Resting-State Functional Connectivity in the Dorsal Attention Network Relates to Behavioral Performance in Spatial Attention Tasks and May Show Task-Related Adaptation

Between-subject variability in cognitive performance has been related to inter-individual differences in functional brain networks. Targeting the dorsal attention network (DAN) we questioned (i) whether resting-state functional connectivity (FC) within the DAN can predict individual performance in spatial attention tasks and (ii) whether there is short-term adaptation of DAN-FC in response to task engagement. Twenty-seven participants first underwent resting-state fMRI (PRE run), they subsequently performed different tasks of spatial attention [including visual search (VS)] and immediately afterwards received another rs-fMRI (POST run). Intra- and inter-hemispheric FC between core hubs of the DAN, bilateral intraparietal sulcus (IPS) and frontal eye field (FEF), was analyzed and compared between PRE and POST. Furthermore, we investigated rs-fMRI-behavior correlations between the DAN-FC in PRE/POST and task performance parameters. The absolute DAN-FC did not change from PRE to POST. However, different significant rs-fMRI-behavior correlations were revealed for intra-/inter-hemispheric connections in the PRE and POST run. The stronger the FC between left FEF and IPS before task engagement, the better was the learning effect (improvement of reaction times) in VS (r = 0.521, p = 0.024). And the faster the VS (mean RT), the stronger was the FC between right FEF and IPS after task engagement (r = −0.502, p = 0.032). To conclude, DAN-FC relates to the individual performance in spatial attention tasks supporting the view of functional brain networks as priors for cognitive ability. Despite a high inter- and intra-individual stability of DAN-FC, the change of FC-behavior correlations after task performance possibly indicates task-related adaptation of the DAN, underlining that behavioral experiences may shape intrinsic brain activity. However, spontaneous state fluctuations of the DAN-FC over time cannot be fully ruled out as an alternative explanation.

Perceived safety and trust in SAE Level 2 partially automated cars: Results from an online questionnaire

The present online study surveyed drivers of SAE Level 2 partially automated cars on automation use and attitudes towards automation. Respondents reported high levels of trust in their partially automated cars to maintain speed and distance to the car ahead (M = 4.41), and to feel safe most of the time (M = 4.22) on a scale from 1 to 5. Respondents indicated to always know when the car is in partially automated driving mode (M = 4.42), and to monitor the performance of their car most of the time (M = 4.34). A low rating was obtained for engaging in other activities while driving the partially automated car (M = 2.27). Partial automation did, however, increase reported engagement in secondary tasks that are already performed during manual driving (i.e., the proportion of respondents reporting to observe the landscape, use the phone for texting, navigation, music selection and calls, and eat during partially automated driving was higher in comparison to manual driving). Unsafe behaviour was rare with 1% of respondents indicating to rarely monitor the road, and another 1% to sleep during partially automated driving. Structural equation modeling revealed a strong, positive relationship between perceived safety and trust (β = 0.69, p = 0.001). Performance expectancy had the strongest effects on automation use, followed by driver engagement, trust, and non-driving related task engagement. Perceived safety interacted with automation use through trust. We recommend future research to evaluate the development of perceived safety and trust in time, and revisit the influence of driver engagement and non-driving related task engagement, which emerged as new constructs related to trust in partial automation.

When Preschoolers Interact with an Educational Robot, Does Robot Feedback Influence Engagement?

In this paper, we examine to what degree children of 3–4 years old engage with a task and with a social robot during a second-language tutoring lesson. We specifically investigated whether children’s task engagement and robot engagement were influenced by three different feedback types by the robot: adult-like feedback, peer-like feedback and no feedback. Additionally, we investigated the relation between children’s eye gaze fixations and their task engagement and robot engagement. Fifty-eight Dutch children participated in an English counting task with a social robot and physical blocks. We found that, overall, children in the three conditions showed similar task engagement and robot engagement; however, within each condition, they showed large individual differences. Additionally, regression analyses revealed that there is a relation between children’s eye-gaze direction and engagement. Our findings showed that although eye gaze plays a significant role in measuring engagement and can be used to model children’s task engagement and robot engagement, it does not account for the full concept and engagement still comprises more than just eye gaze.

The Unfolding of Cognitive Effort During Sentence Processing: Pupillometric Evidence From People With and Without Aphasia

Purpose: Arousal and cognitive effort are relevant yet often overlooked components of attention during language processing. Pupillometry can be used to provide a psychophysiological index of arousal and cognitive effort. Given that much is unknown regarding the relationship between cognition and language deficits seen in people with aphasia (PWA), pupillometry may be uniquely suited to explore those relationships. The purpose of this study was to examine arousal and the time course of the allocation of cognitive effort related to sentence processing in people with and without aphasia. Method: Nineteen PWA and age- and education-matched control participants listened to relatively easy (subject-relative) and relatively difficult (object-relative) sentences and were required to answer occasional comprehension questions. Tonic and phasic pupillary responses were used to index arousal and the unfolding of cognitive effort, respectively, while sentences were processed. Group differences in tonic and phasic responses were examined. Results: Group differences were observed for both tonic and phasic responses. PWA exhibited greater overall arousal throughout the task compared with controls, as evidenced by larger tonic pupil responses. Controls exhibited more effort (greater phasic responses) for difficult compared with easy sentences; PWA did not. Group differences in phasic responses were apparent during end-of-sentence and postsentence time windows. Conclusions: Results indicate that the attentional state of PWA in this study was not consistently supportive of adequate task engagement. PWA in our sample may have relatively limited attentional capacity or may have challenges with allocating existing capacity in ways that support adequate task engagement and performance. This work adds to the body of evidence supporting the validity of pupillometric tasks for the study of aphasia and contributes to a better understanding of the nature of language deficits in aphasia. Supplemental Material https://doi.org/10.23641/asha.16959376

Engaging in dialogue during collaborative writing: The role of affective, cognitive, and social engagement

Collaborative writing (CW) involves two or more students writing a single text together. Previous studies mainly focused on students’ cognitive engagement in CW and investigated their attention to various language-related problems during task interaction. However, little CW research to date has considered that engagement in language-related discussions can manifest from three dimensions: cognitive, social, and affective. Focusing on the multidimensional characteristics of engagement, this study investigated how Russian learners’ social and affective reactions influence their focus on language use while they completed a CW task. Drawing on Svalberg’s framework of engagement with language to identify the three dimensions of engagement, I conducted a mixed-method approach towards analysing the audio-recorded collaborative dialogues by three student pairs ( n = 6), along with a qualitative analysis of their responses to a five-point Likert scale questionnaire. The analyses showed that when learners were interactive and viewed the activity as useful, they noticed many linguistic problems and elaborated on them. In contrast, when learners demonstrated social disengagement and perceived disadvantages from CW, they were likely to withdraw their attention from resolving the language issues they encountered. These findings indicate the complex and dynamic nature of task engagement. They can provide second language (L2) teachers with an in-depth understanding of how to fully engage students in instructional activities to better foster their L2 learning.