Fixation-related potentials during mobile map assisted navigation in the real world: The effect of landmark visualization style.

An often-proposed enhancement for mobile maps to aid assisted navigation is the presentation of landmark information, yet understanding of the manner in which they should be displayed is limited. In this study, we investigated whether the visualization of landmarks as 3D map symbols with either an abstract or realistic style influenced the subsequent processing of those landmarks during route navigation. We utilized a real-world mobile electroencephalography approach to this question by combining several tools developed to overcome the challenges typically encountered in real-world neuroscience research. We coregistered eye-movement and EEG recordings from 45 participants as they navigated through a real-world environment using a mobile map. Analyses of fixation event-related potentials revealed that the amplitude of the parietal P200 component was enhanced when participants fixated landmarks in the real world that were visualized on the mobile map in a realistic style, and that frontal P200 latencies were prolonged for landmarks depicted in either a realistic or abstract style compared with features of the environment that were not presented on the map, but only for the male participants. In contrast, we did not observe any significant effects of landmark visualization style on visual P1-N1 peaks or the parietal late positive component. Overall, the findings indicate that the cognitive matching process between landmarks seen in the environment and those previously seen on a map is facilitated by more realistic map display, while low-level perceptual processing of landmarks and recall of associated information are unaffected by map visualization style.

Neuroadaptive LBS: towards human-, context-, and task-adaptive mobile geographic information displays to support spatial learning for pedestrian navigation.

Well-designed, neuroadaptive mobile geographic information displays (namGIDs) could improve the lives of millions of mobile citizens of the mostly urban information society who daily need to make time critical and societally relevant decisions while navigating. What are the basic perceptual and neurocognitive processes with which individuals make movement decisions when guided by human- and context-adaptive namGIDs? How can we study this in an ecologically valid way, also outside of the highly controlled laboratory? We report first ideas and results from our unique neuroadaptive research agenda that brings us closer to answering this fundamental empirical question. We present our first implemented methodological solutions of novel ambulatory evaluation methods to study and improve Location-based System (LBS) displays, by critical examination of how perceptual, neurocognitive, psychophysiological, and display design factors might influence decision-making and spatial learning in pedestrian mobility across broad ranges of users and mobility contexts.

Visualizing Uncertainty in Sets.

Set visualization facilitates the exploration and analysis of set-type data. However, how sets should be visualized when the data are uncertain is still an open research challenge. To address the problem of depicting uncertainty in set visualization, we ask 1) which aspects of set type data can be affected by uncertainty and 2) which characteristics of uncertainty influence the visualization design. We answer these research questions by first describing a conceptual framework that brings together 1) the information that is primarily relevant in sets (i.e., set membership, set attributes, and element attributes) and 2) different plausible categories of (un)certainty (i.e., certainty, undefined uncertainty as a binary fact, and defined uncertainty as quantifiable measure). Following the structure of our framework, we systematically discuss basic visualization examples of integrating uncertainty in set visualizations. We draw on existing knowledge about general uncertainty visualization and previous evidence of its effectiveness.

Landmark Sequence Learning from Real-World Route Navigation and the Impact of Navigation Aid Visualisation Style.

Primacy and recency features of serial memory are a hallmark of typical memory functions that have been observed for a wide array of tasks. Recently, the ubiquity of this serial position effect has been supported for objects learned during navigation, with canonical serial position functions observed for sequence memory of landmarks that were encountered along a route during a highly controlled virtual navigation task. In the present study, we extended those findings to a real-world navigation task in which participants actively walked a route through a city whilst using a navigation aid featuring either realistic or abstract landmark visualisation styles. Analyses of serial position functions (i.e., absolute sequence knowledge) and sequence lags (i.e., relative sequence knowledge) yielded similar profiles to those observed in a lab based virtual navigation task from previous work and non-spatial list learning studies. There were strong primacy effects for serial position memory in both conditions; recency effects only in the realistic visualisation condition; a non-uniform distribution of item-lags peaking at lag +1; and an overall bias towards positive lags for both visualisation conditions. The findings demonstrate that benchmark serial position memory effects can be observed in uncontrolled, real-world behaviour. In a navigation context, the results support the notion that general memory mechanisms are involved in spatial learning, and that landmark sequence knowledge is a feature of spatial knowledge which is affected by navigation aids.

