Iva L Maruščáková

Pavel Linhart

Victoria F Ratcliffe

Céline Tallet

David Reby

Marek Špinka
email: spinka.marek@vuzv.cz

Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals

Keywords: emotional valence, emotional intensity, vocalizations, personality, empathy

come

Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals

Introduction

Whilst emotions are subjective, affective feelings experienced autonomously (J. [START_REF] Panksepp | The basic emotional circuits of mammalian brains: Do animals have affective lives?[END_REF], they also have a strong social dimension (J. B. [START_REF] Panksepp | Rodent empathy and affective neuroscience[END_REF][START_REF] Špinka | Social dimension of emotions and its implication for animal welfare[END_REF][START_REF] Van Kleef | How emotions regulate social life: the emotions as social information (Easi) model[END_REF] Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870

3 2009; [START_REF] Van Kleef | An interpersonal approach to emotion in social decision making: the emotions as social information model[END_REF]. The social dimension of emotions resides in the fact that emotions are expressed in cues and signals (for instance, in vocalisations) that are readily perceived by conspecifics and can also be discriminated by heterospecific individuals. In comparison to the now extensive body of research investigating the physiological correlates of emotional states in various vertebrate species, the social dimension of animal emotions has been less intensely studied (Špinka, 2012). Specifically, there are few studies addressing the human decoding of emotional content from animal-emitted vocalisations [START_REF] Belin | Human cerebral response to animal affective vocalizations[END_REF][START_REF] Faragó | Humans rely on the same rules to assess emotional valence and intensity in conspecific and dog vocalizations[END_REF]. Human perception of animal emotions is important as this can help in assessing animal welfare [START_REF] Dawkins | The science of animal suffering[END_REF][START_REF] Mendl | An integrative and functional framework for the study of animal emotion and mood[END_REF][START_REF] Panksepp | The basic emotional circuits of mammalian brains: Do animals have affective lives?[END_REF] and enable more effective interactions between humans and animals [START_REF] Hemsworth | Relationships between humananimal interactions and productivity of commercial dairy cows[END_REF].

Besides the more traditional concept of identifying discrete basic emotions [START_REF] Ekman | An argument for basic emotions[END_REF]; J.

Panksepp, 2005; J. [START_REF] Panksepp | Toward a cross-species understanding of empathy[END_REF][START_REF] Sauter | Cross-cultural recognition of basic emotions through nonverbal emotional vocalizations[END_REF], one of the main alternative approach to the study of emotion uses quantitative dimensions to define emotions [START_REF] Laukka | A dimensional approach to vocal expression of emotion[END_REF][START_REF] Mendl | An integrative and functional framework for the study of animal emotion and mood[END_REF][START_REF] Russell | A circumplex model of affect[END_REF][START_REF] Sauter | Cross-cultural recognition of basic emotions through nonverbal emotional vocalizations[END_REF].

The dimensional approach has the advantage of providing a framework for the study of a wide range of emotional states and their overt manifestations. Moreover, the dimensional approach is applicable across different taxa and therefore suitable for comparative studies [START_REF] Mendl | An integrative and functional framework for the study of animal emotion and mood[END_REF].

Different emotional dimensions have been identified: valence (the degree of pleasure/displeasure), arousal (activation, degree of excitation), intensity (how strong is the emotion) and potency (coping potential) [START_REF] Laukka | A dimensional approach to vocal expression of emotion[END_REF]. In some cases, using all of these dimensions may be redundant, as, for instance, perception of arousal and intensity in human verbal expressions have been found to be highly correlated [START_REF] Laukka | A dimensional approach to vocal expression of emotion[END_REF] and hence interchangeable for listeners. Combination of valence dimension and one of the two, either arousal or intensity dimension, can describe most of the emotions for listeners. We accept the assumption that emotional intensity is expressed in higher level of activity of an animal and hence is interchangeable with arousal. In our study, we will

Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 4 henceforth use the terms emotional valence and emotional intensity. We will however continue use the term "arousal" when referring to previous studies that utilized this term.

