Polarization is increasing in American politics and frequently involves disagreement over basic facts. Although this phenomenon is rare, the domain of social and political issues provides an environment where emotions may influence opinions and decisions in seemingly irrational ways. This research explores how individuals judge and respond to evidence about controversial socio-political issues, considering whether behavior is more appropriately modeled by accounts of motivated reasoning or Bayesian updating rules.

We find evidence of an attitude congruency bias, where people judge information to be of higher quality when it aligns with their existing attitudes on an issue. However, we find that this bias does not necessarily lead to polarizing. Instead, people’s change in attitudes is better described by Bayesian updating, where people are sensitive to the amount and quality of information they are presented with. This behavior does not seem to be driven by affect or knowledge in a domain.

Judgment of information, in the form of argument rating, was analyzed by creating separate measures of objective argument quality and individual rating bias. Both factors were found to model attitude change, indicating that participants are sensitive to both the objective quality of evidence and to the effects of their own biases. Accounts of Bayesian information processing and motivated reasoning both predict behavior when information is modeled in terms of these two factors.

Finally, this research explores the role of information choice and shows that a bias toward choosing attitude-congruent information may lead to motivated attitude change, where exposure to a biased set of evidence models attitude change in line with one’s existing views. People exhibit more sensitivity to information quality when they do not choose which information to view, indicating that choice may play a special role in allowing individual bias to outweigh information quality. These findings inspire questions about the role of curated information and people’s capacity for rational behavior in a tense political climate.

Movements of the body beyond those involved in articulation are often exquisitely timed with speech. These embodied cues often inform semantic and pragmatic levels of social understanding but are also relevant for shaping how attention is organized to a speaker’s behavior and for the interpretation of prosodic speech features such as lexical stress. For these reasons, joint action between speech and gesture has been popularized by the term multimodal prosody, however, neurocognitive theories cannot yet account for the way that gestural cues interact with auditory speech processing or describe the necessary conditions for them to do so.As outlined in Chapter 1, the Sensorimotor Account of Multimodal Prosody (SAMP) forages from relatively disparate fields of inquiry to build a neurobiologically plausible hypothesis about mechanisms that service multisensory integration and attentional alignment during spoken language exchange. The SAMP hypothesizes that neural mechanisms tied to self-motion (vestibular) variables may be relevant neural codes that could be used to enforce the instantiation of temporally coupled communicative behaviors during discourse production, and that associated mechanisms assist in coding similar latent variables during discourse comprehension. Chapter 2 investigates a critical prediction of the SAMP: that kinetic, or force-related properties of co-speech movements are informative about a speaker’s vocal output. By training machine learning algorithms to predict amplitude characteristics of speech from whole-body motion capture data, we provide evidence that gravity-compatible movement trajectories are important for learning contingencies between and speech and co-speech movements. This validates the claim that kinetic properties of co-speech movement are informative for a speaker’s vocal output in ecologically relevant contexts. Chapters 3 and 4 use time-sensitive neuroimaging techniques (EEG) to investigate the potential influence of co-speech movement kinematics on auditory speech processing and provide novel evidence for multisensory enhancement effects of co-speech gesture dynamics on the neural representation of speech acoustics. Finally, Chapter 5 provides evidence that kinetic properties of co-speech gestures are relevant for driving multisensory interactivity during discourse processing, as the neural representation of kinetically informative biological motion trajectories were disproportionately impacted by the speaker’s voice. Compatible with radically embodied, biomechanical accounts of multimodal prosody, the SAMP provides a starting point for explaining how audiovisual interactions during discourse comprehension might be explained at this scale. This dissertation offers a theoretically grounded and empirical look into the way bodily movements traditionally defined as “nonverbal” may hold a more direct relationship with spoken language in the brain than is currently recognized. The presented work also motivates current neurocognitive models of speech processing to expand the scope of multisensory interactions that they currently account for–broadening an area of study that has historically focused on phonetics into the domain of prosody.