Peter Harrison


  • Computational cognitive science
  • Statistical cognition
  • Auditory perception
  • Musical aesthetics



2015–2019PhD in Cognitive Science, Queen Mary, University of London
2014–2015MSc in Music, Mind & Brain, Goldsmiths, University of London
2010–2014BA in Music, University of Cambridge



Peter M. C. Harrison, Roberta Bianco, Maria Chait, Marcus T. Pearce (2020, provisionally accepted). PPM-Decay: A computational model of auditory prediction with memory decay. PLOS Computational Biology.

Ioanna Zioga, Peter M. C. Harrison, Marcus T. Pearce, Joydeep Bhattacharya, and Caroline Di Bernardi Luft (2020). Auditory but not audiovisual cues lead to higher neural sensitivity to the statistical regularities of an unfamiliar musical style. Journal of Cognitive Neuroscience.

Daniel Müllensiefen, Peter M. C. Harrison (2020). The impact of music on adolescents’ cognitive and socio-emotional learning. The 'BrainCanDo' handbook of teaching and learning: Practical strategies to bring psychology and neuroscience into the classroom. Routledge.

Roberta Bianco, Peter M. C. Harrison, Mingyue Hu, Cora Bolger, Samantha Picken, Marcus T. Pearce, Maria Chait (2020). Long-term implicit memory for sequential auditory patterns in humans. 'eLife', 9, e56073.

Peter M. C. Harrison (2020). psychTestR: An R package for designing and conducting behavioural psychological experiments. Journal of Open Source Software, 5(49), 2088.

Peter M. C. Harrison, Marcus T. Pearce (2020). Simultaneous consonance in music perception and composition. Psychological Review, 127(2), 216-244.

Peter M. C. Harrison and Marcus T. Pearce (2020). A computational cognitive model for the analysis and generation of voice leadings. Music Perception, 37(3), 208-224.

Vincent Cheung, Peter M. C. Harrison, Lars Meyer, Marcus Pearce, John-Dylan Haynes, Stefan Koelsch (2019). Uncertainty and surprise jointly predict musical pleasure and amygdala, hippocampus, and auditory cortex activity. Current Biology, 29(23), 4084-4092.e4.

Ioanna Zioga, Peter M. C. Harrison, Marcus T. Pearce, Joydeep Bhattacharya, Caroline D. B. Luft (2019). From learning to creativity: Identifying the behavioural and neural correlates of learning to predict human judgements of musical creativity. Neuroimage 

Rémi de Fleurian*, Peter M. C. Harrison*, Marcus T. Pearce*, David R. Quiroga-Martinez* (2019). Reward prediction tells us less than expected about musical pleasure. Proceedings of the National Academy of Sciences. *Equal contribution

Rebecca Gelding, Peter M. C. Harrison, Seb Silas, Blake W. Johnson, William Forde Thompson, Daniel Müllensiefen (2020). An efficient and adaptive test of auditory mental imagery. Psychological Research.

Pauline Larrouy-Maestri, Peter M. C. Harrison, Daniel Müllensiefen (2019). The Mistuning Perception Test: A new measurement instrument. Behavior Research Methods, 51(2), 663—675.

Peter M. C. Harrison (2018). Statistics and Experimental Design for Psychologists: A model comparison approach by Rory Allen (book review). PsyPAG Quarterly, 108.

Peter M. C. Harrison, Daniel Müllensiefen (2018). Development and validation of the Computerised Adaptive Beat Alignment Test (CA-BAT). Scientific Reports, 8.

Peter M. C. Harrison, Marcus T. Pearce (2018). Dissociating sensory and cognitive theories of harmony perception through computational modeling. Proceedings of ICMPC15/ESCOM10.

Peter M. C. Harrison, Marcus T. Pearce (2018). An energy-based generative sequence model for testing sensory theories of Western harmony. Proceedings of the 19th International Society for Music Information Retrieval Conference.

Peter M. C. Harrison, Tom Collins, Daniel Müllensiefen (2017). Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation. Scientific Reports, 7.

Peter M. C. Harrison (2017). Mathemusical conversations: Mathematics and computation in music performance and composition. Empirical Musicology Review, 12(1—2).

Peter M. C. Harrison, J. J. Musil, D. Müllensiefen (2016). Modelling melodic discrimination tests: Descriptive and explanatory approaches. Journal of New Music Research, 45(3), 265—280.

Daniel Müllensiefen, Peter M. C. Harrison, Francesco Caprini, Amy Fancourt (2015). Investigating the importance of self-theories of intelligence and musicality for students' academic and musical achievement. Frontiers in Psychology, 6.

Auszeichnungen & Stipendien

2018£173,318 grant from Innovate UK, “Increasing AI adoption rates in the UK legal and high-value services sectors through use of AI microservices and behavioural change science”. Partnered with Legatics (
2018Jon Rasbash Prize for Quantitative Social Science, Centre for Multilevel Modelling, University of Bristol
2018Travel grant, Society for Education and Music Psychology Research
2016Best poster award, 7th Annual Conference of the British Society for the Psychology of Individual Differences
2015Doctoral studentship, EPSRC/AHRC doctoral training centre for Media & Arts Technology