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Reading is an integral part of life in today's information-driven societies. Since the pioneering work of Dejerine on "word blindness" in brain-lesioned patients, the literature has increased exponentially, from neuropsychological case reports to mechanistic accounts of word processing at the behavioural, neurofunctional and computational levels, tapping into diverse aspects of visual word processing. These studies have revealed some exciting findings about visual word processing, including how the brain learns to read, how changes in literacy impact upon word processing strategies, and whether word processing mechanisms vary across different alphabetic, logographic or artificial writing systems. Other studies have attempted to characterise typical and atypical word processes in special populations in order to explain why dyslexic brains struggle with words, how multilingualism changes the way our brains see words, and what the exact developmental signatures are that would shape the acquisition of reading skills. Exciting new insights have also emerged from recent studies that have investigated word stimuli at the system/network level, by looking for instance, at how the reading system interacts with other cognitive systems in a context-dependent fashion, how visual language stimuli are integrated into the speech processing streams, how both left and right hemispheres cooperate and interact during word processing, and what the exact contributions of subcortical and cerebellar regions to reading are. The contributions to this Research Topic highlight the latest findings regarding the different issues mentioned above, particularly how these findings can explain or model the different processes, mechanisms, pathways or cognitive strategies by which the human brain sees words. The introductory editorial, summarising the contributions included here, highlights how varieties of behavioural tests and neuroimaging techniques can be used to investigate word processing mechanisms across different alphabetic and logographic writing systems.

Word processing. --- Learning --- fMRI --- Word Processing --- Multilingualism --- ERP --- reading --- Dyslexia --- laterality

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Language has long been considered independent from emotions. In the last few years however research has accumulated empirical evidence against this theoretical belief of a purely cognitive-based foundation of language. In particular, through research on emotional word processing it has been shown, that processing of emotional words activates emotional brain structures, elicits emotional facial expressions and modulates action tendencies of approach and avoidance, probably in a similar manner as processing of non-verbal emotional stimuli does. In addition, it has been shown that emotional content is already processed in the visual cortex in a facilitated manner which suggests that processing of emotional language content is able to circumvent in-depth semantic analysis.

Yet, this is only one side of the coin. Very recent research putting words into context suggests that language may also construe emotions and that by studying word processing one can provide a window to one’s own feelings. All in all, the empirical observations support the thesis of a close relationship between language and emotions at the level of word meaning as a specific evolutionary achievement of the human species. As such, this relationship seems to be different from the one between emotions and speech, where emotional meaning is conveyed by nonverbal features of the voice. But what does this relationship between written words and emotions theoretically imply for the processing of emotional information?

The present Research Topic and its related articles aim to provide answers to this question. This book comprises several experimental studies investigating the brain structures and the time course of emotional word processing. Included are studies examining the affective core dimensions underlying affective word processing and studies that show how these basic affective dimensions influence word processing in general as well as the interaction between words, feelings and (expressive) behavior. In addition, new impetus comes from studies that on the one hand investigate how task-, sublexical and intrapersonal factors influence emotional word processing and on the other hand extend emotional word processing to the domains of social context and self-related processing. Finally, future perspectives are outlined including research on emotion and language acquisition, culture and multilingualism.

In summary, this textbook offers scientists from different disciplines insight into the neurophysiological, behavioral and subjective mechanisms underlying emotion and language interactions. It gives new impulses to existing theories on the embodiment of language and emotion and provides new ways of looking at emotion-cognition interactions.

language as context --- self-reference --- mood --- social cognition --- neuronal and behavioral mechanisms of emotional word processing --- embodiment --- poetic aesthetics --- emotion and language --- multilingualism

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This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters. The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.

Computer science. --- Health informatics. --- Data mining. --- Information storage and retrieval systems. --- Information organization. --- Information retrieval. --- Text processing (Computer science). --- Computational linguistics. --- Computer Science. --- Information Storage and Retrieval. --- Health Informatics. --- Document Preparation and Text Processing. --- Language Translation and Linguistics. --- Data Mining and Knowledge Discovery. --- Information storage and retrieval. --- Automatic language processing --- Language and languages --- Language data processing --- Linguistics --- Natural language processing (Linguistics) --- Applied linguistics --- Cross-language information retrieval --- Mathematical linguistics --- Multilingual computing --- Processing, Text (Computer science) --- Database management --- Electronic data processing --- Information storage and retrieval systems --- Word processing --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Clinical informatics --- Health informatics --- Medical information science --- Information science --- Medicine --- Informatics --- Science --- Data processing --- Information storage and retrieva. --- Medical records --- Natural language processing (Computer science). --- Natural Language Processing (NLP). --- Data processing. --- NLP (Computer science) --- Artificial intelligence --- Human-computer interaction --- Semantic computing --- EHR systems --- EHR technology --- EHRs (Electronic health records) --- Electronic health records --- Electronic medical records --- EMR systems --- EMRs (Electronic medical records) --- Medical care --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Medical Records --- Data Mining --- Natural Language Processing --- Text Analysis --- Health Informatics --- Text Mining --- Medical Terminologies --- Health Care Information Systems --- Support Vector Machines