Dr Marcus Pearce

Senior Lecturer
Email: marcus.pearce@qmul.ac.ukTelephone: +44 20 7882 6207Room Number: Peter Landin, CS 406Website: http://webprojects.eecs.qmul.ac.uk/marcusp/Office Hours: Friday 09:00-10:30
Teaching
Music Perception and Cognition (Postgraduate/Undergraduate)
Music is a fundamental part of being human and exists only in the mind of the listener. This module will provide students with advanced training in current understanding of how musical sound is processed by the mind and brain. This is crucial for developing creative tools for musicians and intuitive interfaces for music lovers as well as for using technology in the creative production of new music.
Research
Research Interests:
- Music Cognition
- Empirical Aesthetics and Neuroaesthetics
- Emotion and Music
- Auditory Perception
- Statistical Learning
- Expectation and Prediction
Publications
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Klarlund M, Brattico E, Pearce M et al. (2023). Worlds apart? Testing the cultural distance hypothesis in music perception of Chinese and Western listeners.. nameOfConference
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Hansen NC, Højlund A, Møller C et al. (2022). Musicians show more integrated neural processing of contextually relevant acoustic features. nameOfConference
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Agres K, Tay TY, Pearce M (2022). Comparing Musicians and Non-musicians' Expectations in Music and Vision. nameOfConference
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Kaplan T, Cannon J, Jamone L et al. (2022). Modeling enculturated bias in entrainment to rhythmic patterns. nameOfConference
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Tenderini MS, de Leeuw E, Eilola TM et al. (2022). Reduced Cross-Modal Affective Priming in the L2 of Late Bilinguals Depends on L2 Exposure. nameOfConference
DOI: 10.1037/xlm0000889
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Quiroga-Martinez DR, Hansen NC, Højlund A et al. (2021). Musicianship and melodic predictability enhance neural gain in auditory cortex during pitch deviance detection. nameOfConference
DOI: 10.1002/hbm.25638
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Goldman A, Harrison PMC, Jackson T et al. (2021). Reassessing Syntax-Related ERP Components Using Popular Music Chord Sequences. nameOfConference
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Krishnan S, Carey D, Dick F et al. (2021). Effects of statistical learning in passive and active contexts on reproduction and recognition of auditory sequences.. nameOfConference
DOI: 10.1037/xge0001091
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Hansen NC, Kragness HE, Vuust P et al. (2021). Predictive Uncertainty Underlies Auditory Boundary Perception. nameOfConference
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de Fleurian R, Pearce MT (2021). The Relationship Between Valence and Chills in Music: A Corpus Analysis. nameOfConference
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Hall ETR, Pearce MT (2021). A model of large-scale thematic structure. nameOfConference
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Clemente A, Pearce MT, Skov M et al. (2021). Evaluative judgment across domains: Liking balance, contour, symmetry and complexity in melodies and visual designs. nameOfConference
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Clemente A, Pearce MT, Nadal M (2021). Musical Aesthetic Sensitivity. nameOfConference
DOI: 10.1037/aca0000381
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de Fleurian R, Pearce MT (2021). Chills in Music: A Systematic Review. nameOfConference
DOI: 10.1037/bul0000341
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Nadal M, Pearce M (2021). The Cognitive Neuroscience of Aesthetic Experience. nameOfConference
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Politimou N, Douglass-Kirk P, Pearce M et al. (2020). Melodic expectations in 5- and 6-year-old children. nameOfConference
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Harrison PMC, Bianco R, Chait M et al. (2020). PPM-Decay: A computational model of auditory prediction with memory decay. nameOfConference
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Zioga I, Harrison PMC, Pearce MT et al. (2020). Auditory but not audiovisual cues lead to higher neural sensitivity to the statistical regularities of an unfamiliar musical style. nameOfConference
DOI: 10.1162/jocn_a_01614
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Ycart A, Liu L, Benetos E et al. (2020). Investigating the Perceptual Validity of Evaluation Metrics for Automatic Piano Music Transcription. nameOfConference
DOI: 10.5334/tismir.57
