Harrison, P. M. C., & Pearce, M. T. (2019). A computational model for the analysis and generation of chord voicings. PsyArXiv.

Harrison, P. M. C., & Pearce, M. T. (2019). Instantaneous consonance in the perception and composition of Western music. PsyArXiv.

Larrouy-Maestri, P., Harrison, P. M. C., & Müllensiefen, D. (2019). The mistuning perception test: A new measurement instrument. Behavior Research Methods.

Morrison, S.J., Demorest, S.M., & Pearce, M. T. (2019). Cultural Distance: A Computational Approach to Exploring Cultural Influences on Music Cognition. In M. Thaut and D. Hodges (eds.), Oxford Handbook of Music and the Brain. Oxford: Oxford University Press.

Omigie, D., Pearce, M. T., Lehongre, K., Hasboun, D., Navarro, V., Adam, C., & Samson, S. (2019). Intracranial Recordings and Computational Modeling of Music Reveal the Time Course of Prediction Error Signaling in Frontal and Temporal Cortices. Journal of Cognitive Neuroscience.

Sears, D. R. W., Pearce, M. T., Spitzer, J., Caplin, W. E., & McAdams, S. (2019). Expectations for tonal cadences: Sensory and cognitive priming effects. Quarterly Journal of Experimental Psychology.


Duffy, S. & Pearce, M. T. (2018). What makes rhythms hard to perform? An investigation using Steve Reich’s Clapping Music. PLoS One, 13(10): e0205847.

Harrison, P. M. C. (2018). Statistics and Experimental Design for Psychologists: A model comparison approach (Book review). PsyPAG Quarterly, (108), 41-44.

Harrison, P. M. C., & Müllensiefen, D. (2018). Development and validation of the Computerised Adaptive Beat Alignment Test (CA-BAT). Scientific Reports, 8(12395), 1–19.

Harrison, P. M. C., & Pearce, M. T. (2018). Dissociating sensory and cognitive theories of harmony perception through computational modeling. In Proceedings of ICMPC15/ESCOM10, 23-28 July, Graz, Austria.

Harrison, P. M. C., & Pearce, M. T. (2018). An energy-based generative sequence model for testing sensory theories of Western harmony. In Proceedings of the 19th International Society for Music Information Retrieval Conference, September 23-27, Paris, France.

Pearce, M. T. (2018). Statistical learning and probabilistic prediction in music cognition: mechanisms of stylistic enculturation. Annals of the New York Academy of Sciences, 1423, 378-395.

Sauvé, S.A., Sayed, A., Dean, R. T., & Pearce, M. T. (2018). Effects of pitch and timing expectancy on musical emotion. Psychomusicology. 28, 17-39.

Agres, K., Abdallah, S., & Pearce, M. T. (2018). Information-theoretic properties of auditory sequences dynamically influence expectation and memory. Cognitive Science, 42, 43-76.

Sears, D., Pearce, M. T., Caplin, W. E., & McAdams, S. (2018). Simulating melodic and harmonic expectations for tonal cadences using probabilistic models. Journal of New Music Research, 47, 29-52.

Rohrmeier, M. & Pearce, M. T. (2018). Musical syntax I: Theoretical perspectives. In R. Bader (ed.) Springer Handbook of Systematic Musicology (pp. 473-486). Berlin: Springer-Verlag.

Pearce, M. T. & Rohrmeier, M. (2018). Musical syntax II: Empirical perspectives. In R. Bader (ed.) Springer Handbook of Systematic Musicology (pp. 487-505). Berlin: Springer-Verlag.


Pearce, M. T. & Müllensiefen, D. (2017). Compression-based Modelling of Musical Similarity Perception. Journal of New Music Research, 46, 135-155.

Van der Weij, B., Pearce, M. T., & Honing H. (2017). A probabilistic model of meter perception: simulating enculturation. Frontiers in Psychology, 8, 824.

Cameron, D., Potter, K., Wiggins, G., & Pearce, M. T. (2017). Perception of rhythmic similarity is asymmetrical, and is influenced by musical training, expressive performance, and musical context. Timing and Time Perception, 5, 211-227.

