UCLA

This dissertation investigates psychophysiological mechanisms co-occurring with selected behaviors in conversation, namely turn-taking, silences, pauses, disagreements, and word searches. The main hypothesis of this work is that certain interactional behaviors are modulated by a feedback system embedded in the psychological and physiological individual characteristics of the actors engaged in a conversation. It is based on the assumption that the human autonomic nervous system plays a role in framing and informing social engagement behaviors.

The goals of the study presented here were: (i) to correlate individual psychological characteristics and changes in physiological states to certain conversational behaviors, (ii) to expand the theoretical scope of what comprises embodied cognition to include neurobiological descriptors, and (iii) to present a transdisciplinary methodology for psychophysiological studies of conversation analysis and social engagement behaviors.

Here, conversation analysis was the methodology utilized to study not only speech acts like assessments, word searches, disagreements, requests, among others, but also their sequential organization, participants’ epistemic stances, co-construction of meaning, embedded gestures, and facial expressions that occurred during 28 video-recorded 20-minute-long conversations. In addition, this work has shown that across this dataset, individuals react and respond to contextual cues and demands differently, even across the same type of behavior. Given that psychophysiological variables underlie social behavior, participants’ individual differences in personality traits and states, as well as their physiological predispositions and behavioral tendencies were measured and correlated to the elicited conversational behaviors. Inter-subject differences were also correlated to context, and so were intra-subject differences within tokens of the same behavior.

Thus, this dissertation shows that there are correlations between participants' psychophysiological traits and their conversational behaviors. These sources of additional data can help especially in the study of group behaviors, since there is a more distributed responsibility to maintain the conversation than in dyadic interactions.