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We formulated potential influence from spatiotemporal (dis)continuity by two opposite forces - integration vs. In this study, we manipulated the continuity state (continuous/discontinuous) (Experiment 1) and its predictability (Experiment 2) of whole-body movement sequences and tested participants' working memory for observed movements with a single-probe recognition task. Specifically, spatiotemporal continuity of movements may facilitate integrative processing (“integration”) and enhance memory performance by optimizing the encoding process, but it may also diminish memory benefits from distinctive processing (“separation”).
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However, how the spatiotemporal continuity influences working memory for movements is still unclear. Human movements are dynamic and continuous in nature. The findings may be relevant for expanding the understanding pertaining to auditory perception anomalies underlying affective states and disorders. Altogether, the results suggest that individual trait-anxiety levels moderate the detection of emotions from speech-in-noise, especially those conveying negative/threatening affect. Further, a similar effect was evident when averaging across all emotions. Specifically, Disgust and Fear detection sensitivities worsened with increasing severities of trait-anxiety. We calculated the empirical area under the curve (measure of acoustic signal detection sensitivity) based on signal detection theory to quantify our results.
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In a task, participants (n = 24) accurately discriminated the target emotion conveyed by the temporally unpredictable acoustic signals (signal to noise ratio = 10dB), which were manipulated at four levels (Happy, Neutral, Fear and Disgust). In a supervised, internet-based experiment carried out sans the artificially controlled laboratory environment, we asked if the detection sensitivity of emotions conveyed by human speech-in-noise (acoustic signals) is modulated by individual differences in internal affective states, e.g., anxiety. While sensory perception is known to be influenced by bodily internal states such as anxiety and ambient noise, their relationship to human auditory perception is relatively less understood. Exploratory machine learning analyses suggest that people who represented others more similarly to themselves were more willing to invest effort on their behalf, opening up new avenues for future research.Īuditory perception of emotions in speech is relevant for humans to optimally navigate the social environment. Computational modeling suggests that, unlike prior physical effort findings, cognitive effort discounted the subjective value of rewards linearly. In Study 2, participants (N = 47 225 choices) were more willing to work cognitively for a charity than an intragroup stranger, but again preferred cognitive exertion that benefited themselves. In Study 1, participants (N = 51 150 choices) were less willing to invest cognitive effort for a charity than themselves. In two studies, participants repeatedly decided whether to invest cognitive effort to gain financial rewards for themselves and others. Here, we find that people avoid cognitive effort for others relative to themselves, even when the cause is a personally meaningful charity. How do people decide who is worth their effort? Prior work shows people avoid physical effort for strangers relative to themselves, but invest more physical effort for charity. Yet, people sometimes work hard for others. Effort is aversive and often avoided, even when earning benefits for oneself.