ArticlePLoS computational biology2010
Bistable, irregular firing and population oscillations in a modular attractor memory network.
Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
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Who cites it
60 citing papers in PubMed.
- The Difference Neuron-a new spiking neuron model.Biological cybernetics · 2026Article
- Asynchronous firing and off states in working memory maintenance.Cell reports · 2026Article
- Cortical inhibition and activation during sensorimotor tasks in an aquatic environment: a pilot EEG study based on expert-novice paradigm.Frontiers in sports and active living · 2026Article
- Asynchronous firing and off-states in working memory maintenance.bioRxiv : the preprint server for biology · 2025Article
- Representation and computation in visual working memory.Nature human behaviour · 2024Review
- Spiking representation learning for associative memories.Frontiers in neuroscience · 2024Article
- Oscillations without cortex: Working memory modulates brainwaves in the endbrain of crows.Progress in neurobiology · 2022Article
- New methods for oscillation analyses push new theories of discrete cognition.Psychophysiology · 2022Review
- Rhythms of human attention and memory: An embedded process perspective.Frontiers in human neuroscience · 2022Review
- Activity Stabilization in a Population Model of Working Memory by Sinusoidal and Noisy Inputs.Frontiers in neural circuits · 2021Article
- Prefrontal oscillations modulate the propagation of neuronal activity required for working memory.Neurobiology of learning and memory · 2020Article
- Achieving stable dynamics in neural circuits.PLoS computational biology · 2020Article
- Biophysically grounded mean-field models of neural populations under electrical stimulation.PLoS computational biology · 2020Article
- Article
- Oscillatory recurrent gated neural integrator circuits (ORGaNICs), a unifying theoretical framework for neural dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- The time-course of component processes of selective attention.NeuroImage · 2019Article
- The Role of Hierarchical Dynamical Functions in Coding for Episodic Memory and Cognition.Journal of cognitive neuroscience · 2019Article
- Parietal low beta rhythm provides a dynamical substrate for a working memory buffer.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Bistable Firing Pattern in a Neural Network Model.Frontiers in computational neuroscience · 2019Article
- How the Brain Represents Language and Answers Questions? Using an AI System to Understand the Underlying Neurobiological Mechanisms.Frontiers in computational neuroscience · 2019Article
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3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Attractor neural networks are thought to underlie working memory functions in the cerebral cortex. Several such models have been proposed that successfully reproduce firing properties of neurons recorded from monkeys performing working memory tasks. However, the regular temporal structure of spike trains in these models is often incompatible with experimental data. Here, we show that the in vivo observations of bistable activity with irregular firing at the single cell level can be achieved in a large-scale network model with a modular structure in terms of several connected hypercolumns. Despite high irregularity of individual spike trains, the model shows population oscillations in the beta and gamma band in ground and active states, respectively. Irregular firing typically emerges in a high-conductance regime of balanced excitation and inhibition. Population oscillations can produce such a regime, but in previous models only a non-coding ground state was oscillatory. Due to the modular structure of our network, the oscillatory and irregular firing was maintained also in the active state without fine-tuning. Our model provides a novel mechanistic view of how irregular firing emerges in cortical populations as they go from beta to gamma oscillations during memory retrieval.
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