Characterizing synaptic conductance fluctuations in cortical neurons and their influence on spike generation

Cortical neurons are subject to sustained and irregular synaptic activity which causes important fluctuations of the membrane potential (Vm). We review here different methods to characterize this activity and its impact on spike generation. The simplified, fluctuating point-conductance model of synaptic activity provides the starting point of a variety of methods for the analysis of intracellular Vm recordings. In this model, the synaptic excitatory and inhibitory conductances are described by Gaussian-distributed stochastic variables, or colored conductance noise. The matching of experimentally recorded Vm distributions to an invertible theoretical expression derived from the model allows the extraction of parameters characterizing the synaptic conductance distributions. This analysis can be complemented by the matching of experimental Vm power spectral densities (PSDs) to a theoretical template, even though the unexpected scaling properties of experimental PSDs limit the precision of this latter approach. Building on this stochastic characterization of synaptic activity, we also propose methods to qualitatively and quantitatively evaluate spike-triggered averages of synaptic time-courses preceding spikes. This analysis points to an essential role for synaptic conductance variance in determining spike times. The presented methods are evaluated using controlled conductance injection in cortical neurons in vitro with the dynamic-clamp technique. We review their applications to the analysis of in vivo intracellular recordings in cat association cortex, which suggest a predominant role for inhibition in determining both sub- and supra-threshold dynamics of cortical neurons embedded in active networks.Comment: 9 figures, Journal of Neuroscience Methods (in press, 2008

The global status of insect resistance to neonicotinoid insecticides

This document is the Accepted Manuscript version of the following article: Chris Bass, Ian Denholm, Martin S. Williamson, and Ralf Nauen, ‘The global status of insect resistance to neonicotinoid insecticides’, Pesticide Biochemistry and Physiology, Vol. 121, pp. 78-87, June 2015. The Version of Record is available online at doi: https://doi.org/10.1016/j.pestbp.2015.04.004. Published by Elsevier Copyright © 2015 Elsevier Inc.The first neonicotinoid insecticide, imidacloprid, was launched in 1991. Today this class of insecticides comprises at least seven major compounds with a market share of more than 25% of total global insecticide sales. Neonicotinoid insecticides are highly selective agonists of insect nicotinic acetylcholine receptors and provide farmers with invaluable, highly effective tools against some of the world's most destructive crop pests. These include sucking pests such as aphids, whiteflies, and planthoppers, and also some coleopteran, dipteran and lepidopteran species. Although many insect species are still successfully controlled by neonicotinoids, their popularity has imposed a mounting selection pressure for resistance, and in several species resistance has now reached levels that compromise the efficacy of these insecticides. Research to understand the molecular basis of neonicotinoid resistance has revealed both target-site and metabolic mechanisms conferring resistance. For target-site resistance, field-evolved mutations have only been characterized in two aphid species. Metabolic resistance appears much more common, with the enhanced expression of one or more cytochrome P450s frequently reported in resistant strains. Despite the current scale of resistance, neonicotinoids remain a major component of many pest control programmes, and resistance management strategies, based on mode of action rotation, are of crucial importance in preventing resistance becoming more widespread. In this review we summarize the current status of neonicotinoid resistance, the biochemical and molecular mechanisms involved, and the implications for resistance management.Peer reviewedFinal Accepted Versio

Investigation of the Exclusive ^{3}He(e,e'pn)p Reaction

Cross sections for the ^{3}He(e,e'pn)p reaction were measured for the first time at energy transfers of 220 and 270 MeV for several momentum transfers ranging from 300 to 450 MeV/c. Cross sections are presented as a function of the momentum of the recoil proton and the momentum transfer. Continuum Faddeev calculations using the Argonne V18 and Bonn-B nucleon-nucleon potentials overestimate the measured cross sections by a factor 5 at low recoil proton momentum with the discrepancy becoming much smaller at higher recoil momentum.Comment: 5, pages, 3 figure

Interaction entre conductances synaptiques et<br />l'initiation du potentiel d'action dans les neurones<br />corticaux: modèles computationnels et analyse<br />d'enregistrements intracellulaires

