Dr Andrew Quinn BSc MSc PhD

Dr Andrew Quinn

School of Psychology
Assistant Professor in Psychology

Dr Andrew Quinn works on time-series analysis methods and software for quantifying oscillations in electrophysiological time series. He applies these methods to research questions around visual and auditory perception and how brain function changes across the lifespan and in neurodegenerative disorders.

Qualifications

Bsc Psychology - University of York 2010

MSc Cognitive Neuroscience - University of York 2011

PhD Psychology - University of York 2014

Biography

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, as well as changes in brain function across the lifespan and into neurodegeneration.

Teaching

Research Methods B; Introduction to Data Science

Research

Electrophysiology (EEG, MEG, OPMs); Neuronal Oscillations; Connectivity; Networks; Perception; Statistics; Software Development.

Publications

Recent publications

Article

Tang, C-W, Zich, C, Quinn, AJ, Woolrich, MW, Juan, C-H & Stagg, CJ 2024, 'Post-stroke upper limb recovery is correlated with dynamic resting-state network connectivity', Brain Communications. https://doi.org/10.1093/braincomms/fcae011

Quinn, AJ, Atkinson, LZ, Gohil, C, Kohl, O, Pitt, J, Zich, C, Nobre, AC & Woolrich, MW 2024, 'The GLM-spectrum: A multilevel framework for spectrum analysis with covariate and confound modelling', Imaging Neuroscience, vol. 2, pp. 1-26. https://doi.org/10.1162/imag_a_00082

Gohil, C, Huang, R, Roberts, E, van Es, MWJ, Quinn, AJ, Vidaurre, D, Woolrich, MW & de Lange, FP 2024, 'osl-dynamics, a toolbox for modeling fast dynamic brain activity', eLife, vol. 12, RP91949. https://doi.org/10.7554/elife.91949

Seedat, ZA, Rier, L, Gascoyne, LE, Cook, H, Woolrich, MW, Quinn, AJ, Roberts, TPL, Furlong, PL, Armstrong, C, St Pier, K, Mullinger, KJ, Marsh, ED, Brookes, MJ & Gaetz, W 2023, 'Mapping Interictal activity in epilepsy using a hidden Markov model: a magnetoencephalography study', Human Brain Mapping, vol. 44, no. 1, pp. 66-81. https://doi.org/10.1002/hbm.26118

Zich, C, Quinn, AJ, Bonaiuto, JJ, O'Neill, G, Mardell, LC, Ward, NS & Bestmann, S 2023, 'Spatiotemporal organisation of human sensorimotor beta burst activity', eLife, vol. 12, e80160. https://doi.org/10.7554/eLife.80160

Lanskey, JH, Kocagoncu, E, Quinn, AJ, Cheng, Y-J, Karadag, M, Pitt, J, Lowe, S, Perkinton, M, Raymont, V, Singh, KD, Woolrich, M, Nobre, AC, Henson, RN & Rowe, JB 2022, 'New Therapeutics in Alzheimer’s Disease Longitudinal Cohort study (NTAD): study protocol', BMJ open, vol. 12, no. 12, e055135. https://doi.org/10.1136/bmjopen-2021-055135

Higgins, C, van Es, MWJ, Quinn, AJ, Vidaurre, D & Woolrich, MW 2022, 'The relationship between frequency content and representational dynamics in the decoding of neurophysiological data', NeuroImage, vol. 260, 119462. https://doi.org/10.1016/j.neuroimage.2022.119462

Echeverria-Altuna, I, Quinn, AJ, Zokaei, N, Woolrich, MW, Nobre, AC & van Ede, F 2022, 'Transient beta activity and cortico-muscular connectivity during sustained motor behaviour', Progress in neurobiology, vol. 214, 102281. https://doi.org/10.1016/j.pneurobio.2022.102281

Fabus, MS, Woolrich, MW, Warnaby, CW & Quinn, AJ 2022, 'Understanding harmonic structures through instantaneous frequency', IEEE Open Journal of Signal Processing, vol. 3, pp. 320-334. https://doi.org/10.1109/OJSP.2022.3198012

Fabus, MS, Quinn, AJ, Warnaby, CE & Woolrich, MW 2021, 'Automatic decomposition of electrophysiological data into distinct nonsinusoidal oscillatory modes', Journal of Neurophysiology, vol. 126, no. 5, pp. 1670-1684. https://doi.org/10.1152/jn.00315.2021

Khawaldeh, S, Tinkhauser, G, Torrecillos, F, He, S, Foltynie, T, Limousin, P, Zrinzo, L, Oswal, A, Quinn, AJ, Vidaurre, D, Tan, H, Litvak, V, Kühn, A, Woolrich, M & Brown, P 2021, 'Balance between competing spectral states in subthalamic nucleus is linked to motor impairment in Parkinson's disease', Brain, vol. 145, no. 1, pp. 237-250. https://doi.org/10.1093/brain/awab264

Quinn, AJ, Green, GGR & Hymers, M 2021, 'Delineating between-subject heterogeneity in alpha networks with Spatio-Spectral Eigenmodes', NeuroImage, vol. 240, 118330. https://doi.org/10.1016/j.neuroimage.2021.118330

Zhang, S, Cao, C, Quinn, A, Vivekananda, U, Zhan, S, Liu, W, Sun, B, Woolrich, M, Lu, Q & Litvak, V 2021, 'Dynamic analysis on simultaneous iEEG-MEG data via hidden Markov model', NeuroImage, vol. 233, 117923. https://doi.org/10.1016/j.neuroimage.2021.117923

Quinn, AJ, Lopes-Dos-Santos, V, Dupret, D, Nobre, AC & Woolrich, MW 2021, 'EMD: Empirical Mode Decomposition and Hilbert-Huang spectral analyses in Python', The Journal of Open Source Software, vol. 6, no. 59, 2977. https://doi.org/10.21105/joss.02977

Preprint

Quinn, AJ, Atkinson, LZ, Gohil, C, Kohl, O, Pitt, J, Zich, C, Nobre, AC & Woolrich, MW 2022 'The GLM-Spectrum: a multilevel framework for spectrum analysis with covariate and confound modelling' bioRxiv. https://doi.org/10.1101/2022.11.14.516449

View all publications in research portal