Unisensory and Multisensory Stroop Effects Modulate Gender Differences in Verbal and Nonverbal Emotion Perception

Purpose This study aimed to examine the Stroop effects of verbal and nonverbal cues and their relative impacts on gender differences in unisensory and multisensory emotion perception. Method Experiment 1 investigated how well 88 normal Chinese adults (43 women and 45 men) could identify emotions conveyed through face, prosody and semantics as three independent channels. Experiments 2 and 3 further explored gender differences during multisensory integration of emotion through a cross-channel (prosody-semantics) and a cross-modal (face-prosody-semantics) Stroop task, respectively, in which 78 participants (41 women and 37 men) were asked to selectively attend to one of the two or three communication channels. Results The integration of accuracy and reaction time data indicated that paralinguistic cues (i.e., face and prosody) of emotions were consistently more salient than linguistic ones (i.e., semantics) throughout the study. Additionally, women demonstrated advantages in processing all three types of emotional signals in the unisensory task, but only preserved their strengths in paralinguistic processing and showed greater Stroop effects of nonverbal cues on verbal ones during multisensory perception. Conclusions These findings demonstrate clear gender differences in verbal and nonverbal emotion perception that are modulated by sensory channels, which have important theoretical and practical implications. Supplemental Material https://doi.org/10.23641/asha.16435599

Loss aversion in hotel choice: Psychophysiological evidence

The authors investigate the psychophysiological correlates of loss aversion in hotel choice. Consumers are frequently found reluctant to shift their choice to a subsequent option from their first encountered hotel. The concept of loss aversion can explain this ordering effect. However, there is a knowledge gap about how exactly loss aversion leads to such inertia. The present study provides a more direct measurement of this decision process by examining electrodermal activities and reaction times when consumers are making hotel choices. The choice data provides evidence of reluctance to switch to higher quality hotels, though not to lower rated properties. Such a switch is found emotionally arousing as indicated by consumers’ electrodermal activity. The reaction time data further suggests that the swiftness of such decisions to “trade up” is associated with the greater vigilance and attention, rather than a cognitive conflict caused by the difficult tradeoff between the hotels.

Are there sex differences in physiological parameters and reaction time responses to overload in firefighters?

Male and female firefighters work side-by-side in the same in strenuous and risky conditions. Anthropometrics, physiological, and reaction time (mean of reaction time -MRT-, and errors made -E) parameters of 12 Female and 13 Male firefighters were compared. Effect of overload (step test with and without equipment) on the MRT and E were analyzed on 3 trials (T1 = 1-1s, T2 = 0.5-1s, T3 = 0.5–0.5s), compared with a pre-test condition (basal). T-test between males and females was applied to assess differences (p<0.05) in all parameters. ANOVA with repeated measures and Bonferroni on 3 conditions of step test between males and females was applied in reaction time variables. Between MRT and E, in T1, T2 and T3 trials and the 3 test conditions, ANCOVA models with interactions were used. Differences (p<0.05) in anthropometric, physiological and reaction time data emerged across groups, and on the 3rd trials (T3 vs T1 and T2) in reaction time parameters of each group. ANCOVA showed differences (p<0.001) in E among trials. Post hoc showed significant differences in T1vsT3 and T1vsT2. MRT x trial interaction was extremely significant (P<0.001). Implementing fitness and reaction time exercise programs is important to decrease the injury risk and increase work capacity in firefighters with reference to female workers.

What canonical online and offline measures of statistical learning can and cannot tell us

Statistical learning (SL) allows individuals to rapidly detect regularities in the sensory environment. We replicated previous findings showing that adult participants become sensitive to the implicit structure in a continuous speech stream of repeating tri-syllabic pseudowords within minutes, as measured by standard tests in the SL literature: a target detection task and a 2AFC word recognition task. Consistent with previous findings, we found only a weak correlation between these two measures of learning, leading us to question whether there is overlap between the information captured by these two tasks. Representational similarity analysis on reaction times measured during the target detection task revealed that reaction time data reflect sensitivity to transitional probability, triplet position, word grouping, and duplet pairings of syllables. However, individual performance on the word recognition task was not predicted by similarity measures derived for any of these four features. We conclude that online detection tasks provide richer and multi-faceted information about the SL process, as compared with 2AFC recognition tasks, and may be preferable for gaining insight into the dynamic aspects of SL.

