The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.
Coexisting representations of sensory and mnemonic information in human visual cortex
Open accessAbstract
Traversing sensory environments requires keeping relevant information in mind while simultaneously processing new inputs. Visual information is kept in working memory via feature-selective responses in early visual cortex, but recent work has suggested that new sensory inputs obligatorily wipe out this information. Here we show region-wide multiplexing abilities in classic sensory areas, with population-level response patterns in early visual cortex representing the contents of working memory alongside new sensory inputs. In a second experiment, we show that when people get distracted, this leads to both disruptions of mnemonic information in early visual cortex and decrements in behavioral recall. Representations in the intraparietal sulcus reflect actively remembered information encoded in a transformed format, but not task-irrelevant sensory inputs. Together, these results suggest that early visual areas play a key role in supporting high-resolution working memory representations that can serve as a template for comparison with incoming sensory information. People often remember visual information over brief delays while also seeing new images in their immediate visual surroundings. Areas of the brain known to process visual information are shown to juggle these memory and sensory demands.
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
Brainard, D. H. (1997) · Spatial Vision · doi:10.1163/156856897x00357 · Cited by 19,702
Advances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630
Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002) · NeuroImage · doi:10.1006/nimg.2002.1132 · Cited by 11,888
Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W., & Smith, S. M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.015 · Cited by 11,314
Cortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910
Fast robust automated brain extraction
Smith, S. M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10062 · Cited by 10,496
A global optimisation method for robust affine registration of brain images
Jenkinson, M., & Smith, S. (2001) · Medical Image Analysis · doi:10.1016/s1361-8415(01)00036-6 · Cited by 6,872
Kleiner, M., Brainard, D. H., & Pelli, D. G. (2007) · MPG.PuRe (Max Planck Society) · Cited by 3,602
Accurate and robust brain image alignment using boundary-based registration
Greve, D. N., & Fischl, B. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.06.060 · Cited by 3,596
Andersson, J. L. R., Skare, S., & Ashburner, J. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00336-7 · Cited by 3,469
Cited by
Subjective confidence reflects representation of Bayesian probability in cortex
Geurts, L. S., Cooke, J. R. H., van Bergen, R. S., & Jehee, J. F. M. (2022) · Nature Human Behaviour · doi:10.1038/s41562-021-01247-w · Cited by 104
Tasks and their role in visual neuroscience
Kay, K., Bonnen, K., Denison, R. N., Arcaro, M. J., & Barack, D. L. (2023) · Neuron · doi:10.1016/j.neuron.2023.03.022 · Cited by 61
From remembering to reconstruction: The transformative neural representation of episodic memory.
Xue, G. (2022) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2022.102351 · Cited by 49
Jia, K., Li, Y., Gong, M., Huang, H., Wang, Y., & Li, S. (2021) · The Journal of Neuroscience · doi:10.1523/jneurosci.2780-20.2021 · Cited by 25
Li, S., Zeng, X., Shao, Z., & Yu, Q. (2023) · The Journal of Neuroscience · doi:10.1523/jneurosci.0592-23.2023 · Cited by 23
Metadata
- Authors
- Rademaker, R. L., Chunharas, C., & Serences, J. T.
- Venue
- Nature Neuroscience
- Published
- 2019-07-01
- Volume
- 22
- Issue
- 8
- Pages
- 1336-1344
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W2953406703
- Cited by
- 298
- References
- 71
- FWCI
- 15.14
- 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: Coexisting representations of sensory and mnemonic information in human visual cortex. https://app.cochat.ai/papers/10.1038/s41593-019-0428-x
- The paper
- Rademaker, R. L., Chunharas, C., & Serences, J. T. (2019). Coexisting representations of sensory and mnemonic information in human visual cortex. Nature Neuroscience. https://doi.org/10.1038/s41593-019-0428-x
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.