Nicholas D. Duran

The action dynamics of overcoming the truth

A convincing deceiver must act in discordance with their knowledge of the truth. To do so requires the deceiver to resolve competition between what is known to be true and what is intended to be false. We investigated the temporal signature of this competition by examining the action dynamics of arm movement while participants responded falsely or truthfully to autobiographical information. The participants answered no or yes by navigating a Nintendo Wii Remote to no and yes regions on a large projector screen. Trajectory analyses of the fine-grained arm movements show increased complexity in false responding relative to truthful responding, with the greatest difference in false yes answers. The dynamic motor movements also reveal greater strength of competition during the act of false responding, thereby extending traditional response time measures that capture latent competition alone. These results suggest that deceptive processes may be detectable when action is allowed to covary with thought. Supplemental figures and a list of the sentence stimuli may be downloaded from http://pbr.psychonomic-journals.org/content/supplemental.

Using temporal cohesion to predict temporal coherence in narrative and expository texts

We investigated the linguistic features of temporal cohesion that distinguish variations in temporal coherence. In an analysis of 150 texts, experts rated temporal coherence on three continuous scale measures designed to capture unique representations of time. Coh-Metrix, a computational tool that assesses textual cohesion, correctly predicted the human ratings with five features of temporal cohesion. The correlations between predicted and actual scores were all statistically significant. In a complementary study, we explored the importance of temporal cohesion in characterizing genre. A discriminant function analysis, using Coh-Metrix temporal indices, successfully distinguished the genres of science, history, and narrative texts. The results suggested that history texts are more similar to narrative texts than to science texts in terms of temporal cohesion.

The Linguistic Correlates of Conversational Deception: Comparing Natural Language Processing Technologies

The words people use and the way they use them can reveal a great deal about their mental states when they attempt to deceive. The challenge for researchers is how to reliably distinguish the linguistic features that characterize these hidden states. In this study, we use a natural language processing tool called Coh-Metrix to evaluate deceptive and truthful conversations that occur within a context of computer-mediated communication. Coh-Metrix is unique in that it tracks linguistic features based on cognitive and social factors that are hypothesized to influence deception. The results from Coh-Metrix are compared to linguistic features reported in previous independent research, which used a natural language processing tool called Linguistic Inquiry and Word Count. The comparison reveals converging and contrasting alignment for several linguistic features and establishes new insights on deceptive language and its use in conversation.

Prediction during statistical learning, and implications for the implicit/explicit divide.

Accounts of statistical learning, both implicit and explicit, often invoke predictive processes as central to learning, yet practically all experiments employ non-predictive measures during training. We argue that the common theoretical assumption of anticipation and prediction needs clearer, more direct evidence for it during learning. We offer a novel experimental context to explore prediction, and report results from a simple sequential learning task designed to promote predictive behaviors in participants as they responded to a short sequence of simple stimulus events. Predictive tendencies in participants were measured using their computer mouse, the trajectories of which served as a means of tapping into predictive behavior while participants were exposed to very short and simple sequences of events. A total of 143 participants were randomly assigned to stimulus sequences along a continuum of regularity. Analysis of computer-mouse trajectories revealed that (a) participants almost always anticipate events in some manner, (b) participants exhibit two stable patterns of behavior, either reacting to vs. predicting future events, (c) the extent to which participants predict relates to performance on a recall test, and (d) explicit reports of perceiving patterns in the brief sequence correlates with extent of prediction. We end with a discussion of implicit and explicit statistical learning and of the role prediction may play in both kinds of learning.

Chapter Two – The Self-Organization of Human Interaction

We describe a “centipede’s dilemma” that faces the sciences of human interaction. Research on human interaction has been involved in extensive theoretical debate, although the vast majority of research tends to focus on a small set of human behaviors, cognitive processes, and interactive contexts. The problem is that naturalistic human interaction must integrate all of these factors simultaneously, and grander theoretical mitigation cannot come only from focused experimental or computational agendas. We look to dynamical systems theory as a framework for thinking about how these multiple behaviors, processes, and contexts can be integrated into a broader account of human interaction. By introducing and utilizing basic concepts of self-organization and synergy, we review empirical work that shows how human interaction is flexible and adaptive and structures itself incrementally during unfolding interactive tasks, such as conversation, or more focused goal-based contexts. We end on acknowledging that dynamical systems accounts are very short on concrete models, and we briefly describe ways that theoretical frameworks could be integrated, rather than endlessly disputed, to achieve some success on the centipede’s dilemma of human interaction.

