Permutation Orbifolds and Chaos

We study out-of-time-ordered correlation functions in permutation orbifolds at large central charge. We show that they do not decay at late times for arbitrary choices of low-dimension operators, indicating that permutation orbifolds are non-chaotic theories. This is in agreement with the fact they are free discrete gauge theories and should be integrable rather than chaotic. We comment on the early-time behaviour of the correlators as well as the deformation to strong coupling.Comment: 15 pages, v2: more references and additional comments in the introductio

Similarities in face and voice cerebral processing

In this short paper I illustrate by a few selected examples several compelling similarities in the functional organization of face and voice cerebral processing: (1) Presence of cortical areas selective to face or voice stimuli, also observed in non-human primates, and causally related to perception; (2) Coding of face or voice identity using a “norm-based” scheme; (3) Personality inferences from faces and voices in a same Trustworthiness–Dominance “social space”

A unified coding strategy for processing faces and voices

Both faces and voices are rich in socially-relevant information, which humans are remarkably adept at extracting, including a person's identity, age, gender, affective state, personality, etc. Here, we review accumulating evidence from behavioral, neuropsychological, electrophysiological, and neuroimaging studies which suggest that the cognitive and neural processing mechanisms engaged by perceiving faces or voices are highly similar, despite the very different nature of their sensory input. The similarity between the two mechanisms likely facilitates the multi-modal integration of facial and vocal information during everyday social interactions. These findings emphasize a parsimonious principle of cerebral organization, where similar computational problems in different modalities are solved using similar solutions

Gender differences in the temporal voice areas

There is not only evidence for behavioral differences in voice perception between female and male listeners, but also recent suggestions for differences in neural correlates between genders. The fMRI functional voice localizer (comprising a univariate analysis contrasting stimulation with vocal versus non-vocal sounds) is known to give robust estimates of the temporal voice areas (TVAs). However there is growing interest in employing multivariate analysis approaches to fMRI data (e.g. multivariate pattern analysis; MVPA). The aim of the current study was to localize voice-related areas in both female and male listeners and to investigate whether brain maps may differ depending on the gender of the listener. After a univariate analysis, a random effects analysis was performed on female (n = 149) and male (n = 123) listeners and contrasts between them were computed. In addition, MVPA with a whole-brain searchlight approach was implemented and classification maps were entered into a second-level permutation based random effects models using statistical non-parametric mapping (SnPM; Nichols & Holmes 2002). Gender differences were found only in the MVPA. Identified regions were located in the middle part of the middle temporal gyrus (bilateral) and the middle superior temporal gyrus (right hemisphere). Our results suggest differences in classifier performance between genders in response to the voice localizer with higher classification accuracy from local BOLD signal patterns in several temporal-lobe regions in female listeners

Thermal conductivity in the vortex state of d-wave superconductors

We present the results of a microscopic calculation of the longitudinal thermal conductivity of quasiparticles, $\kappa_{xx}$, in a 2D d-wave superconductor in the vortex state. Our approach takes into account both impurity scattering and a contribution to the thermal transport lifetime due to the scattering of quasiparticles off of vortices. We compare the results with the experimental measurements on high-T$_c$ cuprates and organic superconductors.Comment: 2 pages, submitted to proceedings of M2S-HTSC-VI (Houston

The potential for bias in principal causal effect estimation when treatment received depends on a key covariate

Motivated by a potential-outcomes perspective, the idea of principal stratification has been widely recognized for its relevance in settings susceptible to posttreatment selection bias such as randomized clinical trials where treatment received can differ from treatment assigned. In one such setting, we address subtleties involved in inference for causal effects when using a key covariate to predict membership in latent principal strata. We show that when treatment received can differ from treatment assigned in both study arms, incorporating a stratum-predictive covariate can make estimates of the "complier average causal effect" (CACE) derive from observations in the two treatment arms with different covariate distributions. Adopting a Bayesian perspective and using Markov chain Monte Carlo for computation, we develop posterior checks that characterize the extent to which incorporating the pretreatment covariate endangers estimation of the CACE. We apply the method to analyze a clinical trial comparing two treatments for jaw fractures in which the study protocol allowed surgeons to overrule both possible randomized treatment assignments based on their clinical judgment and the data contained a key covariate (injury severity) predictive of treatment received.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS477 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

The sound of trustworthiness: acoustic-based modulation of perceived voice personality

When we hear a new voice we automatically form a "first impression" of the voice owner’s personality; a single word is sufficient to yield ratings highly consistent across listeners. Past studies have shown correlations between personality ratings and acoustical parameters of voice, suggesting a potential acoustical basis for voice personality impressions, but its nature and extent remain unclear. Here we used data-driven voice computational modelling to investigate the link between acoustics and perceived trustworthiness in the single word "hello". Two prototypical voice stimuli were generated based on the acoustical features of voices rated low or high in perceived trustworthiness, respectively, as well as a continuum of stimuli inter- and extrapolated between these two prototypes. Five hundred listeners provided trustworthiness ratings on the stimuli via an online interface. We observed an extremely tight relationship between trustworthiness ratings and position along the trustworthiness continuum (r = 0.99). Not only were trustworthiness ratings higher for the high- than the low-prototypes, but the difference could be modulated quasi-linearly by reducing or exaggerating the acoustical difference between the prototypes, resulting in a strong caricaturing effect. The f0 trajectory, or intonation, appeared a parameter of particular relevance: hellos rated high in trustworthiness were characterized by a high starting f0 then a marked decrease at mid-utterance to finish on a strong rise. These results demonstrate a strong acoustical basis for voice personality impressions, opening the door to multiple potential applications