Frequency preference in two-dimensional neural models: a linear analysis of the interaction between resonant and amplifying currents

@article{Rotstein2013FrequencyPI,
  title={Frequency preference in two-dimensional neural models: a linear analysis of the interaction between resonant and amplifying currents},
  author={Horacio G. Rotstein and Farzan Nadim},
  journal={Journal of Computational Neuroscience},
  year={2013},
  volume={37},
  pages={9-28}
}
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… 
Frequency Preference Response to Oscillatory Inputs in Two-dimensional Neural Models: A Geometric Approach to Subthreshold Amplitude and Phase Resonance
  • H. Rotstein
  • Physics
    Journal of mathematical neuroscience
  • 2014
TLDR
It is demonstrated that nonlinearities in the voltage equation cause amplifications of the voltage response and shifts in the resonant and phase-resonant frequencies that are not predicted by the corresponding linearized model.
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  • H. Rotstein
  • Physics
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  • 2014
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The results highlight the complexity of the voltage response to oscillatory inputs in nonlinear models and the roles that resonant and amplifying currents have in shaping these responses.
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  • H. Rotstein
  • Biology
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  • 2016
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This work investigates both the biophysical and dynamic mechanisms of generation of STOs and how their attributes depend on the model parameters for biophysical (conductance-based) models having qualitatively different types of resonant currents (activating and inactivating) and an amplifying current.
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Spiking resonances in models with the same slow resonant and fast amplifying currents but different subthreshold dynamic properties
  • H. Rotstein
  • Physics
    Journal of Computational Neuroscience
  • 2017
TLDR
This paper investigates the spiking resonant properties of conductance-based models that are biophysically equivalent at the subthreshold level, but dynamically different (parabolic- and cubic-like voltage nullclines), and demonstrates that the effective time scales that operate at the Subthreshold regime do not necessarily determine the existence of a preferred spiking response to oscillatory inputs in the same frequency band.
Spiking resonances in models with the same slow resonant and fast amplifying currents but different subthreshold dynamic properties
TLDR
This paper investigates the spiking resonant properties of conductance-based models that are biophysically equivalent at the subthreshold level, but functionally different (parabolic- and cubic-like), and uses dynamical systems tools to explain the underlying mechanisms and the mechanistic differences between the resonance types.
Information filtering in resonant neurons
TLDR
The work highlights the crucial role of nonlinearities for the frequency dependence of neuronal information transmission by demonstrating nonlinearity-mediated band-pass filtering of information at frequencies close to the subthreshold impedance resonance in three different model systems.
Mechanisms of generation of membrane potential resonance in a neuron with multiple resonant ionic currents
TLDR
The impedance profile of the biological PD neuron is used to constrain parameter values of a conductance-based model using a genetic algorithm and many optimal parameter combinations were obtained, finding that distinct pairwise correlations between ICa parameters contributed to the maintenance of fres and resonance power (QZ).
Mechanisms of generation of membrane potential resonance in a neuron with multiple resonant ionic currents
TLDR
The PD neuron of the crab pyloric network is used to understand how MPR emerges from the interplay of the biophysical properties of multiple ionic currents, each capable of generating resonance.
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References

SHOWING 1-10 OF 53 REFERENCES
Subthreshold resonance explains the frequency-dependent integration of periodic as well as random stimuli in the entorhinal cortex.
TLDR
Experimental evidence is provided that the integration of non-periodic subth threshold stimuli is determined by the same subthreshold frequency selectivity as that of periodic stimuli, and it is shown that the frequency selectivities in theSubthreshold range extends to suprathreshold responses in terms of firing rate.
The Resonance Frequency Shift, Pattern Formation, and Dynamical Network Reorganization via Sub-Threshold Input
TLDR
A novel mechanism that mediates the rapid and selective pattern formation of neuronal network activity in response to changing correlations of sub-threshold level input is described and might be the basis for reliable spike-timing dependent plasticity.
From subthreshold to firing-rate resonance.
TLDR
It is suggested that resonant neurons are able to communicate their frequency preference to postsynaptic targets when the level of noise is comparable to that prevailing in vivo, and the modulatory effect an additional weak oscillating current has on the instantaneous firing rate.
Dynamics of rat entorhinal cortex layer II and III cells: characteristics of membrane potential resonance at rest predict oscillation properties near threshold
TLDR
It is demonstrated that electrical resonance is closely related though not equivalent to the occurrence of sag‐potentials and MPOs, and MPO frequencies can be predicted from the membrane impedance curve for stellate cells, which underscores the importance of intrinsic noise sources for subthreshold phenomena and rules out a deterministic description of MPOs.
Subthreshold membrane-potential resonances shape spike-train patterns in the entorhinal cortex.
TLDR
A minimal resonate-and-fire type model based on measured physiological parameters captures fundamental properties of neuronal firing statistics surprisingly well and helps to shed light on the mechanisms that shape spike patterns.
Membrane Resonance and Stochastic Resonance Modulate Firing Patterns of Thalamocortical Neurons
TLDR
It is speculated that combined membrane and stochastic resonances have physiological utility in coupling synaptic activity to preferred firing frequency and in network synchronization under noise.
Spike Phase Locking in CA1 Pyramidal Neurons Depends on Background Conductance and Firing Rate
TLDR
The results demonstrate that CA1 pyramidal cells can actively change their synchronization properties in response to global changes in activity associated with different behavioral states, and that spike rate adaptation and frequency resonance in the spike-generating mechanism are implicated in shaping the different phase-locking profiles.
Resonance (∼10 Hz) of excitatory networks in motor cortex: effects of voltage‐dependent ion channel blockers
TLDR
The results indicate that specific voltage‐dependent non‐inactivating K+ currents, such as the M‐current, and persistent sodium currents are critically involved in generating ∼10 Hz oscillations of excitatory motor cortex networks.
...
1
2
3
4
5
...