Using spontaneous eye blink-related brain activity to investigate cognitive load during mobile map-assisted navigation.

The continuous assessment of pedestrians' cognitive load during a naturalistic mobile map-assisted navigation task is challenging because of limited experimental control over stimulus presentation, human-map-interactions, and other participant responses. To overcome this challenge, the present study takes advantage of navigators' spontaneous eye blinks during navigation to serve as event markers in continuously recorded electroencephalography (EEG) data to assess cognitive load in a mobile map-assisted navigation task. We examined if and how displaying different numbers of landmarks (3 vs. 5 vs. 7) on mobile maps along a given route would influence navigators' cognitive load during navigation in virtual urban environments. Cognitive load was assessed by the peak amplitudes of the blink-related fronto-central N2 and parieto-occipital P3. Our results show increased parieto-occipital P3 amplitude indicating higher cognitive load in the 7-landmark condition, compared to showing 3 or 5 landmarks. Our prior research already demonstrated that participants acquire more spatial knowledge in the 5- and 7-landmark conditions compared to the 3-landmark condition. Together with the current study, we find that showing 5 landmarks, compared to 3 or 7 landmarks, improved spatial learning without overtaxing cognitive load during navigation in different urban environments. Our findings also indicate a possible cognitive load spillover effect during map-assisted wayfinding whereby cognitive load during map viewing might have affected cognitive load during goal-directed locomotion in the environment or vice versa. Our research demonstrates that users' cognitive load and spatial learning should be considered together when designing the display of future navigation aids and that navigators' eye blinks can serve as useful event makers to parse continuous human brain dynamics reflecting cognitive load in naturalistic settings.

Susceptibility of domain experts to color manipulation indicate a need for design principles in data visualization.

Color is key for the visual encoding of data, yet its use reportedly affects decision making in important ways. We examined the impact of various popular color schemes on experts' and lay peoples' map-based decisions in two, geography and neuroscience, scenarios, in an online visualization experiment. We found that changes in color mappings influence domain experts, especially neuroimaging experts, more in their decision-making than novices. Geographic visualization experts exhibited more trust in the unfavorable rainbow color scale than would have been predicted by their suitability ratings and their training, which renders them sensitive to scale appropriateness. Our empirical results make a strong call for increasing scientists' awareness for and training in perceptually salient and cognitively informed design principles in data visualization.

Public Health Interventions, Epidemic Growth, and Regional Variation of the 1918 Influenza Pandemic Outbreak in a Swiss Canton and Its Greater Regions.

Public health interventions implemented during the coronavirus disease 2019 (COVID-19) pandemic are based on experience gained from past pandemics. The 1918 influenza pandemic is the most extensively researched historical influenza outbreak. All 9335 reports available in the State Archives on 121 152 cases of influenza-like illness from the canton of Bern from 473 of 497 municipalities (95.2%) were collected; the cases were registered between 30 June 1918 and 30 June 1919. The overall incidence rates of newly registered cases per week for the 9 greater regions of Bern for both the first and second waves of the pandemic were calculated. Relative incidence rate ratios (RIRRs) were calculated to estimate the change in the slope of incidence curves associated with public health interventions. During the first wave, school closures (RIRR, 0.16 [95% CI, 0.15 to 0.17]) and restrictions of mass gatherings (RIRR, 0.57 [CI, 0.54 to 0.61]) were associated with a deceleration of epidemic growth. During the second wave, in autumn 1918, cantonal authorities initially reacted hesitantly and delegated the responsibility to enact interventions to municipal authorities, which was associated with a lack of containment of the second wave. A premature relaxation of restrictions on mass gatherings was associated with a resurgence of the epidemic (RIRR, 1.18 [CI, 1.12 to 1.25]). Strikingly similar patterns were found in the management of the COVID-19 outbreak in Switzerland, with a considerably higher amplitude and prolonged duration of the second wave and much higher associated rates of hospitalization and mortality.

Digital health and the COVID-19 epidemic: an assessment framework for apps from an epidemiological and legal perspective.

