Curious Objects: How Visual Complexity Guides Attention and Engagement

Some things look more complex than others. For example, a crenulate and richly organized leaf may seem more complex than a plain stone. What is the nature of this experience—and why do we have it in the first place? Here, we explore how object complexity serves as an efficiently extracted visual signal that the object merits further exploration. We algorithmically generated a library of geometric shapes and determined their complexity by computing the cumulative surprisal of their internal skeletons—essentially quantifying the “amount of information” within each shape—and then used this approach to ask new questions about the perception of complexity. Experiments 1–3 asked what kind of mental process extracts visual complexity: a slow, deliberate, reflective process (as when we decide that an object is expensive or popular) or a fast, effortless, and automatic process (as when we see that an object is big or blue)? We placed simple and complex objects in visual search arrays and discovered that complex objects were easier to find among simple distractors than simple objects are among complex distractors—a classic search asymmetry indicating that complexity is prioritized in visual processing. Next, we explored the function of complexity: Why do we represent object complexity in the first place? Experiments 4–5 asked subjects to study serially presented objects in a self-paced manner (for a later memory test); subjects dwelled longer on complex objects than simple objects—even when object shape was completely task-irrelevant—suggesting a connection between visual complexity and exploratory engagement. Finally, Experiment 6 connected these implicit measures of complexity to explicit judgments. Collectively, these findings suggest that visual complexity is extracted efficiently and automatically, and even arouses a kind of “perceptual curiosity” about objects that encourages subsequent attentional engagement.     

Generalized Information Theory Meets Human Cognition: Introducing a Unified Framework to Model Uncertainty and Information Search

Searching for information is critical in many situations. In medicine, for instance, careful choice of a diagnostic test can help narrow down the range of plausible diseases that the patient might have. In a probabilistic framework, test selection is often modeled by assuming that people's goal is to reduce uncertainty about possible states of the world. In cognitive science, psychology, and medical decision making, Shannon entropy is the most prominent and most widely used model to formalize probabilistic uncertainty and the reduction thereof. However, a variety of alternative entropy metrics (Hartley, Quadratic, Tsallis, Rényi, and more) are popular in the social and the natural sciences, computer science, and philosophy of science. Particular entropy measures have been predominant in particular research areas, and it is often an open issue whether these divergences emerge from different theoretical and practical goals or are merely due to historical accident. Cutting across disciplinary boundaries, we show that several entropy and entropy reduction measures arise as special cases in a unified formalism, the Sharma–Mittal framework. Using mathematical results, computer simulations, and analyses of published behavioral data, we discuss four key questions: How do various entropy models relate to each other? What insights can be obtained by considering diverse entropy models within a unified framework? What is the psychological plausibility of different entropy models? What new questions and insights for research on human information acquisition follow? Our work provides several new pathways for theoretical and empirical research, reconciling apparently conflicting approaches and empirical findings within a comprehensive and unified information‐theoretic formalism.     

Communication of Information about Genetic Risks: Putting Families at the Center

Genetic information is a family affair. With the expansion of genomic technologies, many new causal genes and variants have been established and the potential for molecular diagnoses increased, with implications not only for patients but also their relatives. The need for genetic counseling and intrafamilial circulation of information on genetic risks grew accordingly. Also, the amount and, particularly, the complexity of the information to convey multiplied. Sharing information about genetic risks with family members, however, has never been an easy matter and often becomes a source of personal and familial conflicts and distress. Ethical requisites generally prevent healthcare professionals from directly contacting their consultands' relatives (affected or still at risk), who often feel unsupported throughout that process. We discuss here the communication of genetic risks to family members. We first consider genomic testing as a basis for family‐centered health care, as opposed to a predominant focus on the individual. We reviewed the literature on sharing genetic risk information with family members, and the associated ethical issues for professionals. Some clinical cases are presented and discussed, and key issues for meeting the needs of individuals and families are addressed. We argue that genetic information is inextricably linked to the family and that communicating about genetic risks is a process grounded within the broader milieu of family relationships and functioning. We conclude for the need for a more family‐centered approach and interventions that can promote sensitive attitudes to the provision of genetic information to and within the family, as well as its inclusion in educational and training programmes for genetic healthcare professionals.     

Delivered as Described: A Successful Case of Cognitive Processing Therapy With an Older Woman Veteran With PTSD

Cognitive processing therapy (CPT) is a first-line, evidence-based treatment for posttraumatic stress disorder (PTSD). Little is known, however, about the use of CPT for older adults. As the United States population continues to grow and age, an understanding of the utility of CPT for older adults is vital. We present a case study describing the assessment and cognitive treatment of a 74-year-old woman veteran with PTSD secondary to military sexual trauma. CPT was associated with decreased PTSD symptoms as measured before and after treatment. Factors contributing to the veteran’s response, as well as contextual and environmental factors, are discussed. The case demonstrates that CPT may be effective for older adults without major modification.     

How is the visual working memory load of driver influenced by information density of traffic signs?

