How emotions are metaphorically embodied: measuring hand and head action strengths of typical emotional states.

This study measured hand and head action strengths of eight typical emotional states using an authentic but implicit emotion elicitation task. Participants listened to and then retold five stories in which eight typical emotional states were experienced by the narrators. The number of hand and head gestures that occur naturally while experiencing an emotional state was used as an index to determine the hand and head action strength of that emotional state. Results showed a larger number of head gestures than hand gestures, suggesting that head action strengths of the eight emotional states are stronger than their hand action strengths. These findings are consistent with the data extracted from Lancaster Sensorimotor Norms (LSN), although the two sets of data were gathered in two completely different experimental conditions and in two different languages. Furthermore, our data showed a prototypical directionality effect for the typical emotional states, specifically, happiness, anger and pride were primarily accompanied by upward gestures but downward gestures for sadness and shame; surprise was primarily accompanied by forward gestures but backward gestures for fear and disgust.

Investigating salience strategies to counteract obesity.

The investigation of the characteristics and attributes that make a brand prominent for shoppers is known as salience research. This line of study concentrates on influencing buying behaviors via the manipulation of shopping environments and food products. Such promotional strategies successfully attract massive food sales and therefore have been associated with changes in dietary patterns and the epidemic expansion of non-communicable diseases, like obesity. Marketers have empirically proven that global buying patterns are influenced by their salience strategies and techniques. However, despite the significance of such methods, empirical salience investigations have rarely been extended beyond their primary business focus to the field of health promotion. Therefore, this study is presenting a way of transferring the salience knowledge to the health promotion field in order to track dietary choices and possibly gain information to identify buying and eating behaviors connected to obesity. The salience literature from various disciplines permits to hypothesize that consumers are more likely to have unhealthy diets when food-choices and conditions are saliently manipulated. A quasi-experimental method (combining salience measures with Bayesian analysis) was used to test this proposition. The results support the hypothesis and endorse the introduced research tool. As predicted, data reflect the latest national overweight and obesity statistics and suggest that habitual unhealthy diets are more likely when salience strategies link food products to taste, social and emotional attributes. These preliminary findings encourage further investigation to enhance the method as a possible epidemiological tool.

Permutation tests are robust and powerful at 0.5% and 5% significance levels.

Recent replication crisis has led to a number of ad hoc suggestions to decrease the chance of making false positive findings. Among them, Johnson (Proceedings of the National Academy of Sciences, 110, 19313-19317, 2013) and Benjamin et al. (Nature Human Behaviour, 2, 6-10 2018) recommend using the significance level of α = 0.005 (0.5%) as opposed to the conventional 0.05 (5%) level. Even though their suggestion is easy to implement, it is unclear whether or not the commonly used statistical tests are robust and/or powerful at such a small significance level. Therefore, the main aim of our study is to investigate the robustness and power curve behaviors of independent (unpaired) two-sample tests for metric and ordinal data at nominal significance levels of α = 0.005 and α = 0.05. Through an extensive simulation study, it is found that the permutation versions of the Welch t-test and the Brunner-Munzel test are particularly robust and powerful while the commonly used two-sample tests which utilize t-distribution tend to be either liberal or conservative, and have peculiar power curve behaviors under skewed distributions with variance heterogeneity.

Nonparametric multiple comparisons.

Nonparametric multiple comparisons are a powerful statistical inference tool in psychological studies. In this paper, we review a rank-based nonparametric multiple contrast test procedure (MCTP) and propose an improvement by allowing the procedure to accommodate various effect sizes. In the review, we describe relative effects and show how utilizing the unweighted reference distribution in defining the relative effects in multiple samples may avoid the nontransitive paradoxes. Next, to improve the procedure, we allow the relative effects to be transformed by using the multivariate delta method and suggest a log odds-type transformation, which leads to effect sizes similar to Cohen's d for easier interpretation. Then, we provide theoretical justifications for an asymptotic strong control of the family-wise error rate (FWER) of the proposed method. Finally, we illustrate its use with a simulation study and an example from a neuropsychological study. The proposed method is implemented in the 'nparcomp' R package via the 'mctp' function.

The allocation of valenced concepts onto 3D space.