The dimensional approach has been used to study how emotions are expressed in animal and human vocalisations [START_REF] Briefer | Vocal expression of emotions in mammals: mechanisms of production and evidence[END_REF][START_REF] Gogoleva | Sign and strength of emotional arousal: vocal correlates of positive and negative attitudes to humans in silver foxes (Vulpes Vulpes)[END_REF][START_REF] Scheiner | Acoustic analyses of developmental changes and emotional expression in the preverbal vocalizations of infants[END_REF]. Both emotional intensity (arousal) and emotional valence were found to correlate with temporal and spectral call features. For example, in young piglets (Sus scrofa), the more negative the situation is, the longer is the duration of the emitted calls [START_REF] Tallet | Encoding of situations in the vocal repertoire of piglets (Sus scrofa): a comparison of discrete and graded classifications[END_REF]. Vocalizations of squirrel monkeys (Saimirisciureus), change in response to increasingly aversive stimuli by shifting the frequency spectrum higher (peak frequency, distribution of frequency amplitudes) and by increasing frequency range, whilst decreasing in tonality [START_REF] Fichtel | On the vocal expression of emotion. A multiparametric analysis of different states of aversion in the squirrel monkey[END_REF][START_REF] Jürgens | Vocalization as an emotional indicator -neuro-ethological study in the squirrel monkey[END_REF]. Transition to higher frequencies (F0, peak frequency, frequency spectrum) and louder expression in human speech also characterize increased arousal (either negative or positive) (reviewed in [START_REF] Bachorowski | Vocal expression of emotion[END_REF]. Correspondingly, human listeners can use the variation in the acoustic qualities of vocalisations to infer emotional context in which various types of human verbal and nonverbal vocalisations were emitted [START_REF] Hammerschmidt | Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals[END_REF][START_REF] Sauter | Perceptual cues in nonverbal vocal expressions of emotion[END_REF][START_REF] Soltis | The signal functions of early infant crying[END_REF]. Listeners are also capable of discriminating above chance levels between basic emotionally-loaded situations (such as pain, fear, feeding and social contact) from recorded calls of mammalian species such as domestic dogs Canis lupus familiaris, cats Felis catus, and pigs [START_REF] Nicastro | Classification of domestic cat (Felis catus) vocalizations by naive and experienced human listeners[END_REF][START_REF] Pongrácz | Acoustic parameters of dog barks carry emotional information for humans[END_REF][START_REF] Tallet | Human perception of the emotional state of domestic piglets through their vocalizations varies with the working experience with pigs[END_REF]. Spectral and temporal cues considerably influence the human perception of emotional content in auditory stimuli (reviewed in: [START_REF] Bachorowski | Vocal expression of emotion[END_REF][START_REF] Scherer | Vocal communication of emotion: A review of research paradigms[END_REF], and the cognitive mechanisms involved in processing 5 heterospecific vocalizations suggests that humans might use similar assessment rules within and across species [START_REF] Faragó | Humans rely on the same rules to assess emotional valence and intensity in conspecific and dog vocalizations[END_REF]. If so, this would resonate with theories of shared emotional systems across mammalian species, first postulated by Darwin in his theory of common emotional expressions across mammals [START_REF] Darwin | The expression of the emotions in man and animals[END_REF], and later described in Morton´s structural-acoustic rules [START_REF] August | Mammal sounds and motivation-structural rules -a test of the hypothesis[END_REF][START_REF] Briefer | Vocal expression of emotions in mammals: mechanisms of production and evidence[END_REF][START_REF] Morton | On the occurrence and significance of motivation-structural rules in some bird and mammal sounds[END_REF].

Besides attributing emotional dimensions in animal vocalisations, humans have also been

shown to have some ability to identify the context in which heterospecific calls are emitted. For example, [START_REF] Pongrácz | Human listeners are able to classify dog (Canis familiaris) barks recorded in different situations[END_REF] found that humans were able to assign dog barks to the correct situation (out of six possible situations that varied in emotional valence) in more than twice as many cases as would be predicted by chance, and that this ability was probably influenced by the tonality, pitch and inter-bark time intervals -with the pitch of the sound being the most influencing factor. In a study where cats´ meows were played to humans, [START_REF] Nicastro | Classification of domestic cat (Felis catus) vocalizations by naive and experienced human listeners[END_REF] found that human listeners could infer the context of cat meows and that this ability increased with their experience of cats. In a study by [START_REF] Tallet | Human perception of the emotional state of domestic piglets through their vocalizations varies with the working experience with pigs[END_REF], the successful identification of context from playbacks of piglet vocalizations exceeded chance for all four of the presented situations, even in naïve listeners with minimal experience with pigs. However, it is not known whether this classification ability is guided by the perceived emotional dimensions in the call.

In our previous study [START_REF] Tallet | Human perception of the emotional state of domestic piglets through their vocalizations varies with the working experience with pigs[END_REF], we found that listeners' experience with pigs and listeners' gender could both affect the classification of the calls. The question arises whether individual psychological variables such as empathic abilities, attitudes towards animals or general personality dimensions can affect the decoding of animal sounds by human listeners. In human psychology, the understanding of emotional content of another human´s nonverbal signals depends

to some degree on empathy [START_REF] Dziobek | Dissociation of cognitive and emotional empathy in adults with asperger syndrome using the multifaceted empathy test (Met)[END_REF] as well as other factors such as emotional stability [START_REF] Guarino | Reconstructing N: a new approach to measuring emotional sensitivity[END_REF]. In human studies, distinction is often made between cognitive empathy and emotional empathy [START_REF] Cohen | Empathy in conduct-disordered and comparison youth[END_REF][START_REF] Lawrence | Measuring empathy: reliability and validity of the empathy quotient[END_REF] Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 6 [START_REF] Lawrence | Measuring empathy: reliability and validity of the empathy quotient[END_REF][START_REF] Mehrabian | Measure of emotional empathy[END_REF][START_REF] Panksepp | Toward a cross-species understanding of empathy[END_REF], the former being defined as the capacity of individuals to take the perspective of others and the latter as the emotional response to the emotional state of another person. We hypothesise that higher cognitive empathy might enable humans to more precisely judge the situational context in which the call was emitted, while the higher emotional empathy might shift the valence and intensity judgments towards more extreme values.

Another psychological factor which can affect human decoding of animal vocalisations is their attitude towards animals [START_REF] Armstrong | Development of an attitude scale to measure attitudes toward humans' use of nonhuman animals[END_REF]. Attitudes towards animals are influenced by factors such as upbringing (urban vs. rural), religious affiliation, type of education, gender, sex-roles, some personality traits [START_REF] Driscoll | Attitudes toward animal use[END_REF][START_REF] Furnham | Personality, empathy and attitudes to animal welfare[END_REF] and even empathy levels [START_REF] Taylor | Empathy and attitudes to animals[END_REF]. However, all these factors account for only a small part of the inter-individual variability in attitude towards animals and, therefore, it is of interest to examine this trait on its own. Attitude towards animals affects how people treat animals [START_REF] Breuer | Behavioural response to humans and the productivity of commercial dairy cows[END_REF][START_REF] Coleman | Modifying stockperson attitudes and behaviour towards pigs at alarge commercial farm[END_REF]. Also, empathetic farmers with a positive attitude to animals have more healthy animals [START_REF] Kielland | Dairy farmer attitudes and empathy toward animals are associated with animal welfare indicators[END_REF]. However, it is unknown whether attitudes towards animals can influence how people perceive cues emitted by animals.