Human Reaction Times: Linking Individual and Collective Behaviour Through Physics Modeling

An individual’s reaction time data to visual stimuli have usually been represented in Experimental Psychology by means of an ex-Gaussian function. In most previous works, researchers have mainly aimed at finding a meaning for the parameters of the ex-Gaussian function which are known to correlate with cognitive disorders. Based on the recent evidence of correlations between the reaction time series to visual stimuli produced by different individuals within a group, we go beyond and propose a Physics-inspired model to represent the reaction time data of a coetaneous group of individuals. In doing so, a Maxwell–Boltzmann-like distribution appeared, the same distribution as for the velocities of the molecules in an Ideal Gas model. We describe step by step the methodology we use to go from the individual reaction times to the distribution of the individuals response within the coetaneous group. In practical terms, by means of this model we also provide a simple entropy-based methodology for the classification of the individuals within the collective they belong to with no need for an external reference which can be applicable in diverse areas of social sciences.

The Effect of Increasing Music Volume on Reaction Time

The purpose of this study was to investigate the impact that music volume has on reaction time. The significance of this study is that music volume is often suggested to be one of the factors and/or distractions that lead young drivers under the age of 25 to experience a high rate of vehicular accidents, and the goal of this study was to quantitatively assess the effect of increasing music volume on the reaction time of subjects in this demographic. Tactile reaction time, using the Brain Gauge, was used to record simple reaction time and choice reaction time data for 20 college students while the Neil Diamond classic “Sweet Caroline” was played at approximately 0dB, 20dB, 40dB, and 80dB. The results demonstrate a significant increase in simple reaction time with increased music volume and shows that louder music impacts an individual’s capacity to react to a stimulus. Although the study was not conducted while the individual was driving, the results strongly suggest that high music volume could significantly impair a driver’s response time.

The Accuracy and Precision of Measurement: Tools for Validating Reaction Time Stimuli

Measurement noise differs by instrument and limits the validity and reliability of findings. Researchers collecting reaction time data introduce noise in the form of response time latency from hardware and software, even when collecting data on standardized computer-based experimental equipment. Reaction time is a measure with broad application for studying cognitive processing in communication research that is vulnerable to response latency noise. In this study, we utilized an Arduino microcontroller to generate a ground truth value of average response time latency in Asteroid Impact, an open source, naturalistic, experimental video game stimulus. We tested if response time latency differed across computer operating system, software, and trial modality. Here we show that reaction time measurements collected using Asteroid Impact were susceptible to response latency variability on par with other response-latency measuring software tests. These results demonstrate that Asteroid Impact is a valid and reliable stimulus for measuring reaction time data. Moreover, we provide researchers with a low-cost and open-source tool for evaluating response time latency in their own labs. Our results highlight the importance of validating measurement tools and support the philosophy of contributing methodological improvements in communication science.

The Accuracy and Precision of Measurement

Measurement noise differs by instrument and limits the validity and reliability of findings. Researchers collecting reaction time data introduce noise in the form of response time latency from hardware and software, even when collecting data on standardized computer-based experimental equipment. Reaction time is a measure with broad application for studying cognitive processing in communication research that is vulnerable to response latency noise. In this study, we utilized an Arduino microcontroller to generate a ground truth value of average response time latency in Asteroid Impact, an open source, naturalistic, experimental video game stimulus. We tested if response time latency differed across computer operating system, software, and trial modality. Here we show that reaction time measurements collected using Asteroid Impact were susceptible to response latency variability on par with other response-latency measuring software tests. These results demonstrate that Asteroid Impact is a valid and reliable stimulus for measuring reaction time data. Moreover, we provide researchers with a low-cost and open-source tool for evaluating response time latency in their own labs. Our results highlight the importance of validating measurement tools and support the philosophy of contributing methodological improvements in communication science.

Bayesian Modeling of Cognitive Impairment in the Presence of Retest Effects

Diagnosing the early onset of neuropathologies, such as mild cognitive impairment (MCI), requires repeated evaluation of cognitive skills several times per year -- a measurement design known as a “burst design.” Detecting the often subtle cognitive decline in the presence of retest effects requires careful statistical modeling. The double exponential model offers a modeling framework to account for retest gains across measurement bursts, as well as warm-up effects within a burst, while quantifying change across bursts in peak performance. This talk highlights how a Bayesian multilevel implementation of the double exponential model allows for flexible extensions of this framework in terms of accommodating different timescales (nesting) and person-level predictors and drawing intuitive inferences on cognitive change with Bayesian posterior probabilities. We will use reaction time data to show how individual differences in asymptotic performance and change can be related to predictors such as age and MCI status. Part of a symposium sponsored by the Measurement, Statistics, and Research Design Interest Group.