The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Reconstructions of Information in Visual Spatial Working Memory Degrade with Memory Load
Open accessAbstract
Summary Working memory (WM) enables the maintenance and manipulation of information relevant to behavioral goals. Variability in WM ability is strongly correlated with IQ [1] and WM function is impaired in many neurological and psychiatric disorders [2, 3], suggesting that this system is a core component of higher cognition. WM storage is thought to be mediated by patterns of activity in neural populations selective for specific properties (e.g., color, orientation, location, motion direction) of memoranda [4–13]. Accordingly, many models propose that differences in the amplitude of these population responses should be related to differences in memory performance [14, 15]. Here, we used functional magnetic resonance imaging (fMRI) and an image reconstruction technique based on a spatial encoding model [16] to visualize and quantify population-level memory representations supported by multivoxel patterns of activation within regions of occipital, parietal and frontal cortex while participants precisely remembered the location(s) of 0, 1, or 2 small stimuli. We successfully reconstructed images containing representations of the remembered – but not forgotten – locations within regions of occipital, parietal, and frontal cortex using delay-period activation patterns. Critically, the amplitude of representations of remembered locations and behavioral performance both decreased with increasing memory load. These results suggest that differences in visual WM performance between memory load conditions are mediated by changes in the fidelity of large-scale population response profiles distributed across multiple areas of human cortex.
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Cites
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
Bayesian inference with probabilistic population codes
Ma, W. J., Beck, J. M., Latham, P. E., & Pouget, A. (2006) · Nature Neuroscience · doi:10.1038/nn1790 · Cited by 1,457
Decoding reveals the contents of visual working memory in early visual areas
Harrison, S. A., & Tong, F. (2009) · Nature · doi:10.1038/nature07832 · Cited by 1,347
A neural measure of precision in visual working memory
Ester, E. F., Anderson, D. E., Serences, J. T., & Awh, E. (2013) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00357 · Cited by 207
Self-citation
Cited by
The Distributed Nature of Working Memory
Christophel, T. B., Klink, P. C., Spitzer, B., Roelfsema, P. R., & Haynes, J.-D. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2016.12.007 · Cited by 882
The neuroscience of working memory capacity and training
Constantinidis, C., & Klingberg, T. (2016) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.43 · Cited by 533
A Primer on Pattern-Based Approaches to fMRI: Principles, Pitfalls, and Perspectives
Haynes, J.-D. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.025 · Cited by 402
Reevaluating the Sensory Account of Visual Working Memory Storage
Xu, Y. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.06.013 · Cited by 264
Short-term memory and long-term memory are still different.
Norris, D. (2017) · Psychological Bulletin · doi:10.1037/bul0000108 · Cited by 256
Metadata
- Authors
- Sprague, T. C., Ester, E. F., & Serences, J. T.
- Venue
- Current Biology
- Publisher
- Elsevier BV
- Published
- 2014-09
- Volume
- 24
- Issue
- 18
- Pages
- 2174-2180
- ISSN
- 0960-9822 (ISSN-L)
- OpenAlex
- W2001753487
- Cited by
- 203
- References
- 4
- FWCI
- 23.06
- Type
- journal article
- Language
- en
- Open access
- bronze
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