The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Motor contributions to the temporal precision of auditory attention
Open accessAbstract
In temporal—or dynamic—attending theory, it is proposed that motor activity helps to synchronize temporal fluctuations of attention with the timing of events in a task-relevant stream, thus facilitating sensory selection. Here we develop a mechanistic behavioural account for this theory by asking human participants to track a slow reference beat, by noiseless finger pressing, while extracting auditory target tones delivered on-beat and interleaved with distractors. We find that overt rhythmic motor activity improves the segmentation of auditory information by enhancing sensitivity to target tones while actively suppressing distractor tones. This effect is triggered by cyclic fluctuations in sensory gain locked to individual motor acts, scales parametrically with the temporal predictability of sensory events and depends on the temporal alignment between motor and attention fluctuations. Together, these findings reveal how top-down influences associated with a rhythmic motor routine sharpen sensory representations, enacting auditory ‘active sensing’.
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Cites
Top-Down Versus Bottom-Up Control of Attention in the Prefrontal and Posterior Parietal Cortices
Buschman, T. J., & Miller, E. K. (2007) · Science · doi:10.1126/science.1138071 · Cited by 2,380
The Normalization Model of Attention
Reynolds, J. H., & Heeger, D. J. (2009) · Neuron · doi:10.1016/j.neuron.2009.01.002 · Cited by 1,457
Sensorimotor synchronization: a review of recent research (2006–2012).
Repp, B. H., & Su, Y.-H. (2013) · Psychonomic Bulletin & Review · doi:10.3758/s13423-012-0371-2 · Cited by 1,204
Expectation (and attention) in visual cognition
Summerfield, C., & Egner, T. (2009) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2009.06.003 · Cited by 950
Bayesian Versus Orthodox Statistics: Which Side Are You On?
Dienes, Z. (2011) · Perspectives on Psychological Science · doi:10.1177/1745691611406920 · Cited by 938 · cited 2×
“…statistics are usually not considered in terms of thresholds, it is generally assumed that a Bayes Factor below 1/3 corresponds to substantial evidence in favour of the ‘null’ hypothesis, whereas a Bayes Factor above 3 corresponds to substantial evidence in favour of the ‘effect’ hypothesis 57 .”
Mechanisms 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
Predictions not commands: Active inference in the motor system
Adams, R. A., Shipp, S., & Friston, K. J. (2013) · Brain Structure and Function · doi:10.1007/s00429-012-0475-5 · Cited by 765
All in a Sniff: Olfaction as a Model for Active Sensing
Wachowiak, M. (2011) · Neuron · doi:10.1016/j.neuron.2011.08.030 · Cited by 353
Fast and Slow Oscillations in Human Primary Motor Cortex Predict Oncoming Behaviorally Relevant Cues
Saleh, M., Reimer, J., Penn, R., Ojakangas, C. L., & Hatsopoulos, N. G. (2010) · Neuron · doi:10.1016/j.neuron.2010.02.001 · Cited by 281 · cited 1×
“…which can act as instruments of sensory selection by modulating the excitability of task-relevant neuronal populations 15 , are the substrate of temporal attention 17,38–40 and are found in the primary motor cortex to co-vary with the occurrence of temporally predictable task-relevant cues 41 .”
Motor cortex feedback influences sensory processing by modulating network state
Zagha, E., Casale, A. E., Sachdev, R. N. S., McGinley, M. J., & McCormick, D. A. (2013) · Neuron · doi:10.1016/j.neuron.2013.06.008 · Cited by 268
Cited by
A New Unifying Account of the Roles of Neuronal Entrainment
Lakatos, P., Gross, J., & Thut, G. (2019) · Current Biology · doi:10.1016/j.cub.2019.07.075 · Cited by 508
Keitel, A., Gross, J., & Kayser, C. (2018) · PLOS Biology · doi:10.1371/journal.pbio.2004473 · Cited by 312
Beta-Band Oscillations Represent Auditory Beat and Its Metrical Hierarchy in Perception and Imagery
Fujioka, T., Ross, B., & Trainor, L. J. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.2397-15.2015 · Cited by 230
Active information sampling varies across the cardiac cycle
Kunzendorf, S., Klotzsche, F., Akbal, M., Villringer, A., Ohl, S., & Gaebler, M. (2019) · Psychophysiology · doi:10.1111/psyp.13322 · Cited by 73
Meng, J., Zhao, Y., Wang, K., Sun, J., Yi, W., Xu, F., Xu, M., & Ming, D. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad0650 · Cited by 5
Metadata
- Authors
- Morillon, B., Schroeder, C. E., & Wyart, V.
- Venue
- Nature Communications
- Published
- 2014-10-15
- Volume
- 5
- Issue
- 1
- Pages
- 5255-5255
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W2009645001
- Cited by
- 222
- References
- 11
- FWCI
- 6.98
- Type
- journal article
- Language
- en
- Open access
- hybrid
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