112 research outputs found

    Anticipatory adjustments to being picked up in infancy

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    Anticipation of the actions of others is often used as a measure of action understanding in infancy. In contrast to studies of action understanding which set infants up as observers of actions directed elsewhere, in the present study we explored anticipatory postural adjustments made by infants to one of the most common adult actions directed to them - picking them up. We observed infant behavioural changes and recorded their postural shifts on a pressure mat in three phases: (i) a prior Chat phase, (ii) from the onset of Approach of the mother's arms, and (iii) from the onset of Contact. In Study 1, eighteen 3-month-old infants showed systematic global postural changes during Approach and Contact, but not during Chat. There was an increase in specific adjustments of the arms (widening or raising) and legs (stiffening and extending or tucking up) during Approach and a decrease in thrashing/general movements during Contact. Shifts in postural stability were evident immediately after onset of Approach and more slowly after Contact, with no regular shifts during Chat. In Study 2 we followed ten infants at 2, 3 and 4 months of age. Anticipatory behavioural adjustments during Approach were present at all ages, but with greater differentiation from a prior Chat phase only at 3 and 4 months. Global postural shifts were also more phase differentiated in older infants. Moreover, there was significantly greater gaze to the mother's hands during Approach at 4 months. Early anticipatory adjustments to being picked up suggest that infants' awareness of actions directed to the self may occur earlier than of those directed elsewhere, and thus enable infants' active participation in joint actions from early in life

    Recurrence quantification analysis of processes and products of discourse: A tutorial in R

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    Processes of naturalistic reading and writing are based on complex linguistic input, stretch-out over time, and rely on an integrated performance of multiple perceptual, cognitive, and motor processes. Hence, naturalistic reading and writing performance is nonstationary and exhibits fluctuations and transitions. However, instead of being just complications for the analysis of such data, they are also informative about cognitive change, fluency, and reading or writing skill. To use and quantify such dynamics, one needs appropriate statistics that capture these aspects. In this article I introduce Recurrence Quantification Analysis (RQA) as a tool to capture such dynamic structure. After a conceptual introduction of the analysis, I present a step-by-step tutorial on how to run RQA using R. Guidance is given with regard to common issues and best practices using this time-series analysis technique. Finally, I review previous results from studies applying RQA to reading and writing and summarize current hypotheses and interpretations of RQA measures in the context of reading and writing

    What the eyes reveal about (reading) poetry

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    This study investigated how rhyme and meter affect eye movements and subjective aesthetic evaluations while reading poems. Earlier findings suggest that the effects might include prosodic predictability-driven cognitive and affective rewards from increased processing fluency (Blohm, Wagner, Schlesewsky and Menninghaus, 2018, McGlone and Tofighbakhsh, 2000), but also semantic and syntactic disfluency, as rhyme and meter are often implemented at the expense of unusual word forms and word order (Menninghaus et al., 2015, Wallot and Menninghaus, 2018). This study set out to investigate the extent to which eye movements might reveal not only distinct effects of fluency and disfluency at the same time, but potentially also hedonic responses that are associated with longer rather than shorter self-motivated exposure, in line with the hypothesis of “savoring” (Frijda and Sundararajan, 2007). The results reveal several fluency-enhancing effects of rhyme and meter on reading times for more global features of the poems, but also increased disfluency effects on gaze durations for some more local features of the poems. Moreover, some of the latter effects are readily interpretable in terms of the savoring hypothesis. Eye movement characteristics that were predictive of higher aesthetic evaluation—irrespective of the presence or absence of rhyme and meter—similarly resulted in increased fluency, disfluency, and savoring effects. Our study thus reveals, for the first time, a complex picture of effects that co-occur while reading poetic prosody, based on analyzing different dimensions of a single psychophysiological variable, namely, eye movements

    Modeling items for text comprehension assessment using confirmatory factor analysis

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    Using measures of reading time regularity (RTR) to quantify eye movement dynamics, and how they are shaped by linguistic information

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    In this article, we present the concept of reading time regularity (RTR) as a measure to capture reading process dynamics. The first study is concerned with examining one of the assumptions of RTR, namely, that process measures of reading, such as eye movement fluctuations and fixation durations, exhibit higher regularity when contingent on sequentially structured information, such as texts. To test this, eye movements of 26 German native speakers were recorded during reading-unrelated and reading-related tasks. To analyze the data, we used recurrence quantification analysis and sample entropy analysis to quantify the degree of temporal structure in time series of gaze steps and fixation durations. The results showed that eye movements become more regular in reading compared to nonreading conditions. These effects were most prominent when calculated on the basis of gaze step data. In a second study, eye movements of 27 native speakers of German were recorded for five conditions with increasing linguistic information. The results replicate the findings of the first study, verifying that these effects are not due to mere differences in task instructions between conditions. Implications for the concept of RTR and for future studies using these metrics in reading research are discussed