Halpern, A., Zioga, I., Shankleman, M., Lindsen, J., Pearce, M. T., & Bhattacharya, J. (2017). That note sounds wrong! Age-related effects in processing of musical expectation. Brain and Cognition, 113, 1-9.

Harrison, P. M. C. (2017). Jordan B. L. Smith, Elaine Chew, & Gérard Assayag (editors), Mathemusical conversations: Mathematics and computation in music performance and composition. Empirical Musicology Review, 12(1-2), 109-114.

Harrison, P. M. C., Collins, T., & Müllensiefen, D. (2017). Applying modern psychometric techniques to melodic discrimination testing: Item response theory, computerised adaptive testing, and automatic item generation. Scientific Reports, 7, 3618. doi:10.1038/s41598-017-03586-z

Pearce, M. T., & Eerola, T. (2017). Predictive modelling of music perception in historical audiences. Journal of Interdisciplinary Music Studies, 8, 91-120.

Eerola, T., & Pearce, M. T. (2017). Modelling historical audiences: What can be inferred? Journal of Interdisciplinary Music Studies, 8, 132-140.


Barascud, N., Pearce, M. T., Griffiths, T. D., Friston, K. J., & Chait, M. (2016). Brain responses in humans reveal ideal observer-like sensitivity to complex acoustic patterns. Proceedings of the National Academy of Sciences, 113, E616-E625.

Pearce, M. T., Zaidel, D. W., Vartanian, O., Skov, M., Leder, M., Chatterjee, A., & Nadal, M. (2016). Neuroaesthetics: the cognitive neuroscience of aesthetic experience. Perspectives in Psychological Science, 11, 265-279.

Gingras, B., Pearce, M. T., Goodchild, M., Dean, R. T., Wiggins, G., & McAdams, S. (2016). Linking melodic expectation to expressive performance timing and perceived musical tension. Journal of Experimental Psychology: Human Perception and Performance, 42, 594-609.

Hansen, N. C., Vuust, P. & Pearce, M. T. (2016). “If you have to ask, you’ll never know”: Effects of specialised stylistic expertise on predictive processing of music. PLoS One, 11(10), e0163584.

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

Song, Y., Dixon, S., Pearce, M. T., & Halpern, A. (2016). Perceived and induced emotion responses to popular music: Categorical and Dimensional Models. Music Perception, 33, 472-492.

Dean, R.T. & Pearce, M. T. (2016). Algorithmically-generated corpora that use serial compositional principles can contribute to the modeling of sequential pitch structure in non-tonal music. Empirical Musicology Review, 11, 27–46.

Schubert, E. & Pearce, M. T. (2016). A new look at musical expectancy: The veridical versus the general in the mental organization of music. In R. Kronland-Martinet, M. Aramaki, and S. Ystad (eds.), Music, Mind and Embodiment (pp. 358–370). Switzerland: Springer International.

Hansen, N. C., Sadakata, M., & Pearce, M. T. (2016). Nonlinear changes in the rhythm of European art music: Quantitative support for historical musicology. Music Perception, 33, 414-431.


Pearce, M. T. (2015). Effects of expertise on the cognitive and neural processes involved in musical appreciation. In J.P. Huston, M. Nadal, L. Agnati, F. Mora, and C.J. Cela-Conde (eds.), The Oxford Handbook of Neuroaesthetics (pp. 319-338). Oxford: Oxford University Press.

Pearce, M. T. & Halpern, A. R. (2015). Age-related patterns in emotions evoked by music. Psychology of Aesthetics, Creativity and the Arts, 9, 248-253.

Carey, D., Rosen, S., Krishnan, S., Pearce, M.T., Shepherd, A., Aydelott, J., & Dick, F. (2015). Generality and specificity in the effects of musical expertise on perception and cognition. Cognition, 137, 81-105.


Hansen, N. C. & Pearce M. T. (2014). Predictive uncertainty in auditory sequence processing. Frontiers in Psychology, 5, 1052.

Duffy, S., & Healey, P. G. T. (2014). The Conversational Organisation of Musical Contributions. Psychology of Music, 42(6), 888–893.