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Bianco R, Harrison PMC, Hu M et al. (2020). Long-term implicit memory for sequential auditory patterns in humans. nameOfConference
DOI: 10.7554/eLife.56073
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Ycart A, Liu L, Benetos E et al. (2020). Musical Features for Automatic Music Transcription Evaluation. nameOfConference
DOI: doi
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Quiroga-Martinez DR, Hansen NC, Højlund A et al. (2020). Decomposing neural responses to melodic surprise in musicians and non-musicians: Evidence for a hierarchy of predictions in the auditory system. nameOfConference
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Clemente A, Vila-Vidal M, Pearce MT et al. (2020). A Set of 200 Musical Stimuli Varying in Balance, Contour, Symmetry, and Complexity: Behavioral and Computational Assessments.. nameOfConference
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Harrison PMC, Pearce MT (2020). A computational cognitive model for the analysis and generation of voice leadings. nameOfConference
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Quiroga-Martinez DR, Hansen NC, Højlund A et al. (2020). Musical prediction error responses similarly reduced by predictive uncertainty in musicians and non-musicians. nameOfConference
DOI: 10.1101/754333
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Quiroga-Martinez DR, C Hansen N, Højlund A et al. (2019). Musical prediction error responses similarly reduced by predictive uncertainty in musicians and non-musicians.. nameOfConference
DOI: 10.1111/ejn.14667
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Harrison P, Pearce M (publicationYear). Simultaneous consonance in music perception and composition. nameOfConference
DOI: 10.1037/rev0000169
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Pearce M, Sauvé S (2019). Information-theoretic Modeling of Perceived Musical Complexity. nameOfConference
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Cheung V, HARRISON PMC, Meyer L et al. (2019). Uncertainty and Surprise Jointly Predict Musical Pleasure and Amygdala, Hippocampus, and Auditory Cortex Activity. nameOfConference
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Zioga I, Harrison P, Pearce M et al. (2019). From learning to creativity: Identifying the behavioural and neural correlates of learning to predict human judgements of musical creativity. nameOfConference
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Gold B, Pearce M, Mas-Herrero E et al. (2019). Predictability and uncertainty in the pleasure of music: a reward for learning?. nameOfConference
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de Fleurian R, Harrison PMC, Pearce MT et al. (2019). Reward prediction tells us less than expected about musical pleasure. nameOfConference
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Cameron DJ, Zioga I, Lindsen JP et al. (2019). Neural entrainment is associated with subjective groove and complexity for performed but not mechanical musical rhythms. nameOfConference
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Quiroga-Martinez DR, Hansen NC, Højlund A et al. (2019). Reduced prediction error responses in high-as compared to low-uncertainty musical contexts. nameOfConference
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Omigie D, Pearce M, Lehongre K et al. (2019). Intracranial Recordings and Computational Modeling of Music Reveal the Time Course of Prediction Error Signaling in Frontal and Temporal Cortices.. nameOfConference
DOI: 10.1162/jocn_a_01388
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Sears DRW, Pearce MT, Spitzer J et al. (2018). Expectations for tonal cadences: Sensory and cognitive priming effects.. nameOfConference
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Duffy S, Pearce M (2018). What makes rhythms hard to perform? An investigation using Steve Reich's Clapping Music.. nameOfConference
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Quiroga-Martinez DR, Hansen NC, Højlund A et al. (2018). Reduced prediction error responses in high- as compared to low-uncertainty musical contexts. nameOfConference
DOI: 10.1101/422949
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PEARCE MT (2018). Statistical Learning and Probabilistic Prediction in Music Cognition: Mechanisms of Stylistic Enculturation. nameOfConference
DOI: 10.1111/nyas.13654
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Sauvé SA, Sayed A, Dean RT et al. (2018). Effects of Pitch and Timing Expectancy on Musical Emotion. nameOfConference
DOI: 10.1037/pmu0000203
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Harrison PMC, Pearce MT (2018). An energy-based generative sequence model for testing sensory theories of Western harmony. nameOfConference
DOI: doi
