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

Champion, T, Grześ, M & Bowman, H 2022, 'Branching Time Active Inference with Bayesian Filtering', Neural Computation, vol. 34, no. 10, pp. 2132–2144. https://doi.org/10.1162/neco_a_01529

Champion, T, Da Costa, L, Bowman, H & Grześ, M 2022, 'Branching time active inference: the theory and its generality', Neural Networks, vol. 151, pp. 295-316. https://doi.org/10.1016/j.neunet.2022.03.036

Champion, T, Bowman, H & Grześ, M 2022, 'Branching time active inference: empirical study and complexity class analysis', Neural Networks, vol. 152, pp. 450-466. https://doi.org/10.1016/j.neunet.2022.05.010

Chen, IY, Karabay, A, Mathȏt, S, Bowman, H & Akyürek, EG 2022, 'Concealed identity information detection with pupillometry in rapid serial visual presentation', Psychophysiology. https://doi.org/10.1111/psyp.14155

Bowman, H, Jones, W, Pincham, H, Fleming, S, Cleeremans, A & Smith, M 2022, 'Modelling the simultaneous encoding/serial experience theory of the perceptual moment: a blink of meta-experience', Neuroscience of Consciousness, vol. 2022, no. 1, niac003. https://doi.org/10.1093/nc/niac003

Hellerstedt, R, Moccia, A, Brunskill, CM, Bowman, H & Bergström, ZM 2021, 'Aging reduces EEG markers of recognition despite intact performance: implications for forensic memory detection', Cortex, vol. 140, pp. 80-97. https://doi.org/10.1016/j.cortex.2021.03.015

Alsufyani, A, Harris, K, Zoumpoulaki, A, Filetti, M & Bowman, H 2021, 'Breakthrough percepts of famous names', Cortex, vol. 139, pp. 267-281. https://doi.org/10.1016/j.cortex.2021.02.030

PLORAS team 2021, 'Damage to Broca's area does not contribute to long-term speech production outcome after stroke', Brain, vol. 144, no. 3, pp. 817-832. https://doi.org/10.1093/brain/awaa460

Ihalainen, R, Gosseries, O, van de Steen, F, Raimondo, F, Panda, R, Bonhomme, V, Marinazzo, D, Bowman, H, Laureys, S & Chennu, S 2021, 'How hot is the hot zone? Computational modelling clarifies the role of parietal and frontoparietal connectivity during anaesthetic-induced loss of consciousness', NeuroImage, vol. 231, 117841. https://doi.org/10.1016/j.neuroimage.2021.117841

Bowman, H, Bonkhoff, A, Hope, TMH, Grefkes, C & Price, C 2021, 'Inflated estimates of proportional recovery from stroke: the dangers of mathematical coupling and compression to ceiling', Stroke, vol. 52, no. 5, pp. 1915-1920. https://doi.org/10.1161/STROKEAHA.120.033031

Champion, T, Grześ, M & Bowman, H 2021, 'Realizing active inference in variational message passing: the outcome-blind certainty seeker', Neural Computation, vol. 33, no. 10, pp. 2662-2626. https://doi.org/10.1162/neco_a_01422

Bonkhoff, AK, Hope, T, Bzdok, D, Hawe, RL, Dukelow, SP, Chollet, F, Lin, DJ, Grefkes, C, Bowman, H & Guggisberg, A 2021, 'Recovery after stroke: the severely impaired are a distinct group', Journal of Neurology Neurosurgery and Psychiatry. https://doi.org/10.1136/jnnp-2021-327211

Parish, G, Michelmann, S, Hanslmayr, S & Bowman, H 2021, 'The Sync-Fire/deSync model: modelling the reactivation of dynamic memories from cortical alpha oscillations', Neuropsychologia, vol. 158, 107867. https://doi.org/10.1016/j.neuropsychologia.2021.107867

Tempesta, AJ, Miller, CE, Litvak, V, Bowman, H & Schofield, AJ 2021, 'The missing N1 or jittered P2: electrophysiological correlates of pattern-glare in the time and frequency domain', European Journal of Neuroscience, vol. 54, no. 6, pp. 6168-6186. https://doi.org/10.1111/ejn.15419

Comment/debate

Bowman, H & Avilés, A 2022, 'No Subliminal Memory for Spaced Repeated Images in Rapid-Serial-Visual-Presentation Streams', Psychological Science. https://doi.org/10.1177/09567976221100229

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