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D-Index & Metrics

Social Sciences and Humanities

D-Index
46
Citations
7717
World Ranking
3669
National Ranking
628

Marcus T. Pearce publication distribution in Social Sciences and Humanities in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Social Sciences and Humanities in 2026. The highlighted bar marks where Marcus T. Pearce sits on this spectrum.

44–53 publications: 28 scientists 54–63 publications: 61 scientists 64–73 publications: 161 scientists 74–83 publications: 225 scientists 84–93 publications: 301 scientists 94–103 publications: 390 scientists 104–113 publications: 406 scientists 114–123 publications: 474 scientists 124–133 publications: 453 scientists 134–143 publications: 434 scientists 144–153 publications: 407 scientists 154–163 publications: 411 scientists 164–173 publications: 391 scientists 174–183 publications: 313 scientists 184–193 publications: 319 scientists 194–203 publications: 304 scientists 204–213 publications: 285 scientists 214–223 publications: 246 scientists 224–233 publications: 213 scientists 234–243 publications: 170 scientists 244–253 publications: 167 scientists 254–263 publications: 162 scientists 264–273 publications: 138 scientists 274–283 publications: 138 scientists 284–293 publications: 113 scientists 294–303 publications: 106 scientists 304–313 publications: 95 scientists 314–323 publications: 101 scientists 324–333 publications: 81 scientists 334–343 publications: 69 scientists 344–353 publications: 56 scientists 354–363 publications: 36 scientists 364–373 publications: 42 scientists 374–383 publications: 41 scientists 384–393 publications: 44 scientists 394–403 publications: 27 scientists 404–413 publications: 30 scientists 414–423 publications: 20 scientists 424–433 publications: 29 scientists 434–443 publications: 29 scientists 444–453 publications: 25 scientists 454–463 publications: 19 scientists 464–473 publications: 21 scientists 474–483 publications: 11 scientists 484–493 publications: 17 scientists 494–503 publications: 7 scientists 504–513 publications: 6 scientists 514–523 publications: 12 scientists 524–533 publications: 10 scientists 534–543 publications: 7 scientists 544–553 publications: 6 scientists 554–563 publications: 12 scientists 564–569 publications: 8 scientists 570+ publications: 100 scientists
44 publications 570+

This scientist: 137 publications — 34th percentile

34% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 570 publications or more.

Marcus T. Pearce D-index placement in Social Sciences and Humanities in 2026

The chart shows the D-index (discipline H-index) distribution of Social Sciences and Humanities scientists ranked by Research.com in 2026. The highlighted bar marks where Marcus T. Pearce sits on this spectrum.

30 D-Index: 177 scientists 31 D-Index: 210 scientists 32 D-Index: 222 scientists 33 D-Index: 188 scientists 34 D-Index: 181 scientists 35 D-Index: 243 scientists 36 D-Index: 261 scientists 37 D-Index: 272 scientists 38 D-Index: 278 scientists 39 D-Index: 300 scientists 40 D-Index: 297 scientists 41 D-Index: 308 scientists 42 D-Index: 313 scientists 43 D-Index: 300 scientists 44 D-Index: 269 scientists 45 D-Index: 260 scientists 46 D-Index: 228 scientists 47 D-Index: 251 scientists 48 D-Index: 203 scientists 49 D-Index: 186 scientists 50 D-Index: 187 scientists 51 D-Index: 166 scientists 52 D-Index: 138 scientists 53 D-Index: 141 scientists 54 D-Index: 131 scientists 55 D-Index: 137 scientists 56 D-Index: 109 scientists 57 D-Index: 129 scientists 58 D-Index: 95 scientists 59 D-Index: 105 scientists 60 D-Index: 106 scientists 61 D-Index: 86 scientists 62 D-Index: 94 scientists 63 D-Index: 77 scientists 64 D-Index: 79 scientists 65 D-Index: 59 scientists 66 D-Index: 68 scientists 67 D-Index: 51 scientists 68 D-Index: 49 scientists 69 D-Index: 40 scientists 70 D-Index: 43 scientists 71 D-Index: 40 scientists 72 D-Index: 50 scientists 73 D-Index: 46 scientists 74 D-Index: 43 scientists 75 D-Index: 45 scientists 76 D-Index: 45 scientists 77 D-Index: 30 scientists 78 D-Index: 25 scientists 79 D-Index: 31 scientists 80 D-Index: 29 scientists 81 D-Index: 18 scientists 82 D-Index: 21 scientists 83 D-Index: 26 scientists 84 D-Index: 15 scientists 85 D-Index: 15 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 12 scientists 89 D-Index: 7 scientists 90 D-Index: 19 scientists 91 D-Index: 20 scientists 92 D-Index: 13 scientists 93 D-Index: 9 scientists 94 D-Index: 13 scientists 95 D-Index: 8 scientists 96 D-Index: 7 scientists 97 D-Index: 6 scientists 98 D-Index: 6 scientists 99 D-Index: 6 scientists 100+ D-Index: 97 scientists
30 D-Index 100+

This scientist: 46 D-Index — 55th percentile

55% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 100 D-Index or more.

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

Geraint A. Wiggins
Geraint A. Wiggins Vrije Universiteit Brussel
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 Aarhus University
Stefan Koelsch
Stefan Koelsch University of Bergen
Andrea R. Halpern
Andrea R. Halpern Bucknell University
Karl J. Friston
Karl J. Friston University College London
Roger T. Dean
Roger T. Dean Western Sydney University
Lauren Stewart
Lauren Stewart Goldsmiths University of London

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