The aim of this study was to investigate how human assessments of pig vocalisations are affected by acoustic qualities of the calls and by the human listeners' psychological properties.

Specifically, four hypotheses were tested (Fig. 1): H1) Acoustic properties of the particular vocal stimulus affect the perceived emotional intensity and valence. Specifically, recordings with longer and higher and less harmonic calls will be judged as more negative and / or more intense. H2)

Psychological attributes of the listener influence the perceived emotional intensity and valence. In particular, people with high emotional empathy, people scoring high on neuroticism and people with positive attitudes towards animals will rates the emotional intensity higher. H3) The perceived 7 emotional intensity and valence of a particular vocal stimulus affect the correct identification of the situation. Specifically, recordings perceived as more intense will be more easy to assign to the correct situation. H4) Psychological attributes of the listener affect the accuracy of identifying situations from the vocalisations. In particular, we expected listeners with higher cognitive empathy and those with more positive attitudes towards animals to identify the situations more accurately.

Materials and methods

Participants

A sample of 60 listeners aged 21 -29 years and balanced in gender (30 women, 30 men) was examined. The listeners were undergraduate and graduate students of humanities recruited during the courses and during the breaks between lectures at Charles University in Prague. A reward of 100

Czech koruna (about € 4) was promised before and paid after the questionnaire was filled.

Procedure

The testing proceeded through a set of four electronic questionnaires run from notebooks owned by the researchers in a university room. The computers were not connected to internet during the testing.

Vocalisation decoding questionnaire

This questionnaire used 48 recordings (12 per 4 situations) of piglet vocalisations. This set of acoustic stimuli was identical to those used in our previous study (see [START_REF] Tallet | Human perception of the emotional state of domestic piglets through their vocalizations varies with the working experience with pigs[END_REF] for recording description). The recordings had been obtained in two positive situations -at the end of a nursing bout and during reunion with the mother after a period of separation -and in two negative situations -during castration and during isolation from the mother and the littermates. More precisely, "nursing" vocalizations were emitted by a piglet near the head of the sow just after the milk intake phase of the nursing. "Reunion" vocalisations were emitted by a piglet immediately at the Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 8 reunion of the piglet and its dam, after 30s of separation. "Castration" vocalizations were emitted during the cutting of the spermatic cords. Finally, "isolation" vocalizations were emitted between the 8 th and 9 th minute of isolation from litter and dam.

Each of the 48 recordings was obtained from a different piglet. Experimental stimuli were constructed from the recordings by selecting a representative high quality sequence from each recording. Our choice was based on the quality of the recordings, avoiding single calls, background noise and vocalizations of other animals. We standardized the length and amplitude of the stimuli.

Each stimulus lasted mean  SD = 2.36  0.49 seconds, and consisted of mean  SD = 5.6  2.6 individual calls. The length of the stimuli did not differ between the 4 situations, ANOVA: F 3,44 = 0.13, p = 0.939). When presented to listeners, these sequences were played back twice with a 0.75s silence interval between each presentation. The amplitudes of the stimuli were also standardized before testing. The peak amplitude of each stimulus was standardised for all recordings using the 'Normalize' function of Avisoft-SASLabPro (R. Specht, Berlin).

The questionnaire consisted of three subsections. In the first part, listeners were asked about their personal data including their gender, age and experience with pigs. In the second part, each listener was required to evaluate the emotional intensity of 12 different recordings (3 per situation), and the emotional valence of 12 different recordings (3 per situation), using 5-point Likert scale. Only at the start of the third part were the listeners informed about the four situations, and they were then asked to judge, for yet another new 12 stimuli (3 per situation), in which of the four situations each of them was recorded. A software module was included in the questionnaire that assigned the recordings to the listeners. For the first listener, three unique sets of 12 recordings were randomly selected for judgement on intensity, valence and situation, respectively, using the rule that none of the recordings were used twice for the same listener. For the following listeners, the same procedure was applied, however the selection was made only from those recordings that had not yet been assessed for that particular purpose. By the fourth listener, all the recordings were evaluated for all

Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 9 three purposes, and the cycle began anew. Thus, each recording was evaluated by 15 listeners for intensity, by another 15 listeners for valence and yet another 15 listeners for situation.

Acoustic analysis of stimuli

The calls within a single stimulus could be of very similar or very different quality (i.e. several call types might be presented, Fig 2). Acoustic analyses were carried out in Avisoft SASLab Pro (Raimund Specht, Berlin) and PRAAT version 5.3.02 [START_REF] Boersma | PRAAT: doing phonetics by computer[END_REF]. Three basic temporal parameters were used in the analyses, namely, the amount of vocalised sound within each stimulus (labelled as "proportion vocalized", calculated as the summed duration of all calls within the stimulus divided by the stimulus duration), the average call duration for each stimulus and average inter-call interval (from the end of the call to the beginning of the following call). Call onsets and offsets were identified by visual inspection of call spectrograms and amplitude envelopes in AvisoftSASLab Pro.