The rapid development of urban roads has resulted in an increase in the amount of information that needs to be displayed on traffic signs. The overloading of information on traffic signs may increase drivers’ visual cognition burden and cause driving errors. It could be an important factor affecting driving safety and result in accidents. To enable drivers to cognize traffic signs, the information density that they could endure under reasonable workload levels should be determined. In this study, we designed and implemented trials to analyze drivers’ visual working memory load (VWML) caused by different information densities (including stimulus intensity (SI) and interval time of stimulus (IS)) of traffic signs. Twenty-four paid participants (12 females) with a mean age of 23.38 years (SD = 1.38) participated in laboratory simulation trials based on the memory retrieval approach. Subjective ratings (rating scale mental effort (RSME)), and performance measurement based on reaction time and accuracy of information-matching task were measured to reflect drivers’ VWML at different information densities. The results show that information density is an important factor affecting drivers’ VWML. The following are the significant observations of the study: (1) The subjective ratings on mental effort increased with increase in the SI. Meanwhile, it first decreased and then increased with increase in the IS. (2) The response accuracy results show that a high accuracy (≥0.7) was achieved by drivers in an IS of 15 s when the SI was at most 14.16 bit/m². Correspondingly, the drivers underwent less mental workload as a result of their better short-term memory characteristic. (3) The mean reaction time was over 1800 ms when the SI was over 14.16 bit/m². This indicated a reduction in the information-processing capability of the drivers. The results indicate that cognition of information of unreasonable density on traffic signs would increase drivers’ VWML. This would, in turn, result in an increase in their reaction time and decrease in accuracy. The threshold of information density was also determined through the experiment. It would satisfy the information demand of drivers and prevent information redundancy. The results contribute to an understanding of drivers’ VWML while cognizing traffic signs with different information densities and provide safety, effectiveness, and information continuity considerations for the design and setting of traffic signs.     

A data–information–knowledge cycle for modeling driving behavior

When talking about automation, “autonomous vehicles”, often abbreviated as AVs, come to mind. In transitioning from the “driver” mode to the different automation levels, there is an inevitable need for modeling driving behavior. This often happens through data collection from experiments and studies, but also information extraction, a key step in behavioral modeling. Particularly, naturalistic driving studies and field operational trials are used to collect meaningful data on drivers’ interactions in real–world conditions. On the other hand, information extraction methods allow to predict or mimic driving behavior, by using a set of statistical learning methods. In simple words, the way to understand drivers’ needs and wants in the era of automation can be represented in a data–information cycle, starting from data collection, and ending with information extraction. To develop this cycle, this research reviews studies with keywords “data collection”, “information extraction”, “AVs”, while keeping the focus on driving behavior. The resulting review led to a screening of about 161 papers, out of which about 30 were selected for a detailed analysis. The analysis included an investigation of the methods and equipment used for data collection, the features collected, the size and frequency of the data along with the main problems associated with the different sensory equipment; the studies also looked at the models used to extract information, including various statistical techniques used in AV studies. This paved the way to the development of a framework for data analytics and fusion, allowing the use of highly heterogeneous data to reach the defined objectives; for this paper, the example of impacts of AVs on a network level and AV acceptance is given. The authors suggest that such a framework could be extended and transferred across the various transportation sectors.     

Visual-Verbal Self/Other-Referential Processing Task: Direct vs. indirect assessment, valence, and experiential correlates

This study evaluated a new methodology for assessing valenced Self-Referential Processing (SRP) in comparison with Other-Referential Processing (ORP). Participants viewed pictures of themselves during certain trials and same-gender strangers during others, intermixed between valenced words. Participants internally-rehearsed the words “I am” or “He/she is” when presented with the respective pictures and read the valenced words, thereby associating the self/other with positivity/negativity on different trials. Participants self-monitored their affective response, and their degree of attention and/or rate of internal speech/reading speed was measured indirectly via button-press response time (RT). Results in 91 young adults demonstrated a self-positivity bias in survey ratings, stronger affective responses during SRP than ORP, slower RT during SRP than ORP, and slower RT during positive than negative valence. Difference scores between SRP of negative- vs. positive-valence trials, and between SRP vs. ORP of negative-valence trials, were correlated among survey ratings, affective responses, and RT. Finally, content analyses of phenomenological reports showed that task conditions differentially provoked a number of socioemotional experiences during both SRP and ORP (e.g., jealousy-envy, sympathy-pity, good will/pride). We discuss potential applications of the task in the study of personality and individual differences.     

Self–other decision making and loss aversion

In eight studies, we tested the prediction that making choices for others involves less loss aversion than making choices for the self. We found that loss aversion is significantly lessened among people choosing for others in scenarios describing riskless choice (Study 1), gambling (Studies 2 and 3), and social aspects of life, such as likeably and status (Studies 4a–e). Moreover, we found this pattern in relatively realistic conditions where people are rewarded for making desirable (i.e., profitable) choices for others (Study 2), when the other for whom a choice is made is physically present (Study 3), and when real money is at stake (Studies 2 and 3). Finally, we found loss aversion is moderated when factors associated with self–other differences in decision making are taken into account, such as decision makers’ construal level (Study 4a), regulatory focus (Study 4b), degree of information seeking (Study 4c), omission bias (Study 4d), and power (Study 4e).     

事件提示和时间提示对新异干扰的影响—— 来自听视跨通道和听通道的证据

采用Oddball范式考察听视跨感觉通道和听感觉通道中“无关刺激”或“无关属性”的信号提示对新异干扰的影响。实验1和实验2分别比较了听视跨通道和听通道中时间事件提示、时间提示和事件提示三种条件。结果表明：(1)时间提示条件下新异干扰效应消失, 而事件提示条件下新异干扰效应仍存在。无关刺激意外变化引起的靶任务行为受损, 不仅与偏差刺激的小概率和新颖性有关, 而且与干扰刺激与靶子间提示信号关联有关, 这种提示关联中事件发生的提示功能比时间间隔的提示功能更为重要。(2)听通道下新异干扰与视听跨通道结果一致, 无关属性也会起到提示信号作用, 同样事件提示功能比时间提示功能更重要。