ArticleProceedings of the National Academy of Sciences of the United States of America2019
Parietal low beta rhythm provides a dynamical substrate for a working memory buffer.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 47 citations in OpenAlex.
- Multi-stable oscillations in cortical networks with two classes of inhibition.PLoS computational biology · 2026Article
- Two-dimensional neural geometry underpins hierarchical organization of sequence in human working memory.Nature human behaviour · 2025Article
- Large-scale interactions in predictive processing: oscillatory versus transient dynamics.Trends in cognitive sciences · 2025Review
- A comparative study of EEG functional and effective connectivity patterns in children with learning difficulties during reading and math tasks.Frontiers in neuroscience · 2025Article
- Deep learning-based electroencephalic decoding of the phase-lagged transcranial alternating current stimulation.Frontiers in human neuroscience · 2025Article
- Abnormal trial-to-trial variability in P300 time-varying directed eeg network of schizophrenia.Medical & biological engineering & computing · 2024Article
- Maintenance and transformation of representational formats during working memory prioritization.Nature communications · 2024Article
- Multi-timescale neural dynamics for multisensory integration.Nature reviews. Neuroscience · 2024Review
- Reward-based option competition in human dorsal stream and transition from stochastic exploration to exploitation in continuous space.Science advances · 2024Article
- Isometric Arm Forces Exerted by Females at Different Levels of Physical Comfort and Their EEG Signatures.Brain sciences · 2023Article
- Article
- Cognitive neuroscience perspective on memory: overview and summary.Frontiers in human neuroscience · 2023Article
- Prefrontal cortical plasticity during learning of cognitive tasks.Nature communications · 2022Article
- Large-scale frontoparietal theta, alpha, and beta phase synchronization: A set of EEG differential characteristics for freezing of gait in Parkinson's disease?Frontiers in aging neuroscience · 2022Article
- Impaired reach-to-grasp kinematics in parkinsonian patients relates to dopamine-dependent, subthalamic beta bursts.NPJ Parkinson's disease · 2021Article
- Neonatal Isoflurane Does Not Affect Sleep Architecture and Minimally Alters Neuronal Beta Oscillations in Adolescent Rats.Frontiers in behavioral neuroscience · 2021Article
- Layer and rhythm specificity for predictive routing.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Interactions of multiple rhythms in a biophysical network of neurons.Journal of mathematical neuroscience · 2020Article
- Phase of firing coding of learning variables across the fronto-striatal network during feature-based learning.Nature communications · 2020Article
- Neural Dynamics in Primate Cortex during Exposure to Subanesthetic Concentrations of Nitrous Oxide.eNeuroArticle
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Working memory (WM) is a component of the brain's memory systems vital for interpretation of sequential sensory inputs and consequent decision making. Anatomically, WM is highly distributed over the prefrontal cortex (PFC) and the parietal cortex (PC). Here we present a biophysically detailed dynamical systems model for a WM buffer situated in the PC, making use of dynamical properties believed to be unique to this area. We show that the natural beta1 rhythm (12 to 20 Hz) of the PC provides a substrate for an episodic buffer that can synergistically combine executive commands (e.g., from PFC) and multimodal information into a flexible and updatable representation of recent sensory inputs. This representation is sensitive to distractors, it allows for a readout mechanism, and it can be readily terminated by executive input. The model provides a demonstration of how information can be usefully stored in the temporal patterns of activity in a neuronal network rather than just synaptic weights between the neurons in that network.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.