Effects of interoceptive accuracy on timing control in the synchronization tapping task

Humans often perform rhythmic synchronized movements. Professional musicians and dancers particularly perform such movement tasks well and have a higher interoceptive accuracy (IAcc) than non-musicians and non-dancers. We thus hypothesized that rhythmic synchronized movements might be enhanced by a higher IAcc. To investigate this hypothesis, this study conducted a heartbeat counting task and a rhythmic synchronization tapping task with normal (easier) and slow (harder) tempi metronomes. Inconsistent with our hypothesis, however, a higher IAcc was negatively correlated with timing control, but only in the slow tempo condition [r (30) = 0.46, p < 0.05]. This suggests that a higher IAcc did not enhance timing control in rhythmic synchronized movements but rather weakened it, resting heart rate variability was not correlated with timing control

Complex sequencing rules of birdsong can be explained by simple hidden Markov processes

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical propertiesof the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable sequences, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. This property is shared with other complex sequential behaviors. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model (GMM)), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex sequences with higher-order dependencies

Revisiting the Transtheoretical Model for Physical Activity: A Large-Scale Cross-Sectional Study on Japanese-Speaking Adults

Objective: The Transtheoretical Model (TTM) has been the basis of health promotion programs, which are, for example, used to tailor behavioral interventions according to the stages of change. Empirical studies have shown that the TTM effectively describes the processes of behavioral adaptation to acquire healthier lifestyles; however, it has been argued that TTM-based interventions are not superior to non-TTM-based interventions for promoting physical activity (PA). Evidence has also highlighted some inconsistencies with theoretical assumptions, especially regarding how each process-of-change strategy emerges across the stages. Therefore, we investigated (a) how well the TTM describes the distributional characteristics of PA levels as well as other relevant variables (e.g., process of change, self-efficacy) across stages, and (b) how predictive the TTM variables are of PA levels within each stage. Methods: We analyzed data from 20,581 Japanese-speaking adults who completed online questionnaires on PA and TTM variables. Results: The results replicated previous findings that stage membership is associated with PA, the process of change, decisional balance, and self-efficacy, albeit with inconclusive evidence of temptations. Regression analyses revealed that some processes of change (self-revaluation, reinforcement management, and self-liberation) were more predictive of PA in pre-action stages than in post-action stages; self-efficacy was predictive of PA only in the maintenance stage but not in the other stages. Conclusions: Overall, the data support the theoretical assumptions of the TTM, but the stage specificity of the active processes may not always be consistent with the theory

Data from: A simple explanation for the evolution of complex song syntax in Bengalese finches

The songs of Bengalese finches (Lonchura striata var. domestica) have complex syntax and provide an opportunity to investigate how complex sequential behavior emerges via the evolutionary process. In the present study, we suggest that a simple mechanism, i.e., many-to-one mapping from internal states onto syllables, may underlie the emergence of apparent complex syllable sequences that have higher-order history dependencies. We analyzed the songs of Bengalese finches and of their wild ancestor, the white-rumped munia (Lonchura striata), whose songs are more stereotypical and simpler compared to those of Bengalese finches. The many-to-one mapping mechanism sufficiently accounted for the differences in the complexity of song syllable sequences of these two strains

Evaluating the performance of personality-based profiling in predicting physical activity as an external outcome

Classifying individuals based on personality and other characteristics is a common statistical approach used in marketing, medicine, and social sciences. This approach has several advantages: it improves the simplicity of data, helps data-driven decision-making, and guides intervention strategies such as personalized care. On the other hand, continuous variables are often used to classify individuals, meaning that dimensional information is reduced to several discrete classes (of individuals) and thus much information is lost through this process. Although the loss of information may be practically or pragmatically acceptable, how much information is lost and what influence this decision has on predicting external outcomes has not been systematically investigated. Therefore, in this study, we examined the predictive performance of the classification approach compared with the dimensional approach by analyzing survey data obtained from approximately 20,000 individuals concerning physical activity and psychological traits, including the Big Five personality traits. First, we classified individuals based on the dimensional data of their psychological traits and obtained several different cluster solutions. Second, these clusters were used to predict the levels of physical activity (i.e., the classification approach), which were then compared with the predictions made by the raw dimensional scales of psychological traits (i.e., the dimensional approach). The results showed that the four-cluster solution, which was supported by the standard criterion for determining the number of clusters, achieved no more than 60% explanatory power of the dimensional approach. To achieve a comparable prediction accuracy, the number of clusters must be increased to at least 20. These findings imply that the cluster solution suggested by the conventional statistical criteria may not be optimal when clusters are used to predict external outcomes