Exploring the movement dynamics of deception

Both the science and the everyday practice of detecting a lie rest on the same assumption: hidden cognitive states that the liar would like to remain hidden nevertheless influence observable behavior. This assumption has good evidence. The insights of professional interrogators, anecdotal evidence, and body language textbooks have all built up a sizeable catalog of non-verbal cues that have been claimed to distinguish deceptive and truthful behavior. Typically, these cues are discrete, individual behaviors—a hand touching a mouth, the rise of a brow—that distinguish lies from truths solely in terms of their frequency or duration. Research to date has failed to establish any of these non-verbal cues as a reliable marker of deception. Here we argue that perhaps this is because simple tallies of behavior can miss out on the rich but subtle organization of behavior as it unfolds over time. Research in cognitive science from a dynamical systems perspective has shown that behavior is structured across multiple timescales, with more or less regularity and structure. Using tools that are sensitive to these dynamics, we analyzed body motion data from an experiment that put participants in a realistic situation of choosing, or not, to lie to an experimenter. Our analyses indicate that when being deceptive, continuous fluctuations of movement in the upper face, and somewhat in the arms, are characterized by dynamical properties of less stability, but greater complexity. For the upper face, these distinctions are present despite no apparent differences in the overall amount of movement between deception and truth. We suggest that these unique dynamical signatures of motion are indicative of both the cognitive demands inherent to deception and the need to respond adaptively in a social context.

Identifying topic sentencehood.

Four experiments were conducted to assess two models of topic sentencehood identification: the derived model and the free model. According to the derived model, topic sentences are identified in the context of the paragraph and in terms of how well each sentence in the paragraph captures the paragraph’s theme. In contrast, according to the free model, topic sentences can be identified on the basis of sentential features without reference to other sentences in the paragraph (i.e., without context). The results of the experiments suggest that human raters can identify topic sentences both with and without the context of the other sentences in the paragraph. Another goal of this study was to develop computational measures that approximated each of these models. When computational versions were assessed, the results for the free model were promising; however, the derived model results were poor. These results collectively imply that humans’ identification of topic sentences in context may rely more heavily on sentential features than on the relationships between sentences in a paragraph.

Self-serving dishonest decisions can show facilitated cognitive dynamics

We use a novel task to test two competing hypotheses concerning the cognitive processes involved in dishonesty. Many existing accounts of deception imply that in order to act dishonestly one has to use cognitive control to overcome a bias toward the truth, which results in more time and effort. A recent hypothesis suggests that lying in order to serve self-interest may be a rapid, even automatic tendency taking less time than refraining from lying. In the current study, we track the action dynamics of potentially dishonest decisions to investigate the underlying cognitive processes. Participants are asked to privately predict the outcome of a virtual coin flip, report their accuracy and receive bonus credit for accurate predictions. The movements of the computer cursor toward the target answer are recorded and used to characterize the dynamics of decisions. Our results suggest that when a self-serving condition holds, decisions that have a high probability of being dishonest take less time and experience less hesitation.

Toward Integrative Dynamic Models for Adaptive Perspective Taking

In a matter of mere milliseconds, conversational partners can transform their expectations about the world in a way that accords with another persons perspective. At the same time, in similar situations, the exact opposite also appears to be true. Rather than being at odds, these findings suggest that there are multiple contextual and processing constraints that may guide when and how people consider perspective. These constraints are shaped by a host of factors, including the availability of social and environmental cues, and intrinsic biases and cognitive abilities. To explain how these might be integrated in a new way forward, we turn to an adaptive account of interpersonal interaction. This account draws from basic principles of dynamical systems, principles that we argue are already expressed, both implicitly and explicitly, within a broad landscape of existing research. We then showcase an initial attempt to develop a computational framework to instantiate some of these principles. This framework, consisting of what we argue to be important mechanistic insights rendered by neural network models, is based on a promising and long-standing approach that has yet to take hold in the current domain. We argue that by bridging this gap, new insights into other theoretical accounts, such as the connections between memory and common ground information, might be revealed.

When expectancies collide: Action dynamics reveal the interaction between stimulus plausibility and congruency

The cognitive architecture routinely relies on expectancy mechanisms to process the plausibility of stimuli and establish their sequential congruency. In two computer mouse-tracking experiments, we use a cross-modal verification task to uncover the interaction between plausibility and congruency by examining their temporal signatures of activation competition as expressed in a computer- mouse movement decision response. In this task, participants verified the content congruency of sentence and scene pairs that varied in plausibility. The order of presentation (sentence-scene, scene-sentence) was varied between participants to uncover any differential processing. Our results show that implausible but congruent stimuli triggered less accurate and slower responses than implausible and incongruent stimuli, and were associated with more complex angular mouse trajectories independent of the order of presentation. This study provides novel evidence of a disassociation between the temporal signatures of plausibility and congruency detection on decision responses.