Gamma and Beta Bursts Underlie Working Memory
Open accessAbstract
Working memory is thought to result from sustained neuron spiking. However, computational models suggest complex dynamics with discrete oscillatory bursts. We analyzed local field potential (LFP) and spiking from the prefrontal cortex (PFC) of monkeys performing a working memory task. There were brief bursts of narrow-band gamma oscillations (45-100 Hz), varied in time and frequency, accompanying encoding and re-activation of sensory information. They appeared at a minority of recording sites associated with spiking reflecting the to-be-remembered items. Beta oscillations (20-35 Hz) also occurred in brief, variable bursts but reflected a default state interrupted by encoding and decoding. Only activity of neurons reflecting encoding/decoding correlated with changes in gamma burst rate. Thus, gamma bursts could gate access to, and prevent sensory interference with, working memory. This supports the hypothesis that working memory is manifested by discrete oscillatory dynamics and spiking, not sustained activity.
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All across cortex, gamma power (>35 Hz)/spiking is higher during bottom-up sensory inputs.
“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 [27]
In Results, Prediction 1 (page unavailable), gamma power increased after stimulus presentation at 126 of 321 recorded sites, and spiking at those sites carried stimulus information. But 61% of sites showed no significant stimulus-related gamma increase, so the findings do not support “all across cortex.” The passages also establish informative spiking, not a cortex-wide increase in spiking rate during sensory input. (LLM, conf=0.88)
Experimental — accuracy not yet measuredGamma power/spiking is anticorrelated with alpha/beta (8 to 30 Hz) power, which is higher under conditions of top-down control (e.g., attention and response inhibition).
“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 [27]
In Results, “Prediction 3: Beta and gamma underlie different network states” (page unavailable), the paper reports a negative correlation between gamma and beta power across the trial at most gamma-modulated sites. It does not establish that relationship for the full stated alpha/beta range of 8–30 Hz or for spiking; it also reports no instantaneous correlation within single-trial 50-ms bins. The separate top-down-control clause cites other sources, not this paper. (LLM, conf=0.85)
Experimental — accuracy not yet measuredAlpha/beta oscillations in deep cortical layers are anticorrelated with superficial-layer gamma associated with spiking carrying sensory inputs.
“Further, alpha/beta oscillations in deep cortical layers are anticorrelated with superficial-layer gamma associated with spiking carrying sensory inputs (26, 27).”
From Layer and rhythm specificity for predictive routing (2020) · cites this paper as [27]
The Results (‘Prediction 3’; page unavailable) report a negative correlation between beta and gamma power across the trial, but no apparent instantaneous relationship within single trials. The Results (‘Prediction 1’; page unavailable) link gamma-modulated sites to spiking that carries stimulus information. The paper does not establish the claim’s deep-versus-superficial layer distinction or an alpha–gamma anticorrelation. (LLM, conf=0.87)
Experimental — accuracy not yet measured
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References 54 · Cited by 846
- Authors
- Lundqvist, M., Rose, J., Herman, P., Brincat, S. L., Buschman, T. J., & Miller, E. K.
- Affiliations
- Massachusetts Institute of Technology (US)
- KTH Royal Institute of Technology (SE)
- Princeton University (US)
- Corresponding author
- Miller, Earl K.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2016-04
- Volume
- 90
- Issue
- 1
- Pages
- 152-164
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC5220584
- OpenAlex
- W2297363866
- Cited by
- 846
- References
- 54
- Citations by year
- 2026: 80 · 2025: 104 · 2024: 99 · 2023: 95 · 2022: 91 · 2021: 99 · 2020: 67 · 2019: 66 · 2018: 61 · 2017: 62 · 2016: 21
- FWCI
- 44.55
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (R01MH091174, R37MH087027)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- working memory, gamma oscillations, beta oscillations, prefrontal cortex, local field potentials, neuronal spiking, memory encoding, memory reactivation, sensory interference
- MeSH terms
- Animals, Beta Rhythm, Brain, Electroencephalography, Macaca fascicularis, Macaca mulatta, Memory, Short-Term, Neurons, Task Performance and Analysis, Prefrontal Cortex, Gamma Rhythm
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