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The role of pain expectancy and its confidence in placebo hypoalgesia and nocebo hyperalgesia

Camerone, E. M., Tosi, G., & Romano, D. (2024) · Pain · doi:10.1097/j.pain.0000000000003495 · Cited by 14 · see citing works

Certainty in ascending sensory signals – The unexplored driver of analgesic placebo response

Kuperman, P., Talmi, D., Katz, N., & Treister, R. (2020) · Medical Hypotheses · doi:10.1016/j.mehy.2020.110113 · Cited by 13 · see citing works

Thermosensory predictive coding underpins an illusion of pain

Ehmsen, J. F., Nikolova, N. E., Christensen, D. E., Banellis, L., Böhme, R. A., Brændholt, M., Courtin, A. S., Krænge, C. E., Mitchell, A. G., Deolindo, C. S., et al. (2025) · Science Advances · doi:10.1126/sciadv.adq0261 · Cited by 12 · see citing works

Pain, placebo, and cognitive penetration

Shevlin, H., & Friesen, P. (2020) · Mind & Language · doi:10.1111/mila.12292 · Cited by 12 · see citing works

Pain perception as hierarchical Bayesian inference: A test case for the theory of constructed emotion

Poublan‐Couzardot, A., & Talmi, D. (2024) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.15141 · Cited by 10 · see citing works

Individual treatment expectations predict clinical outcome after lumbar injections against low back pain

Müller-Schrader, M., Heinzle, J., Müller, A. E., Lanz, C., Häussler, O., Sutter, M. A., Eggspuehler, A., Mare, S., Toussaint, B., Pereira, I., et al. (2022) · Pain · doi:10.1097/j.pain.0000000000002674 · Cited by 10 · see citing works

Statistical learning shapes pain perception and prediction independently of external cues

Onysk, J., Gregory, N., Whitefield, M., Jain, M., Turner, G., Seymour, B., & Mancini, F. (2023) · eLife · doi:10.7554/elife.90634 · Cited by 14 · see citing works

Modeling Learning Patterns to Predict Placebo Analgesic Effects in Healthy and Chronic Orofacial Pain Participants

Wang, Y., Tricou, C., Raghuraman, N., Akintola, T., Haycock, N. R., Blasini, M., Phillips, J. L., Zhu, S., & Colloca, L. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.00039 · Cited by 10 · see citing works

Spatiotemporal integration of contextual and sensory information within the cortical hierarchy in human pain experience

Gim, S., Hong, S., Losin, E. A. R., & Woo, C. (2024) · PLoS Biology · doi:10.1371/journal.pbio.3002910 · Cited by 10 · see citing works

Modulation of the sensory and affective dimensions of pain by expectations and uncertainty: a Bayesian modeling approachPreprint

Poublan‐Couzardot, A., Pagnoni, G., & Antoine Lutz, A. (2022) · doi:10.31219/osf.io/nteg7 · Cited by 9 · see citing works

Controllability changes pain perception by increasing the precision of expectations

Habermann, M., & Büchel, C. (2025) · Nature Communications · doi:10.1038/s41467-025-66038-7 · Cited by 12 · see citing works

Identification of group differences in predictive anticipatory biasing of pain during uncertainty: preparing for the worst but hoping for the best

Strigo, I. A., Kadlec, M., Mitchell, J., & Simmons, A. N. (2024) · Pain · doi:10.1097/j.pain.0000000000003207 · Cited by 8 · see citing works

A Computational Framework for Understanding the Impact of Prior Experiences on Pain Perception and Neuropathic Pain

Ramne, M., & Sensinger, J. W. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012097 · Cited by 7 · see citing works

Testing the Possibility of Model-based Pavlovian Control of Attention to Threat

Talmi, D., Slapkova, M., & Wieser, M. J. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01329 · Cited by 8 · see citing works

Statistical learning shapes pain perception and prediction independently of external cues

Onysk, J., Gregory, N., Whitefield, M., Jain, M., Turner, G., Seymour, B., & Mancini, F. (2024) · eLife · doi:10.7554/elife.90634.3 · Cited by 7 · see citing works

Beyond needling: integrating a Bayesian brain model into acupuncture treatment

Kang, B., Yoon, D.-E., Ryu, Y., Lee, I.-S., & Chae, Y. (2025) · Brain Sciences · doi:10.3390/brainsci15020192 · Cited by 7 · see citing works

What Can We Sense? Interoceptive Accuracy

Köteles, F. G. (2021) · Springer eBooks · doi:10.1007/978-3-030-63201-4_4 · Cited by 7 · see citing works

The placebo effect: To explore or to exploit?

