The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Spectro-temporal modulation transfer function of single voxels in the human auditory cortex measured with high-resolution fMRI
Open accessAbstract
Are visual and auditory stimuli processed by similar mechanisms in the human cerebral cortex? Images can be thought of as light energy modulations over two spatial dimensions, and low-level visual areas analyze images by decomposition into spatial frequencies. Similarly, sounds are energy modulations over time and frequency, and they can be identified and discriminated by the content of such modulations. An obvious question is therefore whether human auditory areas, in direct analogy to visual areas, represent the spectro-temporal modulation content of acoustic stimuli. To answer this question, we measured spectro-temporal modulation transfer functions of single voxels in the human auditory cortex with functional magnetic resonance imaging. We presented dynamic ripples, complex broadband stimuli with a drifting sinusoidal spectral envelope. Dynamic ripples are the auditory equivalent of the gratings often used in studies of the visual system. We demonstrate selective tuning to combined spectro-temporal modulations in the primary and secondary auditory cortex. We describe several types of modulation transfer functions, extracting different spectro-temporal features, with a high degree of interaction between spectral and temporal parameters. The overall low-pass modulation rate preference of the cortex matches the modulation content of natural sounds. These results demonstrate that combined spectro-temporal modulations are represented in the human auditory cortex, and suggest that complex signals are decomposed and processed according to their modulation content, the same transformation used by the visual system.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Neurophysiological investigation of the basis of the fMRI signal
Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001) · Nature · doi:10.1038/35084005 · Cited by 6,551
Object vision and spatial vision: Two cortical pathways
Mishkin, M., Ungerleider, L. G., & Macko, K. A. (1983) · Trends in Neurosciences · doi:10.1016/0166-2236(83)90190-x · Cited by 2,947
Representation of the temporal envelope of sounds in the human brain
Giraud, A.-L., Lorenzi, C., Ashburner, J., Wable, J., Johnsrude, I., Frackowiak, R., & Kleinschmidt, A. (2000) · Journal of Neurophysiology · doi:10.1152/jn.2000.84.3.1588 · Cited by 353
Cited by
Kell, A. J. E., Yamins, D. L. K., Shook, E. N., Norman-Haignere, S. V., & McDermott, J. H. (2018) · Neuron · doi:10.1016/j.neuron.2018.03.044 · Cited by 544
The Encoding of Speech Sounds in the Superior Temporal Gyrus
Yi, H. G., Leonard, M. K., & Chang, E. F. (2019) · Neuron · doi:10.1016/j.neuron.2019.04.023 · Cited by 417
A Primer on Pattern-Based Approaches to fMRI: Principles, Pitfalls, and Perspectives
Haynes, J.-D. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.025 · Cited by 402
Distinct sensitivity to spectrotemporal modulation supports brain asymmetry for speech and melody
Albouy, P., Benjamin, L., Morillon, B., & Zatorre, R. J. (2020) · Science · doi:10.1126/science.aaz3468 · Cited by 298
Self-citationHuman Screams Occupy a Privileged Niche in the Communication Soundscape
Arnal, L. H., Flinker, A., Kleinschmidt, A., Giraud, A.-L., & Poeppel, D. (2015) · Current Biology · doi:10.1016/j.cub.2015.06.043 · Cited by 296
Metadata
- Authors
- Schönwiesner, M., & Zatorre, R. J.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2009-08-25
- Volume
- 106
- Issue
- 34
- Pages
- 14611-14616
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1968707255
- Cited by
- 251
- References
- 3
- FWCI
- 4.72
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Spectro-temporal modulation transfer function of single voxels in the human auditory cortex measured with high-resolution fMRI. https://app.cochat.ai/papers/10.1073/pnas.0907682106
- The paper
- Schönwiesner, M., & Zatorre, R. J. (2009). Spectro-temporal modulation transfer function of single voxels in the human auditory cortex measured with high-resolution fMRI. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0907682106
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.