Staying Together: A Bidirectional Delay–Coupled Approach to Joint Action

To understand how individuals adapt to and anticipate each other in joint tasks, we employ a bidirectional delay–coupled dynamical system that allows for mutual adaptation and anticipation. In delay–coupled systems, anticipation is achieved when one system compares its own time‐delayed behavior, which implicitly includes past information about the other system’s behavior, with the other system’s instantaneous behavior. Applied to joint music performance, the model allows each system to adapt its behavior to the dynamics of the other. Model predictions of asynchrony between two simultaneously produced musical voices were compared with duet pianists’ behavior; each partner performed one voice while auditory feedback perturbations occurred at unpredictable times during live performance. As the model predicted, when auditory feedback from one musical voice was removed, the asynchrony changed: The pianist’s voice that was removed anticipated (preceded) the actions of their partner. When the auditory feedback returned and both musicians could hear each other, they rapidly returned to baseline levels of asynchrony. To understand how the pianists anticipated each other, their performances were fitted by the model to examine change in model parameters (coupling strength, time‐delay). When auditory feedback for one or both voices was removed, the fits showed the expected decrease in coupling strength and time‐delay between the systems. When feedback about the voice(s) returned, the coupling strength and time‐delay returned to baseline. These findings support the idea that when people perform actions together, they do so as a coupled bidirectional anticipatory system.     

Perceptual Categorization: Connectionist Modelling and Decision Rules

Although it is currently popular to model human associative learning using connectionist networks, the mechanism by which their output activations are converted to probabilities of response has received relatively little attention. Several possible models of this decision process are considered here, including a simple ratio rule, a simple difference rule, their exponential versions, and a winner-take-all network. Two categorization experiments that attempt to dissociate these models are reported. Analogues of the experiments were presented to a single-layer, feed-forward, delta-rule network. Only the exponential ratio rule and the winner-take-all architecture, acting on the networks' output activations that corresponded to responses available on test, were capable of fully predicting the mean response results. In addition, unlike the exponential ratio rule, the winner-take-all model has the potential to predict latencies. Further studies will be required to determine whether latencies produced under more stringent conditions conform to the model's predictions.     

How much self-presentation behavior do applicants from the United Arab Emirates exhibit?

Applicants from different cultures vary in their self-presentation behavior during job interviews. This study investigates self-presentation behavior in the United Arab Emirates (UAE), the second largest economy in the Arab world. Specifically, it examines self-presentation behavior of applicants from the UAE and compares it to the behavior of American, European, and Chinese applicants from previous studies. The randomized response technique was used to gather self-presentation prevalence data of 111 UAE applicants regarding self-presentation behavior in their last job interview. Prevalence rates were lower than those from the United States and from China but higher than those from Iceland and from Switzerland. Results indicate that though UAE culture values modesty, UAE applicants still engage in distinct self-presentation behavior.