UC Merced

The aim of this dissertation is to take a journey into exploring more informative and rather continuous measures for assessing the cognitive processes experienced by humans. The traditional measures, such as Reaction Time, although incredibly helpful fail to provide any particular insight into what mental processes the participants undergo to produce a final result. In the recent years, it is becoming clear that a rich and semi-continuous set of measures is extractable from relatively implicit behaviors such as hand or eye movements. It has been shown that spatial and temporal dynamics of motor movements (i.e. action dynamics) can shed light on the progression of high-level cognitive tasks. This rich body of data could provide a nearly real-time translation of unfolding cognitive processes.

Throughout this document, I present a series of studies on how action dynamics could provide a window to observe the emergence of cognitive processes involved in deception and predictive learning. These are two areas in which action dynamics have not been explored nearly enough. I utilized a novel task to test two competing hypotheses concerning the cognitive processes involved in dishonesty. Moreover, a novel paradigm was provided for testing hypothesis regarding sequential learning and the role of prediction in implicit learning.

I close with a report of findings about the processes underlying deceptive behavior and predictive learning. The findings are followed by a discussion about implications of this work for the field of cognitive science and the limitations in action dynamics approach. On the one hand this work takes advantage of action dynamics to get under the hood as these complex cognitive processes unfold in the brain. On the other hand, it utilizes these cognitive phenomena to demonstrate the power of action dynamics in studying higher level complex cognitive processes.