As COVID-19 spreads across the globe, crowdsourced digital technology harbours the potential to improve surveillance and epidemic control, primarily through increased information coverage, higher information speed, fast case tracking and improved proximity tracing. Targeting those aims, COVID-19-related smartphone and web-based health applications are continuously emerging, leading to a multitude of options, raising ethical and legal challenges and potentially overwhelming end users. Building on an existing trustworthiness checklist for digital health applications, we searched the literature and developed a framework to guide the assessment of smartphone and web-based applications that aim to contribute to controlling the current epidemic or mitigating its effects. It further integrates epidemiological subject knowledge and a legal analysis, outlining the mechanisms through which new applications can support the fight against COVID-19. The resulting framework includes 40 questions across 8 domains on “purpose”, “usability”, “information accuracy”, “organisational attributes / reputation”, “transparency”, “privacy” and “user control / self-determination”. All questions should be primarily answerable from publicly available data, as provided by application manufacturers. The framework aims to guide end users in choosing a transparent, safe and valuable application and suggests a set of information items that developers ideally make available to allow a balanced judgement and facilitate the trustworthiness of their products.

Exploring Uncertainty in Canine Cancer Data Sources Through Dasymetric Refinement.

In spite of the potentially groundbreaking environmental sentinel applications, studies of canine cancer data sources are often limited due to undercounting of cancer cases. This source of uncertainty might be further amplified through the process of spatial data aggregation, manifested as part of the modifiable areal unit problem (MAUP). In this study, we explore potential explanatory factors for canine cancer incidence retrieved from the Swiss Canine Cancer Registry (SCCR) in a regression modeling framework. In doing so, we also evaluate differences in statistical performance and associations resulting from a dasymetric refinement of municipal units to their portion of residential land. Our findings document severe underascertainment of cancer cases in the SCCR, which we linked to specific demographic characteristics and reduced use of veterinary care. These explanatory factors result in improved statistical performance when computed using dasymetrically refined units. This suggests that dasymetric mapping should be further tested in geographic correlation studies of canine cancer incidence and in future comparative studies involving human cancers.

How does navigation system behavior influence human behavior?

Navigation systems are ubiquitous tools to assist wayfinders of the mobile information society with various navigational tasks. Whenever such systems assist with self-localization and path planning, they reduce human effort for navigating. Automated navigation assistance benefits navigation performance, but research seems to show that it negatively affects attention to environment properties, spatial knowledge acquisition, and retention of spatial information. Very little is known about how to design navigation systems for pedestrian navigation that increase both navigation performance and spatial knowledge acquisition. To this end, we empirically tested participants (N = 64) using four different navigation system behaviors (between-subject design). Two cognitive processes with varying levels of automation, self-localization and allocation of attention, define navigation system behaviors: either the system automatically executes one of the processes (high level of automation), or the system leaves the decision of when and where to execute the process to the navigator (low level of automation). In two experimental phases, we applied a novel empirical framework for evaluating spatial knowledge acquisition in a real-world outdoor urban environment. First, participants followed a route assisted by a navigation system and, simultaneously, incidentally acquired spatial knowledge. Second, participants reversed the route using the spatial knowledge acquired during the assisted phase, this time without the aid of the navigation system. Results of the route-following phase did not reveal differences in navigation performance across groups using different navigation system behaviors. However, participants using systems with higher levels of automation seemed not to acquire enough spatial knowledge to reverse the route without navigation errors. Furthermore, employing novel methods to analyze mobile eye tracking data revealed distinct patterns of human gaze behavior over time and space. We thus can demonstrate how to increase spatial knowledge acquisition without harming navigation performance when using navigation systems, and how to influence human navigation behavior with varying navigation system behavior. Thus, we provide key findings for the design of intelligent automated navigation systems in real-world scenarios.

Virtual environments as memory training devices in navigational tasks for older adults.

