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Windows update 1709 download manuella allen - windows update 1709 download manuella allen.The Eye is Listening: Music-Induced Arousal and Individual Differences Predict Pupillary Responses
A randomized target order 5-point HV5 calibration routine was performed 5-point calibration was deemed sufficient since pupil diameter was the only measurement of interest and participants were asked to continuously fixate the area corresponding to the center of the screen , followed by a separate validation using the EyeLink software.
Participants were asked not to move their head during the experiment and to look at the fixation cross located at the center of the screen and try to avoid blinking when it was displayed they were shown an image of the cross. The cross color was dark gray RGB: 75,75, The smiley face was the same color as the cross and approximately the same size.
As with the rating experiment, participants first practiced with three excerpts not included in the actual stimulus set and were then exposed to all 80 excerpts from the stimulus set. For each excerpt, the fixation cross was first shown for 2 s, then the music played for 6 s, then the cross was displayed for another 2 s, for a total of 10 s of recording of the pupillary response per trial. After 40 stimuli midway through the experiment , participants were allowed to take a pause. Upon resuming the experiment, calibration correction was performed complete calibration was performed if necessary.
Once all excerpts had been played, participants were invited to fill in a post-experiment paper questionnaire about their socio-demographic background and musical interests. Participants also completed the SRS Schulz et al. Finally, participants were paid 5 Euros for their participation, thanked, and debriefed.
The entire experiment lasted approximately 30 min. Gaze coordinates were also recorded in order to track the gaze position and exclude samples for which the participants did not fixate the screen area corresponding to the center cross.
Blinks were identified by the proprietary algorithm of the Eyelink eye-tracking system, using default settings. Data samples from 50 ms before the beginning of blinks to 50 ms after the end of blinks were discarded to exclude pre- and post-blink artifacts 1.
In addition, given that pupil size estimation is less accurate when participants are not fixating the center of the screen Gagl et al. A total of 50 of trials 2. Frequency responses in pupil size variation that occur at rates faster than 2 Hz are considered to be noise Richer and Beatty, ; Privitera and Stark, Accordingly, pupil diameter data were low-passed using a fourth-order Butterworth filter with a cutoff frequency of 4 Hz. The baseline pupil diameter was measured as the average pupil diameter for a period of ms immediately preceding the stimulus onset.
Baseline-corrected pupil diameters were computed by subtracting the baseline pupil diameter from the raw pupil diameter after stimulus onset. To allow for comparisons between participants and to correct for possible tonic changes in pupil diameter over the course of the experiment, raw pupil diameters were converted into relative pupil diameter by expressing them as a proportional difference from the baseline diameter van Rijn et al.
Subscale scores were analyzed using a MANOVA design, with experimental group subjective ratings versus pupillary response as a between-subject factor. The overall mean familiarity rating for the 80 excerpts was 2.
To evaluate whether participants rated the excerpts in a consistent manner, inter-rater reliability was assessed by computing the average measure intraclass correlation coefficient ICC using the ICC 2, k form Shrout and Fleiss, , which corresponds to a two-way random effects model for consistency McGraw and Wong, The ICC values obtained for arousal and pleasantness were nearly identical to those reported in Gingras et al.
Moreover, the mean arousal and pleasantness ratings obtained here were also consistent with those obtained on the same excerpts, but with different participants Gingras et al. Mean subjective arousal, tension, and pleasantness ratings for 80 six-second excerpts selected from Romantic piano trios. The numbers identify the excerpts for a complete listing of the excerpts, see Appendix in the Supplementary Material.
The full scale for all three ratings ranged from 1 to 7, but a restricted range is displayed here to facilitate viewing. Figure 1 shows the two-dimensional emotion spaces corresponding to the set of 80 excerpts, displaying the mean arousal, tension, and pleasantness ratings obtained on each excerpt.
Mean pleasantness ratings range: 3. Mean arousal and mean tension ratings range: 2. A SRS total scores Schulz et al. To visualize whether the time course of pupillary responses is similar for low- and high-arousing stimuli, we categorized the excerpts into low- and high-arousal brackets. The time course displayed a similar pattern for the 40 excerpts rated as most arousing and the 40 rated as least arousing, although the relative dilation was larger for the high-arousing excerpts Figure 3.
A sharp increase in pupil size occurs about ms after the stimulus onset. The peak dilation is reached around 1. A small dilation occurs ms after the offset, followed by a rapid constriction.
These observations are in line with earlier investigations of pupillary responses to affective sounds Partala and Surakka, Time course of the pupillary response for high- and low-arousing excerpts.
Pupil dilation is calculated as a percentage of the mean pupil diameter observed during the ms before the onset baseline. High-arousing excerpts correspond to the 40 excerpts rated as most arousing, whereas low-arousing excerpts are the 40 rated as least arousing. Because the subjective ratings obtained on the excerpts were retrospective ratings of the entire excerpts, pupillary responses were averaged over the entire 6-s duration of the excerpts Partala and Surakka, in order to allow a meaningful investigation of the association between ratings and pupillary responses.
As a preliminary analysis of this association, we first computed the correlations between the mean pupillary responses observed for each excerpt and the mean subjective ratings obtained for each excerpt treating each excerpt as the unit of analysis on the one hand Table 1 , and between the mean pupillary responses observed for each participant and the participant-specific features i.
