Synchronization of Firing in Cortical Fast-Spiking Interneurons at Gamma Frequencies: A Phase-Resetting Analysis

Gouwens, Nathan W.; Zeberg, Hugo; Tsumoto, Kunichika; Tateno, Toshitake; Aihara, Kazuyuki; Robinson, Hugh P. C.

doi:10.1371/journal.pcbi.1000951

Cited by 31 publications

(39 citation statements)

References 47 publications

(90 reference statements)

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“…Given the diversity of voltage-gated ion channels (143 channel genes in the human genome (1)), it is of general interest to consider what constitutes the variability and what functional role it plays in forming and regulating neuronal firing patterns (2)(3)(4)(5)(6)(7)(8)(9)(10). The basic functional channel parameters are ion selectivity and gating, the latter characterized by opening/closing kinetics and the voltage dependence of the channel's open probability.…”

Section: Introductionmentioning

confidence: 99%

Extracellular Linkers Completely Transplant the Voltage Dependence from Kv1.2 Ion Channels to Kv2.1

Elinder

Madeja

Zeberg

et al. 2016

Biophysical Journal

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The transmembrane voltage needed to open different voltage-gated K (Kv) channels differs by up to 50 mV from each other. In this study we test the hypothesis that the channels' voltage dependences to a large extent are set by charged amino-acid residues of the extracellular linkers of the Kv channels, which electrostatically affect the charged amino-acid residues of the voltage sensor S4. Extracellular cations shift the conductance-versus-voltage curve, G(V), by interfering with these extracellular charges. We have explored these issues by analyzing the effects of the divalent strontium ion (Sr 2þ ) on the voltage dependence of the G(V) curves of wild-type and chimeric Kv channels expressed in Xenopus oocytes, using the voltage-clamp technique. Out of seven Kv channels, Kv1.2 was found to be most sensitive to Sr 2þ (50 mM shifted G(V) by þ21.7 mV), and Kv2.1 to be the least sensitive (þ7.8 mV). Experiments on 25 chimeras, constructed from Kv1.2 and Kv2.1, showed that the large Sr 2þ -induced G(V) shift of Kv1.2 can be transferred to Kv2.1 by exchanging the extracellular linker between S3 and S4 (L3/4) in combination with either the extracellular linker between S5 and the pore (L5/P) or that between the pore and S6 (LP/6). The effects of the linker substitutions were nonadditive, suggesting specific structural interactions. The free energy of these interactions was~20 kJ/mol, suggesting involvement of hydrophobic interactions and/or hydrogen bonds. Using principles from double-layer theory we derived an approximate linear equation (relating the voltage shifts to altered ionic strength), which proved to well match experimental data, suggesting that Sr 2þ acts on these channels mainly by screening surface charges. Taken together, these results highlight the extracellular surface potential at the voltage sensor as an important determinant of the channels' voltage dependence, making the extracellular linkers essential targets for evolutionary selection.

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Section: Introductionmentioning

confidence: 99%

Extracellular Linkers Completely Transplant the Voltage Dependence from Kv1.2 Ion Channels to Kv2.1

Elinder

Madeja

Zeberg

et al. 2016

Biophysical Journal

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“…PRCs measure the phase shift of an oscillator in response to a brief perturbation as a function of the timing of the input. PRCs in conjunction with coupled oscillators theory have been widely used in neuroscience to understand how changes in a neuron's intrinsic properties affect its frequency (Schwemmer and Lewis 2011;Ly and Ermentrout 2011), how neuronal oscillators phase-lock to external input (Brumberg and Gutkin 2007;Gouwens et al 2010), and how networks of neurons synchronize (e.g., Ermentrout 1984;Hansel 1995;Mancilla 2007). In almost all cases, the oscillatory units have been taken to be the individual neurons.…”

Section: Introductionmentioning

confidence: 99%

Phase response properties of half-center oscillators

Zhang

Lewis

2013

J Comput Neurosci

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We examine the phase response properties of half-center oscillators (HCOs) that are modeled by a pair of Morris-Lecar-type neurons connected by strong fast inhibitory synapses. We find that the two basic mechanisms for half-center oscillations, "release" and "escape", give rise to strikingly different phase response curves (PRCs). Release-type HCOs are most sensitive to perturbations delivered to cells at times when they are about to transition from the active to the suppressed state, and PRCs are dominated by a large negative peak (phase delays) at corresponding phases. On the other hand, escape-type HCOs are most sensitive to perturbations delivered to cells at times when they are about to transition from the suppressed to the active state, and PRCs are dominated by a large positive peak (phase advances) at corresponding phases. By analyzing the phase space structure of Morris-Lecar-type HCO models with fast synaptic dynamics, we identify the dynamical mechanisms underlying the shapes of the PRCs. To demonstrate the significance of the different shapes of the PRCs for the release-type and escape-type HCOs, we link the shapes of the PRCs to the different frequency modulation properties of release-type

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“…IV.D.2. For example, Tateno and Robinson (2007) and Gouwens et al (2010) experimentally reconstructed the phase response curves for different types of interneurons in rat cortex, in order to better understand the mechanisms of neural synchronization.…”

Section: Coupling Functions Revealing Mechanismsmentioning

confidence: 99%

Coupling functions: Universal insights into dynamical interaction mechanisms

et al. 2017

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The dynamical systems found in nature are rarely isolated. Instead they interact and influence each other. The coupling functions that connect them contain detailed information about the functional mechanisms underlying the interactions and prescribe the physical rule specifying how an interaction occurs. A coherent and comprehensive review is presented encompassing the rapid progress made recently in the analysis, understanding, and applications of coupling functions. The basic concepts and characteristics of coupling functions are presented through demonstrative examples of different domains, revealing the mechanisms and emphasizing their multivariate nature. The theory of coupling functions is discussed through gradually increasing complexity from strong and weak interactions to globally coupled systems and networks. A variety of methods that have been developed for the detection and reconstruction of coupling functions from measured data is described. These methods are based on different statistical techniques for dynamical inference. Stemming from physics, such methods are being applied in diverse areas of science and technology, including chemistry, biology, physiology, neuroscience, social sciences, mechanics, and secure communications. This breadth of application illustrates the universality of coupling functions for studying the interaction mechanisms of coupled dynamical systems.

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Synchronization of Firing in Cortical Fast-Spiking Interneurons at Gamma Frequencies: A Phase-Resetting Analysis

Cited by 31 publications

References 47 publications

Extracellular Linkers Completely Transplant the Voltage Dependence from Kv1.2 Ion Channels to Kv2.1

Extracellular Linkers Completely Transplant the Voltage Dependence from Kv1.2 Ion Channels to Kv2.1

Phase response properties of half-center oscillators

Coupling functions: Universal insights into dynamical interaction mechanisms

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