ArticleJournal of computational neuroscience2014
Frequency preference in two-dimensional neural models: a linear analysis of the interaction between resonant and amplifying currents.
Article in Journal of computational neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed, 81 citations in OpenAlex.
- Frequency-dependent coupling in response to oscillatory inputs in minimal networks of electrically coupled nodes: Gap junction networks and spatially extended neurons.Biological cybernetics · 2026Article
- A nullcline-guided discrete-time map for neurons with subcritical Hopf bifurcation dynamics.Frontiers in computational neuroscience · 2026Article
- Postsynaptic frequency filters shaped by the interplay of synaptic short-term plasticity and cellular time scales.Journal of computational neuroscience · 2025Article
- Transient frequency preference responses in cell signaling systems.NPJ systems biology and applications · 2024Article
- A linearized modeling framework for the frequency selectivity in neurons postsynaptic to vibration receptors.Cognitive neurodynamics · 2024Article
- Frequency-domain analysis of membrane polarization in two-compartment model neurons with weak alternating electric fields.Cognitive neurodynamics · 2024Article
- Dynamics of interaction betweenCognitive neurodynamics · 2024Article
- Theta and gamma rhythmic coding through two spike output modes in the hippocampus during spatial navigation.Cell reports · 2023Article
- Low-dimensional models of single neurons: a review.Biological cybernetics · 2023Review
- Distinct mechanisms underlie electrical coupling resonance and its interaction with membrane potential resonance.Frontiers in systems biology · 2023Article
- Temporal filters in response to presynaptic spike trains: interplay of cellular, synaptic and short-term plasticity time scales.Journal of computational neuroscience · 2022Article
- Oscillations and variability in neuronal systems: interplay of autonomous transient dynamics and fast deterministic fluctuations.Journal of computational neuroscience · 2022Article
- Network resonance can be generated independently at distinct levels of neuronal organization.PLoS computational biology · 2022Article
- Frequency-preference response in covalent modification cycles under substrate sequestration conditions.NPJ systems biology and applications · 2021Article
- Diversity amongst human cortical pyramidal neurons revealed via their sag currents and frequency preferences.Nature communications · 2021Article
- Differential contributions of synaptic and intrinsic inhibitory currents to speech segmentation via flexible phase-locking in neural oscillators.PLoS computational biology · 2021Article
- Modeling Reveals Human-Rodent Differences in H-Current Kinetics Influencing Resonance in Cortical Layer 5 Neurons.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Active membrane conductances and morphology of a collision detection neuron broaden its impedance profile and improve discrimination of input synchrony.Journal of neurophysiology · 2019Article
- Frequency-dependent responses of neuronal models to oscillatory inputs in current versus voltage clamp.Biological cybernetics · 2019Article
- Membrane potential resonance in non-oscillatory neurons interacts with synaptic connectivity to produce network oscillations.Journal of computational neuroscience · 2019Article
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2 authors at 1 institution in 1 country.
Funding
Abstract
Many neuron types exhibit preferred frequency responses in their voltage amplitude (resonance) or phase shift to subthreshold oscillatory currents, but the effect of biophysical parameters on these properties is not well understood. We propose a general framework to analyze the role of different ionic currents and their interactions in shaping the properties of impedance amplitude and phase in linearized biophysical models and demonstrate this approach in a two-dimensional linear model with two effective conductances g L and g1. We compute the key attributes of impedance and phase (resonance frequency and amplitude, zero-phase frequency, selectivity, etc.) in the g(L) - g1 parameter space. Using these attribute diagrams we identify two basic mechanisms for the generation of resonance: an increase in the resonance amplitude as g1 increases while the overall impedance is decreased, and an increase in the maximal impedance, without any change in the input resistance, as the ionic current time constant increases. We use the attribute diagrams to analyze resonance and phase of the linearization of two biophysical models that include resonant (I h or slow potassium) and amplifying currents (persistent sodium). In the absence of amplifying currents, the two models behave similarly as the conductances of the resonant currents is increased whereas, with the amplifying current present, the two models have qualitatively opposite responses. This work provides a general method for decoding the effect of biophysical parameters on linear membrane resonance and phase by tracking trajectories, parametrized by the relevant biophysical parameter, in pre-constructed attribute diagrams.
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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.