ArticleJournal of mathematical biology2013
Phase resetting reduces theta-gamma rhythmic interaction to a one-dimensional map.
Article in Journal of mathematical biology, 2013. 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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Who cites it
12 citing papers in PubMed.
- A mean field theory for pulse-coupled neural oscillators based on the spike time response curve.Journal of neurophysiology · 2025Article
- Existence and stability criteria for global synchrony and for synchrony in two alternating clusters of pulse-coupled oscillators updated to include conduction delays.Mathematical biosciences · 2024Article
- Dynamic models for musical rhythm perception and coordination.Frontiers in computational neuroscience · 2023Review
- Article
- Non-linear auto-regressive models for cross-frequency coupling in neural time series.PLoS computational biology · 2017Article
- Bifurcation Analysis on Phase-Amplitude Cross-Frequency Coupling in Neural Networks with Dynamic Synapses.Frontiers in computational neuroscience · 2017Article
- Article
- Hippocampal CA1 Ripples as Inhibitory Transients.PLoS computational biology · 2016Article
- A Role of Phase-Resetting in Coordinating Large Scale Neural Networks During Attention and Goal-Directed Behavior.Frontiers in systems neuroscience · 2016Review
- Phase-resetting as a tool of information transmission.Current opinion in neurobiology · 2015Review
- Misidentifications of specific forms of cross-frequency coupling: three warnings.Frontiers in neuroscience · 2015Article
- Effect of heterogeneity and noise on cross frequency phase-phase and phase-amplitude coupling.Network (Bristol, England)Article
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Authors and funding
2 authors.
Funding
Abstract
Gamma and theta oscillations of the hippocampus are known to interact, but the mechanisms underlying such interaction are not well understood. We focus on a previously published computational model of hippocampal activity that shows the gamma rhythms nesting in the theta rhythms, and investigate the dynamical mechanisms underlying that interaction. There are three types of neurons in the model: pyramidal cells, fast-spiking interneurons, and "oriens lacunosum-moelculare" (O-LM cells); the latter is an inhibitory cell whose inhibition has a longer time scale, and which has currents associated with intrinsic theta-rhythm behavior. We identify two main modes of interaction among the slow and the fast rhythms in the model, modulated by the strength of the excitatory synapse on the O-LM cells. Using resets of phases after each pyramidal cell and O-LM spike, we extend the use of the phase transition map (PTM) to encode the stability type of spiking patterns in networks where different frequencies interact. The tailored application of the PTM to the model network measures how the interaction between the shape of the phase response curves and the length of the gamma period determines the number of gamma spikes in theta cycles, and provides an explicit formula for the length of theta intervals in nesting regimes. Using the PTM, we also explain the covariance of the gamma and theta rhythms as drive is changed over some intervals.
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Registered trials
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.