    Use of recurrence quantification analysis to examine associations between changes in text structure across an expressive writing intervention and reductions in distress symptoms in women wth breast cancer

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    The current study presents an exploratory analysis of using Recurrence Quantification Analysis (RQA) to analyze text data from an Expressive Writing Intervention (EWI) for Danish women treated for Breast Cancer. The analyses are based on the analysis of essays from a subsample with the average age 54.6 years (SD = 9.0), who completed questionnaires for cancer-related distress (IES) and depression symptoms (BDI-SF). The results show a significant association between an increase in recurrent patterns of text structure from first to last writing session and a decrease in cancer-related distress at 3 months post-intervention. Furthermore, the change in structure from first to last essay displayed a moderate, but significant correlation with change in cancer-related distress from baseline to 9 months post-intervention. The results suggest that changes in recurrence patterns of text structure might be an indicator of cognitive restructuring that leads to amelioration of cancer-specific distress

    Psychophysiology

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    Abstract Joint performance can lead to the synchronization of physiological processes among group members during a shared task. Recently, it has been shown that synchronization is indicative of subjective ratings of group processes and task performance. However, different methods have been used to quantify synchronization, and little is known about the effects of the choice of method and level of analysis (individuals, dyads, or triads) on the results. In this study, participants performed a decision-making task in groups of three while physiological signals (heart rate and electrodermal activity), positive affective behavior, and personality traits were measured. First, we investigated the effects of different levels of analysis of physiological synchrony on affective behavior. We computed synchrony measures as (a) individual contributions to group synchrony, (b) the average dyadic synchrony within a group, and (c) group-level synchrony. Second, we assessed the association between physiological synchrony and positive affective behavior. Third, we investigated the moderating effects of trait anxiety and social phobia on behavior. We discovered that the effects of physiological synchrony on positive affective behavior were particularly strong at the group level but nonsignificant at the individual and dyadic levels. Moreover, we found that heart rate and electrodermal synchronization showed opposite effects on group members' display of affective behavior. Finally, trait anxiety moderated the relationship between physiological synchrony and affective behavior, perhaps due to social uncertainty, while social phobia did not have a moderating effect. We discuss these results regarding the role of different physiological signals and task demands during joint action

    Four methods to distinguish between fractal dimensions in time series through recurrence quantification analysis

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    Fractal properties in time series of human behavior and physiology are quite ubiquitous, and several methods to capture such properties have been proposed in the past decades. Fractal properties are marked by similarities in statistical characteristics over time and space, and it has been suggested that such properties can be well-captured through recurrence quantification analysis. However, no methods to capture fractal fluctuations by means of recurrence-based methods have been developed yet. The present paper takes this suggestion as a point of departure to propose and test several approaches to quantifying fractal fluctuations in synthetic and empirical time-series data using recurrence-based analysis. We show that such measures can be extracted based on recurrence plots, and contrast the different approaches in terms of their accuracy and range of applicability

    Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis with crqa

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    Recurrence quantification analysis is a widely used method for characterizing patterns in time series. This article presents a comprehensive survey for conducting a wide range of recurrence based analyses to quantify the dynamical structure of single and multivariate time series and capture coupling properties underlying leader-follower relationships. The basics of recurrence quantification analysis (RQA) and all its variants are formally introduced step-by-step from the simplest auto recurrence to the most advanced multivariate case. Importantly, we show how such RQA methods can be deployed under a single computational framework in R using a substantially renewed version of our crqa 2.0 package. This package includes implementations of several recent advances in recurrence based analysis, among them applications to multivariate data and improved entropy calculations for categorical data. We show concrete applications of our package to example data, together with a detailed description of its functions and some guidelines on their usage

    Global temporal typing patterns in foreign language writing: Exploring language proficiency through recurrence quantification analysis (RQA)

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    Recurrence quantification analysis (RQA) is a time-series analysis method that uses autocorrelation properties of typing data to detect regularities within the writing process. The following paper first gives a detailed introduction to RQA and its application to time series data. We then apply RQA to keystroke logging data of first and foreign language writing to illustrate how outcome measures of RQA can be understood as skill-driven constraints on keyboard typing performance. Forty native German students performed two prompted writing assignments, one in German and one in English, a standardized copy task, and a standardized English placement test. We assumed more fluent and skilled writing to reveal more structured typing time series patterns. Accordingly, we expected writing in a well-mastered first language to coincide with higher values in relevant RQA measures as compared to writing in a foreign language. Results of mixed model ANOVAs confirmed our hypothesis. We further observed that RQA measures tend to be higher, thus indicating more structured data, whenever parameters of pause, burst, and revision analyses indicate more fluent writing. Multiple regression analyses revealed that, in addition to typing skills, language proficiency significantly predicts outcomes of RQA. Thus, the present data emphasize RQA being a valuable resource for studying time series data that yields meaningful information about the effort a writer must exert during text production
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