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Social Sciences and Humanities

D-Index
46
Citations
7717
World Ranking
3669
National Ranking
627

Overview

Marcus T. Pearce is affiliated with Queen Mary University of London in the United Kingdom. Their research spans areas including neuroscience and computer science, with a particular focus on cognitive neuroscience and signal processing within these fields.

The scientist's work primarily addresses topics related to neuroscience and music perception, music and audio processing, and neural dynamics and brain function. Additional research areas include music technology and sound studies, multisensory perception and integration, hearing loss and rehabilitation, and diverse musicological studies.

Frequent publication venues for their work include bioRxiv (Cold Spring Harbor Laboratory), PLoS Computational Biology, Cognition, Psychology of Aesthetics Creativity and the Arts, and Music Perception An Interdisciplinary Journal.

Among their recent papers are:

  • "Long-term implicit memory for sequential auditory patterns in humans," 2020, eLife
  • "Decomposing neural responses to melodic surprise in musicians and non-musicians: Evidence for a hierarchy of predictions in the auditory system," 2020, NeuroImage
  • "PPM-Decay: A computational model of auditory prediction with memory decay," 2020, PLoS Computational Biology
  • "Predictive Uncertainty Underlies Auditory Boundary Perception," 2021, Psychological Science
  • "Modeling enculturated bias in entrainment to rhythmic patterns," 2022, PLoS Computational Biology

Notable frequent co-authors include:

  • Maria Chait
  • Roberta Bianco
  • Peter M. C. Harrison
  • Peter Vuust
  • Ana Clemente

The main fields of study reflect a strong orientation towards the intersection of cognitive neuroscience and computational approaches. Subfields also highlight a focus on experimental and cognitive psychology as well as computer vision and pattern recognition.

Best Publications

  • EXPECTATION IN MELODY: THE INFLUENCE OF CONTEXT AND LEARNING

    Marcus T. Pearce;Geraint A. Wiggins

  • The construction and evaluation of statistical models of melodic structure in music perception and composition

    Marcus Thomas Pearce

  • Neuroaesthetics: The Cognitive Neuroscience of Aesthetic Experience.

    Marcus T. Pearce;Dahlia W. Zaidel;Oshin Vartanian;Martin Skov

  • Unsupervised statistical learning underpins computational, behavioural, and neural manifestations of musical expectation

    Marcus T. Pearce;Marcus T. Pearce;María Herrojo Ruiz;Selina Kapasi;Geraint A. Wiggins

  • Auditory Expectation: The Information Dynamics of Music Perception and Cognition

    Marcus T. Pearce;Geraint A. Wiggins

  • Brain responses in humans reveal ideal observer-like sensitivity to complex acoustic patterns

    Nicolas Barascud;Marcus T. Pearce;Timothy D. Griffiths;Karl J. Friston

  • Uncertainty and Surprise Jointly Predict Musical Pleasure and Amygdala, Hippocampus, and Auditory Cortex Activity

    Vincent Ka Ming Cheung;Peter M. C. Harrison;Lars Meyer;Marcus T. Pearce;Marcus T. Pearce

  • The neuroaesthetics of music.

    Elvira Brattico;Marcus Pearce

  • Probabilistic models of expectation violation predict psychophysiological emotional responses to live concert music

    Hauke Egermann;Hauke Egermann;Marcus T. Pearce;Geraint A. Wiggins;Stephen McAdams

  • A Survey of Music Recommendation Systems and Future Perspectives

    Yading Song;Simon Dixon;Marcus Pearce

  • Statistical learning and probabilistic prediction in music cognition: mechanisms of stylistic enculturation.

    Marcus T. Pearce

  • Predictability and Uncertainty in the Pleasure of Music: A Reward for Learning?

    Benjamin P. Gold;Marcus T. Pearce;Ernest Mas-Herrero;Alain Dagher

  • Predictive uncertainty in auditory sequence processing.

    Marcus T. Pearce

  • Improved Methods for Statistical Modelling of Monophonic Music

    Marcus T. Pearce;Geraint A. Wiggins

  • The Role of Expectation and Probabilistic Learning in Auditory Boundary Perception: A Model Comparison:

    Marcus T Pearce;Daniel Müllensiefen;Geraint A Wiggins

  • The Copenhagen Neuroaesthetics conference: Prospects and pitfalls for an emerging field

    Marcos Nadal;Marcus T. Pearce

  • Electrophysiological correlates of melodic processing in congenital amusia

    Diana Omigie;Marcus T. Pearce;Victoria J. Williamson;Lauren Stewart

  • Towards a framework for the evaluation of machine compositions

    M. T. Pearce;G. A. Wiggins

  • EVALUATION OF MUSICAL FEATURES FOR EMOTION CLASSIFICATION

    Yading Song;Simon Dixon;Marcus T. Pearce

  • Simultaneous consonance in music perception and composition.

    Peter M C Harrison;Marcus T Pearce

  • Motivations and Methodologies for Automation of the Compositional Process

    Marcus Pearce;David Meredith;Geraint Wiggins

Frequent Co-Authors

Peter Vuust
Peter Vuust Royal Academy of Music
Joydeep Bhattacharya
Joydeep Bhattacharya Goldsmiths University of London
Marcos Nadal
Marcos Nadal University of the Balearic Islands
Elvira Brattico
Elvira Brattico University of Helsinki
Karl J. Friston
Karl J. Friston University College London
Lauren Stewart
Lauren Stewart Goldsmiths University of London
Stefan Koelsch
Stefan Koelsch University of Bergen
Andrea R. Halpern
Andrea R. Halpern Bucknell University
Roger T. Dean
Roger T. Dean Western Sydney University
Stephen McAdams
Stephen McAdams McGill University

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