The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.
Interplay between persistent activity and activity-silent dynamics in the prefrontal cortex underlies serial biases in working memory
Open accessAbstract
Persistent neuronal spiking has long been considered the mechanism underlying working memory, but recent proposals argue for alternative ‘activity-silent’ substrates. Using monkey and human electrophysiology data, we show here that attractor dynamics that control neural spiking during mnemonic periods interact with activity-silent mechanisms in the prefrontal cortex (PFC). This interaction allows memory reactivations, which enhance serial biases in spatial working memory. Stimulus information was not decodable between trials, but remained present in activity-silent traces inferred from spiking synchrony in the PFC. Just before the new stimulus, this latent trace was reignited into activity that recapitulated the previous stimulus representation. Importantly, the reactivation strength correlated with the strength of serial biases in both monkeys and humans, as predicted by a computational model that integrates activity-based and activity-silent mechanisms. Finally, single-pulse transcranial magnetic stimulation applied to the human PFC between successive trials enhanced serial biases, thus demonstrating the causal role of prefrontal reactivations in determining working-memory behavior. Barbosa, Stein et al. show that rather than operating independently, PFC persistent activity and ‘activity-silent’ mechanisms interact dynamically to produce serial effects in working memory, consistent with attractor models with synaptic plasticity.
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
nlme : Linear and nonlinear mixed effects models
DebRoy, S. (2006) · Medical Entomology and Zoology · Cited by 10,009
Rossi, S., Hallett, M., Rossini, P. M., & Pascual-Leone, A. (2009) · Clinical Neurophysiology · doi:10.1016/j.clinph.2009.08.016 · Cited by 5,367
Large-scale automated synthesis of human functional neuroimaging data.
Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C., & Wager, T. D. (2011) · Nature Methods · doi:10.1038/nmeth.1635 · Cited by 3,686
Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex
Funahashi, S., Bruce, C. J., & Goldman-Rakic, P. S. (1989) · Journal of Neurophysiology · doi:10.1152/jn.1989.61.2.331 · Cited by 2,685
Neuron Activity Related to Short-Term Memory
Fuster, J. M., & Alexander, G. E. (1971) · Science · doi:10.1126/science.173.3997.652 · Cited by 2,085
The Importance of the Normality Assumption in Large Public Health Data Sets
Lumley, T., Diehr, P., Emerson, S., & Chen, L. (2002) · Annual Review of Public Health · doi:10.1146/annurev.publhealth.23.100901.140546 · Cited by 1,803
Worden, M. S., Foxe, J. J., Wang, N., & Simpson, G. V. (2000) · The Journal of Neuroscience · doi:10.1523/jneurosci.20-06-j0002.2000 · Cited by 1,268
Synaptic theory of working memory
Mongillo, G., Barak, O., & Tsodyks, M. (2008) · Science · doi:10.1126/science.1150769 · Cited by 1,253
Compte, A. (2000) · Cerebral Cortex · doi:10.1093/cercor/10.9.910 · Cited by 1,143
Self-citationDifferential signaling via the same axon of neocortical pyramidal neurons
Markram, H., Wang, Y., & Tsodyks, M. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.9.5323 · Cited by 1,102
Cited by
Wang, X., Luo, F., & Li, B. (2025) · Neurobiology of Disease · doi:10.1016/j.nbd.2025.107186 · Cited by 1
Metadata
- Authors
- Barbosa, J., Stein, H., Martinez, R. L., Galan-Gadea, A., Li, S., Dalmau, J., Adam, K. C. S., Valls-Solé, J., Constantinidis, C., & Compte, A.
- Venue
- Nature Neuroscience
- Published
- 2020-06-22
- Volume
- 23
- Issue
- 8
- Pages
- 1016-1024
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W3036274064
- Cited by
- 269
- References
- 83
- FWCI
- 17.65
- 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: Interplay between persistent activity and activity-silent dynamics in the prefrontal cortex underlies serial biases in working memory. https://app.cochat.ai/papers/10.1038/s41593-020-0644-4
- The paper
- Barbosa, J., Stein, H., Martinez, R. L., Galan-Gadea, A., Li, S., Dalmau, J., Adam, K. C. S., Valls-Solé, J., Constantinidis, C., & Compte, A. (2020). Interplay between persistent activity and activity-silent dynamics in the prefrontal cortex underlies serial biases in working memory. Nature Neuroscience. https://doi.org/10.1038/s41593-020-0644-4
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.