During natural network states in vivo, neocortical neurons are subject to a high and fluctuating membrane conductance. However, the integrative properties of neurons during such “high-conductance” (HC) states are still unknown. We have (1) characterized the link between conductance dynamics and action potential (AP) initiation in HC states; (2) compared different models of AP response (PSTH) during such states. We distinguish two discharge modes, according to whether the AP is evoked by an increase of excitation or by a decrease of inhibition. We have proposed a new method to calculate the “spike-triggered average” (STA) of conductances solely from the Vm, tested this method numerically and in vitro, as well as applied this method to in vivo recordings. We demonstrate that inhibitory APs are predominant in the awake cat, which reveals a major role for inhibition.Pendant les états naturels d'activité in vivo, les neurones neocorticaux sont sujets à une conductance membranaire forte et fluctuante. Cependant, les propriétés intégratives des neurones ne sont pas connues pendant ces états de “haute conductance” (HC). Nous avons (1) caractérisé le lien entre la dynamique des conductances et l'initiation du potentiel d'action (PA) dans les neurones corticaux dans les états HC; (2) comparé différents modèles de réponse de PA (PSTH) pendant ces états. Nous distinguons deux modes de décharge, selon que le PA est évoqué par une augmentation d'excitation ou par une diminution d'inhibition. Nous avons proposé une nouvelle méthode pour calculer les “spike-triggered average” (STA) des conductances à partir du Vm, testé cette méthode numériquement et in vitro, ainsi que appliqué cette méthode aux enregistrements in vivo. Nous démontrons que les PAs inhibiteurs sont majoritaires chez le chat éveillé, ce qui révèle un rôle majeur de l'inhibition

Interaction entre conductances synaptiques et l'initiation du potentiel d'action dans les neurones corticaux (modèles computationnels et analyse d'enregistrements intracellulaires)

Pendants les etats naturels d'activite in vivo, les neurones neocorticaux sont sujets a une conductance membranaire forte et fluctuante. Cependant, les proprietes integratives des neurones ne sont pas connues pendant ces etats de "haute conductance" (HC). Nous avons (1) caracterise le lien entre la dynamique des conductances et l'initiation du potentiel d'action (PA) dans les neurones corticaux dans les etats HC; (2) compare differents modeles de reponse de PA (PSTH) pendant ces etats. Nous distinguons deux modes de decharge, selon que le PA est evoque par une augmentation d'excitation ou par une diminution d'inhibition. Nous avons propose une nouvelle methode pour calculer les "spike-triggered average" (STA) des conductances a partir du potentiel membranaire, teste cette methode numeriquement et in vitro, ainsi que applique cette methode aux enregistrements in vivo. Nous demontrons que les PAs inhibiteurs sont majoritaires chez le chat eveille, ce qui revele un role majeur de l'inhibitionPARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF

Characterizing neuronal activity by describing the membrane potential as a stochastic process.

International audienceCortical neurons behave similarly to stochastic processes, as a consequence of their irregularity and dense connectivity. Their firing pattern is close to a Poisson process, and their membrane potential (V(m)) is analogous to colored noise. One way to characterize this activity is to identify V(m) to a multidimensional stochastic process. We review here this approach and how it can be used to extract important statistical signatures of neuronal activity. The "VmD method" consists of fitting the V(m) distribution obtained intracellularly to analytic expressions derived from stochastic processes, and thereby deduce synaptic conductance parameters. However, this method requires at least two levels of V(m), which prevents applications to single-trial measurements. We also discuss methods that can be applied to single V(m) traces, such as power spectral analysis and the "STA method" to calculate spike-triggered average conductances based on a maximum likelihood procedure. A recently proposed method, the "VmT method", is based on the fusion of these two concepts. This method is analogous to the VmD method and estimates the mean excitatory and inhibitory conductances and their variances. However, it does so by using a maximum-likelihood estimation, and can thus be applied to single V(m) traces. All methods were tested using controlled conductance injection in dynamic-clamp experiments