ArticleFrontiers in computational neuroscience2017
Phase Difference between Model Cortical Areas Determines Level of Information Transfer.
Article in Frontiers in computational neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Human neuronal firing varies with the frequency of local field potential oscillations.PLoS biology · 2026Article
- Human neuronal firing is modulated by the frequency of local field potential oscillations.bioRxiv : the preprint server for biology · 2025Article
- Attentional selection and communication through coherence: Scope and limitations.PLoS computational biology · 2024Article
- Delay-dependent transitions of phase synchronization and coupling symmetry between neurons shaped by spike-timing-dependent plasticity.Cognitive neurodynamics · 2023Article
- Phase-locking patterns underlying effective communication in exact firing rate models of neural networks.PLoS computational biology · 2022Article
- Mutual information resonances in delay-coupled limit cycle and quasi-cycle brain rhythms.Biological cybernetics · 2022Article
- Malleability of gamma rhythms enhances population-level correlations.Journal of computational neuroscience · 2021Article
- On the emergence of cognition: from catalytic closure to neuroglial closure.Journal of biological physics · 2020Article
- Rhythmic modulation of thalamic oscillations depends on intrinsic cellular dynamics.Journal of neural engineering · 2019Article
- Engagement of Pulvino-cortical Feedforward and Feedback Pathways in Cognitive Computations.Neuron · 2019Article
- The Orientation Selectivity of Spike-LFP Synchronization in Macaque V1 and V4.Frontiers in computational neuroscience · 2019Article
- Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation.PLoS computational biology · 2017Article
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2 authors.
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Abstract
Communication between cortical sites is mediated by long-range synaptic connections. However, these connections are relatively static, while everyday cognitive tasks demand a fast and flexible routing of information in the brain. Synchronization of activity between distant cortical sites has been proposed as the mechanism underlying such a dynamic communication structure. Here, we study how oscillatory activity affects the excitability and input-output relation of local cortical circuits and how it alters the transmission of information between cortical circuits. To this end, we develop model circuits showing fast oscillations by the PING mechanism, of which the oscillatory characteristics can be altered. We identify conditions for synchronization between two brain circuits and show that the level of intercircuit coherence and the phase difference is set by the frequency difference between the intrinsic oscillations. We show that the susceptibility of the circuits to inputs, i.e., the degree of change in circuit output following input pulses, is not uniform throughout the oscillation period and that both firing rate, frequency and power are differentially modulated by inputs arriving at different phases. As a result, an appropriate phase difference between the circuits is critical for the susceptibility windows of the circuits in the network to align and for information to be efficiently transferred. We demonstrate that changes in synchrony and phase difference can be used to set up or abolish information transfer in a network of cortical circuits.
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