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Extensive research with musicians has shown that instrumental musical training can have a profound impact on how acoustic features are processed in the brain. However, less is known about the influence of singing training on neural activity during voice perception, particularly in response to salient acoustic features, such as the vocal vibrato in operatic singing. To address this gap, the present study employed functional magnetic resonance imaging (fMRI) to measure brain responses in trained opera singers and musically untrained controls listening to recordings of opera singers performing in two distinct styles: a full operatic voice with vibrato, and a straight voice without vibrato. Results indicated that for opera singers, perception of operatic voice led to differential fMRI activations in bilateral auditory cortical regions and the default mode network. In contrast, musically untrained controls exhibited differences only in bilateral auditory cortex. These results suggest that operatic singing training triggers experience-dependent neural changes in the brain that activate self-referential networks, possibly through embodiment of acoustic features associated with one's own singing style. [ABSTRACT FROM AUTHOR]

The receptorial responsiveness method (RRM) enables the estimation of a change in concentration of an (even degradable) agonist, near its receptor, via curve fitting to (at least) two concentration-effect (E/c) curves of a stable agonist. One curve should be generated before this change, and the other afterwards, in the same system. It follows that RRM yields a surrogate parameter ("cx") as the concentration of the stable agonist being equieffective with the change in concentration of the other agonist. However, regression can be conducted several ways, which can affect the accuracy, precision and ease-of-use. This study utilized data of previous ex vivo investigations. Known concentrations of stable agonists were estimated with RRM by performing individual (local) or global fitting, this latter with one or two model(s), using a logarithmic (logcx) or a nonlogarithmic (cx) parameter (the latter in a complex or in a simplified equation), with ordinary least-squares or robust regression, and with an "allat-once" or "pairwise" fitting manner. We found that the simplified model containing logcx was superior to all alternative models. The most complicated individual regression was the most accurate, followed closely by the moderately complicated two-model global regression and then by the easy-to-perform onemodel global regression. The two-model global fitting was the most precise, followed by the individual fitting (closely) and by the one-model global fitting (from afar). Pairwise fitting (two E/c curves at once) improved the estimation. Thus, the two-model global fitting, performed pairwise, and the individual fitting are recommended for RRM, using the simplified model containing logcx. [ABSTRACT FROM AUTHOR]

The receptorial responsiveness method (RRM) was proposed to estimate changes in the concentration of an agonist in the microenvironment of its receptor. Usually, this is done by providing the equieffective concentration of another agonist for the same receptor or for a largely overlapping postreceptorial signaling ('test agonist'). The RRM is a special nonlinear regression algorithm to analyze a concentration-response (E/c) curve that represents the simultaneous actions of a single agonist concentration to be estimated and of increasing concentrations of the test agonist. The aim of this study was to explore whether asymmetry of the E/c curve to be analyzed influences the reliability of the RRM. For this purpose, computer simulation was performed by constructing symmetric and asymmetric E/c curves using the operational model of agonism, and then these curves were analyzed with the RRM. To perform the RRM, 2 types of equations were used: one involving the Hill equation, the simplest model of the E/c relationship, and one containing the Richards equation, an advanced model properly handling E/c curve asymmetry. Results of this study indicate that E/c curve asymmetry does not significantly influence the accuracy of the estimates provided by the RRM. Thus, when using the RRM, it is not necessary to replace the Hill equation with the Richards equation to obtain useful estimates. Furthermore, it was found that estimation of a high concentration of a high-efficacy agonist can fail when the RRM is performed with a low-efficacy test agonist in a system characterized by a small operational slope factor. Key words: concentration-response curve, symmetry, operational model, efficacy, slope, concentration estimation, receptorial responsiveness method, RRM. On a propose la methode de reactivite des recepteurs (RRM pour receptorial responsiveness method) pour eevaluer les modifications de la concentration d'un agoniste dans le microenvironnement de son recepteur. L'evaluation est habituellement effectuee a partir des concentrations d'un agoniste distinct pour le meme recepteur ou pour une voie de signalisation post-recepteurs chevauchante etendue (<< agoniste temoin >>). La RRM est un algorithme de regression non lineaire special qui analyse une courbe concentration-response (E/c) representant les actions simultanees d'une concentration de l'agoniste a estimer et de concentrations croissantes de l'agoniste temoin. La presente etude a eu pour but d'examiner si l'asymetrie de la courbe E/c a analyser influence la fiabilite de la RRM. A cet effet, on a effectuee une simulation par ordinateur en construisant des courbes E/c symetriques et asymetriques a l'aide du modele operationnel d'agonisme, puis on a analyse ces courbes avec la RRM. Pour appliquer la methode, on a utilise: deux equations : l'une faisant appel a l'equation de Hill, le modele le plus simple de la relation E/c, et l'autre contenant l'equation de Richards, un modele avance capable de prendre en compte adequatement l'asymetrie de la courbe E/c. Les resultats de cette etude indiquent que l'asymetrie des courbes E/c n'influence pas significativement la precision des estimations fournies par la RRM. Ainsi, avec la RRM, il n'est pas necessaire de remplacer l'equation de Hill par l'equation de Richards pour obtenir de bonnes estimations. De plus, l'etude a montre que l'estimation d'une concentration elevee d'un agoniste de grande efficacite pourrait echouer lorsque la RRM est realisee avec un agoniste temoin de faible efficacitee dans un systeme caracterisee par un facteur de pente operationnel de faible amplitude. Mots-cles: courbe concentration-response, symetrie, modele operationnel, efficacite, pente, estimation de concentration, methode de reactivite des recepteurs, RRM. [Traduit par la Redaction], Introduction Using a special nonlinear regression algorithm, the receptorial responsiveness method (RRM) is capable of determining an increase in the near-receptor concentration of an agonist. The theoretical basis, execution, advantages, [...]