Barnes, K., Rottman, B. M., & Colagiuri, B. (2021) · Cognition · doi:10.1016/j.cognition.2021.104753 · Cited by 6 · see citing works

Conditioned Placebo- and Nocebo-Like Effects in Adolescents: The Role of Conscious Awareness, Sensory Discrimination, and Executive Function

Neuenschwander, R., Weik, E., Tipper, C. M., Jensen, K. B., & Oberlander, T. F. (2020) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2020.586455 · Cited by 6 · see citing works

Placebo Effects Are Small on Average in the 7.5% CO2 Inhalational Model of Generalized Anxiety

Huneke, N. T. M., Cross, C., Fagan, H. A., Molteni, L., Phillips, N., Garner, M. J., & Baldwin, D. S. (2024) · The International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyae019 · Cited by 5 · see citing works

Psychomotor Predictive Processing

Fox, S. (2021) · Entropy · doi:10.3390/e23070806 · Cited by 5 · see citing works

Bayesian surprise intensifies pain in a novel visual-noxious association

Ishikawa, R., Ono, G., & Izawa, J. (2025) · Cognition · doi:10.1016/j.cognition.2025.106064 · Cited by 4 · see citing works

Updating beliefs about pain following advice: Trustworthiness of social advice predicts pain expectations and experience

Krahé, C., Koukoutsakis, A., & Fotopoulou, A. (2024) · Cognition · doi:10.1016/j.cognition.2024.105756 · Cited by 4 · see citing works

Painful decisions: How classifying sensations can change the experience of pain

van der Meulen, M., Anton, F., & Petersen, S. (2017) · European Journal of Pain · doi:10.1002/ejp.1061 · Cited by 3 · see citing works

Expectations and uncertainty shape pain perception during learning

Lacombe-Thibault, M., & Coll, M. (2025) · Journal of Pain · doi:10.1016/j.jpain.2025.105569 · Cited by 2 · see citing works

A Survey on Data Perception in Cognitive Internet of Things

Bhajantri, L. B., & Balugari, P. (2019) · Journal of Telecommunications and Information Technology · doi:10.26636/jtit.2019.131419 · Cited by 2 · see citing works

The temporal and spectral characteristics of expectations and prediction errors in pain and thermoceptionPreprint

Strube, A., Rose, M., Fazeli, S., & Büchel, C. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.09.10.291658 · Cited by 2 · see citing works

The Computational Neuroanatomy of Predictive Dynamics of Pain PerceptionPreprint

Ishikawa, R., & Izawa, J. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.04.13.488260 · Cited by 2 · see citing works

Validating a measure of the precision of ascending noxious signalsPreprint

Singh, A., Treister, R., Charalambous, C., Mancini, F., & Talmi, D. (2024) · doi:10.31234/osf.io/9s5gj · Cited by 2 · see citing works

Pain without inference

Casser, L. (2024) · Philosophy and Phenomenological Research · doi:10.1111/phpr.13134 · Cited by 1 · see citing works

Probabilistic processing: Possible, probable, or preposterous? A dialectical essay

Loued‐Khenissi, L., & Pascucci, D. (2025) · New Ideas in Psychology · doi:10.1016/j.newideapsych.2025.101212 · Cited by 1 · see citing works

Temporal predictions shape somatosensory perception

Strube, A., & Büchel, C. (2026) · Nature Communications · doi:10.1038/s41467-026-71600-y · Cited by 1 · see citing works

The Anatomy of Placebo Effects: How Placebos Influence Mind, Brain and Behavior

Schmidt, L., & Koban, L. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-819641-0.00087-6 · Cited by 1 · see citing works

A Bayesian Model for Chronic PainPreprint

Eckert, A.-L., Pabst, K., & Endres, D. (2022) · doi:10.31234/osf.io/7ajvz · Cited by 1 · see citing works

Uncertainty in Thermosensory Expectations Enhances an Illusion of PainPreprint

Ehmsen, J. F., Nikolova, N. E., Christensen, D. E., Banellis, L., Brændholt, M., Courtin, A. S., Krænge, C. E., Mitchell, A. G., Deolindo, C. S., Steenkjær, C. H., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.03.27.587070 · Cited by 1 · see citing works

Model-based Pavlovian control of attention to threatPreprint

Talmi, D., Slapkova, M., & Wieser, M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/288027

Le cerveau du patient douloureux chronique se « trompe »-t-il ?

