This Open Access book presents the current state of the art knowledge on social and affective neuroscience based on empirical findings. This volume is divided into several sections first guiding the reader through important theoretical topics within affective neuroscience, social neuroscience and moral emotions, and clinical neuroscience. Each chapter addresses everyday social interactions and various aspects of social interactions from a different angle taking the reader on a diverse journey. The last section of the book is of methodological nature. Basic information is presented for the reader to learn about common methodologies used in neuroscience alongside advanced input to deepen the understanding and usability of these methods in social and affective neuroscience for more experienced readers.

Despite substantial progress in the development of neuroimaging methodologies, translational applications of neuroimaging remain scarce. This Research Topic invites article submissions that present promising neuroimaging applications and methods addressing critical needs for improving health outcomes. These may include Original Research, Clinical Trial, Systematic Review or Methods articles that investigate neuroimaging metrics as outcome measures or in combination with neural perturbation techniques (e.g., neurofeedback, neurostimulation), other translational applications (e.g., guiding neurosurgery). To foster debate, we also welcome critical Review, Opinion, and Perspective articles that survey the field and its progress towards clinical utility.

Within the healthcare sector, a pressing need for transformative changes is growing. From chronic diseases to complex diagnostic procedures, the industry stands at the crossroads of technological innovation and a burgeoning demand for more efficient, precise interventions. Patient expectations are soaring, and the deluge of medical data is overwhelming traditional healthcare systems. It is within this challenging environment that AI-Driven Innovations in Digital Healthcare: Emerging Trends, Challenges, and Applications emerges as a beacon of insight and practical solutions. The traditional healthcare framework is struggling to keep pace with the diverse demands of patients and the ever-expanding volume of medical data. As diseases become more intricate, attempts to provide timely identification and precise treatment of ailments become increasingly elusive. The urgency for a paradigm shift in healthcare delivery is emphasized by the critical need for early interventions, particularly in disease prediction. This challenge necessitates a holistic approach that harnesses the power of artificial intelligence (AI) and innovative technologies to steer healthcare toward a more responsive and patient-centric future.

We are profoundly social creatures--more than we know. In Social, renowned psychologist Matthew Lieberman explores groundbreaking research in social neuroscience revealing that our need to connect with other people is even more fundamental, more basic, than our need for food or shelter. Because of this, our brain uses its spare time to learn about the social world--other people and our relation to them. It is believed that we must commit 10,000 hours to master a skill. According to Lieberman, each of us has spent 10,000 hours learning to make sense of people and groups by the time we are ten. Social argues that our need to reach out to and connect with others is a primary driver behind our behavior. We believe that pain and pleasure alone guide our actions. Yet, new research using fMRI--including a great deal of original research conducted by Lieberman and his UCLA lab--shows that our brains react to social pain and pleasure in much the same way as they do to physical pain and pleasure. Fortunately, the brain has evolved sophisticated mechanisms for securing our place in the social world. We have a unique ability to read other people’s minds, to figure out their hopes, fears, and motivations, allowing us to effectively coordinate our lives with one another. And our most private sense of who we are is intimately linked to the important people and groups in our lives. This wiring often leads us to restrain our selfish impulses for the greater good. These mechanisms lead to behavior that might seem irrational, but is really just the result of our deep social wiring and necessary for our success as a species. Based on the latest cutting edge research, the findings in Social have important real-world implications. Our schools and businesses, for example, attempt to minimalize social distractions. But this is exactly the wrong thing to do to encourage engagement and learning, and literally shuts down the social brain, leaving powerful neuro-cognitive resources untapped. The insights revealed in this pioneering book suggest ways to improve learning in schools, make the workplace more productive, and improve our overall well-being.

The first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines. Active inference is a way of understanding sentient behavior—a theory that characterizes perception, planning, and action in terms of probabilistic inference. Developed by theoretical neuroscientist Karl Friston over years of groundbreaking research, active inference provides an integrated perspective on brain, cognition, and behavior that is increasingly used across multiple disciplines including neuroscience, psychology, and philosophy. Active inference puts the action into perception. This book offers the first comprehensive treatment of active inference, covering theory, applications, and cognitive domains. Active inference is a “first principles” approach to understanding behavior and the brain, framed in terms of a single imperative to minimize free energy. The book emphasizes the implications of the free energy principle for understanding how the brain works. It first introduces active inference both conceptually and formally, contextualizing it within current theories of cognition. It then provides specific examples of computational models that use active inference to explain such cognitive phenomena as perception, attention, memory, and planning.

Since interactions may occur between animals, humans, or computational agents, an interdisciplinary approach which investigates foundations of affective communication in a variety of platforms is indispensable. In the field of affective computing, a collection of research, merging decades of research on emotions in psychology, cognition and neuroscience will inspire creative future research projects and contribute to the prosperity of this emerging field. Affective Computing and Interaction: Psychological, Cognitive and Neuroscientific Perspectives examines the current state and the future prospects of affect in computing within the context of interactions. Uniting several aspects of affective interactions and topics in affective computing, this reference reviews basic foundations of emotions, furthers an understanding of the contribution of affect to our lives and concludes by revealing current trends and promising technologies for reducing the emotional gap between humans and machines, all within the context of interactions.

This book collects and reviews, for the first time, a wide range of advances in the area of human aging biomarkers. This accumulated data allows researchers to assess the rate of aging processes in various organs and systems, and to individually monitor the effectiveness of therapies intended to slow aging. In an introductory chapter, the editor defines biomarkers of aging as molecular, cellular and physiological parameters that demonstrate reproducible changes - quantitative or qualitative - with age. The introduction recounts a study which aimed to create a universal model of biological age, whose most predictive parameters were albumin and alkaline phosphatase (indication liver function), glucose (metabolic syndrome), erythrocytes (respiratory function) and urea (renal function). The book goes on to describe DNA methylation, known as the "epigenetic clock," as currently the most comprehensive predictor of total mortality. It is also useful for predicting mortality from cancer and cardiovascular diseases, and for analyzing the effects of lifestyle factors including diet, exercise, and education. Individual contributions draw additional insight from research on genetics and epigenetic aging markers, and immunosenescence and inflammaging markers. A concluding chapter outlines the challenge of integrating of biological and clinical markers of aging. Biomarkers of Human Aging is written for professionals and practitioners engaged in the study of aging, and will be useful to both advanced students and researchers.

Written by a stellar team of experts, Analyzing Social Networks is a practical book on how to collect, visualize, analyze and interpret social network data with a particular emphasis on the use of the software tools UCINET and Netdraw. The book includes a clear and detailed introduction to the fundamental concepts of network analyses, including centrality, subgroups, equivalence and network structure, as well as cross-cutting chapters that helpfully show how to apply network concepts to different kinds of networks. Written using simple language and notation with few equations, this book masterfully covers the research process, including: · The initial design stage · Data collection and manipulation · Measuring key variables · Exploration of structure · Hypothesis testing · Interpretation This is an essential resource for students, researchers and practitioners across the social sciences who want to use network analysis as part of their research. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.

This book proposes a framework for integrating neuroscience and cyberpsychology for the study of social, cognitive, and affective processes.