engineering. The design, conduct, and dissemination of the research would also be informed by discussions with a user-group of people with lived experience of stroke.

Entry Requirements

Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a related area/subject. Candidates with previous laboratory experience are particularly encouraged to apply.

How To Apply

For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (https://www.bmh.manchester.ac.uk/study/research/apply/). Informal enquiries may be made directly to the primary supervisor. On the online application form select the appropriate subject title.

For international students, we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences.

Equality, Diversity and Inclusion

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-inclusion/”

Funding Notes

Applications are invited from self-funded students. This project has a Band 2 fee. Details of our different fee bands can be found on our website View Website


Brown, L.J.E., Adlam, T., Hwang, F., Khadra, H., Maclean, L.M., Rudd, B., Smith, T., Timon, C., Williams, E.A., Astell, A.J.A. (2016). Computer-based tools for assessing micro-longitudinal patterns of cognitive function in older adults. Age, 38, 335-350. Doi: 10.1007/s11357-016-9934-x
Fox, S., Brown, L.J.E., Antrobus, S., Brough, D., Drake, R., Jury, F., Leroi, I., Parry-Jones, A., & Machin, M. (2022). Co-design of a Smartphone App for People Living With Dementia by Applying Agile, Iterative Co-design Principles: Development and Usability Study. JMIR mHealth and uHealth, 10(1),e24483. doi: 10.2196/24483.
Gamaldo, A.A., & Allaire, J.C. (2015) Daily fluctuations in everyday cognition. Is it meaningful? Journal of Aging and Health, 28, 834-40. doi:10.1177/0898264315611669
Paradee, C.C., Rapport, L.J., Hanks, R.A., & Levy, J.A. (2005) Circadian preference and cognitive functioning among rehabilitation inpatients. Clinical Neuropsychology, 19, 55–72.
Schmidt, C., Collette, F., Cajochen, C., & Peigneux, P. (2007). A time to think: circadian rhythms in human cognition. Cognitive Neuropsychology. 24, 755-789. Doi: 10.1080/02643290701754158
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