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In this preregistration, we describe the study entitled "Identifying age from motion? – The impact of age and experience on age identification from movement stimuli " that is part of the German Research Foundation (DFG) project "Climbing to Yourself: A developmental embodied cognition perspective on the relation between the minimal self and sensorimotor and cognitive skills" (PIs: Markus Raab and Azzurra Ruggeri, SPP 2134 Ι RA 940/21-1 Ι RU 2272/1-1). It has been recently proposed that movements can be considered “kinematic fingerprints” (Coste et al., 2020, p. 1) and we are interested in whether age, being an important identifying factor, can be estimated from movement kinematics. If you think of the typical walk of a one-year-old and compare this to the walk of a school-aged child, it might indeed be possible that movements tell us something about the age of the person performing it. From a developmental embodied cognition perspective, we aim to better understand whether children, adolescents, and adults can identify age from movements and to which degree this depends on the age of the person presented in the movement stimulus as well as the participants’ own age and experience. In the present study, we will therefore present participants with kinematic recordings of human climbing movements presented as point-light display videos and test whether they can identify the age of the person climbing. The general theoretical starting point is an embodied cognition perspective which suggests that our minds and bodies, movements and thoughts are bi-directionally linked (e.g., Gentsch et al., 2015; Wilson, 2002) with the interaction changing throughout development (Musculus et al., 2021). Based on the general assumptions that cognition is for action and that off-line cognition is body-based (cf., Wilson, 2002), one can assume that the cognitive identification of how old someone is based on how they move, should be based on own motor experience. Different embodiment mechanisms have been proposed that help distinguishing own from other movements for example, ranging from common coding (e.g., Coste et al., 2020), to simulation (e.g., Hohmann et al., 2011), to internal models (e.g., Kennel et al., 2014). These have also been tested using complex movements such as basketball dribbling (Hohmann et al., 2011) or hurdling (Kennel et al., 2014). So, in general we assume an internal model mechanism according to which the age of a person moving (i.e., presented in a movement stimulus) should be identified by inferring discrepancies between how the person should move if he/she was the same age, i.e., predicted based on own bodily and motor experiences, in comparison to how the person is perceived to move. In a similar fashion, research has shown that people are better able to identify movements of people they have experienced more often (i.e., team members of a basketball team) as compared to the same movements of people (i.e., other basketball players) they have not experienced as often (Hohmann et al., 2011). This finding suggests that the experience with a specific movement also seems to play a role. However, whether and how age identification from movements is at all possible is still an open empirical question. To get an overview of the state of the art, we conducted a systematic literature search on „age from motion“ using the following keywords „age identification, age judgement, age recognition or age perception“ combined with „point light, dynamic, move or motion“ (see Appendix Figure 1 for PRISMA flowchart). This search resulted in 240 matching articles. After analyzing the titles, 56 articles remained. By reading the abstract of the remaining articles, 11 articles were deemed of interest. The full-text check of these articles showed that there is so far no published research regarding the question whether age identification from movement is possible given that not a single article addressed this question. What this literature search revealed is that there is published research on age identification from pictures presenting human faces. Regarding age identification, the studies discussed in the review form Rhodes et al. (2009) present evidence that people are able to identify age from face pictures accurately. The studies used different methods for age identification: In some the participants had to categorize pictures according to an age category (e.g., young, middle-age, older; in Anastasi & Rhodes, 2005), sort them from the youngest to oldest face presented or vice versa (Markey, 1934, Pittenger & Shaw, 1975), or discriminate between two pictures which of the faces presented was older or younger (George et al., 2000). Regarding the question when the ability to accurately identify age develops, research suggests that from about the age of 9 to 10 years and onwards, children are able to identify age in an adult-like fashion (Bell et al. 2000). This line of research indicates improvements in age identification from face pictures until late childhood. A similar developmental trajectory was portrayed in a line of research relevant to the research question at hand, in which the ability to identify biological motion was studied (see Federici et al., 2020). Starting in infancy, a recent meta-analysis (Simion et al., 2008) found that already two-day-old infants spontaneously prefer biological motion over non biological movement. Later, by the age of 3 months, infants are then able to discriminate between biological motion and their scrambled counterparts (Zhang et al., 2013). Depicting the development during childhood, the identification of biological motion improves between the ages 3 to 5 years (Pavlova et al. , 2001) and even further from age 7 to 10 years (Carter & Pelphrey , 2006). Only at the age of 14 years, adolescents seem to be as good as adults at identifying biological movement (Hadad et al. 2011). Therefore, the accurate identification of biological motion seems to undergo quite a portrayed developmental trajectory reaching adult-like levels only in adolescence. General (developmental) embodied cognition assumptions (e.g., Gentsch et al., 2015; Musculus et al., 2021; Wilson, 2002) and the integration of research on the ability of humans to identify age from human face pictures as well as on the developmental trajectories presented for the ability to identify age and biological motion accurately provide the theoretical foundation for the present study. Based thereon the present study will shed light onto the research question whether people of different age and experience are able to identify a person’s age from how they move. Therefore, the present study will uncover whether movements indeed approximate “kinematic fingerprint(s)” (Coste et al., 2020, p. 1), indeed revealing relevant identifying information such as age. In detail, we test the performance of children (6–12 year-olds), adolescents (14-16 year-olds), and adults (18-40 years old) in an age–identification task using human climbing movements, by examining to what degree such performance is dependent on a) the age of the person presented in the movement stimuli (cf., Rhodes et al., 2009), b) the participants’ age (Carter & Pelphrey , 2006; Hadad et al., 2011), and c) the participants’ experience (e.g., Hohmann et al., 2011) in climbing and with different age groups presented in the stimuli. To do so, we designed an online study, in which video stimuli of climbing kinematics presented as point-light displays and produced by the participants of previous studies will be shown to the participants. Children and adults will be asked how old the persons in the PLD stimuli are (see Figure 1 for procedure of the age identification task). Figure 1. Age identification from climbing-specific movement stimuli. Procedure and exemplary screenshots from point-light display videos.

