How retaining objects containing multiple features in visual working memory regulates the priority for access to visual awareness

The content of visual working memory influences the access to visual awareness. Thus far, research has focused on retention of a single feature, whereas memoranda in real life typically contain multiple features. Here, we intermixed a delayed match-to-sample task to manipulate VWM content, and a breaking Continuous Flash Suppression (b-CFS) task to measure prioritization for visual awareness. Observers memorized either the color (Exp. 1), the shape (Exp. 2) or both the features (Exp. 3) of an item and indicated the location of a suppressed target. We observed that color-matching targets broke suppression faster than color-mismatching targets both when color was memory relevant or irrelevant. Shape only impacted priority for visual awareness through an interaction with color. We conclude that: (1) VWM can regulate the priority of visual information to access visual awareness along a single feature dimension; (2) different features of a memorandum vary in their potency to impact access to visual awareness, and the more dominant feature may even suppress the effect of the less dominant feature; (3) even stimuli that match an irrelevant feature dimension of the memorandum can be prioritized for visual awareness.     

Delivering Intensive PTSD Treatment Virtually: The Development of a 2-Week Intensive Cognitive Processing Therapy–Based Program in Response to COVID-19

Of the many vulnerable groups affected by the spread of COVID-19, veterans have been especially impacted by the pandemic. Beginning in March 2020, nationwide shelter-in-place orders rapidly led to widespread job loss and economic upheaval; disruption and breakdown of multiple support systems; and increases in family stress, all of which may exacerbate underlying PTSD symptoms. Although telehealth has proven an effective means of delivering evidence-based psychotherapies for PTSD, little is known about the delivery of these treatments in an intensive, daily format over telehealth. There is growing need for intensive treatment options to reduce treatment-interfering barriers such as high dropout rates. In order to address this gap in the literature, this paper details several design considerations as well as patient selection procedures for a 2-week virtual intensive treatment program (vITP) for veterans with posttraumatic stress disorder (PTSD), consisting of daily individual Cognitive Processing Therapy (CPT) and other adjunctive interventions. We also describe two cases of veterans who successfully completed the vITP including their clinical outcomes, therapist reflections on the process, feedback regarding the program, as well as challenges patients encountered with the telehealth platform. Intensive evidence-based psychotherapy for PTSD delivered through a virtual format seems to show promise, but more systemic research is needed.     

From anticipation to behavioral intention: Insights into human processing of multiple retrieval cues in road traffic

Anticipation in road traffic enables safer and more comfortable driving. Anticipatory driving is achieved through effective retrieval of prior driving-relevant knowledge using mental models and appropriate cues. Knowing when and which retrieval cues have a critical impact on the anticipation process and how information compatibility affects anticipation can be the basis for supporting people in anticipating and appropriate behavior in road traffic.For generating in-depth insights into the processing of retrieval cues, a video-based experimental study was conducted combining specific compatible and incompatible retrieval cues in urban driving scenarios. From a driver's perspective, participants were asked to anticipate in a two-step approach (measuring low and high certainty anticipation) whether a vehicle ahead would enter their lane or turn onto another street due to a lane blockage ahead. Further, they choose their preferred behavioral intention (accelerate, decelerate or maintain speed). In general, drivers strived for coherent situation representation, and in this process, multiple retrieval cues influenced anticipation in different ways. Participants were more likely to be consistent in their anticipation response. That is, they tend to follow their first intention (equivalent low and high certainty anticipation for either lane change or turn) even in the presence of incompatible stimuli. Inconsistent compared to consistent anticipation responses, however, led to reduced subjective confidence, and in part to increased criticality. Not only anticipation but also intended behavior was influenced by retrieval cues. In accordance, the anticipation of others' behaviors can be considered a predictor of specific intended behavior in road traffic.     

