Frontiers has organized a series of Research Topics to highlight the latest advancements in research across the field of cognition, with articles from Members of our accomplished Editorial Boards and from a curated list of experts in their field. This editorial initiative of particular relevance, led by Prof. Juan Lupiáñez, Specialty Chief Editor of the Attention section, is focused on new insights, novel developments, current challenges, latest discoveries, recent advances, and future perspectives in the field of attention.

Submission closed. Guidelines We are now entering the third decade of the 21st Century, and, especially in the last years, the achievements made by scientists have been exceptional, leading to significant advancements in the fast-growing field of Cognitive Neuroscience. Frontiers have organized a series of Research Topics to highlight the latest advancements in research across the field of Cognitive Neuroscience. This editorial initiative of relevance, led by Dr. Kida, Associate Editor of the Cognitive Neuroscience section, together with Dr. Okamoto, Associate Editor of both the Brain-Imaging and Sensory Neuroscience sections, is focused on new insights, novel developments, current challenges, latest discoveries, recent advances, and future perspectives in the field of the Cognitive Neuroscience of attention.

In the burdened scenes of everyday life, our brains must select from among many competing inputs for perceptual synthesis - so that only the most relevant receive full attention and irrelevant (distracting) information is suppressed. At the same time, we must remain responsive to salient events outside our current focus of attention - and balancing these two processing modes is a fundamental task our brain constantly needs to solve. Both the physical saliency of a stimulus, as well as top-down predictions about imminent sensations crucially influence attentional selection and consequently the response to unexpected events. Research over recent decades has identified two separate brain networks involved in predictive top-down control and reorientation to unattended events (or oddball stimuli): the dorsal and ventral fronto-parietal attention systems of the human brain. Moreover, specific electrophysiological brain responses are known to characterize attentional orienting as well as the processing of deviant stimuli. However, many key questions are outstanding. What are the exact functional differences between these cortical attention systems? How are they lateralised in the two hemispheres? How do top-down and bottom-up signals interact to enable flexible attentional control? How does structural damage to one system affect the functionality of the other in brain damaged patients? Are there sensory-specific and supra-modal attentional systems in the brain? In addition to these questions, it is now accepted that brain responses are not only affected by the saliency of external stimuli, but also by our expectations about sensory inputs. How these two influences are balanced, and how predictions are formed in cortical networks, or generated on the basis of experience-dependent learning, are intriguing issues. In this Research Topic, we aim to collect innovative contributions that shed further light on the (cortical) mechanisms of attentional control in the human brain. In particular, we would like to encourage submissions that investigate the behavioural correlates, functional anatomy or electrophysiological markers of attentional selection and reorientation. Special emphasis will be given to studies investigating the context-sensitivity of these attentional processes in relation to prior expectations, trial history, contextual cues or physical saliency. We would like to encourage submissions employing different research methods (psychophysical recordings, neuroimaging techniques such as fMRI, MEG, EEG or ECoG, as well as neurostimulation methods such as TMS or tDCS) in healthy volunteers or neurological patients. Computational models and animal studies are also welcome. Finally, we also welcome submission of meta-analyses and reviews articles that provide new insights into, or conclusions about recent work in the field.

Master the art and science of data storytelling—with frameworks and techniques to help you craft compelling stories with data. The ability to effectively communicate with data is no longer a luxury in today’s economy; it is a necessity. Transforming data into visual communication is only one part of the picture. It is equally important to engage your audience with a narrative—to tell a story with the numbers. Effective Data Storytelling will teach you the essential skills necessary to communicate your insights through persuasive and memorable data stories. Narratives are more powerful than raw statistics, more enduring than pretty charts. When done correctly, data stories can influence decisions and drive change. Most other books focus only on data visualization while neglecting the powerful narrative and psychological aspects of telling stories with data. Author Brent Dykes shows you how to take the three central elements of data storytelling—data, narrative, and visuals—and combine them for maximum effectiveness. Taking a comprehensive look at all the elements of data storytelling, this unique book will enable you to: Transform your insights and data visualizations into appealing, impactful data stories Learn the fundamental elements of a data story and key audience drivers Understand the differences between how the brain processes facts and narrative Structure your findings as a data narrative, using a four-step storyboarding process Incorporate the seven essential principles of better visual storytelling into your work Avoid common data storytelling mistakes by learning from historical and modern examples Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals is a must-have resource for anyone who communicates regularly with data, including business professionals, analysts, marketers, salespeople, financial managers, and educators.

This collection surveys the key debates and issues that currently face fashion journalism, going beyond traditional print media to consider its multiple contexts and iterations in an ever-evolving post-digital media environment. Bringing together a diverse range of contributors, Insights on Fashion Journalism explores the characteristics, complexities, shifts and specificities of the field. The book is organized into three sections, mapping fashion journalism’s established and emerging practices and exploring its parameters from mainstream to marginal. Section One focuses on the complex relationships between those who practice fashion journalism, the fashion industry and the media context in which they operate; Section Two considers the ways in which fashion journalism responds to the socio-political and cultural contexts in which it is created, as well as the impact these contexts have on tone, content and style; and Section Three investigates how language is employed in different media. Approaching fashion journalism through a critically diverse lens, this collection is an asset for academics and students in the fields of fashion studies, journalism, communication, cultural studies and digital media.

Maximizing student outcomes in education presents a significant challenge, as traditional assessment methods often fall short in providing actionable insights for improvement. Perspectives on Learning Analytics for Maximizing Student Outcomes addresses this challenge by offering a comprehensive solution. Edited by esteemed scholars Gürhan Durak and Serkan Çankaya, this book provides innovative knowledge and practical experiences on emerging technologies and processes in learning analytics. It covers topics such as data collection, visualization, predictive analytics, and ethical considerations, serving as a guide for academic scholars, technology enthusiasts, and educational institutions. This book empowers professionals and researchers to leverage learning analytics effectively, enabling data-informed decision-making, improved teaching practices, and tailored educational programs. By presenting best practices and future directions, it equips readers with the necessary tools to optimize learning environments and drive student success. With a focus on the transformative potential of learning analytics, this book propels education toward a more efficient and effective system that prioritizes student outcomes.

This cutting-edge Handbook offers a comprehensive introduction to the emerging research field of artificial intelligence (AI) in human resource management (HRM). Broadly mapping AI fields relevant for HR, it not only considers the more well-known areas of machine learning and natural language processing, but also lesser-known fields such as affective computing and robotic process automation.