Calls had clear onsets and offsets, resulting in their reliable identification. The number of calls and sum of call durations per recording were highly correlated between two independent observers: 10 harmonic-to-noise ratio was obtained from the 'voice report' function, which uses an automatic cross-correlation algorithm to detect acoustic periodicity in voiced sections of the call (detailed in [START_REF] Boersma | Accurate short-term analysis of the fundamental frequency and the harmonicsto-noise ratio of a sampled sound[END_REF]. The presence or absence of subharmonics was judged based on visual inspection of the spectrograms (by VFR). To check reliability of subharmonics identification, the presence of subharmonics was assessed independently by a second person and the agreement was compared using Cohen's kappa coefficient which revealed 'substantial agreement' between observers (kappa = 0.67). The call parameters were averaged within each stimulus.

Personality test

The Czech version of NEO-FFI personality inventory [START_REF] Hřebíčková | Internal consistency of Czech version of NEO-FFI inventory[END_REF] was used to assess the personality profiles of listeners. This test is based on the concept of the "Big used for psychology testing worldwide, in Czech language. The raw scores of each factor of every listener were used for the analysis.

Empathy test

The Interpersonal Reactivity Index (IRI) test was chosen to measure the situational empathy of listeners [START_REF] Davis | Empathy: a social psychological approach[END_REF]. The IRI consists of 28 questions divided equally among four subscales. For the purposes of our study, we used two subscales for the final analysis. Perspective Taking, described as the tendency to spontaneously adopt the psychological view of others in everyday life, was taken as a measure of cognitive empathy and Empathic Concern, defined by the author as the tendency to experience feelings of sympathy or compassion for unfortunate others, was used as a measure of 11 emotional empathy [START_REF] Davis | Measuring individual differences in empathy -evidence for a multidimensional approach[END_REF]. We hypothesized that the former may affect more strongly the situational judgement of piglets´ calls whereas the latter may influence to the valence and/or intensity judgments. The raw score for the two subscales, as well as the total raw score, was used for the statistical analysis.

Attitudes towards animals:

For quantification of attitudes towards animals, we administered the AAS -the Animal Attitudes Scale [START_REF] Herzog | Gender, sex role orientation, and attitudes toward animals[END_REF][START_REF] Signal | Attitude to animals and empathy: Comparing animal protection and general community samples[END_REF][START_REF] Taylor | Empathy and attitudes to animals[END_REF]. The scale assesses individual differences in listeners´ attitudes towards the treatment of animals in various areas. It contains 20 items and has a high internal consistency. Again, the total raw score of each listener was used for statistical analysis.

Statistical analysis

The effects of the acoustic and psychological variables on the perceived emotional intensity and valence (Hypotheses H1 and H2) were tested through stepwise multiple linear regression mixed models. We started with a full model containing the following predictors: 7 acoustic variables 12 and acoustic variables were also calculated to help the interpretation of the model results. Since castration calls were quite different from the vocalisations in the other three situations, this process was accomplished first for all four situations and then for the three situations excluding castration.

Next we assessed which predictors affected the correct identification of the context from the heard playbacks. First we tested whether the probability of the correct identification depended on the perceived intensity and valence of the particular vocal stimulus (Hypothesis H3). The dependent variable was the proportion of correct context identifications for the particular stimulus. Second, we investigated the influence of the psychological variables on correct identification (Hypothesis H4). A backward stepwise model reduction procedure was applied similarly as in tests for Hypotheses H1 and H2. The models were generalised linear models with binary distributions. The full model contained situation, the 9 psychological variables and gender and was iteratively reduced by omission of the least significant factor until all remaining factors were significant at p < 0.05. The final model was constructed using a randomly selected half of the observations and the second half was used for significance testing of the variables in the final model. The effect sizes were estimated using Cohen's f 2 according to [START_REF] Selya | A practical guide to calculating Cohen's f2, a measure of local effect size, from PROC MIXED[END_REF].

Results

The effect of vocalisations' acoustic properties on intensity and valence judgements (Hypothesis 1)

For the emotional intensity judgements, the final model contained two significant acoustic variables.

The perceived intensity increased with increasing pitch of the vocal stimulus (F 1,266 = 38.00, p < Overall, results of multiple regression were in agreement with the results of the simple correlations (Table 1), with few exceptions: the duration and proportion vocalized were both associated with intensity and valence judgements, which mirrored strong association between these two acoustic variables. Further, presence of subharmonics was associated with both intensity and valence judgements. In the reduced dataset without castration calls, harmonic-to-noise ratio and call interval were associated with valence. On the other hand, none of the acoustic variables were significantly correlated to intensity in the reduced dataset but proportion vocalized showed the strongest association with intensity among acoustic variables, followed by call duration and call pitch.

The effect of psychological variables on intensity and valence judgements (Hypothesis 2)

The final models contained no significant effect of any of the psychological variables on either the perceived intensity or valence (p > 0.05). The listeners' gender also did not exert a significant effect on either the perceived intensity or the valence (p > 0.05).

Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870

14

The effect of perceived intensity and valence on the correct identification of context (Hypothesis 3) An interaction between type of situation and perceived intensity affected the proportion of stimuli that were assigned correctly to the situation (Fig 4, F 3,36 = 8.58, p < 0.001). The effect size of this factor was very large (local f 2 =1.06). Specifically, the probability that a particular castration stimulus would be correctly assigned to the castration situation increased with the perceived intensity of that stimulus (t = 2.67, p < 0.05). Similarly, for the reunion vocal stimuli, correct identification of context increased with perceived intensity (t = 2.90, p < 0.01). The opposite was true for nursing vocal stimuli, where less intensively perceived vocal stimuli were more often correctly classified ( t= -3.07, p<0.01). Neither the estimated valence nor the situation*valence interaction affected the accuracy of context identification (p > 0.05).

The effect of psychological variables on the correct identification of context (Hypothesis 4)

The final model contained none of the psychological attributes, nor the gender of the responder,

showing that these personal variables had no significant effect on the success rate of the individual listeners in context identification (p > 0.05).

Relationship between intensity and valence; differences between contexts

The correlation between the mean judged intensity and valence was high (r = -0.86, p < 0.0001, N = 48, Table 1). Without the castration stimuli, the relationship between intensity and valence became much weaker (r = -0.39, p < 0.05, N = 36). Castration stimuli had much higher judged intensity than any of the remaining three situations (ANOVA followed by paired t-tests, p < 0.0001). Castration calls were also judged as more negative (of lower valence) than the other three situations (ANOVA followed by paired t-tests, p < 0.05) while isolation was perceived as more negative than reunion and nursing (p < 0.05).

Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870

15

Discussion

Effect of acoustic characteristics on perception of stimuli

Our study indicates that listeners rated the intensity and valence of the stimuli based on very simple acoustic criteria. Judgments were affected by the mean pitch of the stimuli and two macroscopic temporal features of stimuli, namely the proportion of sound within stimulus and the duration of calls. The more complex acoustic variables (jitter, harmonics-to-noise ratio, subharmonics) seemed to be much less, if at all, important for listeners' judgments. While none of these variables were retained in the multiple regression models, simple correlations indicated that listeners may have used the presence of subharmonics to detect the higher emotional intensity and lower emotional valence in castration calls (the subharmonics variable was dropped from the multiple regression model because it was highly correlated with other time-and pitch-related variables. Also, harmonicto-noise ratio showed a simple correlation with valence and therefore, listeners could have used it for ratings despite the fact that it was not a significant predictor of valence ratings in final model.

It is worth noting that each of our stimuli consisted of several calls. Some of the stimuli contained calls that were quite similar to each other (e.g., the reunion example in Fig. 2A) while others consisted of calls that differed substantially in quality, e.g. in duration, pitch and frequency modulation (the isolation example in Fig. 2D). This reflects the natural variation in the piglet vocal repertoire, where in some situations, calls of one predominant type are used while in other situations, a rich mixture of call types are emitted [START_REF] Tallet | Encoding of situations in the vocal repertoire of piglets (Sus scrofa): a comparison of discrete and graded classifications[END_REF]. It is unknown whether humans are affected in their judgment of vocalizations by this uniformity-versus-diversity dimension. Our results indicate that simple average acoustic properties that do not take account of the variability of call types within a stimulus may be used by humans to judge the emotional content of juvenile mammal vocalizations.

Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870

16

Stimuli features and intensity rating

We found that the perceived emotional intensity increased with an increasing proportion of vocal sound ("proportion vocalized").Proportion vocalized may involve both longer call durations and shorter inter-call intervals. Both of these two components were also associated with emotional intensity, according to the simple correlations. Due to the correlative nature of our study, it is impossible to determine which of the time variables were truly used by listeners to judge the emotional content. Nevertheless, temporal variables clearly are potential cues for emotional judgements. This is in agreement with [START_REF] Laukka | A dimensional approach to vocal expression of emotion[END_REF] who found that pause proportion (silence between syllables and words within a phrase) decreased with perceived increasing intensity. They further report decreasing speech rate with increasing intensity, suggesting that longer syllable durations during speech might indicate increased emotional intensity. On the other hand, in striking contrast to the strongly positive relationship in our study, the duration of non-verbal sounds in humanswas reported to be negatively correlated (longer utterances = lower intensity) with perceived intensity [START_REF] Sauter | Perceptual cues in nonverbal vocal expressions of emotion[END_REF] and duration of dog calls was found to be negatively associated to human-perceived emotional intensity [START_REF] Faragó | Humans rely on the same rules to assess emotional valence and intensity in conspecific and dog vocalizations[END_REF].

Pitch was related to perceived emotional intensity in our data but only in the full dataset. In previous studies, too, the perceived emotional intensity has been found to correlate positively with pitch (fundamental frequency, energy distribution) both for verbal [START_REF] Laukka | A dimensional approach to vocal expression of emotion[END_REF] as well as for non-verbal [START_REF] Sauter | Perceptual cues in nonverbal vocal expressions of emotion[END_REF] human utterances. Also, dog calls of higher fundamental frequency were perceived as more intensive in the study of [START_REF] Faragó | Humans rely on the same rules to assess emotional valence and intensity in conspecific and dog vocalizations[END_REF] and the solicitation purrs of cats that have conspicuous high frequency components were perceived as more urgent, i.e. as having higher intensity, than non-solicitation purrs [START_REF] Mccomb | The cry embedded within the purr[END_REF]. However, after castration calls were removed from our dataset, there was no relation between pitch and intensity. The reason for that may be that the very stark contrast in pitch between the castration and non-castration calls over shadowed the more subtle differences in pitch among the stimuli from the other three situations. One way to test this assumption would be a

Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 17 similar study in which the listeners are not exposed at all to the high pitched, high intensity playback stimuli.

