Institution
King's College London
Education•London, United Kingdom•
About: King's College London is a education organization based out in London, United Kingdom. It is known for research contribution in the topics: Population & Mental health. The organization has 43107 authors who have published 113125 publications receiving 4498103 citations. The organization is also known as: King's & KCL.
Papers published on a yearly basis
Papers
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Ghent University1, University of California, San Diego2, Leiden University3, Dresden University of Technology4, Stanford University5, University of Maryland, College Park6, Indiana University7, University of Cambridge8, Cardiff University9, University of Western Ontario10, Monash University, Clayton campus11, University of Toronto12, University of Vermont13, University of Oregon14, University of Tasmania15, University of Oslo16, Utrecht University17, Katholieke Universiteit Leuven18, Yale University19, Vanderbilt University20, University of Amsterdam21, Anglia Ruskin University22, Indian Institute of Science23, Queen's University24, King's College London25, Michigan State University26, University of Iowa27, Trinity College, Dublin28
TL;DR: The goal is to facilitate a more accurate use of the stop-signal task and provide user-friendly open-source resources intended to inform statistical-power considerations, facilitate the correct implementation of the task, and assist in proper data analysis.
Abstract: Response inhibition is essential for navigating everyday life. Its derailment is considered integral to numerous neurological and psychiatric disorders, and more generally, to a wide range of behavioral and health problems. Response-inhibition efficiency furthermore correlates with treatment outcome in some of these conditions. The stop-signal task is an essential tool to determine how quickly response inhibition is implemented. Despite its apparent simplicity, there are many features (ranging from task design to data analysis) that vary across studies in ways that can easily compromise the validity of the obtained results. Our goal is to facilitate a more accurate use of the stop-signal task. To this end, we provide 12 easy-to-implement consensus recommendations and point out the problems that can arise when they are not followed. Furthermore, we provide user-friendly open-source resources intended to inform statistical-power considerations, facilitate the correct implementation of the task, and assist in proper data analysis.
617 citations
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TL;DR: In this paper, the authors present a detailed literature review of fluvial geomorphology, riparian plant ecology and hydraulic engineering knowledge, and propose a "fluvial biogeomorphic succession" concept.
617 citations
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TL;DR: Preference increases in neural response to sad but not happy facial expressions in neural regions involved in the processing of emotional stimuli in depressed individuals are indicated.
617 citations
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TL;DR: Sudden unexpected death in epilepsy rates, risk factors, triggers, and proposed mechanisms are reviewed, and potential preventive strategies are critically assessed.
Abstract: Although largely neglected in earlier literature, sudden unexpected death in epilepsy (SUDEP) is the most important epilepsy-related mode of death, and is the leading cause of death in people with chronic uncontrolled epilepsy. Research during the past two to three decades has shown that incidence varies substantially depending on the epilepsy population studied, ranging from 0.09 per 1000 patient-years in newly diagnosed patients to 9 per 1000 patient-years in candidates for epilepsy surgery. Risk profiles have been delineated in case-control studies. These and other studies indicate that SUDEP mainly occurs in the context of a generalised tonic-clonic seizure. However, it remains unclear why a seizure becomes fatal in a person that might have had many similar seizures in the past. Here, we review SUDEP rates, risk factors, triggers, and proposed mechanisms, and critically assess potential preventive strategies. Gaps in knowledge are discussed and ways forward are suggested.
616 citations
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TL;DR: The only clinical feature that distinguishes recognized hereditary from apparently sporadic ALS is a lower mean age of onset in the former, and all the clinical features reported in hereditary cases have also been observed in sporadic cases.
Abstract: Hereditary amyotrophic lateral sclerosis (ALS) encompasses a group of genetic disorders characterized by adult-onset loss of the lower and upper motor neuron systems, often with involvement of other parts of the nervous system. Cases of hereditary ALS have been attributed to mutations in 12 different genes, the most common being SOD1, FUS and TARDBP-mutations in the other genes are rare. The identified genes explain 25-35% of cases of familial ALS, but identifying the remaining genes has proved difficult. Only a few genes seem to account for significant numbers of ALS cases, with many others causing a few cases each. Hereditary ALS can be inherited in an autosomal dominant, autosomal recessive or X-linked manner, and families with low disease penetrance are frequently observed. In such families, the genetic predisposition may remain unnoticed, so many patients carry a diagnosis of isolated or sporadic ALS. The only clinical feature that distinguishes recognized hereditary from apparently sporadic ALS is a lower mean age of onset in the former. All the clinical features reported in hereditary cases (including signs of extrapyramidal, cerebellar or cognitive involvement) have also been observed in sporadic cases. Genetic counseling and risk assessment in relatives depend on establishing the specific gene defect and the disease penetrance in the particular family.
615 citations
Authors
Showing all 43962 results
Name | H-index | Papers | Citations |
---|---|---|---|
Cyrus Cooper | 204 | 1869 | 206782 |
David Miller | 203 | 2573 | 204840 |
Rob Knight | 201 | 1061 | 253207 |
Mark I. McCarthy | 200 | 1028 | 187898 |
Michael Rutter | 188 | 676 | 151592 |
Eric Boerwinkle | 183 | 1321 | 170971 |
Terrie E. Moffitt | 182 | 594 | 150609 |
Kenneth S. Kendler | 177 | 1327 | 142251 |
John Hardy | 177 | 1178 | 171694 |
Dorret I. Boomsma | 176 | 1507 | 136353 |
Barry Halliwell | 173 | 662 | 159518 |
Feng Zhang | 172 | 1278 | 181865 |
Simon Baron-Cohen | 172 | 773 | 118071 |
Phillip A. Sharp | 172 | 614 | 117126 |
Yang Yang | 171 | 2644 | 153049 |