A sense of agency (SoA) is the experience of subjective awareness regarding the control of one’s actions. Humans have a natural tendency to generate prediction models of the environment and adapt their models according to changes in the environment. The SoA is associated with the degree of the adaptation of the prediction models, e.g., insufficient adaptation causes low predictability and lowers the SoA over the environment. Thus, identifying the mechanisms behind the adaptation process of a prediction model related to the (...) SoA is essential for understanding the generative process of the SoA. In the first half of the current study, we constructed a mathematical model in which the SoA represents a likelihood value for a given observation (sensory feedback) in a prediction model of the environment and in which the prediction model is updated according to the likelihood value. From our mathematical model, we theoretically derived a testable hypothesis that the prediction model is updated according to a Bayesian rule or a stochastic gradient. In the second half of our study, we focused on the experimental examination of this hypothesis. In our experiment, human subjects were repeatedly asked to observe a moving square on a computer screen and press a button after a beep sound. The button press resulted in an abrupt jump of the moving square on the screen. Experiencing the various stochastic time intervals between the action execution button-press) and the consequent event square jumping caused gradual changes in the subjects' degree of their SoA. By comparing the above theoretical hypothesis with the experimental results, we concluded that the update (adaptation) rule of the prediction model based on the SoA is better described by a Bayesian update than by a stochastic gradient descent. (shrink)

Objective: Clock variance is an important statistic in many clinical and developmental studies. Existing methods require a large number of trials for accurate clock variability assessment, which is problematic in studies using clinical or either young or aged participants. Furthermore, these existing methods often implicitly convolute clock and memory processes, making it difficult to disentangle whether the clock or memory system are driving the observed deviations. Here we assessed whether twenty repeated productions of a well-engrained interval (1 second), a task (...) that does not incorporate memory updating nor the processing of feedback, could provide an accurate assessment of clock variability. Method: Sixty-eight undergraduate students completed two tasks: a 1-second production task in which they were asked to produce a 1-second duration by ending a tone by a keypress, and a multi-duration reproduction task. Durations presented in the reproduction task were tones lasting 1.17, 1.4 and 1.68 seconds. No feedback was presented in either task, and the order of presentation was counterbalanced between participants. Results: The observed central tendency in the reproduction task was better explained by models including the measures of clock variability derived from the 1-second production task than by models without it. Three clock variability measures were calculated for each participant (standard deviation, root mean squared residuals (RMSR) from an estimated linear slope, and RMSR scaled by mean production duration). The model including the scaled RMSR was prefered over the alternative models, and no notable effects of the order of presentation were observed. These results suggest that (1) measures of variability should account for drift, (2) the presentation of another timing task before a 1-second production task did not influence the assessment of the clock variability, and (3) the observed variability adheres to the scalar property and predicts temporal performance, and is thus a usable index of clock variability. Conclusion: This study shows that just 20 repeated productions of 1 second provide a reliable index of clock variability. As administering this task is fast and easy, it could prove to be useful in a large variety of developmental and clinical populations. (shrink)

Our senses receive a manifold of sensory signals at any given moment in our daily lives. For a coherent and unified representation of information and precise motor control, our brain needs to temporally bind the signals emanating from a common causal event and segregate others. Traditionally, different mechanisms were proposed for the temporal binding phenomenon in multisensory and motor-sensory contexts. This paper reviews the literature on the temporal binding phenomenon in both multisensory and motor-sensory contexts and suggests future research directions (...) for advancing the field. Moreover, by critically evaluating the recent literature, this paper suggests that common computational principles are responsible for the temporal binding in multisensory and motor-sensory contexts. These computational principles are grounded in the Bayesian framework of uncertainty reduction rooted in the Helmholtzian idea of unconscious causal inference. (shrink)

The thesis that consists of three studies investigated how visual affective stimuli or action as contexts influence crossmodal time processing, particularly on the role of the crossmodal/sensorimotor linkage in time perception. By using different types of emotional stimuli and manipulating the possibility of near-body interactions, three studies disassociated the impacts of embodied action from emotional dimensions on crossmodal emotional modulation in time perception. The whole thesis thus offered the first behavioral evidence that embodied action is an important factor that expands (...) subjective tactile duration and facilitates tactile selection in emotion and action contexts. Moreover, subjective expansion of duration by threat and action contexts may reflect the evolutionary coupling of our perceptual and motor systems to adapt to the specific environments for survival and success. (shrink)