Abstract

Speaker: Visiting in person – Dr. Andrew Quinn, School of Psychology, University of Birmingham, UK

Title: Robust and replicable effects of ageing on resting state brain electrophysiology measured with MEG

Abstract: Non-invasive recordings of brain electrophysiology offer insight into age-related declines in neuronal function, as reflected by alterations in the power spectrum of EEG and MEG recordings. Statistically rigorous analysis methodologies are needed to translate these findings into clinically meaningful metrics that address the global challenge of maintaining brain health in ageing populations.

This talk presents findings that consolidate multiple ageing-related effects into a single statistical spectrum. I will examine the reproducibility of this spectrum across open-access MEG datasets and its robustness to common covariates. Building on this foundation, I propose a framework for estimating the statistical power of age-related effects to support future study design. Finally, I will talk about how these electrophysiological ageing effects interact with individual differences in white matter tracts and the presence of neurodegenerative disease.

Bio: Dr Andrew Quinn completed his PhD in 2014 at the University of York, developing methods for estimating time-varying functional connectivity during visual word recognition from Magnetoencephalography data. He then worked as a postdoctoral scientist at the Oxford Centre for Human Brain Activity (OHBA) where he developed a range of novel time series analysis techniques targeted at analysis of brain changes in neurodegenerative disorders. Dr Quinn started as an Assistant Professor at the University of Birmingham in 2022. His research continues to explore novel analysis of electrophysiological time series in the context of visual and auditory perception and changes in brain function across the lifespan and into neurodegeneration.

Venue: MRC CBU West Wing Seminar Room and Zoom https://us02web.zoom.us/j/82385113580?pwd=RmxIUmphQW9Ud1JBby9nTDQzR0NRdz09 (Meeting ID: 823 8511 3580; Passcode: 299077)