These analyses showed that mean subjective arousal and tension ratings were positively correlated with the mean pupillary response observed for each excerpt Table 1.
TABLE 1. Correlations computed over the mean values obtained for each music excerpt. TABLE 2. Correlations computed over the values obtained for each participant. In doing so, we sought to quantify the contribution of excerpt-specific affective characteristics and listener-specific traits to the observed variance in pupillary response among excerpts and participants using maximum-likelihood linear mixed models. Given that each excerpt was heard by each participant, excerpts and participants were treated as fully crossed random effects Baayen et al.
Here, we began with a full model including all fixed and random effects of interest, and implemented a backward stepwise model selection procedure. Hence, our initial model included arousal, pleasantness, and familiarity ratings as excerpt-specific features tension ratings were not included to reduce multicollinearity , and gender, mood subscales, SRS scores, and attitudes toward music role of music, liking for the excerpts, and frequency of felt emotions as listener-specific features.
Additionally, all two-way interactions between each excerpt-specific feature and listener-specific trait were considered i. Participant, excerpt, and gender were coded as categorical factors, whereas all other predictors were treated as covariates and grand mean centered Enders and Tofighi, According to the model, males were predicted to show stronger pupillary dilations than females 1. Moreover, each additional unit increment in the mean arousal ratings predicted an increase of 0.
However, the effect of arousal was much weaker for listeners who liked the excerpts greatly, with a Spearman correlation coefficient between arousal ratings and pupillary responses of 0. An analogous model was obtained when predicting pupillary responses using tension ratings instead of arousal ratings, with significant effects of gender, reported role of music, tension ratings, and a significant interaction between tension and overall liking for the excerpts.
The coefficients and statistical tests also yielded very similar values to those obtained for the arousal model, which is to be expected considering the very high correlation between arousal and tension ratings. Pupillary responses to musical stimuli have rarely been investigated. In this study, we collected pupillary responses of non-musicians to a set of 80 six-second music excerpts for which we separately obtained subjective ratings of felt arousal, pleasantness, tension, and familiarity.
A correlational analysis showed that, as predicted, arousal and tension ratings were significantly correlated with mean pupillary response. A linear mixed model analysis including both music- and listener-specific features resulted in a best-fitting model with gender, role of music and arousal ratings as predictors of the pupillary response. Furthermore, an interaction between arousal ratings and liking was found. In general, these results are in line with the hypothesized contribution of excerpt-specific and listener-specific characteristics to pupillary responses to music.
However, contrary to our predictions, female participants showed smaller pupillary dilations than males, even though male and female listeners did not significantly differ in their attitude toward music or in their scores on the subscales of the MDBF mood questionnaire. Taken together, these results lend support to models that predict that responses to music depend on characteristics of the listener as well as on the music itself Hargreaves et al.
Regarding excerpt-specific features, it is worth noting that pleasantness was not significantly correlated with pupillary responses.
This is in agreement with previous reports indicating that pupillary responses are determined by emotional arousal, independently of the perceived pleasantness of the stimuli Bradley et al. Furthermore, we note that pleasantness ratings are not as consistent across participants as arousal and tension ratings, and are also more difficult to predict from the acoustical features of the stimuli Schubert, ; Eerola, ; Gingras et al.
Sound intensity, which is one of the main predictors of music-induced subjective arousal, is known to be correlated with physiological responses such as skin conductance Gomez and Danuser, However, our findings not only suggest that the range of subjective music-induced arousal ratings is largely unaffected by amplitude normalization Gingras et al.
More generally, because personality traits, such as neuroticism, have been shown to predict pupillary responses to sound stimuli Antikainen and Niemi, , future research in this domain should consider the role of personality traits in greater depth.
The larger pupil dilations observed for male listeners stand in contrast to earlier studies reporting stronger psychophysiological, but not psychological, responses to high-arousing, unpleasant music in females compared to males Nater et al. This discrepancy with earlier results may be due to the fact that our musical stimuli were not selected to induce high levels of unpleasantness, which is supported by the fact that stress reactivity was not a significant predictor of pupil dilation.
Moreover, in contrast to Nater et al. Although we controlled for the potential effect of familiarity by selecting music excerpts from a little-known genre, we observed a positive but non-significant correlation between familiarity and pupil dilation.
Because the range of familiarity ratings was very restricted, we may suppose that the effect of familiarity and exposure on pupillary responses would be more evident with a set of music excerpts ranging from unfamiliar to very familiar. This is supported by recent findings showing that repeated exposure to unfamiliar music significantly increased skin conductance a marker of emotional arousal and that self-reported familiarity ratings were positively related to skin conductance van den Bosch et al.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. We thank Andreas Gartus for his technical assistance and Helmut Leder for providing laboratory space for collecting subjective ratings.
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Wundt, W. Grundriss der Psychologie. Leipzig: Engelmann. David C. Waller, Dorsey, Robert E. Marko Kryvobokov, Xiaolong Liu, Tracking spatial location of clusters of geographically weighted regression estimates of price determinants ," Land Use Policy , Elsevier, vol. More about this item Keywords Real estate market ; Automated valuation models ; Investment ; Geocoding ; French cities ; Machine learning ; Artificial intelligence ; All these keywords.
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