Cognition plays a key role in sports performance. This meta-analytic review synthesizes research that examined the relationship between cognitive functions, skills, and sports performance. We identified literature by searching Cochrane Library, APA PsycINFO, PubMed, and Web of Science. We included studies conducted on competitive athletes, assessed cognitive prerequisites, and included performance measures related to the sport. Of the 9,433 screened records, 136 reports were included, containing 142 studies, 1,227 effect sizes, and 8,860 participants. Only 11 studies used a prospective study design. The risk of bias was assessed using the Risk of Bias Assessment Tool for Nonrandomized Studies. The multilevel meta-analysis showed a medium effect size for the overall difference in cognitive functions and skills, with higher skilled athletes scoring better than lower skilled athletes (Hedges’ g = 0.59, 95% CI [0.49, 0.69]). The moderator analysis showed larger effect size for tests of cognitive decision-making skills (g = 0.77, 95% CI [0.6, 0.94]) compared to basic (g = 0.39, 95% CI [0.21, 0.56]) and higher cognitive functions (g = 0.44, 95% CI [0.26, 0.62]), as well as larger effect for sport-specific task stimuli compared to general ones. We report that higher skilled athletes perform better on cognitive function tests than lower skilled athletes. There was insufficient evidence to determine whether cognitive functions and skills can predict future sport performance. We found no evidence to support claims that tests of general cognitive functions, such as executive functioning, should be used by practitioners for talent identification or player selection. Correspondence concerning this article should be addressed to Anton Kalén

part of the DFG SPP 1772 Human performance under multiple cognitive task requirements: From basic mechanisms to optimized task scheduling