The receptorial responsiveness method (RRM) was proposed to characterize changes in the concentration of degradable agonists in the microenvironment of their receptors. The characterization is done by providing concentrations of a stable agonist for the same receptor that is equieffective with the change in concentration to be characterized. RRM is based on the analysis of concentration--effect (E/c) curves reflecting the simultaneous action of the degradable and the stable agonist. In the present study, we investigated whether dissimilar affinity and (or) efficacy of the coacting agonists as well as the steepness of the E/c curves influence the reliability of RRM. E/c curves were simulated based on the operational model and then analyzed with RRM. We found that dissimilarity in affinity of the coacting agonists did not affect the accuracy of RRM estimates. In contrast, accuracy of the estimation depended on the magnitude of the concentration to be assessed, the operational slope factor, and the operational efficacy ratio of the coacting agonists. However, our results suggest that proper choice of a stable agonist for a degradable one can help to ensure reliable results, since information about the change in concentration of a degradable agonist is otherwise difficult to obtain. Key words: concentration estimation, affinity, efficacy, slope, receptorial responsiveness method, RRM. On a propose; la methode de reactivite des recepteurs (RRM : receptorial responsiveness method) pour caracteriser les changements de concentration des agonistes deegradables dans le microenvironnement de leurs recepteurs. La caracterisation est effectuee a partir des concentrations d'un agoniste stable pour un recepteur dont l'efficacite reste constante avec le changement de concentration de l'agoniste degradable. La RRM repose sur l'analyse des courbes de concentration--effet (E/c) refletant l'action simultanee de l'agoniste degradable et de l'agoniste stable. Dans la presente etude, nous avons examine; si la difference d'affinite et (ou) d'efficacite des deux agonistes et de la raideur des courbes E/c influent sur la fiabilite de la RRM. Nous avons simulee les courbes E/c a partir du modele operationnel, puis nous les avons analysees avec la RRM. Nous avons trouve que la divergence d'affinite des deux agonistes n'influence pas la precision des estimations de la RRM. En revanche, la precision de l'estimation a ete fonction de la concentration a analyser, du facteur de pente operationnel et du rapport d'efficacite; operationnel des deux agonistes. Toutefois, nos reesultats donnent a penser que le choix judicieux de l'agoniste stable pour un agoniste degradable peut garantir la fiabilite des resultats, et permettre de disposer d'une information sur le changement de concentration d'un agoniste degradable, qui, autrement, serait difficile a determiner. Mots-cles: estimation de la concentration, affinite, efficacite, pente, methode de reactivite des reecepteurs, RRM. [Traduit par la Redaction], Introduction The functions of multicellular organisms (possessing a 'milieu interieur') are influenced by several endogenous regulatory molecules, most of which can be considered receptor agonists. The link between the concentration [...]