Barde-Cabusson, Y. (2019) · Douleurs Évaluation - Diagnostic - Traitement · doi:10.1016/j.douler.2018.12.002

You’ll never know if you never try

Glogan, E. (2021) · doi:10.26481/dis.20211215eg

Faculty Opinions recommendation of Symptom perception, placebo effects, and the Bayesian brain.

Chwistek, M. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.733816406.793554728

Modeling pain perception within a Bayesian framework – a novel computational approach to quantify predictive pain processing using quantitative sensory testingPreprint

Drusko, A., Baumeister, D., Christensen, M. E. M., Kold, S., Treede, R., Powers, A. R., Graven‐Nielsen, T., & Tesarz, J. (2022) · Research Square · doi:10.21203/rs.3.rs-2337507/v1

Statistical learning shapes pain perception and prediction independently of external cuesPreprint

Onysk, J., Gregory, N., Whitefield, M., Jain, M., Turner, G., Seymour, B., & Mancini, F. (2023) · medRxiv · doi:10.1101/2023.03.23.23287656

Neurophysiology of pain for non-neurophysiologists: a systematic reviewPreprint

Ramne, M., Elam, M., Löken, L. S., & Ortiz-Catalan, M. (2023) · Research Square · doi:10.21203/rs.3.rs-2942949/v1

Statistical learning shapes pain perception and prediction independently of external cuesPreprint

Onysk, J., Gregory, N., Whitefield, M., Jain, M., Turner, G., Seymour, B., & Mancini, F. (2023) · eLife · doi:10.7554/elife.90634.1

Author Response: Statistical learning shapes pain perception and prediction independently of external cues

Onysk, J., Gregory, N., Whitefield, M., Jain, M., Turner, G., Seymour, B., & Mancini, F. (2023) · eLife · doi:10.7554/elife.90634.1.sa4

Statistical learning shapes pain perception and prediction independently of external cuesPreprint

Onysk, J., Gregory, N., Whitefield, M., Jain, M., Turner, G., Seymour, B., & Mancini, F. (2024) · eLife · doi:10.7554/elife.90634.2

The prediction of the analgesic placebo effect is moderated by direction of attention: Results from fibromyalgia and healthy controls

Agostinho, M. R., Emergui, G., Canaipa, R., & Treister, R. (2025) · Journal of Pain · doi:10.1016/j.jpain.2025.105512

Dynamic learning of the meaning of information changes pain perception

Hird, E., Charalambous, C., El‐Deredy, W., Jones, A. K. P., & Talmi, D. (2025) · Scientific Reports · doi:10.1038/s41598-025-14299-z

Полифакторность хронической боли: понимание основополагающих механизмов и путь к успешной терапии

Аленикова, О. А. (2026) · Неврология и нейрохирургия Восточная Европа · doi:10.34883/pi.2026.16.2.063

Beyond Bayesian integration: how meaning shapes placebo effects

Wiech, K., Eippert, F., Jensen, K. B., Vase, L., & Bingel, U. (2026) · Trends in Neurosciences · doi:10.1016/j.tins.2026.07.005

RESEARCH ARTICLE A Bayesian Perspective on Sensory and Cognitive Integration in Pain Perception and Placebo Analgesia

Anchisi, D., & Zanon, M. (2016)

Evaluation of a Bayesian model of pain modulation and placebo effect

Zanon, M., Michele, G., & Anchisi, D. (2011) · Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna)

Resistance to placebo analgesia is explained by greater reliance on somatic input: a Bayesian model comparison studyPreprint

Delgado-Sánchez, A., Trujillo‐Barreto, N. J., Brown, C. A., Watson, A., Jones, A. K. P., & El‐Deredy, W. (2022) · doi:10.31234/osf.io/tuzbn

On symptom perception, placebo effects, and the Bayesian brain

Arandia-Romero, I., & Paolo, E. A. D. (2022) · Pain · doi:10.1097/j.pain.0000000000002488 · Cited by 8 · see citing works

Symptom perception, placebo effects, and the Bayesian brain

Ongaro, G., & Kaptchuk, T. J. (2018) · Pain · doi:10.1097/00006396-900000000-98882 · Cited by 16 · see citing works