The valence-space metaphor research area investigates the metaphorical mapping of valenced concepts onto space. Research findings from this area indicate that positive, neutral, and negative concepts are associated with upward, midward, and downward locations, respectively, in the vertical plane. The same research area has also indicated that such concepts seem to have no preferential location on the horizontal plane. The approach-avoidance effect consists in decreasing the distance between positive stimuli and the body (i.e. approach) and increasing the distance between negative stimuli and the body (i.e. avoid). Thus, the valence-space metaphor accounts for the mapping of valenced concepts onto the vertical and horizontal planes, and the approach-avoidance effect accounts for the mapping of valenced concepts onto the "depth" plane. By using a cube conceived for the study of allocation of valenced concepts onto 3D space, we show in three studies that positive concepts are placed in upward locations and near the participants' body, negative concepts are placed in downward locations and far from the participants' body, and neutral concepts are placed in between these concepts in both planes.

Placing joy, surprise and sadness in space: a cross-linguistic study.

The valence-space metaphor posits that emotion concepts map onto vertical space such that positive concepts are in upper locations and negative in lower locations. Whilst previous studies have demonstrated this pattern for positive and negative emotions e.g. 'joy' and 'sadness', the spatial location of neutral emotions, e.g. 'surprise', has not been investigated, and little is known about the effect of linguistic background. In this study, we first characterised the emotions joy, surprise and sadness via ratings of their concreteness, imageability, context availability and valence before examining the allocation of these emotions in vertical space. Participants from six linguistic groups completed either a rating task used to characterise the emotions or a word allocation task to implicitly assess where these emotions are positioned in vertical space. Our findings suggest that, across languages, gender, handedness, and ages, positive emotions are located in upper spatial locations and negative emotions in lower spatial locations. In addition, we found that the neutral emotional valence of surprise is reflected in this emotion being mapped mid-way between upper and lower locations onto the vertical plane. This novel finding indicates that the location of a concept on the vertical plane mimics the concept's degree of emotional valence.

Drawing sounds: representing tones and chords spatially.

Research on the crossmodal correspondences has revealed that seemingly unrelated perceptual information can be matched across the senses in a manner that is consistent across individuals. An interesting extension of this line of research is to study how sensory information biases action. In the present study, we investigated whether different sounds (i.e. tones and piano chords) would bias participants' hand movements in a free movement task. Right-handed participants were instructed to move a computer mouse in order to represent three tones and two chords. They also had to rate each sound in terms of three visual analogue scales (slow-fast, unpleasant-pleasant, and weak-strong). The results demonstrate that tones and chords influence hand movements, with higher-(lower-)pitched sounds giving rise to a significant bias towards upper (lower) locations in space. These results are discussed in terms of the literature on forward models, embodied cognition, crossmodal correspondences, and mental imagery. Potential applications sports and rehabilitation are discussed briefly.

Modeling neural activity with cumulative damage distributions.

Neurons transmit information as action potentials or spikes. Due to the inherent randomness of the inter-spike intervals (ISIs), probabilistic models are often used for their description. Cumulative damage (CD) distributions are a family of probabilistic models that has been widely considered for describing time-related cumulative processes. This family allows us to consider certain deterministic principles for modeling ISIs from a probabilistic viewpoint and to link its parameters to values with biological interpretation. The CD family includes the Birnbaum-Saunders and inverse Gaussian distributions, which possess distinctive properties and theoretical arguments useful for ISI description. We expand the use of CD distributions to the modeling of neural spiking behavior, mainly by testing the suitability of the Birnbaum-Saunders distribution, which has not been studied in the setting of neural activity. We validate this expansion with original experimental and simulated electrophysiological data.

Crossmodal integration between visual linguistic information and flavour perception.

Many studies have found processing interference in working memory when complex information that enters the cognitive system from different modalities has to be integrated to understand the environment and promote adjustment. Here, we report on a Stroop study that provides evidence concerned with the crossmodal processing of flavour perception and visual language. We found a facilitation effect in the congruency condition. Acceleration was observed for incomplete words and anagrams compared to complete words. A crossmodal completion account is presented for such findings. It is concluded that the crossmodal integration between flavour and visual language perception requires the active participation of top-down and bottom-up processing.

