The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Predictive motor control of sensory dynamics in auditory active sensing
Open accessAbstract
Neuronal oscillations present potential physiological substrates for brain operations that require temporal prediction. We review this idea in the context of auditory perception. Using speech as an exemplar, we illustrate how hierarchically organized oscillations can be used to parse and encode complex input streams. We then consider the motor system as a major source of rhythms (temporal priors) in auditory processing, that act in concert with attention to sharpen sensory representations and link them across areas. We discuss the anatomo-functional pathways that could mediate this audio-motor interaction, and notably the potential role of the somatosensory cortex. Finally, we reposition temporal predictions in the context of internal models, discussing how they interact with feature-based or spatial predictions. We argue that complementary predictions interact synergistically according to the organizational principles of each sensory system, forming multidimensional filters crucial to perception.
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
Perception of the speech code.
Liberman, A. M., Cooper, F. S., Shankweiler, D. P., & Studdert-Kennedy, M. (1967) · Psychological Review · doi:10.1037/h0020279 · Cited by 3,722
Entrainment of Neuronal Oscillations as a Mechanism of Attentional Selection
Lakatos, P., Karmos, G., Mehta, A. D., Ulbert, I., & Schroeder, C. E. (2008) · Science · doi:10.1126/science.1154735 · Cited by 1,719
Self-citationMechanisms underlying selective neuronal tracking of attended speech at a “cocktail party”
Zion Golumbic, E. M., Ding, N., Bickel, S., Lakatos, P., Schevon, C. A., McKhann, G. M., Goodman, R. R., Emerson, R., Mehta, A. D., Simon, J. Z., et al. (2013) · Neuron · doi:10.1016/j.neuron.2012.12.037 · Cited by 909
Self-citationCorollary discharge across the animal kingdom
Crapse, T. B., & Sommer, M. A. (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2457 · Cited by 789
Statistically optimal perception and learning: from behavior to neural representations
Fiser, J., Berkes, P., Orbán, G., & Lengyel, M. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.01.003 · Cited by 672
Speech rhythms and multiplexed oscillatory sensory coding in the human brain
Gross, J., Hoogenboom, N., Thut, G., Schyns, P., Panzeri, S., Belin, P., & Garrod, S. (2013) · PLoS Biology · doi:10.1371/journal.pbio.1001752 · Cited by 643
Functional Anatomy of the Attentional Modulation of Time Estimation
Coull, J. T., Vidal, F., Nazarian, B., & Macar, F. (2004) · Science · doi:10.1126/science.1091573 · Cited by 642
A synaptic and circuit basis for corollary discharge in the auditory cortex
Schneider, D. M., Nelson, A., & Mooney, R. (2014) · Nature · doi:10.1038/nature13724 · Cited by 580
Active sensation: Insights from the rodent vibrissa sensorimotor system
Kleinfeld, D., Ahissar, E., & Diamond, M. E. (2006) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2006.06.009 · Cited by 374
Synergistic effect of combined temporal and spatial expectations on visual attention
Doherty, J. R., Rao, A., Mesulam, M. M., & Nobre, A. C. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.1821-05.2005 · Cited by 357
Cited by
Keitel, A., Gross, J., & Kayser, C. (2018) · PLOS Biology · doi:10.1371/journal.pbio.2004473 · Cited by 312
Roles of supplementary motor areas in auditory processing and auditory imagery
Lima, C. F., Krishnan, S., & Scott, S. K. (2016) · Trends in Neurosciences · doi:10.1016/j.tins.2016.06.003 · Cited by 227
Pando‐Naude, V., Matthews, T. E., Højlund, A., Jakobsen, S., Østergaard, K., Johnsen, E., Garza‐Villarreal, E. A., Witek, M. A. G., Penhune, V., & Vuust, P. (2024) · European Journal of Neuroscience · doi:10.1111/ejn.16128 · Cited by 29
Metadata
- Authors
- Morillon, B., Hackett, T. A., Kajikawa, Y., & Schroeder, C. E.
- Venue
- Current Opinion in Neurobiology
- Publisher
- Elsevier BV
- Published
- 2015-04
- Volume
- 31
- Pages
- 230-238
- ISSN
- 0959-4388 (ISSN-L)
- OpenAlex
- W2043356452
- Cited by
- 181
- References
- 11
- FWCI
- 1.49
- 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: Predictive motor control of sensory dynamics in auditory active sensing. https://app.cochat.ai/papers/10.1016/j.conb.2014.12.005
- The paper
- Morillon, B., Hackett, T. A., Kajikawa, Y., & Schroeder, C. E. (2015). Predictive motor control of sensory dynamics in auditory active sensing. Current Opinion in Neurobiology. https://doi.org/10.1016/j.conb.2014.12.005
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.