The power and sensitivity of four core driver workload measures for benchmarking the distraction potential of new driver vehicle interfaces

This study evaluated the power and sensitivity of several core driver workload measures in order to better understand their use as a component of future driver distraction potential evaluation procedures of the in-vehicle human machine interface (HMI). Driving is a task that requires visual, manual and cognitive resources to perform. Secondary tasks, such as mobile phone use and interaction with in-built navigation, which load onto any of these three processing resources increase driver workload and can lead to impaired driving. Because workload and distraction potential are interrelated, a comprehensive method to assess driver workload that produces valid and predictive results is needed to advance the science of distraction potential evaluation. It is also needed to incorporate into New Car Assessment Program (NCAP) testing regimes. Workload measures of cognitive (DRT [Detection Response Task] Reaction Time), visual (DRT Miss Rate), subjective (NASA-TLX [driver workload questionnaire]), and temporal demand (Task Interaction Time) were collected as participants drove one of 40 vehicles while completing a variety of secondary tasks with varying interaction requirements. Of the evaluated measures, variance and power analyses demonstrated that Task Interaction Time is the most sensitive in detecting differences in driver workload between different in-vehicle HMIs, followed by DRT Miss Rate, NASA-TLX and finally DRT Reaction Time. There were relatively weak correlations between each of the four measures. These results suggest that Task Interaction Time, coupled with a reliable visual demand metric such as DRT Miss Rate, eye glance coding, or visual occlusion, more efficiently detect differences in driver workload between different HMIs compared to DRT Reaction Time and the NASA-TLX questionnaire. These results can be used to improve the understanding of the utility of each of these core driver workload measures in assessing driver distraction potential.     

Effects of visual factors during automated driving of mobility scooters on user comfort: An exploratory simulator study

An automated mobility scooter is expected to provide convenient and safe transportation for users in their living area. However, there is limited research on user comfort compared to that on user safety for the automated driving of mobility scooters. Because the user does not perform driving tasks in automated driving, the visual information from the peripheral environment and visual behavior is expected to closely affect the psychological comfort of the user. This study clarifies the effects of factors related to the automated driving of mobility scooters and the peripheral environment on the visual behavior and psychological comfort of the user. Effects of driving velocity and pedestrian density on the visual behavior and psychophysiological responses of users were investigated via a driving simulator. The results showed that automated driving in an environment with a high pedestrian density can result in a decrease in fixation duration, deactivation of visual processing, sympathetic activation, and feeling of negative emotion. This implies that the assessment of visual behaviors of users is important for the design of automated mobility scooters to improve user comfort.     

A cross-cultural comparison of where drivers choose to look when viewing driving scenes

A substantial proportion of road accidents occur as a result of drivers having poor or insufficient visual search strategies. However, the majority of research into drivers visual search comes from high income Western countries where roads are relatively safe, with less being known about the visual search of drivers from non-western, low and middle income countries with much higher crash rates. This is despite the fact that cross-cultural studies have shown differences in visual search outside of driving between Western and Eastern individuals. The current study aimed to see whether these differences were present in driving by asking UK and Malaysian drivers to select where they would look when viewing images of roads from the perspective of a driver. Results showed that all drivers selected a similar number of focal objects, however there was a difference in the type of background information drivers chose to attend to, with Malaysian drivers selecting more task irrelevant information at the expense of task relevant information. Results suggest that there are cultural differences in what drivers choose to attend to which may contribute to the increased crash rate amongst drivers from low and middle income countries.     

Modeling the influence of mobile phone use distraction on pedestrian reaction times to green signals: A multilevel mixed-effects parametric survival model

Understanding and modeling the influence of mobile phone use on pedestrian behaviour is important for several safety and performance evaluations. Mobile phone use affects pedestrian perception of the surrounding traffic environment and reduces situation awareness. This study investigates the effect of distraction due to mobile phone use (i.e., visual and auditory) on pedestrian reaction time to the pedestrian signal. Traffic video data was collected from four crosswalks in Canada and China. A multilevel mixed-effects accelerated failure time (AFT) approach is used to model pedestrian reaction times, with random intercepts capturing the clustered-specific (countries) heterogeneity. Potential reaction time influencing factors were investigated, including pedestrian demographic attributes, distraction characteristics, and environment-related parameters. Results show that pedestrian reaction times were longer in Canada than in China under the non-distraction and distraction conditions. The auditory and visual distractions increase pedestrian reaction time by 67% and 50% on average, respectively. Pedestrian reactions were slower at road segment crosswalks compared to intersection crosswalks, at higher distraction durations, and for males aged over 40 compared to other pedestrians. Moreover, pedestrian reactions were faster at higher traffic awareness levels.     