Vocal production (encoding) studies, i.e. investigations that relate the acoustic quality of vocalizations to objective differences in the arousal of animals, are also in agreement with our decoding results. In her review, [START_REF] Briefer | Vocal expression of emotions in mammals: mechanisms of production and evidence[END_REF] documents that the majority of studies have found increased call durations and decreased inter-call intervals (leading to larger vocalization proportions within a sample) in situations with higher emotional intensity. Also, the pitch of calls invariably increased with emotional intensity [START_REF] Briefer | Vocal expression of emotions in mammals: mechanisms of production and evidence[END_REF].

Stimuli features and valence rating

Calls of shorter duration were perceived as more positive in our study. This is consistent with the decoding studies of [START_REF] Faragó | Humans rely on the same rules to assess emotional valence and intensity in conspecific and dog vocalizations[END_REF] on dog calls. Also, in their study on human speech, [START_REF] Laukka | A dimensional approach to vocal expression of emotion[END_REF] reported that perceived valence increases with speech rate, suggesting that the duration of syllables/words decreased with increasing valence (the pause proportion did not decrease with valence). However, the duration of human non-verbal sounds did not correlate with the perceived valence in the study of [START_REF] Sauter | Perceptual cues in nonverbal vocal expressions of emotion[END_REF]. Also, humans seemingly ignored growl duration when attempting to distinguish between play and aggression in dog vocalizations, and used vocalization rate as a cue instead [START_REF] Mccomb | The cry embedded within the purr[END_REF]. Published studies on valence encoding confirm the relationship between increased emotional valence and shorter call duration in some non-human species, such as dogs [START_REF] Mccomb | The cry embedded within the purr[END_REF], but not in others (see [START_REF] Briefer | Vocal expression of emotions in mammals: mechanisms of production and evidence[END_REF] for review; e.g. african elephants Loxodonta africana: Soltis, Blowers, & Savage, 2011). In piglets, the average call duration has been found to correlate negatively with emotional valence across 11 different situations [START_REF] Tallet | Encoding of situations in the vocal repertoire of piglets (Sus scrofa): a comparison of discrete and graded classifications[END_REF]. In contrast, [START_REF] Weary | Vocal response to pain in piglets[END_REF] did not find any difference in the call durations of castrated and sham-castrated piglets, which may be due to the fact that both situations were near to the very negative end of the valence spectrum. In human infants, both elongation of cries [START_REF] Scheiner | Acoustic analyses of developmental changes and emotional expression in the preverbal vocalizations of infants[END_REF] and shortening of cries (Porter, Miller, & Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 18 Marshall, 1986) have been reported as responses to negative situations and their varying intensity.

This might indicate a non-linear relationship between valence and call duration with calls from positive and very negative situations being shorter than calls from mildly negative situations.

However, we found no indication of non-linear relationships in the scatterplots of our data.

Therefore, we did not test for quadratic effects because our full models anyway started with a numerous set of explanatory variables.

We further found that higher pitch piglet vocalizations were judged as more negative. During decoding of human vocalizations, higher pitched verbal and non-verbal utterances were also assigned more negative valence ratings [START_REF] Laukka | A dimensional approach to vocal expression of emotion[END_REF][START_REF] Sauter | Perceptual cues in nonverbal vocal expressions of emotion[END_REF].

Humans also associated higher pitched animal calls with negative emotions in several previous studies. Higher pitched solicitation purrs of cats are rated as less pleasant [START_REF] Mccomb | The cry embedded within the purr[END_REF].

Furthermore, human listeners associated high pitched dog barks with emotions such as despair and fear [START_REF] Pongrácz | Acoustic parameters of dog barks carry emotional information for humans[END_REF]; high pitch was also a common attribute of macaque calls assigned to anger and fear contexts by listeners [START_REF] Leinonen | Vocal communication between species -Man and Macaque[END_REF]. On the other hand, no relationship was found between human-perceived valence and fundamental frequency in dog calls [START_REF] Faragó | Humans rely on the same rules to assess emotional valence and intensity in conspecific and dog vocalizations[END_REF].

Emotion encoding studies across many species found shifts to higher frequencies in vocalizations emitted in negatively loaded situations (squirrel monkeys [START_REF] Fichtel | On the vocal expression of emotion. A multiparametric analysis of different states of aversion in the squirrel monkey[END_REF]humans: Porter et al., 1986;[START_REF] Scheiner | Acoustic analyses of developmental changes and emotional expression in the preverbal vocalizations of infants[END_REF]African elephants: Soltis et al., 2011). Piglets also use more vocalizations of higher pitch in more negative situations [START_REF] Tallet | Encoding of situations in the vocal repertoire of piglets (Sus scrofa): a comparison of discrete and graded classifications[END_REF]. Nevertheless, examples in different species exist as well when calls associated with positive states have higher pitch [START_REF] Briefer | Vocal expression of emotions in mammals: mechanisms of production and evidence[END_REF][START_REF] Brudzynski | Ultrasonic calls of rats as indicator variables of negative or positive states: acetylcholine-dopamine interaction and acoustic coding[END_REF][START_REF] Millot | Effects of pleasant and unpleasant ambient odors on human voice pitch[END_REF].

