Neural Signals of Video Advertisement Liking:Insights into Psychological Processes and their Temporal Dynamics

What drives the liking of video advertisements? The authors analyzed neural signals during ad exposure from three functional magnetic resonance imaging (fMRI) data sets (113 participants from two countries watching 85 video ads) with automated meta-analytic decoding (Neurosynth). These brain-based measures of psychological processes—including perception and language (information processing), executive function and memory (cognitive functions), and social cognition and emotion (social-affective response)—predicted subsequent self-report ad liking, with emotion and memory being the earliest predictorsafter the first three seconds. Over the span of ad exposure, while the predictiveness of emotion peaked early and fell, that of social cognition had a peak-and-stable pattern, followed by a late peak of predictiveness in perception and executive function.At the aggregate level, neural signals—especially those associated with social-affective response—improved the prediction of out-of-sample ad liking compared with traditional anatomically based neuroimaging analysis and self-report liking. Finally, earlyonset social-affective response predicted population ad liking in a behavioral replication. Overall, this study helps delineate the psychological mechanisms underlying ad processing and ad liking and proposes a novel neuroscience-based approach for generating psychological insights and improving out-of-sample predictions

A Human-Centered Approach for the Design of Perimeter Office Spaces Based on Visual Environment Criteria

With perimeter office spaces with large glazing facades being an indisputable trend in modern architecture, human comfort has been in the scope of Building science; the necessity to improve occupants’ satisfaction, along with maintaining sustainability has become apparent, as productivity and even the well-being of occupants are connected with maintaining a pleasant environment in the interior. While thermal comfort has been extensively studied, the satisfaction with the visual environment has still aspects that are either inadequately explained, or even entirely absent from literature. This Thesis investigated most aspects of the visual environment, including visual comfort, lighting energy performance through the utilization of daylight and connection to the outdoors, using experimental studies, simulation studies and human subjects’ based experiments

Screen real estate ownership based mechanism for negotiating advertisement display

As popularity of online video grows, a number of models of advertising are emerging. It is typically the brokers – usually the operators of websites – who maintain the balance between content and advertising. Existing approaches focus primarily on personalizing advertisements for viewer segments, with minimal decision-making capacity for individual viewers. We take a resource ownership view on this problem. We view consumers’ attention space, which can be abstracted as a display screen for an engaged viewer, as precious resource owned by the viewer. Viewers pay for the content they wish to view in dollars, as well as in terms of their attention. Specifically, advertisers may make partial payment for a viewer’s content, in return for receiving the viewer’s attention to their advertising. Our approach, named “FlexAdSense”, is based on CyberOrgs model, which encapsulates distributed owned resources for multi-agent computations. We build a market of viewers’ attention space in which advertisers can trade, just as viewers can trade in a market of content. We have developed key mechanisms to give viewers flexible control over the display of advertisements in real time. Specific policies needed for automated negotiations can be plugged-in. This approach relaxes the exclusivity of the relationship between advertisers and brokers, and empowers viewers, enhancing their viewing experience. This thesis presents the rationale, design, implementation, and evaluation of FlexAdSense. Feature comparison with existing advertising mechanisms shows how FlexAdSense enables viewers to control with fine-grained flexibility. Experimental results demonstrate the scalability of the approach, as the number of viewers increases. A preliminary analysis of user overhead illustrates minimal attention overhead for viewers as they customize their policies

Contributions to Variable Selection in Complexly Sampled Case-control Models, Epidemiology of 72-hour Emergency Department Readmission, and Out-of-site Migration Rate Estimation Using Pseudo-tagged Longitudinal Data

This work consists of three different projects. In the first project, I analyze complexly sampled survey data, representative of the US population, to determine what lifestyle behaviors and notions held by participants are most significant with having had a cancer diagnosis. A logistic regression model was built using automatic variable selection with forward selection with backwards elimination. Our results show that sunscreen usage, level of agreeing with the statement behaviors can affect high blood pressure , age, intent to eat more or less fruit, average daily hours spent watching tv or playing video games, and level of agreeing with the statement I would rather not know my chances of getting cancer were significant variables associated with a having had a cancer diagnosis. In the second project, I developed a novel method for tracking untagged organisms over a 20-year period, data collected at 6-month intervals. Our results showed that the staying rates, emigration/mortality rates, and immigration rates were approximately 50%. We also found that 44.1% of the limpets emigrate/die within their first 6-month time interval. In the third project, I investigated the most significant predictors of a return to the Emergency Department within 72 hours, with a focus on adult patients with a respiratory condition. High return rates are a burden to both the Emergency Department and patients. We used a dataset extracted from a database containing billions of patient visits and implemented a nested mixed effects model to determine the most significant predictors. There were 20 risk factors found, including demographic variables, diagnostic conditions, and respiratory conditions