In this pre-registration, we describe the study entitled “Identifying self from motion – The impact of the minimal self and age on self-other discrimination from movement stimuli” that is part of our DFG project "Climbing to Yourself: A developmental embodied cognition perspective on the relation between the minimal self and sensorimotor and cognitive skills" (PIs: Markus Raab and Azzurra Ruggeri, SPP 2134 Ι RA 940/21-1 Ι RU 2272/1-1). In the present study, we aim to better understand whether children and adults can identify themselves from their own movements and to which degree this depends on their minimal self. In detail, we will present participants with kinematic recordings of their own and other people’s climbing movements presented in point-light display videos and test whether they can discriminate themselves from others. In addition, we examine whether the participants’ minimal-self representation, which is defined as the phenomenological experience in the here and now, “accessible to immediate self-consciousness” (Gallagher, 2000, p. 15) as well as their age will affect their self-other discrimination performance. Our general theoretical starting point to tackle this goal is an embodied cognition perspective assuming a bidirectional link between cognition and action (e.g., Gentsch et al., 2015), which has been also specified from a developmental perspective (Musculus et al., 2021). In general, human movements are like “kinematic fingerprint(s)” (Coste et al., 2020, p. 1), clearly distinguishing ourselves from others. For self-other discrimination from movements in particular, evidence suggests that especially motor experience benefits discrimination performance (e.g., Hohmann et al., 2011; Kennel et al., 2014). Therefore, our movements and motor experience are crucial for developing distinct self-representations and should matter for self-other discrimination. To explain self-other discrimination, competing mechanisms have been proposed, from common coding (e.g., Coste et al., 2020), to simulation (e.g., Hohmann et al., 2011), to internal models (e.g., Kennel et al., 2014). Nevertheless, it is still unclear how exactly the human brain is able to do this computationally and when this ability emerges (e.g., Liu et al., 2019). With the present study, we aim to make a theoretical contribution by further scrutinizing the underlying mechanism and testing potential influencing factors. First, to shed light on how participants make the self-other discrimination, we will ask them about their strategy. Based on previous research using sport-movement stimuli (i.e., hurdling, Kennel et al., 2014), we expect that the (other) agent depicted in a movement stimulus will be identified by noting discrepancies between the predicted movement based on self-experience and the actual perceived movement of the other (cf. internal model; Kennel et al., 2014), opting for an internal-model mechanism. Given the relevance of a clear bodily and movement representation to identify own movements, a person’s so-called minimal self (Gallagher, 2000) might impact how well one is able to distinguish oneself from someone else. The minimal self is the phenomenal experience in the here and now, rooted in bodily, motor experiences, perceptions, and representations (Fotopoulou & Tsakiris, 2017; Gallagher, 2000). Further, the minimal self comprises a body ownership and agency component, which refer to the representation of whether body parts belong to oneself (or not) and whether an action such as a movement was conducted by oneself (or not; Georgie et al., 2019). In this study, we consider the minimal self as a potential influencing factor in self-other discrimination from movements. In addition, given the developmental embodied cognition perspective of our project and the lack of evidence on when the ability to identify oneself from movements emerges, we will also explore the effects of the participants’ age on self-other discrimination performance. We will enroll children and adults to test whether age-effects in self-other discrimination from movements emerge. Taken together, in the present study, we examine whether the self-other discrimination performance of children (6–12 years old) and adults (18-40 years old) from climbing movements is dependent on the participants’ minimal-self accuracy and/or age. To do so, we designed an online study, in which movement stimuli of climbing kinematics, that were previously captured in an ongoing climbing training study (see pre-registration on OSF), were presented as point-light display videos to the participants. The movement stimuli either showed the participant him/herself (self-trials) or someone else (other-trials). The children and adults participating will be asked to decide whether the movement stimuli presented showed themselves or someone else (see Figure 1 for procedure of the self-other discrimination task). Figure 1. Self-other discrimination from climbing-specific movement stimuli. Exemplary screenshots from point-light display videos.

The project investigates how time as a source of information supports multitasking. The experiments proposed here will systematically investigate the mechanism underlying the effect from time-based predictability in one task on performance in a concurrent task. Hypotheses are derived from converging theorizing about predictability by multiple projects in the priority program SPP 1772. A first set of experiments will investigate how performance in both tasks is related to each other, and which interval durations primarily drive the effect. A second set of experiments is devoted to the domain specificity of the effects. Does time-based predictability in one task support timing related second tasks in particular? A last set of experiments will be deal with the cognitive representations of time processed in the adaptation effect. Does it involve relative representations, such as adaptation to task prediction? Or does it employ absolute representation, as typical for some related movement timing tasks?