The activation of representative emotional verbal contexts interacts with vertical spatial axis.

Several experimental studies have shown that there exists an association between emotion words and the vertical spatial axis. However, the specific conditions under which this conceptual-physical interaction emerges are still unknown, and no study has been devised to test whether longer linguistic units than words can lead to a mapping of emotions on vertical space. In Experiment 1, Spanish and Colombian participants performed a representative verbal emotional contexts production task (RVEC task) requiring participants to produce RVEC for the emotions of joy, sadness, surprise, anger, fear, and disgust. The results showed gender and cultural differences regarding the average number of RVEC produced. The most representative contexts of joy and sadness obtained in Experiment 1 were used in Experiment 2 in a novel spatial-emotional congruency verification task (SECV task). After reading a sentence, the participants had to judge whether a probe word, displayed in either a high or low position on the screen, was congruent or incongruent with the previous sentence. The question was whether the emotion induced by the sentence could modulate the responses to the probes as a function of their position in a vertical axis by means of a metaphorical conceptual-spatial association. Overall, the results indicate that a mapping of emotions on vertical space can occur for linguistic units larger than words, but only when the task demands an explicit affective evaluation of the target.

The different effects of a sensorimotor grounding on AoA between bilingual concepts.

Introduction: Psycholinguistic studies have argued for the age of acquisition (AoA) of words as a marker of concept learning, showing that the semantic features of concepts themselves influence the age at which their labels are learned. However, empirical evidence suggests that semantic features such as imageability and linguistic phenomena such as frequency do not adequately predict AoA. The present study takes the developmental approach of embodied cognition and investigates the effects of sensorimotor experiences on the ease of acquisition of the concept acquired in bilinguals. Specifically, we investigated (1) whether the sensorimotor experience can explain AoA beyond frequency; (2) and whether these patterns are consistent across L1 Chinese and L2 English. Methods: We conducted sensorimotor rating measures in both Chinese and English on 207 items in which Chinese-English bilingual adults were requested to evaluate the extent to which they experienced concepts by employing six perceptual senses and five effectors for actions located in various regions of the body. Meanwhile, data on AoA and frequency were collected. Results: The present study showed the sensorimotor experience was closely linked with AoAs in both languages. However, the correlation analysis revealed a trend of higher correlations between AoAs for the same concepts and L1 Chinese, relative to L2 English for the present Chinese-English bilinguals. Importantly, the hierarchical regression analysis demonstrated that after controlling for frequency, sensorimotor experience explained additional variance in L1 AoA. However, L2 sensorimotor experience did not explain the variance in L2 AoA. Sensorimotor experience explained more share of variance in L1 AoA but frequency accounted for more variance in L2 AoA. Discussion: The findings suggest that concept acquisition should consider the grounding in appropriate sensorimotor experience beyond linguistic phenomena like frequency.

EDA-Graph: Graph Signal Processing of Electrodermal Activity for Emotional States Detection.

The continuous detection of emotional states has many applications in mental health, marketing, human-computer interaction, and assistive robotics. Electrodermal activity (EDA), a signal modulated by sympathetic nervous system activity, provides continuous insight into emotional states. However, EDA possesses intricate nonstationary and nonlinear characteristics, making the extraction of emotion-relevant information challenging. We propose a novel graph signal processing (GSP) approach to model EDA signals as graphical networks, termed EDA-graph. The GSP leverages graph theory concepts to capture complex relationships in time-series data. To test the usefulness of EDA-graphs to detect emotions, we processed EDA recordings from the CASE emotion dataset using GSP by quantizing and linking values based on the Euclidean distance between the nearest neighbors. From these EDA-graphs, we computed the features of graph analysis, including total load centrality (TLC), total harmonic centrality (THC), number of cliques (GNC), diameter, and graph radius, and compared those features with features obtained using traditional EDA processing techniques. EDA-graph features encompassing TLC, THC, GNC, diameter, and radius demonstrated significant differences (p<0.05) between five emotional states (Neutral, Amused, Bored, Relaxed, and Scared). Using machine learning models for classifying emotional states evaluated using leave-one-subject-out cross-validation, we achieved a five-class F1 score of up to 0.68.

