Studies of patients with schizophrenia using facial affect recognition and voice discrimination tasks have identified emotional dysfunction as a prominent clinical feature. In the present study we examine whether emotion processing in patients is also impaired in a less explicitly social context -- continuous self-report of emotions during music using a two-dimensional (pleasantness X activation) emotion space. Electroencephalographic (EEG) activity was also recorded during this task since previous studies using EEG measures have found underlying cortical processes related to emotion. Twelve patients with schizophrenia and eleven controls listened to five 25-second songs. These songs included J.S. Bach‟s Invention #13 in A minor (BWV 784) (designated the original piece), and four computer-generated pieces of which two were designed to be similar to the original, and two were designed to be different. While no significant effects were found in the activation dimension of the self-report measures, the pattern of pleasantness ratings was significantly less differentiated among songs in the patient group than in controls. EEG asymmetry indices at frontal and central electrodes provided evidence of greater hemispheric activation asymmetry (with higher activation on the left) in controls than in patients, a difference that was significant at the central electrodes (C3 and C4). These findings indicate that individuals with schizophrenia interpret emotion-eliciting music differently than do controls, even in a relatively non-social setting, possibly because of less differentiated hemispheric representations.
Hazard perception has received little attention compared to measures of vehicle control in studies exploring the effects of texting on driving performance, despite being a more direct measure of crash risk. Furthermore, the driver strategies attempting to moderate such distraction are not well understood. The current study attempts to address these two facets of texting while driving. Participants (10 male; 10 female) drove a low fidelity simulator that measures situational awareness, while text messaging in order to assess hazard perception performance. Participants were required to identify and appropriately respond to events that would result in a collision. Two text message conditions (i.e., copying and alphabetizing a 5-letter string) were used to compare low vs. high cognitive load, respectively. Participants missed more hazards in the alphabetize-text compared to the copy-text and driving only conditions. Signal Detection Theory (SDT) analyses revealed the adoption of a more liberal response bias (B") (i.e., participants increased false) when required to copy the text message but not when required to alphabetize. Last, participants were slower to react to hazards in the alphabetize-text condition compared to the copy-text and driving only conditions. These findings suggest that the impact of text messaging on the detection of driving hazards depends in part, on the cognitive load imposed by the text messaging task and the adoption of strategies to compensate for the interference on the driving task.
Research indicates that using a cell phone to talk or text while maneuvering a vehicle impairs driving performance. However, few published studies directly compare the distracting effects of texting using a hands-free (i.e., speech-based interface) versus handheld cell phone, which is an important issue for legislation, automotive interface design and driving safety training. This study compared the effect of speech-based versus handheld texting on simulated driving performance by asking participants to perform a car following task while controlling the duration of a secondary texting task. Results showed that both speech-based and handheld texting impaired driving performance relative to the drive-only condition by causing more variation in speed and lane position. Handheld texting also increased the brake response time and increased variation in headway distance. Texting using a speechbased cell phone was less detrimental to driving performance than handheld texting. Nevertheless, the speech-based texting task still significantly impaired driving compared to the drive-only condition. These results suggest that speech-based interaction disrupts driving, but reduces the levels of performance interference compared to handheld devices. In addition, the difference in the distraction effect caused by speech-based and handheld texting is not simply due to the difference in task duration.
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