Identifying when children with visual impairment share attention: A novel protocol and the impact of visual acuity

BackgroundIn Coordinated Joint Engagement (CJE), children acknowledge that they and their social partners are paying attention to the same object. The achievement of CJE, critical for healthy development, is at risk in infants with visual impairment (VI). Research on CJE in these children is limited because investigators use a child’s gaze switch between social partner and object to index CJE. Research is needed that identifies CJE in children with VI using behaviors that do not require normal vision and that explores the relationship between CJE and visual function. This study aimed to (a) develop a protocol for identifying CJE in children with VI, and (b) explore the relationship between CJE and infants’ visual acuity (VA) and contrast sensitivity (CS), measured with Preferential Looking (PL) techniques and Visual Evoked Potential (VEP).MethodsA protocol that included 9 indices of CJE that did not require normal vision was developed to code videos of 20 infants with VI (mean age =1 year, 6 months, 27 days) and their caregivers. The percentage of CJE episodes in which each index was observed was calculated. Inter-coder reliability was measured using Cohen’s Kappa. Linear regression analysis was used to examine the relationship between the infants’ visual function and CJE.ResultsInter-rater reliability between a first coder and each of two second coders were 0.98 and 0.90 for determining whether the child participated in CJE. The following indices were observed the most (in 43–62 % of CJE): child’s body orientation to caregiver, gaze switch between caregiver and object, and vocalization to caregiver. The only significant model included VA (measured with PL) as a single predictor and explained 26.8 % of the variance in CJE.ConclusionsThe novel protocol can be used to identify CJE in children with VI with good inter-coder reliability. The data suggest that children with lower VA exhibited less CJE.     

Children’s scale errors and object processing: Early evidence for cross-cultural differences

Scale errors are observed when young children make mistakes by attempting to put their bodies into miniature versions of everyday objects. Such errors have been argued to arise from children’s insufficient integration of size into their object representations. The current study investigated whether Japanese and UK children’s (18–24 months old, N = 80) visual exploration in a categorization task related to their scale error production. UK children who showed greater local processing made more scale errors, whereas Japanese children, who overall showed greater global processing, showed no such relationship. These results raise the possibility that children’s suppression of scale errors emerges not from attention to size per se, but from a critical integration of global (i.e., size) and local (i.e., object features) information during object processing, and provide evidence that this mechanism differs cross-culturally.     

Do Humans and Deep Convolutional Neural Networks Use Visual Information Similarly for the Categorization of Natural Scenes?

The investigation of visual categorization has recently been aided by the introduction of deep convolutional neural networks (CNNs), which achieve unprecedented accuracy in picture classification after extensive training. Even if the architecture of CNNs is inspired by the organization of the visual brain, the similarity between CNN and human visual processing remains unclear. Here, we investigated this issue by engaging humans and CNNs in a two-class visual categorization task. To this end, pictures containing animals or vehicles were modified to contain only low/high spatial frequency (HSF) information, or were scrambled in the phase of the spatial frequency spectrum. For all types of degradation, accuracy increased as degradation was reduced for both humans and CNNs; however, the thresholds for accurate categorization varied between humans and CNNs. More remarkable differences were observed for HSF information compared to the other two types of degradation, both in terms of overall accuracy and image-level agreement between humans and CNNs. The difficulty with which the CNNs were shown to categorize high-passed natural scenes was reduced by picture whitening, a procedure which is inspired by how visual systems process natural images. The results are discussed concerning the adaptation to regularities in the visual environment (scene statistics); if the visual characteristics of the environment are not learned by CNNs, their visual categorization may depend only on a subset of the visual information on which humans rely, for example, on low spatial frequency information.