Jonathan Berger is the Denning Family Provostial Professor in Music at Stanford University, where he teaches composition, music theory, and cognition at the Center for Computer Research in Music and Acoustics (CCRMA). He was the founding co-director of the Stanford Institute for Creativity and the Arts (SICA, now the Stanford Arts Institute) and founding director of Yale University’s Center for Studies in Music Technology

Academic Appointments

2016-17 Courses

Stanford Advisees

All Publications

  • In Search of a Perceptual Metric for Timbre: Dissimilarity Judgments among Synthetic Sounds with MFCC-Derived Spectral Envelopes JOURNAL OF THE AUDIO ENGINEERING SOCIETY Terasawa, H., Berger, J., Makino, S. 2012; 60 (9): 674-685
  • Commissioning and quality assurance for a respiratory training system based on audiovisual biofeedback. Journal of applied clinical medical physics Cui, G., Gopalan, S., Yamamoto, T., Berger, J., Maxim, P. G., Keall, P. J. 2010; 11 (4): 3262-?


    A respiratory training system based on audiovisual biofeedback has been implemented at our institution. It is intended to improve patients' respiratory regularity during four-dimensional (4D) computed tomography (CT) image acquisition. The purpose is to help eliminate the artifacts in 4D-CT images caused by irregular breathing, as well as improve delivery efficiency during treatment, where respiratory irregularity is a concern. This article describes the commissioning and quality assurance (QA) procedures developed for this peripheral respiratory training system, the Stanford Respiratory Training (START) system. Using the Varian real-time position management system for the respiratory signal input, the START software was commissioned and able to acquire sample respiratory traces, create a patient-specific guiding waveform, and generate audiovisual signals for improving respiratory regularity. Routine QA tests that include hardware maintenance, visual guiding-waveform creation, auditory sounds synchronization, and feedback assessment, have been developed for the START system. The QA procedures developed here for the START system could be easily adapted to other respiratory training systems based on audiovisual biofeedback.

    View details for PubMedID 21081883

  • Analysis of Pitch Perception of Inharmonicity in Pipa Strings Using Response Surface Methodology JOURNAL OF NEW MUSIC RESEARCH Chin, S. H., Berger, J. 2010; 39 (1): 63-73
  • Commissioning and quality assurance for a respiratory training system based on audiovisual biofeedback JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS Cui, G., Gopalan, S., Yamamoto, T., Berger, J., Maxim, P. G., Keall, P. J. 2010; 11 (4): 42-56
  • Neural dynamics of event segmentation in music: Converging evidence for dissociable ventral and dorsal networks NEURON Sridharan, D., Levitin, D. J., Chafe, C. H., Berger, J., Menon, V. 2007; 55 (3): 521-532


    The real world presents our sensory systems with a continuous stream of undifferentiated information. Segmentation of this stream at event boundaries is necessary for object identification and feature extraction. Here, we investigate the neural dynamics of event segmentation in entire musical symphonies under natural listening conditions. We isolated time-dependent sequences of brain responses in a 10 s window surrounding transitions between movements of symphonic works. A strikingly right-lateralized network of brain regions showed peak response during the movement transitions when, paradoxically, there was no physical stimulus. Model-dependent and model-free analysis techniques provided converging evidence for activity in two distinct functional networks at the movement transition: a ventral fronto-temporal network associated with detecting salient events, followed in time by a dorsal fronto-parietal network associated with maintaining attention and updating working memory. Our study provides direct experimental evidence for dissociable and causally linked ventral and dorsal networks during event segmentation of ecologically valid auditory stimuli.

    View details for DOI 10.1016/j.neuron.2007.07.003

    View details for Web of Science ID 000248711000017

    View details for PubMedID 17678862

  • Melody extraction and musical onset detection via probabilistic models of framewise STFT peak data IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING Thornburg, H., Leistikow, R. J., Berger, J. 2007; 15 (4): 1257-1272
  • SICIB: An interactive music composition system using body movements COMPUTER MUSIC JOURNAL Morales-Manzanares, R., Morales, E. F., Dannenberg, R., Berger, J. 2001; 25 (2): 25-36