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Rohrmeier M, Pearce M (2018). Musical Syntax I: Theoretical Perspectives. nameOfConference
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Pearce M, Rohrmeier M (2018). Musical Syntax II: Empirical Perspectives. nameOfConference
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Sears DRW, PEARCE MT, Caplin WE et al. (2017). Simulating melodic and harmonic expectations for tonal cadences using probabilistic models. nameOfConference
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Cameron D, Potter K, Wiggins G et al. (2017). Perception of Rhythmic Similarity is Asymmetrical, and Is Influenced by Musical Training, Expressive Performance, and Musical Context. nameOfConference
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van der Weij B, Pearce MT, Honing H (2017). A Probabilistic Model of Meter Perception: Simulating Enculturation.. nameOfConference
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Pearce M, Müllensiefen D (2017). Compression-based Modelling of Musical Similarity Perception. nameOfConference
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Agres K, Abdallah S, Pearce M (2017). Information-Theoretic Properties of Auditory Sequences Dynamically Influence Expectation and Memory. nameOfConference
DOI: 10.1111/cogs.12477
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Halpern AR, Zioga I, Shankleman M et al. (2017). That note sounds wrong! Age-related effects in processing of musical expectation.. nameOfConference
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Hansen NC, Vuust P, Pearce M (2016). "If You Have to Ask, You'll Never Know": Effects of Specialised Stylistic Expertise on Predictive Processing of Music. nameOfConference
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Bhattacharya J, Halpern A, Zioga L et al. (2016). Brains of older adults process melodic expectancy differently from those of younger adults. Proceedings of the 18th World Congress of Psychophysiology
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Dean RT, Pearce MT (2016). Algorithmically-generated Corpora that use Serial Compositional Principles Can Contribute to the Modeling of Sequential Pitch Structure in Non-tonal Music. nameOfConference
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Hansen NC, Sadakata M, Pearce M (2016). Nonlinear Changes in the Rhythm of European Art Music: Quantitative Support for Historical Musicology. nameOfConference
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Gingras B, Pearce MT, Goodchild M et al. (2016). Linking melodic expectation to expressive performance timing and perceived musical tension. nameOfConference
DOI: 10.1037/xhp0000141
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Pearce MT, Zaidel DW, Vartanian O et al. (2016). Neuroaesthetics: The Cognitive Neuroscience of Aesthetic Experience. nameOfConference
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Barascud N, Pearce MT, Griffiths TD et al. (2016). Brain responses in humans reveal ideal observer-like sensitivity to complex acoustic patterns. nameOfConference
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PEARCE MT, Schubert E (2016). A New Look at Musical Expectancy: The Veridical Versus the General in the Mental Organization of Music. nameOfConference
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Song Y, Dixon S, Pearce MT et al. (2016). Perceived and Induced Emotion Responses to Popular Music: Categorical and Dimensional Models. nameOfConference
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Pearce MT, Halpern AR (2015). Age-related patterns in emotions evoked by music. nameOfConference
DOI: 10.1037/a0039279
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Carey D, Rosen S, Krishnan S et al. (2015). Generality and specificity in the effects of musical expertise on perception and cognition. nameOfConference
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Hansen NC, Pearce MT (2014). Predictive uncertainty in auditory sequence processing.. nameOfConference
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Whorley R, Wiggins GA, Rhodes CS et al. (2013). Multiple Viewpoint Systems: Time Complexity and the Construction of Domains for Complex Musical Viewpoints. nameOfConference
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Bailes F, Dean RT, Pearce MT (2013). Music cognition as mental time travel. nameOfConference
DOI: 10.1038/srep02690
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Omigie D, Pearce MT, Williamson VJ et al. (2013). Electrophysiological correlates of melodic processing in congenital amusia. nameOfConference
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Omigie D, Pearce MT, Stewart L et al. (2013). Electrophysiological correlates of melodic processing in congenital amusia. nameOfConference