This chapter provides the reader with a summary of the most important results or take-home messages one should remember after reading this book. For each of the 10 previous chapters, a rule is provided that summarizes the general heuristic attached to decisions in many areas under conditions of limited time and knowledge. The 10 rules are as follows: (1) Choices are embodied choices. (2) Choices are governed by a less-is-more strategy. (3) Choices are grounded in your movements. (4) Actions enable perception and cognition. (5) Decisions are influenced by your long-term movement history. (6) Choices in the real environment can change the impact of the body. (7) Embodied choices are individualized and culture dependent. (8) First-time choices can be embodied. (9) Embodied choices are tuned by evolution. (10) Embodied choices can be trained.

This chapter answers the question of how to cope with uncertainty. The COVID-19 pandemic is used to illustrate how uncertain and dynamic information influences choices of individuals, groups, or societies. Providing examples of reliable sources of information and rate decisions of governments as a reaction of growing infection rates allows the reader to make informed decisions under uncertainty. A major tenet of this chapter is that we need to understand risk, fight against base rate neglect, and train risk literacy to be prepared for unpreceded situations. A personal choice in such situations is easy to be evaluated in hindsight but to predict consequences of such choices using the most valid information and dynamic context a person finds itself in is needed to prepare for uncertainty.

Interoception is an often neglected but crucial aspect of the human minimal self. In this perspective, we extend the embodiment account of interoceptive inference to explain the development of the minimal self in humans. To do so, we first provide a comparative overview of the central accounts addressing the link between interoception and the minimal self. Grounding our arguments on the embodiment framework, we propose a bidirectional relationship between motor and interoceptive states, which jointly contribute to the development of the minimal self. We present empirical findings on interoception in development and discuss the role of interoception in the development of the minimal self. Moreover, we make theoretical predictions that can be tested in future experiments. Our goal is to provide a comprehensive view on the mechanisms underlying the minimal self by explaining the role of interoception in the development of the minimal self., Zweitveröffentlichungen der Universität Potsdam : Humanwissenschaftliche Reihe; 755

Auditory and visual percepts are integrated even when they are not perfectly temporally aligned with each other, especially when the visual signal precedes the auditory signal. This window of temporal integration for asynchronous audiovisual stimuli is relatively well examined in the case of speech, while other natural action-induced sounds have been widely neglected. Here, we studied the detection of audiovisual asynchrony in three different whole-body actions with natural action-induced sounds–hurdling, tap dancing and drumming. In Study 1, we examined whether audiovisual asynchrony detection, assessed by a simultaneity judgment task, differs as a function of sound production intentionality. Based on previous findings, we expected that auditory and visual signals should be integrated over a wider temporal window for actions creating sounds intentionally (tap dancing), compared to actions creating sounds incidentally (hurdling). While percentages of perceived synchrony differed in the expected way, we identified two further factors, namely high event density and low rhythmicity, to induce higher synchrony ratings as well. Therefore, we systematically varied event density and rhythmicity in Study 2, this time using drumming stimuli to exert full control over these variables, and the same simultaneity judgment tasks. Results suggest that high event density leads to a bias to integrate rather than segregate auditory and visual signals, even at relatively large asynchronies. Rhythmicity had a similar, albeit weaker effect, when event density was low. Our findings demonstrate that shorter asynchronies and visual-first asynchronies lead to higher synchrony ratings of whole-body action, pointing to clear parallels with audiovisual integration in speech perception. Overconfidence in the naturally expected, that is, synchrony of sound and sight, was stronger for intentional (vs. incidental) sound production and for movements with high (vs. low) rhythmicity, presumably because both encourage predictive processes. In contrast, high event density appears to increase synchronicity judgments simply because it makes the detection of audiovisual asynchrony more difficult. More studies using real-life audiovisual stimuli with varying event densities and rhythmicities are needed to fully uncover the general mechanisms of audiovisual integration., Finanziert durch den Open-Access-Publikationsfonds der Westfälischen Wilhelms-Universität Münster (WWU Münster).