The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Time for Action: Neural Basis of the Costs and Benefits of Temporal Predictability for Competing Response Choices
Open accessAbstract
The brain can anticipate the time of imminent events to optimize sensorimotor processing. Yet, there can be behavioral costs of temporal predictability under situations of response conflict. Here, we sought to identify the neural basis of these costs and benefits by examining motor control processes in a combined EEG–EMG study. We recorded electrophysiological markers of response activation and inhibition over motor cortex when the onset-time of visual targets could be predicted, or not, and when responses necessitated conflict resolution, or not. If stimuli were temporally predictable but evoked conflicting responses, we observed increased intertrial consistency in the delta range over the motor cortex involved in response implementation, perhaps reflecting increased response difficulty. More importantly, temporal predictability differentially modulated motor cortex activity as a function of response conflict before the response was even initiated. This effect occurred in the hemisphere ipsilateral to the response, which is involved in inhibiting unwanted actions. If target features all triggered the same response, temporal predictability increased cortical inhibition of the incorrect response hand. Conversely, if different target features triggered two conflicting responses, temporal predictability decreased inhibition of the incorrect, yet prepotent, response. This dissociation reconciles the well-established behavioral benefits of temporal predictability for nonconflicting responses as well as its costs for conflicting ones by providing an elegant mechanism that operates selectively over the motor cortex involved in suppressing inappropriate actions just before response initiation. Taken together, our results demonstrate that temporal information differentially guides motor activity depending on response choice complexity.
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
PsychoPy2: Experiments in behavior made easy
Peirce, J., Gray, J. R., Simpson, S., MacAskill, M., Höchenberger, R., Sogo, H., Kastman, E., & Lindeløv, J. K. (2019) · Behavior Research Methods · doi:10.3758/s13428-018-01193-y · Cited by 5,166
MEG and EEG data analysis with MNE-Python
Gramfort, A. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00267 · Cited by 3,784
Spherical splines for scalp potential and current density mapping
Perrin, F., Pernier, J., Bertrand, O., & Echallier, J. F. (1989) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(89)90180-6 · Cited by 2,706
Coull, J. T., & Nobre, A. C. (1998) · The Journal of Neuroscience · doi:10.1523/jneurosci.18-18-07426.1998 · Cited by 1,269
Self-citationForeperiod and simple reaction time.
Niemi, P., & Näätänen, R. (1981) · Psychological Bulletin · doi:10.1037/0033-2909.89.1.133 · Cited by 1,133
Hodges, P. (1996) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/s0013-4694(96)95190-5 · Cited by 983
Signal-space projection method for separating MEG or EEG into components
Uusitalo, M. A., & Ilmoniemi, R. J. (1997) · Medical & Biological Engineering & Computing · doi:10.1007/bf02534144 · Cited by 913
Anticipated moments: temporal structure in attention
Nobre, A. C., & van Ede, F. (2018) · Nature Reviews Neuroscience · doi:10.1038/nrn.2017.141 · Cited by 568
Response Inhibition and Response Selection: Two Sides of the Same Coin
Mostofsky, S. H., & Simmonds, D. J. (2008) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2008.20500 · Cited by 514
Spatial and temporal resolutions of EEG: Is it really black and white? A scalp current density view
Burle, B., Spieser, L., Roger, C., Casini, L., Hasbroucq, T., & Vidal, F. (2015) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2015.05.004 · Cited by 414
Self-citation
Cited by
Neural correlates of the DMT experience assessed with multivariate EEG
Timmermann, C., Roseman, L., Schartner, M., Milliere, R., Williams, L. T. J., Erritzoe, D., Muthukumaraswamy, S., Ashton, M., Bendrioua, A., Kaur, O., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-51974-4 · Cited by 315
Mowlem, F. D., Skirrow, C., Reid, P., Maltezos, S., Nijjar, S. K., Merwood, A., Barker, E., Cooper, R., Kuntsi, J., & Asherson, P. (2019) · Journal of Attention Disorders · doi:10.1177/1087054716651927 · Cited by 156
Metacognitive Monitoring of Executive Control Engagement During Childhood
Chevalier, N., & Blaye, A. (2016) · Child Development · doi:10.1111/cdev.12537 · Cited by 75
Willing to Think Hard? The Subjective Value of Cognitive Effort in Children
Chevalier, N. (2018) · Child Development · doi:10.1111/cdev.12805 · Cited by 70
What makes the dorsomedial frontal cortex active during reading the mental states of others?
Isoda, M., & Noritake, A. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00232 · Cited by 64
Metadata
- Authors
- Korolczuk, I., Burle, B., Coull, J. T., & Śmigasiewicz, K.
- Venue
- Journal of Cognitive Neuroscience
- Publisher
- MIT Press
- Published
- 2021-12-23
- Volume
- 34
- Issue
- 2
- Pages
- 1-17
- ISSN
- 0898-929X (ISSN-L)
- 1530-8898
- OpenAlex
- W3216971378
- Cited by
- 528
- References
- 54
- FWCI
- 28.67
- 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: Time for Action: Neural Basis of the Costs and Benefits of Temporal Predictability for Competing Response Choices. https://app.cochat.ai/papers/10.1162/jocn_a_01795
- The paper
- Korolczuk, I., Burle, B., Coull, J. T., & Śmigasiewicz, K. (2021). Time for Action: Neural Basis of the Costs and Benefits of Temporal Predictability for Competing Response Choices. Journal of Cognitive Neuroscience. https://doi.org/10.1162/jocn_a_01795
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.