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Cognitive theories on causes of developmental dyslexia can be divided into language-specific and general accounts. While the former assume that words are special in that associated processing problems are rooted in language-related cognition (e.g., phonology) deficits, the latter propose that dyslexia is rather rooted in a general impairment of cognitive (e.g., visual and/or auditory) processing streams. In the present study, we examined to what extent dyslexia (typically characterized by poor orthographic representations) may be associated with a general deficit in visual long-term memory (LTM) for details. We compared object- and detail-related visual LTM performance (and phonological skills) between dyslexic primary school children and IQ-, age-, and gender-matched controls. The results revealed that while the overall amount of LTM errors was comparable between groups, dyslexic children exhibited a greater portion of detail-related errors. The results suggest that not only phonological, but also general visual resolution deficits in LTM may play an important role in developmental dyslexia.
Oculomotor dominance in multitasking: Mechanisms of conflict resolution in cross-modal action
(2014)
In daily life, eye movement control usually occurs in the context of concurrent action demands in other effector domains. However, little research has focused on understanding how such cross-modal action demands are coordinated, especially when conflicting information needs to be processed conjunctly in different action modalities. In two experiments, we address this issue by studying vocal responses in the context of spatially conflicting eye movements (Experiment 1) and in the context of spatially conflicting manual actions (Experiment 2, under controlled eye fixation conditions). Crucially, a comparison across experiments allows us to assess resource scheduling priorities among the three effector systems by comparing the same (vocal) response demands in the context of eye movements in contrast to manual responses. The results indicate that in situations involving response conflict, eye movements are prioritized over concurrent action demands in another effector system. This oculomotor dominance effect corroborates previous observations in the context of multiple action demands without spatial response conflict. Furthermore, and in line with recent theoretical accounts of parallel multiple action control, resource scheduling patterns appear to be flexibly adjustable based on the temporal proximity of the two actions that need to be performed.
Out of the corner of the driver's eye: Peripheral processing of hazards in static traffic scenes
(2016)
Effective gaze control in traffic, based on peripheral visual information, is important to avoid hazards. Whereas previous hazard perception research mainly focused on skill-component development (e.g., orientation and hazard processing), little is known about the role and dynamics of peripheral vision in hazard perception. We analyzed eye movement data from a study in which participants scanned static traffic scenes including medium-level versus dangerous hazards and focused on characteristics of fixations prior to entering the hazard region. We found that initial saccade amplitudes into the hazard region were substantially longer for dangerous (vs. medium-level) hazards, irrespective of participants' driving expertise. An analysis of the temporal dynamics of this hazard-level dependent saccade targeting distance effect revealed that peripheral hazard-level processing occurred around 200–400 ms during the course of the fixation prior to entering the hazard region. An additional psychophysical hazard detection experiment, in which hazard eccentricity was manipulated, revealed better detection for dangerous (vs. medium-level) hazards in both central and peripheral vision. Furthermore, we observed a significant perceptual decline from center to periphery for medium (but not for highly) dangerous hazards. Overall, the results suggest that hazard processing is remarkably effective in peripheral vision and utilized to guide the eyes toward potential hazards.
Cross-modal Action Complexity: Action- and Rule-related Memory Retrieval in Dual-response Control
(2017)
Normally, we do not act within a single effector system only, but rather coordinate actions across several output modules (cross-modal action). Such cross-modal action demands can vary substantially with respect to their complexity in terms of the number of task-relevant response combinations and to-be-retrieved stimulus-response (S-R) mapping rules. In the present study, we study the impact of these two types of cross-modal action complexity on dual-response costs (i.e., performance differences between single- and dual-action demands). In Experiment 1, we combined a manual and an oculomotor task, each involving four response alternatives. Crucially, one (unconstrained) condition involved all 16 possible combinations of response alternatives, whereas a constrained condition involved only a subset of possible response combinations. The results revealed that preparing for a larger number of response combinations yielded a significant, but moderate increase in dual-response costs. In Experiment 2, we utilized one common lateralized auditory (e.g., left) stimulus to trigger incompatible response compounds (e.g., left saccade and right key press or vice versa). While one condition only involved one set of task-relevant S-R rules, another condition involved two sets of task-relevant rules (coded by stimulus type: noise/tone), while the number of task-relevant response combinations was the same in both conditions. Here, an increase in the number of to-be-retrieved S-R rules was associated with a substantial increase in dual-response costs that were also modulated on a trial-by-trial basis when switching between rules. Taken together, the results shed further light on the dependency of cross-modal action control on both action- and rule-related memory retrieval processes.
This is a pilot study that examined the effect of cell-phone conversation on cognition using a continuous multitasking paradigm. Current theorizing argues that phone conversation affects behavior (e.g., driving) by interfering at a level of cognitive processes (not peripheral activity) and by implying an attentional-failure account. Within the framework of an intermittent spare–utilized capacity threading model, we examined the effect of aspects of (secondary-task) phone conversation on (primary-task) continuous arithmetic performance, asking whether phone use makes components of automatic and controlled information-processing (i.e., easy vs. hard mental arithmetic) run more slowly, or alternatively, makes processing run less reliably albeit with the same processing speed. The results can be summarized as follows: While neither expecting a text message nor expecting an impending phone call had any detrimental effects on performance, active phone conversation was clearly detrimental to primary-task performance. Crucially, the decrement imposed by secondary-task (conversation) was not due to a constant slowdown but is better be characterized by an occasional breakdown of information processing, which differentially affected automatic and controlled components of primary-task processing. In conclusion, these findings support the notion that phone conversation makes individuals not constantly slower but more vulnerable to commit attention failure, and in this way, hampers stability of (primary-task) information processing.
