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Working Memory 2.0
Open accessAbstract
Working memory is the fundamental function by which we break free from reflexive input-output reactions to gain control over our own thoughts. It has two types of mechanisms: online maintenance of information and its volitional or executive control. Classic models proposed persistent spiking for maintenance but have not explicitly addressed executive control. We review recent theoretical and empirical studies that suggest updates and additions to the classic model. Synaptic weight changes between sparse bursts of spiking strengthen working memory maintenance. Executive control acts via interplay between network oscillations in gamma (30-100 Hz) in superficial cortical layers (layers 2 and 3) and alpha and beta (10-30 Hz) in deep cortical layers (layers 5 and 6). Deep-layer alpha and beta are associated with top-down information and inhibition. It regulates the flow of bottom-up sensory information associated with superficial layer gamma. We propose that interactions between different rhythms in distinct cortical layers underlie working memory maintenance and its volitional control.
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“A key observation is that, all across cortex, gamma power (>35 Hz)/spiking is higher during bottom-up sensory inputs.”
From Layer and rhythm specificity for predictive routing (2020) · cites this paper as [29]
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“They are anticorrelated with alpha/beta (8 to 30 Hz) power (26–29), which is higher under conditions of top-down control (e.g., attention and response inhibition) (30–34).”
From Layer and rhythm specificity for predictive routing (2020) · cites this paper as [29]
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Uluç, I., Paulk, A. C., Bush, A., Gumenyuk, V., Peled, N., Kotlarz, P. L., Lankinen, K., Mamashli, F., Matsuda, N., Cosgrove, G. R., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.04.552073 · Cited by 5
Dynamic layer-specific processing in the prefrontal cortex during working memoryPreprint
Degutis, J. K., Chaimow, D., Haenelt, D., Assem, M., Duncan, J., Haynes, J., Weiskopf, N., & Lorenz, R. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.27.564330 · Cited by 6
Lim, H., & Lee, I. (2024) · PLoS Biology · doi:10.1371/journal.pbio.3002713 · Cited by 6
Bencze, D., Marián, M., Szöllősi, Á., Simor, P., & Racsmány, M. (2024) · Cortex · doi:10.1016/j.cortex.2024.11.012 · Cited by 5
Behaviorally Irrelevant Feature Matching Increases Neural and Behavioral Working Memory Readout
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Metadata
- Authors
- Miller, E. K., Lundqvist, M., & Bastos, A. M.
- Affiliations
- Massachusetts Institute of Technology (US)
- Corresponding author
- Miller, Earl K.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 100
- Issue
- 2
- Pages
- 463-475
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC8112390
- OpenAlex
- W2898524098
- Cited by
- 797
- References
- 165
- Citations by year
- 2026: 100 · 2025: 130 · 2024: 134 · 2023: 143 · 2022: 116 · 2021: 87 · 2020: 63 · 2019: 22 · 2018: 1
- FWCI
- 5.77
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIMH (R37MH087027)
- ONR (MURI N00014-16-1-2832)
- The Picower Fellows Program
- MIT Picower Institute
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- working memory, working memory maintenance, executive function, synaptic plasticity, gamma oscillations, alpha oscillations, beta oscillations, cortical layers, top-down control, neural oscillations
- MeSH terms
- Animals, Brain, Humans, Memory, Short-Term, Models, Neurological
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