Brattico, E. & Pearce, M. T. (2013). The neuroaesthetics of music. Psychology of Aesthetics, Creativity and the Arts, 7, 48-61.

Omigie, D., Pearce, M. T., Williamson, V., & Stewart, L. (2013). Electrophysiological correlates of melodic processing in congenital amusia. Neuropsychologia, 51, 1749-1762.

Egermann, H., Pearce, M. T., Wiggins, G. A., & McAdams. (2013). Probabilistic models of expectation violation predict psychophysiological emotional responses to live concert music. Cognitive, Affective and Behavioural Neuroscience, 13, 533-553.

Bailes, F., Dean, R. T., & Pearce M. T. (2013). Music cognition as mental time travel. Scientific Reports, 3, 2690.

Song C., Simpson A. J. R., Harte C. A., Pearce M. T., & Sandler M. B. (2013). Syncopation and the Score. PLoS ONE 8(9): e74692.

Whorley, R., Wiggins, G., Rhodes, C. & Pearce, M. T. (2013). Multiple Viewpoint Systems: Time Complexity and the Construction of Domains for Complex Musical Viewpoints in the Harmonisation Problem. Journal of New Music Research, 42, 237-266.

Cherla, S., Weyde, T., Garcez, A. d’Avila & Pearce, M. T. (2013). Learning Distributed Representations for Multiple-Viewpoint Melodic Prediction. Paper presented at the 14th International Society for Music Information Retrieval Conference, 4 – 8 Nov 2013, Curitiba, PR, Brazil.

Agres, K., Abdallah, S., & Pearce, M. T. (2013). An Information-Theoretic Account of Musical Expectation and Memory. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 127-132). Austin, Texas: Cognitive Science Society.

Song Y., Dixon, S., Pearce, M. & Halpern, A. (2013). Do Online Social Tags Predict Perceived or Induced Emotional Responses to Music. Proceedings of the 14th International Society for Music Information Retrieval (ISMIR), 4-8 Nov 2013, Brazil.

Song, Y., Dixon, S. & Pearce, M. (2013). Using Tags to Select Stimuli in the Study of Music and Emotion. Proceedings of the 3rd International Conference on Music and Emotion (ICME), 11-15 Jun 2013, Finland.


Carrus, E., Pearce, M. T., & Bhattacharya, J. (2012). Melodic pitch expectation interacts with neural responses to syntactic but not semantic violations. Cortex.

Pearce, M. T. & Rohrmeier, M. (2012). Music cognition and the cognitive sciences. TopiCS in Cognitive Science, 4, 468-484.

Cameron, D. J., Stewart, L., Pearce, M. T., Grube, M., & Muggleton, N. G. (2012). Modulation of motor excitability by metricality of tone sequences. Psychomusicology, 22, 122-128.

Omigie, D., Pearce, M. T., & Stewart, L. (2012). Tracking of pitch probabilities in congenital amusia. Neuropsychologia, 50, 1483-1493.

Pearce, M. T. & Wiggins, G. A. (2012). Auditory expectation: The information dynamics of music perception and cognition. TopiCS in Cognitive Science, 4, 625-652.

Pearce, M. T., Christensen, J.F. (2012). Conference Report: The Neurosciences and Music – IV – Learning and Memory.Psychomusicology, 22, 70-73.

Song, Y., Dixon, S., & Pearce, M. T. (2012). Evaluation of Musical Features for Emotion Classification. In proceedings of the 13th International Society for Music Information Retrieval (ISMIR), 8-12 Oct 2012, Portugal.

Song, Y., Dixon, S., & Pearce, M. T. (2012). A Survey of Music Recommendation Systems and Future Perspectives. In proceedings of the 9th International Symposium on Computer Music Modelling and Retrieval (CMMR), 19-22 Jun 2012, London


Pearce, M. T. (2011). Time-series analysis of Music: Perceptual and Information Dynamics. Empirical Musicology Review, 6, 125-130.

Nadal, M., & Pearce, M. T. (2011). The Copenhagen Neuroaesthetics conference: Prospects and pitfalls for an emerging field. Brain and Cognition, 76, 172-183.