A negative mood-congruent attention bias has been consistently observed, for example, in clinical studies on major depression. This bias is assumed to be dysfunctional in that it supports maintaining a sad mood, whereas a potentially adaptive role has largely been neglected. Previous experiments involving sad mood induction techniques found a negative mood-congruent attention bias specifically for young individuals, explained by an adaptive need for information transfer in the service of mood regulation. In the present study we investigated the attentional bias in typically developing children (aged 6–12 years) when happy and sad moods were induced. Crucially, we manipulated the age (adult vs. child) of the displayed pairs of facial expressions depicting sadness, anger, fear and happiness. The results indicate that sad children indeed exhibited a mood specific attention bias toward sad facial expressions. Additionally, this bias was more pronounced for adult faces. Results are discussed in the context of an information gain which should be stronger when looking at adult faces due to their more expansive life experience. These findings bear implications for both research methods and future interventions.
Models of eye-movement control distinguish between different control levels, ranging from automatic (bottom-up, stimulus-driven selection) and automatized (based on well-learned routines) to voluntary (top-down, goal-driven selection, e.g., based on instructions). However, one type of voluntary control has yet only been examined in the manual and not in the oculomotor domain, namely free-choice selection among arbitrary targets, that is, targets that are of equal interest from both a bottom-up and top-down processing perspective. Here, we ask which features of targets (identity- or location-related) are used to determine such oculomotor free-choice behavior. In two experiments, participants executed a saccade to one of four peripheral targets in three different choice conditions: unconstrained free choice, constrained free choice based on target identity (color), and constrained free choice based on target location. The analysis of choice frequencies revealed that unconstrained free-choice selection closely resembled constrained choice based on target location. The results suggest that free-choice oculomotor control is mainly guided by spatial (location-based) target characteristics. We explain these results by assuming that participants tend to avoid less parsimonious recoding of target-identity representations into spatial codes, the latter being a necessary prerequisite to configure oculomotor commands.
Background
While the coordination of oculomotor and manual behavior is essential for driving a car, surprisingly little is known about this interaction, especially in situations requiring a quick steering reaction. In the present study, we analyzed oculomotor gaze and manual steering behavior in approach and avoidance tasks. Three task blocks were implemented within a dynamic simulated driving environment requiring the driver either to steer away from/toward a visual stimulus or to switch between both tasks.
Results
Task blocks requiring task switches were associated with higher manual response times and increased error rates. Manual response times did not significantly differ depending on whether drivers had to steer away from vs toward a stimulus, whereas oculomotor response times and gaze pattern variability were increased when drivers had to steer away from a stimulus compared to steering toward a stimulus.
Conclusion
The increased manual response times and error rates in mixed tasks indicate performance costs associated with cognitive flexibility, while the increased oculomotor response times and gaze pattern variability indicate a parsimonious cross-modal action control strategy (avoiding stimulus fixation prior to steering away from it) for the avoidance scenario. Several discrepancies between these results and typical eye–hand interaction patterns in basic laboratory research suggest that the specific goals and complex perceptual affordances associated with driving a vehicle strongly shape cross-modal control of behavior.
When processing of two tasks overlaps, performance is known to suffer. In the well-established psychological refractory period (PRP) paradigm, tasks are triggered by two stimuli with a short temporal delay (stimulus onset asynchrony; SOA), thereby allowing control of the degree of task overlap. A decrease of the SOA reliably yields longer RTs of the task associated with the second stimulus (Task 2) while performance in the other task (Task 1) remains largely unaffected. This Task 2-specific SOA effect is usually interpreted in terms of central capacity limitations. Particularly, it has been assumed that response selection in Task 2 is delayed due to the allocation of less capacity until this process has been completed in Task 1. Recently, another important factor determining task prioritization has been proposed—namely, the particular effector systems associated with tasks. Here, we study both sources of task prioritization simultaneously by systematically combining three different effector systems (pairwise combinations of oculomotor, vocal, and manual responses) in the PRP paradigm. Specifically, we asked whether task order-based task prioritization (SOA effect) is modulated as a function of Task 2 effector system. The results indicate a modulation of SOA effects when the same (oculomotor) Task 1 is combined with a vocal versus a manual Task 2. This is incompatible with the assumption that SOA effects are solely determined by Task 1 response selection duration. Instead, they support the view that dual-task processing bottlenecks are resolved by establishing a capacity allocation scheme fed by multiple input factors, including attentional weights associated with particular effector systems.
Data analytics as a field is currently at a crucial point in its development, as a commoditization takes place in the context of increasing amounts of data, more user diversity, and automated analysis solutions, the latter potentially eliminating the need for expert analysts. A central hypothesis of the present paper is that data visualizations should be adapted to both the user and the context. This idea was initially addressed in Study 1, which demonstrated substantial interindividual variability among a group of experts when freely choosing an option to visualize data sets. To lay the theoretical groundwork for a systematic, taxonomic approach, a user model combining user traits, states, strategies, and actions was proposed and further evaluated empirically in Studies 2 and 3. The results implied that for adapting to user traits, statistical expertise is a relevant dimension that should be considered. Additionally, for adapting to user states different user intentions such as monitoring and analysis should be accounted for. These results were used to develop a taxonomy which adapts visualization recommendations to these (and other) factors. A preliminary attempt to validate the taxonomy in Study 4 tested its visualization recommendations with a group of experts. While the corresponding results were somewhat ambiguous overall, some aspects nevertheless supported the claim that a user-adaptive data visualization approach based on the principles outlined in the taxonomy can indeed be useful. While the present approach to user adaptivity is still in its infancy and should be extended (e.g., by testing more participants), the general approach appears to be very promising.