Aerospace Medicine and Biology. A continuing bibliography with indexes

This bibliography lists 244 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1981. Aerospace medicine and aerobiology topics are included. Listings for physiological factors, astronaut performance, control theory, artificial intelligence, and cybernetics are included

Socio-Cognitive and Affective Computing

Social cognition focuses on how people process, store, and apply information about other people and social situations. It focuses on the role that cognitive processes play in social interactions. On the other hand, the term cognitive computing is generally used to refer to new hardware and/or software that mimics the functioning of the human brain and helps to improve human decision-making. In this sense, it is a type of computing with the goal of discovering more accurate models of how the human brain/mind senses, reasons, and responds to stimuli. Socio-Cognitive Computing should be understood as a set of theoretical interdisciplinary frameworks, methodologies, methods and hardware/software tools to model how the human brain mediates social interactions. In addition, Affective Computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects, a fundamental aspect of socio-cognitive neuroscience. It is an interdisciplinary field spanning computer science, electrical engineering, psychology, and cognitive science. Physiological Computing is a category of technology in which electrophysiological data recorded directly from human activity are used to interface with a computing device. This technology becomes even more relevant when computing can be integrated pervasively in everyday life environments. Thus, Socio-Cognitive and Affective Computing systems should be able to adapt their behavior according to the Physiological Computing paradigm. This book integrates proposals from researchers who use signals from the brain and/or body to infer people's intentions and psychological state in smart computing systems. The design of this kind of systems combines knowledge and methods of ubiquitous and pervasive computing, as well as physiological data measurement and processing, with those of socio-cognitive and affective computing

Reduced emotional resonance in bilinguals’ L2: Potential causes, methods of measurement, and behavioural implications

Bilinguals often report feeling “less” in their second language (L2). While a speaker might be fully proficient in their L2, it may not feel the same as one’s L1 does; in some cases bilinguals feel like their L2 is more emotionally distant, or even fake. This phenomenon, called reduced emotional resonance of L2, has been studied using a number of different methodologies ranging from questionnaire-based approaches to physiological measurement of emotion. The field, while truly interdisciplinary, lacks consensus on measurement practices. This thesis aims to address some of the most prevalent methodological issues in studying reduced emotional resonance of L2, namely how the word stimuli should be selected and normed, and provide guidance to conducting studies with word stimuli. This thesis presents six studies, which investigate the causes, measurement methods and implications of reduced emotional resonance in bilinguals’ L2. Chapter 2 focuses on the causes of reduced emotional resonance, and measures it with pupillometry. The potential causes of reduced emotional resonance are examined by trying to predict bilinguals’ physiological responses to emotional language from their language background information. Chapters 3-5 focus on the methodological aspects of reduced emotional resonance. Chapter 3 attempts to contrast different physiological measurement techniques of emotion. Comparing pupillometry and skin-conductance measurement, the chapter points out differences in paradigm design and sensitivity of these two techniques. Chapter 4 investigates the reliability of cognitive paradigms as measures of bilingual emotion, points out the importance of including stimulus item covariates in both stimulus selection, as well as analysis stage, and discusses why the use of translation equivalents is problematic. In this chapter, we compare a Lexical Decision Task to a pupillometry task in bilinguals’ L1 vs. L2, and in bilinguals vs. monolinguals. Chapter 5 looks into metacognitive measurement and compares affective word ratings with a pupillometry task to establish whether physiological responses to, and conscious evaluations of emotional words are related. Chapter 6 focuses on the behavioural implications of reduced emotional resonance of L2. Behavioural implications have typically been studied in the context of moral decision-making. Here, we expand this literature to attributions. Through two experiments, this chapter investigates whether Optimality bias (assigning more blame to actors who make suboptimal choices) will be mediated by the Foreign Language Effect. In other words, whether doing the experiment in one’s L2 will mitigate the Optimality bias. Finally, chapter 7 discusses the key findings and common themes to stem from the experiments, as well as the limitations and potential future directions for the field. The main contribution of this thesis is to provide systematic, methodology-focused work on reduced emotional resonance in bilinguals’ L2, to point out methodological inconsistencies, and to provide more robust alternatives for stimulus selection processes and statistical analyses of bilingual data

Ubiquitous Technologies for Emotion Recognition

Emotions play a very important role in how we think and behave. As such, the emotions we feel every day can compel us to act and influence the decisions and plans we make about our lives. Being able to measure, analyze, and better comprehend how or why our emotions may change is thus of much relevance to understand human behavior and its consequences. Despite the great efforts made in the past in the study of human emotions, it is only now, with the advent of wearable, mobile, and ubiquitous technologies, that we can aim to sense and recognize emotions, continuously and in real time. This book brings together the latest experiences, findings, and developments regarding ubiquitous sensing, modeling, and the recognition of human emotions