Use Patterns of Smartphone Apps and Wearable Devices Supporting Physical Activity and Exercise: Large-Scale Cross-Sectional Survey

Abstract BackgroundPhysical inactivity is a global health issue, and mobile health (mHealth) apps are expected to play an important role in promoting physical activity. Empirical studies have demonstrated the efficacy and efficiency of app-based interventions, and an increasing number of apps with more functions and richer content have been released. Regardless of the success of mHealth apps, there are important evidence gaps in the literature; that is, it is largely unknown who uses what app functions and which functions are associated with physical activity. ObjectiveThis study aims to investigate the use patterns of apps and wearables supporting physical activity and exercise in a Japanese-speaking community sample. MethodsWe recruited 20,573 web-based panelists who completed questionnaires concerning demographics, regular physical activity levels, and use of apps and wearables supporting physical activity. Participants who indicated that they were using a physical activity app or wearable were presented with a list of app functions (eg, sensor information, goal setting, journaling, and reward), among which they selected any functions they used. ResultsApproximately one-quarter (n=4465) of the sample was identified as app users and showed similar demographic characteristics to samples documented in the literature; that is, compared with app nonusers, app users were younger (odds ratio [OR] 0.57, 95% CI 0.50-0.65), were more likely to be men (OR 0.83, 95% CI 0.77-0.90), had higher BMI scores (OR 1.02, 95% CI 1.01-1.03), had higher levels of education (university or above; OR 1.528, 95% CI 1.19-1.99), were more likely to have a child (OR 1.16, 95% CI 1.05-1.28) and job (OR 1.28, 95% CI 1.17-1.40), and had a higher household income (OR 1.40, 95% CI 1.21-1.62). Our results revealed unique associations between demographic variables and specific app functions. For example, sensor information, journaling, and GPS were more frequently used by men than women (ORs <0.84). Another important finding is that people used a median of 2 (IQR 1-4) different functions within an app, and the most common pattern was to use sensor information (ie, self-monitoring) and one other function such as goal setting or reminders. ConclusionsRegardless of the current trend in app development toward multifunctionality, our findings highlight the importance of app simplicity. A set of two functions (more precisely, self-monitoring and one other function) might be the minimum that can be accepted by most users. In addition, the identified individual differences will help developers and stakeholders pave the way for the personalization of app functions

<b>Asymmetric Error Correction in the Synchronization Tapping Task</b>

In synchronization tapping tasks, tapping onset often precedes metronome one by a few tens of milliseconds, which is known as negative mean asynchrony. However, the mechanism by which negative mean asynchrony occurs remains incompletely understood. This study hypothesized that one of the mechanisms was the asymmetric error correction process for asynchrony. We examined this hypothesis using a generalized linear mixed model. The results suggested that the error correction rate for the positive asynchrony was larger than that for the negative asynchrony. This finding may contribute to improving mathematical models of the synchronization tapping task.</p

Audio data of white-rumped munia songs

This file contains the sound (wav) files of the white-rumped munia songs we analyzed. Each directory labeled WMXX contains songs from one bird where XX indicates the bird ID

Audio data of Bengalese finch songs

This file contains the sound (wav) files of the Bengalese finch songs we analyzed. Each directory labeled BFXX contains songs from one bird where XX indicates the bird ID

Characterisation of an aptamer against the Runt domain of AML1 (RUNX1) by NMR and mutational analyses

Since the invention of systematic evolution of ligands by exponential enrichment, many short oligonucleotides (or aptamers) have been reported that can bind to a wide range of target molecules with high affinity and specificity. Previously, we reported an RNA aptamer that shows high affinity to the Runt domain (RD) of the AML1 protein, a transcription factor with roles in haematopoiesis and immune function. From kinetic and thermodynamic studies, it was suggested that the aptamer recognises a large surface area of the RD, using numerous weak interactions. In this study, we identified the secondary structure by nuclear magnetic resonance spectroscopy and performed a mutational study to reveal the residue critical for binding to the RD. It was suggested that the large contact area was formed by a DNA‐mimicking motif and a multibranched loop, which confers the high affinity and specificity of binding