Cognitive training approaches using virtual environments (VEs) might counter age-related visuospatial memory decline and associated difficulties in wayfinding. However, the effects of the visual design of a VE in route learning are not fully understood. Therefore, we created a custom-designed VE optimized for route learning, with adjusted levels of realism and highlighted landmark locations (MixedVE). Herein we tested participants' route recall performance in identifying direction of turn at the intersection with this MixedVE against two baseline alternatives (AbstractVE, RealisticVE). An older vs. a younger group solved the tasks in two stages (immediate vs. delayed recall by one week). Our results demonstrate that the MixedVE facilitates better recall accuracy than the other two VEs for both age groups. Importantly, this pattern persists a week later. Additionally, our older participants were mostly overconfident in their route recall performance, but the MixedVE moderated this potentially detrimental overconfidence. Before the experiment, participants clearly preferred the RealisticVE, whereas after the experiment, most of the younger, and many of the older participants, preferred the MixedVE. Taken together, our findings provide insights into the importance of tailoring visualization design in route learning with VEs. Furthermore, we demonstrate the great potential of the MixedVE and by extension, of similar VEs as memory training devices for route learning, especially for older participants.

The importance of regional models in assessing canine cancer incidences in Switzerland.

Fitting canine cancer incidences through a conventional regression model assumes constant statistical relationships across the study area in estimating the model coefficients. However, it is often more realistic to consider that these relationships may vary over space. Such a condition, known as spatial non-stationarity, implies that the model coefficients need to be estimated locally. In these kinds of local models, the geographic scale, or spatial extent, employed for coefficient estimation may also have a pervasive influence. This is because important variations in the local model coefficients across geographic scales may impact the understanding of local relationships. In this study, we fitted canine cancer incidences across Swiss municipal units through multiple regional models. We computed diagnostic summaries across the different regional models, and contrasted them with the diagnostics of the conventional regression model, using value-by-alpha maps and scalograms. The results of this comparative assessment enabled us to identify variations in the goodness-of-fit and coefficient estimates. We detected spatially non-stationary relationships, in particular, for the variables related to biological risk factors. These variations in the model coefficients were more important at small geographic scales, making a case for the need to model canine cancer incidences locally in contrast to more conventional global approaches. However, we contend that prior to undertaking local modeling efforts, a deeper understanding of the effects of geographic scale is needed to better characterize and identify local model relationships.

Assessing effects of structural zeros on models of canine cancer incidence: a case study of the Swiss Canine Cancer Registry.

Epidemiological research of canine cancers could inform comparative studies of environmental determinants for a number of human cancers. However, such an approach is currently limited because canine cancer data sources are still few in number and often incomplete. Incompleteness is typically due to under-ascertainment of canine cancers. A main reason for this is because dog owners commonly do not seek veterinary care for this diagnosis. Deeper knowledge on under-ascertainment is critical for modelling canine cancer incidence, as an indication of zero incidence might originate from the sole absence of diagnostic examinations within a given sample unit. In the present case study, we investigated effects of such structural zeros on models of canine cancer incidence. In doing so, we contrasted two scenarios for modelling incidence data retrieved from the Swiss Canine Cancer Registry. The first scenario was based on the complete enumeration of incidence data for all Swiss municipal units. The second scenario was based on a filtered sample that systematically discarded structural zeros in those municipal units where no diagnostic examination had been performed. By means of cross-validation, we assessed and contrasted statistical performance and predictive power of the two modelling scenarios. This analytical step allowed us to demonstrate that structural zeros impact on the generalisability of the model of canine cancer incidence, thus challenging future comparative studies of canine and human cancers. The results of this case study show that increased awareness about the effects of structural zeros is critical to epidemiological research.

Not all anxious individuals get lost: Trait anxiety and mental rotation ability interact to explain performance in map-based route learning in men.

Navigation through an environment is a fundamental human activity. Although group differences in navigational ability are documented (e.g., gender), little is known about traits that predict these abilities. Apart from a well-established link between mental rotational abilities and navigational learning abilities, recent studies point to an influence of trait anxiety on the formation of internal cognitive spatial representations. However, it is unknown whether trait anxiety affects the processing of information obtained through externalized representations such as maps. Here, we addressed this question by taking into account emerging evidence indicating impaired performance in executive tasks by high trait anxiety specifically in individuals with lower executive capacities. For this purpose, we tested 104 male participants, previously characterised on trait anxiety and mental rotation ability, on a newly-designed map-based route learning task, where participants matched routes presented dynamically on a city map to one presented immediately before (same/different judgments). We predicted an interaction between trait anxiety and mental rotation ability, specifically that performance in the route learning task would be negatively affected by anxiety in participants with low mental rotation ability. Importantly, and as predicted, an interaction between anxiety and mental rotation ability was observed: trait anxiety negatively affected participants with low-but not high-mental rotation ability. Our study reveals a detrimental role of trait anxiety in map-based route learning and specifies a disadvantage in the processing of map representations for high-anxious individuals with low mental rotation abilities.

