Neural Computation for Sound and Recognition
(led by Dr. Johanna Rimmele)
Language and music are fundamental aspects of our lives—with impairment resulting in serious derogation. While we understand spoken language (or follow music) seemingly effortlessly, the cognitive computations and neural implementations are far from understood.
The research interests of the Neural Computation for Sound and Recognition Team lie in how the brain connects sensory information to recognition, involving auditory perception, particularly speech (and music), and understanding how malleable, trainable, or plastic the mechanisms are. Particularly, we investigate the role of brain rhythms and the motor system. Our methodology includes psychophysics, electrophysiology, and neuroimaging (particularly EEG, MEG, MRI). Furthermore, we are interested in computational modeling approaches.
Current Research Areas
Neural computations of episodic memory processing of speech and song
Individual differences in predictive processing during speech (and music) perception
Endogenous brain rhythms and neural oscillatory accounts of speech perception
Neural oscillatory accounts of auditory-motor interactions and other top-down influences during speech perception
Predictive coding in auditory perception in health and disorder
Latest Publications & Science Communication
Atanasova, T., Gross, J., Keitel, A., & Rimmele, J. M. (2025). The involvement
of endogenous brain rhythms in speech processing. PsyArXiv Preprints. doi:10.31234/osf.io/rukwp_v1.
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Lubinus, C., Keitel, A., Obleser, J., Poeppel, D., & Rimmele, J. M. (2025). Endogenous
auditory and motor brain rhythms predict individual speech tracking. bioRxiv. doi:10.1101/2025.03.24.644939.
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Rimmele, J. M., & Keitel, A. (2025). Region-specific endogenous brain rhythms and
their role for speech and language (in press). In L. Meyer, & A. Strauss (
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Barchet, A. V., Bruera, A., Wend, J., Rimmele, J. M., Obleser, J., & Hartwigsen, G. (2025).
Attentional engagement with target and distractor streams predicts speech comprehension in multitalker environments. bioRxiv. doi:10.1101/2025.04.04.647157.
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Bahmer, A., Rimmele, J. M., & Gupta, D. S. (2024). Editorial: Understanding the
role of oscillations, mutual information and synchronization in perception and action. Frontiers in
Computational Neuroscience,18: 1452001. doi:10.3389/fncom.2024.1452001.
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Keitel, A., Pelofi, C., Guan, X., Watson, E., Wight, L., Allen, S., Mencke, I., Keitel, C., & Rimmele, J. M. (2024).
Cortical and behavioral tracking of rhythm in music: Effects of pitch predictability, enjoyment, and expertise.
Annals of the New York Academy of Sciences,1546(1), 120-135. doi:10.1111/nyas.15315.
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Barchet, A. V., Rimmele, J. M., & Pelofi, C. (2024). TenseMusic: An automatic prediction
model for musical tension. PLOS ONE,19(1): e0296385.
doi:10.1371/journal.pone.0296385.
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Contact
Team
Alumni
Vivien Barchet
Master Student
Oliver Kohl
Master Student, University of Oxford
Pius Kern
Bachelor Student, Philipps Universität Marburg