Nori Jacoby

About

Nori Jacoby is an assistant professor in the Department of Psychology at Cornell University. His research focuses on the internal representations that support and shape sensory and cognitive abilities, and on how these representations are determined by both nature and nurture. He addresses these classic issues by applying machine learning techniques to behavioral experiments and expanding the scale and scope of experimental research through massive online experiments and fieldwork in locations around the globe. Nori completed his Ph.D. at the Edmond and Lily Safra Center for Brain Sciences (ELSC) at the Hebrew University of Jerusalem under the supervision of Naftali Tishby and Merav Ahissar. He has held postdoctoral positions at MIT's Computational Audition Lab, UC Berkeley's Computational Cognitive Science Lab, and as a Presidential Scholar in Society and Neuroscience at Columbia University. Before joining Cornell, he was a Research Group Leader at the Max Planck Institute for Empirical Aesthetics in Frankfurt.

Research topics

• Computer Science
• Communication
• Biology
• Sociology
• Social Science
• Psychology
• Evolutionary biology
• Neuroscience
• Speech recognition
• Social psychology

Selected publications

• Flexible tapping synchronization in macaques: dynamic switching of timing strategies within rhythmic sequences

  Journal of Neurophysiology · 2025-06-09 · 8 citations

  articleOpen access

  We trained macaques in a visual synchronization tapping task and using an inference model, we found that they are highly precise and accurate in their rhythmic performance. The model also captured a dynamic switch in behavior. At the beginning of the task, the monkeys used their prior knowledge about the interval statistics and then switched to an error correction mechanism to generate intervals depending on the previously produced duration.

  PublisherDOI

• Mechanisms of cultural diversity in urban populations

  Nature Communications · 2025-06-04 · 5 citations

  articleOpen access

  Large cities exhibit greater cultural diversity. Due to limited data on individual behaviour, previous research could not discern whether this stems from demographic heterogeneity or enhanced individual cultural exploration. Analysing 250 million listening events from 2.5 million users across France, Brazil, and Germany, we investigate mechanisms driving urban cultural diversity. We assess the collective shared musical repertoire in each geographical area, while concurrently measuring individual…

  PublisherOA PDFDOI

• Revealing rhythm categorization in human brain activity

  Science Advances · 2025-07-30 · 4 citations

  articleOpen access

  Humans across cultures show an outstanding capacity to perceive, learn, and produce musical rhythms. These skills rely on mapping the infinite space of possible rhythmic sensory inputs onto a finite set of internal rhythm categories. What is the nature of the brain processes underlying rhythm categorization? We used electroencephalography to measure brain activity as human participants listened to a continuum of rhythmic sequences characterized by repeating patterns of two interonset intervals.…

  PublisherDOI

• Does synchronised singing enhance social bonding more than speaking does? A global experimental Stage 1 Registered Report

  2025-04-07 · 2 citations

  preprintOpen access

  The evolution of music, speech, and sociality have been debated since before Darwin. The social bonding hypothesis proposes that these phenomena may be interlinked: musicality may have facilitated the evolution of social bonding beyond the possibilities of spoken language. Although dozens of experimental studies have argued that synchronised rhythms can promote bonding, methodological issues including publication bias, sample bias, experimenter effects, and appropriateness of experimental contro…

  PublisherOA PDFDOI

• GlobalMood: A cross-cultural benchmark for music emotion recognition

  ArXiv.org · 2025-05-14 · 1 citations

  preprintOpen accessSenior author

  Human annotations of mood in music are essential for music generation and recommender systems. However, existing datasets predominantly focus on Western songs with terms derived from English, which may limit generalizability across diverse linguistic and cultural backgrounds. We introduce 'GlobalMood', a novel cross-cultural benchmark dataset comprising 1,180 songs sampled from 59 countries, with large-scale annotations collected from 2,519 individuals across five culturally and linguistically d…

  PublisherOA PDFDOI

Frequent coauthors

• Raja Marjieh

  Princeton University

  27 shared

• Manuel Anglada-Tort

  Goldsmiths University of London

  25 shared

• Pol van Rijn

  Max Planck Institute for Empirical Aesthetics

  24 shared

• Thomas L. Griffiths

  24 shared

• Peter M. C. Harrison

  University of Cambridge

  23 shared

• Ofer Tchernichovski

  Hunter College

  22 shared

• Josh H. McDermott

  Harvard University

  20 shared

• Rainer Polak

  University of Oslo

  17 shared

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• Shimon Edelmanh-47