Combining user logging with eye tracking for interactive and dynamic applications.

User evaluations of interactive and dynamic applications face various challenges related to the active nature of these displays. For example, users can often zoom and pan on digital products, and these interactions cause changes in the extent and/or level of detail of the stimulus. Therefore, in eye tracking studies, when a user's gaze is at a particular screen position (gaze position) over a period of time, the information contained in this particular position may have changed. Such digital activities are commonplace in modern life, yet it has been difficult to automatically compare the changing information at the viewed position, especially across many participants. Existing solutions typically involve tedious and time-consuming manual work. In this article, we propose a methodology that can overcome this problem. By combining eye tracking with user logging (mouse and keyboard actions) with cartographic products, we are able to accurately reference screen coordinates to geographic coordinates. This referencing approach allows researchers to know which geographic object (location or attribute) corresponds to the gaze coordinates at all times. We tested the proposed approach through two case studies, and discuss the advantages and disadvantages of the applied methodology. Furthermore, the applicability of the proposed approach is discussed with respect to other fields of research that use eye tracking-namely, marketing, sports and movement sciences, and experimental psychology. From these case studies and discussions, we conclude that combining eye tracking and user-logging data is an essential step forward in efficiently studying user behavior with interactive and static stimuli in multiple research fields.

Bundled Visualization of DynamicGraph and Trail Data.

Depicting change captured by dynamic graphs and temporal paths, or trails, is hard. We present two techniques for simplified visualization of such data sets using edge bundles. The first technique uses an efficient image-based bundling method to create smoothly changing bundles from streaming graphs. The second technique adds edge-correspondence data atop of any static bundling algorithm, and is best suited for graph sequences. We show how these techniques can produce simplified visualizations of streaming and sequence graphs. Next, we show how several temporal attributes can be added atop of our dynamic graphs. We illustrate our techniques with data sets from aircraft monitoring, software engineering, and eye-tracking of static and dynamic scenes.

Colorful brains: 14 years of display practice in functional neuroimaging.

Neuroimaging results are typically graphically rendered and color-coded, which influences the process of knowledge generation within neuroscience as well as the public perception of brain research. Analyzing these issues requires empirical information on the display practice in neuroimaging. In our study we evaluated more than 9000 functional images (fMRI and PET) published between 1996 and 2009 with respect to the use of color, image structure, image production software and other factors that may determine the display practice. We demonstrate a variety of display styles despite a remarkable dominance of few image production sites and software systems, outline some tendencies of standardization, and identify shortcomings with respect to color scale explication in neuroimages. We discuss the importance of the finding for knowledge production in neuroimaging, and we make suggestions to improve the display practice in neuroimaging, especially on regimes of color coding.

Thinking about the weather: How display salience and knowledge affect performance in a graphic inference task.

Three experiments examined how bottom-up and top-down processes interact when people view and make inferences from complex visual displays (weather maps). Bottom-up effects of display design were investigated by manipulating the relative visual salience of task-relevant and task-irrelevant information across different maps. Top-down effects of domain knowledge were investigated by examining performance and eye fixations before and after participants learned relevant meteorological principles. Map design and knowledge interacted such that salience had no effect on performance before participants learned the meteorological principles; however, after learning, participants were more accurate if they viewed maps that made task-relevant information more visually salient. Effects of display design on task performance were somewhat dissociated from effects of display design on eye fixations. The results support a model in which eye fixations are directed primarily by top-down factors (task and domain knowledge). They suggest that good display design facilitates performance not just by guiding where viewers look in a complex display but also by facilitating processing of the visual features that represent task-relevant information at a given display location. (PsycINFO Database Record (c) 2009 APA, all rights reserved).