Laugh Like You Mean It:Authenticity Modulates Acoustic, Physiological and Perceptual Properties of Laughter

Several authors have recently presented evidence for perceptual and neural distinctions between genuine and acted expressions of emotion. Here, we describe how differences in authenticity affect the acoustic and perceptual properties of laughter. In an acoustic analysis, we contrasted spontaneous, authentic laughter with volitional, fake laughter, finding that spontaneous laughter was higher in pitch, longer in duration, and had different spectral characteristics from volitional laughter that was produced under full voluntary control. In a behavioral experiment, listeners perceived spontaneous and volitional laughter as distinct in arousal, valence, and authenticity. Multiple regression analyses further revealed that acoustic measures could significantly predict these affective and authenticity judgements, with the notable exception of authenticity ratings for spontaneous laughter. The combination of acoustic predictors differed according to the laughter type, where volitional laughter ratings were uniquely predicted by harmonics-to-noise ratio (HNR). To better understand the role of HNR in terms of the physiological effects on vocal tract configuration as a function of authenticity during laughter production, we ran an additional experiment in which phonetically trained listeners rated each laugh for breathiness, nasality, and mouth opening. Volitional laughter was found to be significantly more nasal than spontaneous laughter, and the item-wise physiological ratings also significantly predicted affective judgements obtained in the first experiment. Our findings suggest that as an alternative to traditional acoustic measures, ratings of phonatory and articulatory features can be useful descriptors of the acoustic qualities of nonverbal emotional vocalizations, and of their perceptual implications

New Insights into Metabolic Properties of Marine Bacteria Encoding Proteorhodopsins

Proteorhodopsin phototrophy was recently discovered in oceanic surface waters. In an effort to characterize uncultured proteorhodopsin-exploiting bacteria, large-insert bacterial artificial chromosome (BAC) libraries from the Mediterranean Sea and Red Sea were analyzed. Fifty-five BACs carried diverse proteorhodopsin genes, and we confirmed the function of five. We calculate that proteorhodopsin-exploiting bacteria account for 13% of microorganisms in the photic zone. We further show that some proteorhodopsin-containing bacteria possess a retinal biosynthetic pathway and a reverse sulfite reductase operon, employed by prokaryotes oxidizing sulfur compounds. Thus, these novel phototrophs are an unexpectedly large and metabolically diverse component of the marine microbial surface water

Actigraph Accelerometer-Defined Boundaries for Sedentary Behaviour and Physical Activity Intensities in 7 Year Old Children

Background: Accurate objective assessment of sedentary and physical activity behaviours during childhood is integral to the understanding of their relation to later health outcomes, as well as to documenting the frequency and distribution of physical activity within a population.Purpose: To calibrate the Actigraph GT1M accelerometer, using energy expenditure (EE) as the criterion measure, to define thresholds for sedentary behaviour and physical activity categories suitable for use in a large scale epidemiological study in young children.Methods: Accelerometer-based assessments of physical activity (counts per minute) were calibrated against EE measures (kcal.kg(-1).hr(-1)) obtained over a range of exercise intensities using a COSMED K4b(2) portable metabolic unit in 53 seven-year-old children. Children performed seven activities: lying down viewing television, sitting upright playing a computer game, slow walking, brisk walking, jogging, hopscotch and basketball. Threshold count values were established to identify sedentary behaviour and light, moderate and vigorous physical activity using linear discriminant analysis (LDA) and evaluated using receiver operating characteristic (ROC) curve analysis.Results: EE was significantly associated with counts for all non-sedentary activities with the exception of jogging. Threshold values for accelerometer counts (counts. minute(-1)) were = 3841 for light, moderate and vigorous physical activity respectively. The area under the ROC curves for discrimination of sedentary behaviour and vigorous activity were 0.98. Boundaries for light and moderate physical activity were less well defined (0.61 and 0.60 respectively). Sensitivity and specificity were higher for sedentary (99% and 97%) and vigorous (95% and 91%) than for light (60% and 83%) and moderate (61% and 76%) thresholds.Conclusion: The accelerometer cut points established in this study can be used to classify sedentary behaviour and to distinguish between light, moderate and vigorous physical activity in children of this age