The perception of good and bad natural scene category exemplars

Images of natural scenes are easily categorized by human observers. Recent work has shown that “good” images, or those that are more representative of their category, are more easily categorized than “bad” ones. The present research investigates a novel hypothesis: that “good” images of scenes are more easily perceived than bad images. Participants performed a two-alternative forced choice task in which they indicated whether an image was an intact or phase-scrambled scene photograph. In this task, observers were able to “see” good images better than bad scenes, more accurately detecting their brief presentations. This effect is not influenced by prior knowledge about the categories used in the experiment. Scene inversion is also shown to have a similar effect on the intact/scrambled discrimination effect, but it does not interact with category representativeness, indicating that the advantage conferred by good exemplars is invariant to inversion. Finally, the good and bad images were analyzed using an objective estimate of image typicality, and this factor was also shown to predict observers' ability to detect the images. These results document a close relationship between natural scene categorization and detection, suggesting that rapid scene perception is strongly influenced by our experience with typical and representative environments

Portable Weather Applications for General Aviation Pilots

Objective: The objective of this study was to examine the potential benefits and impact on pilot behavior from the use of portable weather applications. Method: Seventy general aviation (GA) pilots participated in the study. Each pilot was randomly assigned to an experimental or a control group and flew a simulated single-engine GA aircraft, initially under visual meteorological conditions (VMC). The experimental group was equipped with a portable weather application during flight. We recorded measures for weather situation awareness (WSA), decision making, cognitive engagement, and distance from the aircraft to hazardous weather. Results: We found positive effects from the use of the portable weather application, with an increased WSA for the experimental group, which resulted in credibly larger route deviations and credibly greater distances to hazardous weather (≥30 dBZ cells) compared with the control group. Nevertheless, both groups flew less than 20 statute miles from hazardous weather cells, thus failing to follow current weather-avoidance guidelines. We also found a credibly higher cognitive engagement (prefrontal oxygenation levels) for the experimental group, possibly reflecting increased flight planning and decision making on the part of the pilots. Conclusion: Overall, the study outcome supports our hypothesis that portable weather displays can be used without degrading pilot performance on safety-related flight tasks, actions, and decisions as measured within the constraints of the present study. However, it also shows that an increased WSA does not automatically translate to enhanced flight behavior. Application: The study outcome contributes to our knowledge of the effect of portable weather applications on pilot behavior and decision making

The Effect of Weather State-Change Notifications on General Aviation Pilots' Behavior, Cognitive Engagement, and Weather Situation Awareness

Objective: Results from the WTIC Phase 2 study showed that general aviation (GA) pilots performed poorly at detecting aviation routine weather report (METAR) symbol changes during flight (Ahlstrom & Suss, 2014)—attributed to the change-blindness phenomena. Here, we address this gap by examining the potential benefits of weather state-change notifications on pilots’ behavior and Weather Situation Awareness (WSA) during a simulated flight. A second objective of this study was to assess pilot sensitivity to weather symbology changes on Topological, Visual Flight Rules (VFR), and Instrument Flight Rules (IFR) aeronautical map backgrounds in a change-detection experiment. Method: Seventy-three GA pilots volunteered to participate in the study. During a simulated weather scenario, participants were randomly assigned to an experimental or a control group and flew a single-engine GA aircraft, initially under Visual Meteorological Conditions (VMC). The experimental group was equipped with a vibrating bracelet that notified participants of state-changes to displayed METAR, Special-Use Airspace (SUA), and Significant Meteorological Information (SIGMET) symbols. During the simulation, we recorded each participant’s horizontal and vertical flight profile, WSA, decision-making, cognitive engagement, weather presentation interaction, and distance from the aircraft to hazardous weather. Finally, we used a change-detection experiment to assess participant sensitivity to changes in weather symbols on three different backgrounds. Results: By assessing WSA, we found that the experimental group provided credibly more communications of weather information and maneuver/course change information and a higher number of “out-the-window” reports to the pilot following than the control group provided. This supports our hypothesis that weather state-change notifications result in earlier and more accurate recognition of weather state-changes and, thereby, positively improves participant WSA. The results of distance-to-weather analyses showed that both groups kept similar distances to 30 dBZ precipitation cells. It also showed, however, that participants in both groups flew closer to hazardous weather than what is recommended in current guidelines. Although not a credible difference, there were more participant reports of VFR flights into Instrument Meteorological Conditions (IMC) in the control group (N = 33) than in the experimental group (N = 27). When analyzing the functional near-infrared (fNIR) data, we found credibly higher prefrontal oxygenation levels in the control group compared to the experimental group. We attribute the reduced cognitive load in the experimental group to increased participant WSA. Because of the state-change notifications, participants were more attentive to information on the weather presentation, which enhanced planning and decision-making and reduced cognitive load. Finally, participant discrimination performance for symbol changes was low on the Topological, IFR, and VFR map backgrounds when compared to the performance of a simulated group of ideal observers. We interpret these findings to indicate that much work is still needed to optimize the symbology for cockpit weather presentations to achieve good symbol discrimination and reduce the time needed to differentiate weather presentation elements on all backgrounds. Conclusion: Weather state-change notifications improved WSA and reduced cognitive workload. However, these improvements did not translate to changes in participants’ weather-avoiding behavior, indicating gaps in pilot understanding of the information or gaps in pilot decision making. Applications: This simulation is part of an ongoing assessment of the effects of weather-presentation symbology related to the optimization of weather presentations in cockpits