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Egermann H, Pearce MT, Wiggins GA et al. (2013). Probabilistic models of expectation violation predict psychophysiological emotional responses to live concert music.. nameOfConference
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Song C, Simpson AJR, Harte CA et al. (2013). Syncopation and the score.. nameOfConference
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Brattico E, Pearce MT (2013). The Neuroaesthetics of Music. nameOfConference
DOI: 10.1037/a0031624
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Cameron DJ, Stewart L, Pearce MT et al. (2012). Modulation of Motor Excitability by Metricality of Tone Sequences. nameOfConference
DOI: 10.1037/a0031229
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Pearce M, Rohrmeier M (2012). Music Cognition and the Cognitive Sciences. nameOfConference
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Pearce MT, Wiggins GA (2012). Auditory Expectation: The Information Dynamics of Music Perception and Cognition. nameOfConference
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Pearce MT, Christensen JF (2012). Conference Report: The Neurosciences and Music - IV - Learning and Memory. nameOfConference
DOI: 10.1037/a0027235
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Carrus E, Pearce MT, Bhattacharya J (2012). Melodic pitch expectation interacts with neural responses to syntactic but not semantic violations. nameOfConference
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Omigie D, Pearce MT, Stewart L (2012). Tracking of pitch probabilities in congenital amusia. nameOfConference
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Pearce MT (2011). Time-series analysis of Music: Perceptual and Information Dynamics. nameOfConference
DOI: 10.18061/1811/51214
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Pearce MT, Müllensiefen D, Wiggins GA (2010). The role of expectation and probabilistic learning in auditory boundary perception: a model comparison.. nameOfConference
DOI: 10.1068/p6507
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Pearce MT, Müllensiefen D, Wiggins GA (2010). Melodic Grouping in Music Information Retrieval: New Methods and Applications. nameOfConference
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Pearce MT, Müllensiefen D, Wiggins GA (2010). Melodic grouping in music information retrieval: New methods and applications. nameOfConference
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Wiggins GA, Müllensiefen D, Pearce MT (2010). On the non-existence of Music: Why music theory is a figment of the imagination. nameOfConference
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Nadal M, Pearce MT (2010). The Copenhagen Neuroaesthetics conference: Prospects and pitfalls for an emerging field. nameOfConference
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Pearce MT, Müllensiefen D, Wiggins GA (2010). The role of expectation and probabilistic learning in auditory boundary perception: A model comparison. nameOfConference
DOI: 10.1068/p6507
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Pearce MT, Herrojo Ruiz M, Kapasi S et al. (2010). Unsupervised Statistical Learning Underpins Computational, Behavioural and Neural Manifestations of Musical Expectation. nameOfConference
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Wiggins GA, Pearce MT, Müllensiefen D (2009). Computational Modelling of Music Cognition and Musical Creativity. nameOfConference
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Pearce MT, Müllensiefen D (2008). David Huron, Sweet Anticipation: Music and the Psychology of Expectation. Cambridge, Massachusetts: MIT Press, 2007, 512 pp., ISBN 0262083450, (Hardcover).. nameOfConference
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Potter K, Wiggins GA, Pearce MT (2007). Towards greater objectivity in music theory: Information-dynamic analysis of minimalist music. nameOfConference
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Pearce MT, Wiggins GA (2006). Expectation in Melody: The Influence of Context and Learning. nameOfConference
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Pearce MT, Conklin D, Wiggins GA (2005). Methods for Combining Statistical Models of Music. nameOfConference
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Pearce MT, Wiggins GA (2004). Improved Methods for Statistical Modelling of Monophonic Music. nameOfConference
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Pearce M, Wiggins GA, Meredith D (2001). Motivations and Methodologies for Automation of the Compositional Process.. nameOfConference
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