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Dr Magda Chechlacz

Supervisor Details

Dr Magda Chechlacz

Contact Details

Dr Magda Chechlacz

School of Psychology, University of Birmingham

Research Interests

Dr Chechlacz’s research is broadly concerned with understanding how variability in the neurochemical, structural and functional organisation of the brain affect cognitive performance, in particularly attentional functions, as well as whether and how these individual differences predict the susceptibility to neurological disorders and the way we age. Her prior research programme funded by the British Academy examined whether variability in the organisation of the visual attention networks is associated with individual differences in attentional functions, whether structural lateralization underlies functional lateralization in the organisation of attention and whether behavioural asymmetries are causally linked to the structural asymmetries in attention networks. Her current work aims to test for associations between common genetic variants in neurotransmitter signalling and resting state connectivity within attention networks as well as examine the links between those functional genetic polymorphisms and individual differences in age-related cognitive decline in attention.

Scientific Inspiration

Santiago Ramón y Cajal, not just for his groundbreaking discoveries and contributions to neuroscience but also beautiful drawings of neurons and neural networks. His line sketches used to capture my imagination when as neurobiology student I used to study axonal growth under the microscope and also inspire my current fascination with diffusion tractography, a magnetic resonance imaging technique used to non-invasively explore human brain connectivity underlying normal functions and dysfunctions in neurological disorders.

Project Details

Dr Chechlacz is supervisor on the below project:

Cognitive deficits and accelerated brain ageing in older adults at risk for undiagnosed sleep apnea

Secondary Supervisor(s): Professor Andrew Bagshaw 

University of Registration: University of Birmingham

BBSRC Research Themes: Understanding the Rules of Life (Neuroscience and Behaviour)

Apply here!

Deadline: 4 January, 2024

Project Outline

Cognitive ageing is inevitable but numerous studies indicate a large heterogeneity in the rate of cognitive deterioration, ranging from a gradual drop in cognitive functioning to dementia. With an increasingly ageing UK population, one of the key research challenges is understanding factors associated with a risk of hastened cognitive decline. The proposed project stems from the hypothesis that undetected obstructive sleep apnea (OSA) in older adults leads to accelerated brain and cognitive ageing, and subsequently aims to expand understanding of the mechanisms of OSA-mediated cognitive decline in elderly population.

OSA is one of the leading causes of poor cardiovascular and cerebrovascular health and has been associated with increased risk of hypertension, coronary heart disease, and stroke. The links between OSA and cognitive deficits are poorly understood and often controversial. However, in the last few years OSA has emerged as a potentially modifiable risk factor for cognitive decline and dementia in the elderly population. It has been further suggested that OSA and dementia might share several common pathomechanisms, such as cerebrovascular changes, inflammation and neurodegeneration. Despite the increasing awareness of the negative health and cognitive consequences of OSA, current statistics indicate that only a relatively small number of older adults are tested and treated for OSA. In middle-aged individuals who are overweight or obese, loud snoring, waking up during the night, mental fatigue associated with concentration problems and memory lapses, excessive daytime sleepiness and napping are considered symptoms of OSA and trigger medical referral. By contrast, the same symptoms in older individuals are frequently attributed to normal ageing and not medically investigated. In one recent study (n=1,052), 56% of community-dwelling older adults, were classified as being at high risk of OSA based on detailed questionnaire screening, and in 94% of these cases OSA was medically confirmed. Strikingly, only 8% of these adults were previously referred to be tested for OSA.

The research addressing the mechanistic processes underlying the link between OSA and cognitive decline in older adults is only beginning to emerge. While recently published studies firmly indicate that robust structural brain changes contribute to cognitive deficits in older adults diagnosed with OSA, there is a paucity of studies exploring mechanisms underpinning the observed brain changes. Crucially, there is a lack of research specifically asking whether and to what extent the undiagnosed and untreated OSA not only hastens brain ageing and cognitive decline in the elderly, but also contributes to diminished quality of life and mental health problems. The proposed project aims to address these gaps. Specifically, the proposed project is based on the hypothesis that cerebrovascular changes and inflammation in older adults with undiagnosed OSA result in brain atrophy underpinning accelerated brain ageing and cognitive deficits. By combining detailed characterization of sleep fragmentation, airflow/breathing patterns, oxygen saturation and cerebrovascular health with advanced neuroimaging methods, inflammation markers and comprehensive cognitive testing, the project aims (1) to examine markers of inflammation and cerebrovascular health in older adults with poor sleep quality and/or excessive daytime sleepiness who has not been previously tested for OSA, and (2) to link these markers to measures of cognitive dysfunction, and accelerated brain ageing (brain changes exceeding these expected for chronological age of an individual).


  1. Hayden KM et al (2011). Age and ageing, 40, 684-689
  2. Culebras A & Anwar, S. (2018). Curr Neurol Neurosci Rep, 18, 53
  3. Gosselin N et al., (2019). Am J Respir Crit Care Med, 199, 142-148
  4. Polsek D et al (2018). Neurosci Biobehav Rev, 86, 142-149
  5. Braley TJ et al (2018). J Am Geriatr Soc, 66, 1296-1302
  6. Shi Y et al (2017). Sci Rep, 7, 10095


  • Programming Skills (e.g., Bash, Python, Matlab, R)
  • Advances statistical and machine learning analyses
  • Structural and perfusion/arterial spin labelling MRI
  • Physiological data modelling

Dr Chechlacz is also co-supervising on a project with Dr Davinia Fernández-Espejo.

Previous Project

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