Professor Howard Bowman PhD

Professor Howard Bowman

School of Psychology
Professor of Cognitive Neuroscience

Contact details

Email
bowmanh@adf.bham.ac.uk
View my research portal
Address
School of Psychology
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Professor Bowman applies the methods of Cognitive Neuroscience, especially EEG and Neural Modelling, to understanding a spectrum of Cognitive phenomena, including conscious perception, temporal attention and subliminal search. Much of his work focuses on verifying the simultaneous Type/ Serial Token theory of temporal attention and working memory encoding, which he developed with Brad Wyble.

Professor Bowman is a member of the Centre for Computational Neuroscience and Cognitive Robotics (CNCR).

Qualifications

BSc. Hons (first class) Mathematics & Computing, Lancaster University
PhD. Computer Science, Lancaster University

Biography

Professor Bowman completed a PhD and Postdoc at Lancaster University and then took up a lectureship in Computer Science at the University of Kent at Canterbury. In this first phase of his career he developed mathematical theories of computation, particularly in concurrency theory. He was appointed to a chair at Kent in 2006. He now holds part-time positions at Kent and at Birmingham, with his work now exclusively focused on Cognitive Neuroscience.

Postgraduate supervision

Professor Bowman’s PhD students are all currently at the University of Kent in Canterbury (9 altogether). See his PhD students page for more detail. He is interested in also supervising PhD students at Birmingham; enquiries should be made to bowmanh@adf.bham.ac.uk.

View a list of possible PhD topics related to his interests part way down his Kent profile page. 

Research

Research interests

The interaction between brain and mind in human conscious perception, temporal attention, working memory encoding and subliminal search; and the interpretation and analysis of EEG signals in this context.

View more details of Professor Bowman's research.

Other activities

  • Professor of Cognition and Logic, University of Kent at Canterbury (2006 to present)
  • Current Programme Committee Member of NeSy (International Workshop on Neural-Symbolic Learning and Reasoning)
  • Programme Committee Member of over 30 conferences during career.
  • Over 100 publications
  • Has held research funding from RCUK, EPSRC, European Commission, British Telecom, British Council, and the London Mathematical Society.

Publications

Recent publications

Article

Hope, TMH, Bowman, H, Leff, AP & Price, CJ 2025, 'Deep convolutional neural networks outperform vanilla machine learning when predicting language outcomes after stroke', NeuroImage: Clinical, vol. 48, 103880. https://doi.org/10.1016/j.nicl.2025.103880

Dogan, C, Miller, CE, Jefferis, T, Saranti, M, Tempesta, AJ, Schofield, AJ, Palaniappan, R & Bowman, H 2025, 'Headache-specific hyperexcitation sensitises and habituates on different time scales: An event related potential study of pattern-glare', Neuroimage. Reports, vol. 5, no. 3, 100271. https://doi.org/10.1016/j.ynirp.2025.100271

Hope, TMH, Bowman, H, Bruce, RM, Leff, AP & Price, CJ 2025, 'Precision-Optimised Post-Stroke Prognoses', Annals of Clinical and Translational Neurology, vol. 12, no. 8, pp. 1619-1627. https://doi.org/10.1002/acn3.70077

Saranti, M, Neville, D, White, A, Rotshtein, P, Hope, TMH, Price, CJ & Bowman, H 2025, 'Predicting language outcome after stroke using machine learning: in search of the big data benefit', NeuroImage: Clinical, vol. 48, 103858. https://doi.org/10.1016/j.nicl.2025.103858

Avilés, A, Orun, E & Bowman, H 2025, 'Stimuli presented on the fringe of awareness do not cause proactive interference', Neuroscience of Consciousness, vol. 2025, no. 1, niaf027. https://doi.org/10.1093/nc/niaf027

Zeng, J, Gao, Z, Xiong, X, Hou, X, Qin, H, Liu, Y, Bowman, H, Ritchie, C, O'Brien, JT & Su, L 2025, 'The effects of two Alzheimer's disease related genes APOE and MAPT in healthy young adults: An attentional blink study ', Journal of Alzheimer's Disease, vol. 103, no. 1, pp. 167-179. https://doi.org/10.1177/13872877241299124

Champion, T, Grześ, M, Bonheme, L & Bowman, H 2024, 'Deconstructing Deep Active Inference: A Contrarian Information Gatherer', Neural Computation, vol. 36, no. 11, pp. 2403-2445. https://doi.org/10.1162/neco_a_01697

Champion, T, Grześ, M & Bowman, H 2024, 'Multimodal and Multifactor Branching Time Active Inference', Neural Computation, vol. 36, no. 11, pp. 2479-2504. https://doi.org/10.1162/neco_a_01703

White, A, Saranti, M, d'Avila Garcez, A, Hope, TMH, Price, CJ & Bowman, H 2024, 'Predicting recovery following stroke: Deep learning, multimodal data and feature selection using explainable AI', NeuroImage: Clinical, vol. 43, 103638. https://doi.org/10.1016/j.nicl.2024.103638

Garner, KG, Nolan, CR, Nydam, A, Nott, Z, Bowman, H & Dux, PE 2024, 'Quantifying error in effect size estimates in attention, executive function, and implicit learning', Journal of Experimental Psychology: Learning, Memory, and Cognition. https://doi.org/10.1037/xlm0001338

Jefferis, T, Dogan, C, Miller, CE, Karathanou, M, Tempesta, A, Schofield, AJ & Bowman, H 2024, 'Sensitization and Habituation of Hyper-Excitation to Constant Presentation of Pattern-Glare Stimuli', Neurology international, vol. 16, no. 6, pp. 1585-1610. https://doi.org/10.3390/neurolint16060116

Hosseini, M, Zivony, A, Eimer, M, Wyble, B & Bowman, H 2024, 'Transient Attention Gates Access Consciousness: Coupling N2pc and P3 Latencies Using Dynamic Time Warping', The Journal of Neuroscience, vol. 44, no. 26, e1798232024. https://doi.org/10.1523/JNEUROSCI.1798-23.2024

Kolibius, LD, Roux, F, Parish, G, Ter Wal, M, Van Der Plas, M, Chelvarajah, R, Sawlani, V, Rollings, DT, Lang, JD, Gollwitzer, S, Walther, K, Hopfengärtner, R, Kreiselmeyer, G, Hamer, H, Staresina, BP, Wimber, M, Bowman, H & Hanslmayr, S 2023, 'Hippocampal neurons code individual episodic memories in humans', Nature Human Behaviour. https://doi.org/10.1038/s41562-023-01706-6

Letter

Hope, TMH, Halai, A, Crinion, J, Castelli, P, Price, CJ & Bowman, H 2024, 'Principal component analysis-based latent-space dimensionality under-estimation, with uncorrelated latent variables', Brain, vol. 147, no. 2, pp. e14-e16. https://doi.org/10.1093/brain/awad355

Review article

Wyble, B, Tam, J, Deal, I & Bowman, H 2025, 'Understanding the flexibility of working memory: Compositionality, generative processing, anchors and holistic representations', Neuroscience and biobehavioral reviews, vol. 179, 106387. https://doi.org/10.1016/j.neubiorev.2025.106387

View all publications in research portal