Initial Assessment of Portable Weather Presentations for General Aviation Pilots

Objective: (a) To examine the potential benefits and effect on pilot flying behavior from the use of portable weather presentations and (b) to assess pilot sensitivity to weather symbology changes. Method: Seventy-three General Aviation (GA) pilots volunteered to participate in the study. During simulated flights, participants were randomly assigned either to an experimental group or to a control group and flew a simulated single-engine GA aircraft under Visual Flight Rules (VFR) while avoiding hazardous weather. The experimental group was equipped with a portable “weather application” during flight. We recorded flight profile parameters, Weather Situation Awareness (WSA), decision-making, cognitive engagement, weather-application interaction, and aircraft distance-to-weather. Using a change-detection experiment, we assessed participants’ sensitivity to symbology changes in portable weather presentations. Results: We found positive effects from the use of the portable weather application with an increased WSA for the experimental group. This resulted in credibly larger route deviations and credibly greater distances to hazardous weather (≥ 30 dBZ cells) in the experimental group than in the control group. Nevertheless, both groups flew too closely to hazardous weather compared to what is recommended in current Federal Aviation Administration guidelines. We also found a credibly higher cognitive engagement (prefrontal oxygenation levels) for the experimental group, possibly reflecting increased flight planning and decision-making among the participants. Using a change-detection experiment, we assessed participant discriminability of signal and noise trials using cloud ceiling, precipitation, and PIREP information. We found that discrimination performance was low for all conditions in comparison to the performance of a group of ideal observers as measured by the signal detection (SD) metric for discriminability (d). Conclusion: The study outcome supports our hypothesis that the portable weather application can be used without degrading pilot performance on safety-related flight tasks, actions, and decisions. However, it also shows that an increased WSA does not automatically transfer over to improved flight behavior. The outcome shows that participants could learn and operate the portable weather application with relative ease, but training is necessary to help pilots translate weather information into improved flight-behavior strategies. The outcome from the change-detection experiment shows that work is still needed to optimize the symbology for portable cockpit weather presentations. Applications: This simulation is part of an initial assessment of the effects of portable weather applications on pilot behavior and decision-making

Categorization influences detection: A perceptual advantage for representative exemplars of natural scene categories

Traditional models of recognition and categorization proceed from registering low-level features, perceptually organizing that input, and linking it with stored representations. Recent evidence, however, suggests that this serial model may not be accurate, with object and category knowledge affecting rather than following early visual processing. Here, we show that the degree to which an image exemplifies its category influences how easily it is detected. Participants performed a twoalternative forced-choice task in which they indicated whether a briefly presented image was an intact or phase-scrambled scene photograph. Critically, the category of the scene is irrelevant to the detection task. We nonetheless found that participants ''see'' good images better, more accurately discriminating them from phase-scrambled images than bad scenes, and this advantage is apparent regardless of whether participants are asked to consider category during the experiment or not. We then demonstrate that good exemplars are more similar to same-category images than bad exemplars, influencing behavior in two ways: First, prototypical images are easier to detect, and second, intact good scenes are more likely than bad to have been primed by a previous trial

Modeling the Effect of Selection History on Pop-Out Visual Search

<div><p>While attentional effects in visual selection tasks have traditionally been assigned “top-down” or “bottom-up” origins, more recently it has been proposed that there are three major factors affecting visual selection: (1) physical salience, (2) current goals and (3) selection history. Here, we look further into <i>selection history</i> by investigating Priming of Pop-out (POP) and the Distractor Preview Effect (DPE), two inter-trial effects that demonstrate the influence of recent history on visual search performance. Using the Ratcliff diffusion model, we model observed saccadic selections from an oddball search experiment that included a mix of both POP and DPE conditions. We find that the Ratcliff diffusion model can effectively model the manner in which selection history affects current attentional control in visual inter-trial effects. The model evidence shows that bias regarding the current trial's most likely target color is the most critical parameter underlying the effect of selection history. Our results are consistent with the view that the 3-item color-oddball task used for POP and DPE experiments is best understood as an attentional decision making task.</p></div

An Illustration of the Ratcliff Diffusion Model.

<p>Evidence starts accumulating at starting point <i>z</i> (inter-trial variation <i>S_z</i>). It accumulates with a drift rate mean of <i>v</i> and standard deviation of <i>s</i> (a scaling parameter not shown). The mean drift rate has an inter-trial variation of <i>η</i>. The evidence accumulates towards one of two decision thresholds, which are separated by the boundary separation <i>a</i>. An additional parameter is the non-decision time, <i>T_er</i> (inter-trial variation <i>S_t</i>).</p

Best-Fit Parameters of Full Model.

<p>Best-Fit Parameters of Full Model.</p

Model Goodness of Fit.

<p>(a) Quantile probability plots for the correct trials. These compare reaction time distributions from the model (lines) with empirical reaction times (x's) for every experimental condition. (b) Number of error trials generated by the model (red) is compared to the number of empirical error trials (blue) for every experimental condition.</p

AIC Model Comparison.

<p>Akaike information criterion (AIC) values are compared between several sub-models of the RDM. Each sub-model has one or two constrained parameters compared with the full model. This comparison is done for every subject, and the sum of AIC values is used for an across-subjects comparison. Note that AIC biases model selection towards models with more parameters.</p