Visual search and childhood vision impairment: A GAMLSS-oriented multiverse analysis approach.

The aim of this report was to analyze reaction times and accuracy in children with a vision impairment performing a feature-based visual search task using a multiverse statistical approach. The search task consisted of set sizes 4, 16, and 24, consisting of distractors (circle) and a target (ellipse) that were presented randomly to school-aged individuals with or without a vision impairment. Interactions and main effects of key variables relating to reaction times and accuracy were analyzed via a novel statistical method blending GAMLSS (generalized additive models for location, scale, and shape) and distributional regression trees. Reaction times for the target-present and target-absent conditions were significantly slower in the vision impairment group with increasing set sizes (p < .001). Female participants were significantly slower than were males for set sizes 16 and 24 in the target-absent condition (p < .001), with male participants being significantly slower than females in the target-present condition (p < .001). Accuracy was only significantly worse (p = .03) for participants less than 14 years of age for the target-absent condition with set sizes 16 and 24. There was a positive association between binocular visual acuity and search time (p < .001). The application of GAMLSS with distributional regression trees to the analysis of visual search data may provide further insights into underlying factors affecting search performance in case-control studies where psychological or physical differences may influence visual search outcomes.

The role of perceptual and action effector strength of graphs and bases of mathematical metaphors in the metaphorical processing of mathematical concepts.

Metaphors that describe an abstract concept in terms of a motion concept are widely used to enhance our understanding of abstract concepts. These metaphors are used not only in our daily language but also in learning mathematics. As an example, in the process of understanding the abstract representation of a mathematical concept, a graphical representation may play the role of a mediatory domain. This graphical representation could have a high degree of perceptual and action effector strength. This is particularly the case when a gestures (as a motion) is used to depict the graphical representation. After looking at this example, we discuss perceptual and action effector strength of the base domains of several mathematical metaphors that describe mathematical concepts in terms of spatial and motion concepts. Then, based on the data in the Lancaster Sensorimotor Norms, it is suggested that high degrees of perceptual and action effector strength of the base domains of these metaphors play an important role in the grounding of abstract mathematical concepts in the physical environment.

Group comparisons of the individual electroretinogram time trajectories for the ascending limb of the b-wave using a raw and registered time series.

OBJECTIVES: The electroretinogram is a clinical test commonly used in the diagnosis of retinal disorders with the peak time and amplitude of the a- and b-waves used as the main indicators of retinal function. However, subtle changes that affect the shape of the electroretinogram waveform may occur in the early stages of disease or in conditions that have a neurodevelopmental or neurodegenerative origin. In such cases, we introduce a statistical approach to mathematically model the shape of the electroretinogram waveform that may aid clinicians and researchers using the electroretinogram or other biological signal recordings to identify morphological features in the waveforms that may not be captured by the time or time-frequency domains of the waveforms. We present a statistical graphics-based analysis of the ascending limb of the b-wave (AL-b) of the electroretinogram in children with and without a diagnosis of autism spectrum disorder (ASD) with a narrative explanation of the statistical approach to illustrate how different features of the waveform based on location and scale derived from raw and registered time series can reveal subtle differences between the groups. RESULTS: Analysis of the raw time trajectories confirmed findings of previous studies with a reduced and delayed b-wave amplitude in ASD. However, when the individual time trajectories were registered then group differences were visible in the mean amplitude at registered time ~ 0.6 suggesting a novel method to differentiate groups using registration of the ERG waveform.

Distributed embodiment of metaphorical hope in hand, head, and eyebrow gestures.

This study aimed to examine the embodied conceptualization of hope through metaphors. We asked a group of participants to discuss their hopes in a semi-structured interview. We examined the types of hand, head, and eyebrow gestures produced when they were talking about their future hopes. The obtained results showed that when participants talked about their future hopes, they mainly used forward hand gestures, rightward head gestures, and upward eyebrow gestures. Based on these results, it is suggested that various semantic components and emotional associations of hope are metaphorically embodied in different manners in various parts of the body. The future aspect of hope is conceptualized as a forward movement and is embodied as a forward hand gesture. The good or positive emotional aspect associated with future hopes is metaphorically conceptualized as a rightward head gesture or an upward eyebrow gesture. We call this process distributed embodiment of a metaphorical concept. Our proposal is supported by the findings of past studies that have found future is metaphorically embodied as something in front of us (or forward movement), and good is metaphorically embodied as upper space (or upward movement) or right side (or rightward movement).