Situation recognition through perceived intensity

Our results match previous evidence for cross-species understanding of vocalization contexts and specifically for the human ability to recognize the contexts in which vocalizations are emitted by

Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 19 other species [START_REF] Leinonen | Vocal communication between species -Man and Macaque[END_REF][START_REF] Pongrácz | Human listeners are able to classify dog (Canis familiaris) barks recorded in different situations[END_REF][START_REF] Tallet | Human perception of the emotional state of domestic piglets through their vocalizations varies with the working experience with pigs[END_REF]. Our novel findings indicate that situational recognition may be mediated by the perceived intensity of emotion. It is not surprising that the most intensive castration calls were the most successfully recognized. Less intuitively, reunion vocalizations were also more correctly identified if they were perceived as more intense and the opposite pattern (easier recognition of less intense stimuli) was found in nursing vocalizations. One potential mechanism by which perceived call intensity might be used to identify context is that listeners have a preconception of the emotional impact / intensity of the different situations. For example, they may assume that castration, as a situation including strong pain, and also reunion as a situation involving active greeting are relatively high intensity events whilst nursing, presumable experienced as contentment, is a low intensity event. These preconceptions may originate from their personal experience with similar situations, including social situations with other humans. Similar mechanisms may be at work when human adults decode vocalizations of preverbal children [START_REF] Zeifman | An ethological analysis of human infant crying: Answering Tinbergen's four questions[END_REF]Lindová et al. in prep.).

The listeners had little experience with live pigs. Therefore, their recognition of the situation was most likely based on some general judgement procedure rather than on specific knowledge about the species. Together with our finding that intensity is estimated through simple acoustic cues, our results point to the possibility that humans apply simple algorithms when they estimate situations from vocalizations in a species they are not well acquainted with.

Castration vocalizations different from other situations

The vocalizations emitted during castration were very different from the three other situations, both in their objective acoustic properties and in the intensity and valence values assigned by the listeners. The results based on full dataset were different from results based on three situations after the exclusion of castration. Castration calls were perceived as very intensive and very negative, with little overlap with other situations. Therefore it seems that the main information decoded from piglet

Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 20 vocalisations is whether the piglet is in pain and therefore whether there is a need for urgent action.

The very intensive and very negative values of castration calls created a strong correlation between the intensity and valence values across the whole dataset. When the castration stimuli were excluded, the relationship became much weaker. Thus when the most urgent situation is excluded, valence and intensity became perceived as separate characteristics of vocal stimuli. In this restricted dataset, valence judgements were much better explained by acoustic properties than intensity judgements. Taken together, these results indicate a two-layer system of encoding and decoding of emotions from vocal stimuli. The first layer is a quick-and-rough identification of the most urgent very negative calls that should incite immediate action without delaying deliberation. This notion corresponds to the fact that sows' reactions to these most urgent calls are rather unspecific, for example, sows react readily to calls of alien piglets [START_REF] Held | Using the Piglet Scream Test to enhance piglet survival on farms: data from outdoor sows[END_REF][START_REF] Spinka | Dimensions of maternal behaviour characteristics in domestic and wild x domestic crossbred sows[END_REF].

The second layer is a finer (and less precise) distinction between not-so-urgent calls arising from other situations.

Lack of effect of psychological attributes on listeners' judgements about pig vocalizations

The ability of humans to recognize the context of vocalizations emitted by other animals is apparently present from an early age [START_REF] Linnankoski | Recognition of emotions in Macaque vocalizations by children and adults[END_REF][START_REF] Pongrácz | Do children understand man's best friend? Classification of dog barks by pre-adolescents and adults[END_REF] but can be to some extent improved by experience [START_REF] Linnankoski | Recognition of emotions in Macaque vocalizations by children and adults[END_REF][START_REF] Tallet | Human perception of the emotional state of domestic piglets through their vocalizations varies with the working experience with pigs[END_REF]. Our listeners had very limited experience with pigs and we hypothesized that in "naïve" humans, other psychological differences between individuals might influence their assessment of emotions in the piglet voices and/or their ability to discern the situation from the calls.

However, neither the emotional empathy nor the cognitive empathy nor the attitudes toward animals had any effect on the judgements. This was not due to the masking effect of the very negative castration calls as no effect was found in the dataset after the exclusion of the castration vocalisations. As this is the first study investigating this connection, the results need to be checked [START_REF] Dziobek | Dissociation of cognitive and emotional empathy in adults with asperger syndrome using the multifaceted empathy test (Met)[END_REF].

To summarize, we provide the evidence that human decoding of the emotional content of animal vocalisation may be based on very simple acoustic criteria. Also, recognition of the situation of the calling animal could be based on the perceived emotional intensity of the calls. Surprisingly, listeners' psychological profiles neither significantly affected the emotional intensity and valence decoding nor it affected accuracy of contexts recognition.

Acknowledgement

This study was supported by the grants P505/10/1411 from the Czech Grant Agency and 0002701404 from the Czech Ministry of Agriculture. Iveta Červenková helped with conducting reliability test of call identification. We would like to thank to three anonymous referees for their useful comments and suggestions.

Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V.

  human and animal affective vocalisations may have a similar basis. Using fMRI scans, Belin et al. (2008) detected significant common activation of ventro-lateralorbito-frontal cortex when people listened to affectively valenced vocalizations of cats, rhesus monkeys and human non-verbal vocalizations. Direct comparison of how people assess emotional content in conspecific and Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870

  Pearson's r = 0.93 for number of calls and 0.95 for sum of call durations. Mean fundamental frequency (F0; labelled as "pitch") for each call was detected by the PRAAT 'To Pitch' command with following settings: window length = 0.01 -0.05; voicing threshold = 0.15; silence threshold = 0.03; pitch range for F0 = 30 -6000Hz. Window length and pitch range for F0 were set up for each call separately based upon likely range of the pitch of the call determined by measuring the periods and calculating the multiplicative inverse to obtain the frequency (F=1/T). Final settings were adjusted for each particular call based on the comparison of detected pitch trace at the spectrogram. Finally, three parameters characterizing the tonal quality of calls were also measured: jitter, harmonic-tonoise ratio, and presence / absence of subharmonics. Jitter, which measures cycle-to-cycle variability in F0 across the call, was calculated by averaging three measurement values of jitter: local, relative average perturbation, and 5-point period perturbation quotients[START_REF] Charlton | Perception of male caller identity in koalas (Phascolarctos Cinereus): acoustic analysis and playback experiments[END_REF]. The Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870

  Five" personality factors (Neuroticism, Extraversion, Openness to Experience, Agreeableness, Conscientiousness). The concept of the Big Five is considered a universal personality structure across human cultures[START_REF] De Raad | Only three factors of personality description are fully replicable across languages: a comparison of 14 trait taxonomies[END_REF][START_REF] Mccrae | Personality trait structure as a human universal[END_REF]. The NEO-FFI is the shortened version (60 statements) of the larger NEO-PI-R inventory[START_REF] Mccrae | Personality trait structure as a human universal[END_REF]. Within the normal population, the five factor scores appear to be internally consistent, stable and valid. Administration and assessment was done on the HTS -Hogrefe Test System 4.0 system (Hogrefe -Testcentrum, s.r.o., Prague, Czech Republic),

(

  proportion vocalized, inter-call interval, call duration, mean pitch, mean jitter, harmonic-to-noise ratio, subharmonics) and 10 psychological variables (Neuroticism, Extraversion, Openness to Experience, Agreeableness, Conscientiousness, IRI total score, IRI empathetic concern score, IRI perspective taking score, AAS Attitude towards animals score and gender of the listener). The scatterplots did not indicate non-linear effects and therefore we did not include quadratic terms in the full model. The random factors of vocal stimulus identity and the listener identity were included in the model. Using the backward selection model on a randomly selected half of the dataset, we gradually reduced the model by removing the least significant predictor until all the remaining predictors were significant at the p < 0.05 level. Utilizing the hold-out method of cross-validation, the second half of the dataset was then used for assessment of the p values of predictors contained in the final model. Simple correlations between average intensity and valence ratings for each stimulus Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870

0. 0001 ,

 0001 Fig 3A) and with increasing proportion vocalized in the stimulus (F 1,266 = 11.46, p < 0.001, Fig 3B). Cohen's f 2 for the global effect of fixed variables in the final model was 0.11, indicating that the two acoustic variables together had a medium effect on perceived intensity. When castration recordings were omitted from the data set, the pitch ceased to be significantly related to judged Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 13 intensity (Fig 3A), but proportion vocalized was still positively affecting the perceived intensity (Fig 3B, F 1,176 = 3.90, p < 0.05). Nevertheless, the effect was small (f 2 =0.01). For valence judgements, the final model consisted of two predictor variables. The perceived valence decreased, i.e. changed to more negative with increasing pitch of the stimulus(F 1,240 = 41.23, p < 0.0001, Fig 3C) and with increasing duration of the calls (F 1,240 = 21.87, p < 0.0001, Fig 3D). The effect of the two acoustic variables on perceived valence was large (f 2 =0.37). The same predictor variables were significant and had medium effect (f 2 =0.17) also for the reduced data set from which the castration stimuli were omitted (pitch effect F 1,155 = 4.65, p < 0.05, Fig 3C; call duration effect F 1,155 = 35.38, p < 0.0001, Fig 3D).

  F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 28 Tables

FiguresFigure 1 .Figure 2 .Figure 3 .Figure 4 .

 1234 Figures

  investigations, perhaps using a more detailed, less verbally based empathy tests, such as the Multifaceted Empathy Test

Comment citer ce document : Marušáková, I. L., Linhart, P., Ratcliffe, V. F., Tallet, C., Reby, D., Špinka, M. (2015). Humans (Homo sapiens) judge the emotional content of piglet (Sus scrofa domestica) calls based on simple acoustic parameters, not personality, empathy, nor attitude toward animals. Journal of Comparative Psychology, 129 (2), 121-131. DOI : 10.1037/a0038870 21 with further

Table 1

 1 Simple correlations between emotional intensity, valence and acoustic variables

	variable		1	2	3	4	5	6	7	8	9
	1. intensity	-	-0.39*	0.32	0.24	-0.08	0.22	-0.06	0.07	-0.05
	2. valence	-0.86***	-	-0.32	-0.70*** -0.33*	-0.44**	0.22	-0.40*	-0.10
	3. vocprop 1	0.70*** -0.71***	-	0.56*** -0.34*	-0.14	0.00	-0.03	0.08
	4. duration	0.70*** -0.79*** 0.72***	-	0.30	0.16	-0.27	0.42*	0.21
	5. callint	2	-0.14	-0.04	-0.32*	0.16	-	0.25	-0.10	0.27	0.16
	6. pitch		0.81*** -0.87*** 0.58***	0.63*** -0.08	-	-0.08	0.64*** 0.15
	7. jitter		0.00	0.08	0.03	-0.03	-0.07	-0.03	-	-0.37*	0.11
	8. HNR 3		0.01	-0.16	-0.05	0.11	0.21	0.25	-0.41**	-	0.17