A multi-analyses approach of inductive/deductive asymmetry in the affective priming paradigm.

Rapidly evaluating our environment's beneficial and detrimental features is critical for our successful functioning. A classic paradigm used to investigate such fast and automatic evaluations is the affective priming (AP) paradigm, where participants classify valenced target stimuli (e.g., words) as good or bad while ignoring the valenced primes (e.g., words). We investigate the differential impact that verbs and adjectives used as primes and targets have on the AP paradigm. Based on earlier work on the Linguistic Category Model, we expect AP effect to be modulated by non-evaluative properties of the word stimuli, such as the linguistic category (e.g., if the prime is an adjective and the target is a verb versus the reverse). A reduction in the magnitude of the priming effect was predicted for adjective-verb prime-target pairs compared to verb-adjective prime-target pairs. Moreover, we implemented a modified crowdsourcing of statistical analyses implementing independently three different statistical approaches. Deriving our conclusions on the converging/diverging evidence provided by the different approaches, we show a clear deductive/inductive asymmetry in AP paradigm (exp. 1), that this asymmetry does not require a focus on the evaluative dimension to emerge (exp. 2) and that the semantic-based asymmetry weakly extends to valence (exp. 3).

The Roles of Gestural and Symbolic Schematizations in Inhibition as a Component of Executive Functions.

The role of gestural schematization in enhancing thinking processes has been the subject of a large body of works. In this process, contextually unimportant or irrelevant information related to a concept (or a system of concepts) is deleted or ignored, while relevant spatial information is maintained. This process is a special type of inhibition, which is one of the key components of executive functions. In this short paper, it is suggested that gestural schematization is a special type of symbolic schematization, a much more general process through which irrelevant information related to features of a concept (or a system of concepts) is suppressed, while relevant information (spatial and non-spatial) is maintained. Through symbolic schematization, abstract structural similarity between two concepts or between two systems of concepts can be discovered. In this way, an individual's knowledge about the first situation can be generalized to the second situation. Symbolic schematization is the basis of abstraction, knowledge generalization, and knowledge development. This is particularly the case with abstract mathematical thinking. This proposal offers a picture of cognitive mechanisms through which knowledge of abstract mathematical concepts is created and developed in the mind.

Generalised exponential-Gaussian distribution: a method for neural reaction time analysis.

Reaction times (RTs) are an essential metric used for understanding the link between brain and behaviour. As research is reaffirming the tight coupling between neuronal and behavioural RTs, thorough statistical modelling of RT data is thus essential to enrich current theories and motivate novel findings. A statistical distribution is proposed herein that is able to model the complete RT's distribution, including location, scale and shape: the generalised-exponential-Gaussian (GEG) distribution. The GEG distribution enables shifting the attention from traditional means and standard deviations to the entire RT distribution. The mathematical properties of the GEG distribution are presented and investigated via simulations. Additionally, the GEG distribution is featured via four real-life data sets. Finally, we discuss how the proposed distribution can be used for regression analyses via generalised additive models for location, scale and shape (GAMLSS).

Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics.

The advent of technological developments is allowing to gather large amounts of data in several research fields. Learning analytics (LA)/educational data mining has access to big observational unstructured data captured from educational settings and relies mostly on unsupervised machine learning (ML) algorithms to make sense of such type of data. Generalized additive models for location, scale, and shape (GAMLSS) are a supervised statistical learning framework that allows modeling all the parameters of the distribution of the response variable with respect to the explanatory variables. This article overviews the power and flexibility of GAMLSS in relation to some ML techniques. Also, GAMLSS' capability to be tailored toward causality via causal regularization is briefly commented. This overview is illustrated via a data set from the field of LA. This article is categorized under:Application Areas > Education and LearningAlgorithmic Development > StatisticsTechnologies > Machine Learning.