Microstates in language-related brain potential maps show noun-verb differences

Brain processing of grammatical word class was studied analyzing event-related potential (ERP) brain fields. Normal subjects observed a randomized sequence of single German nouns and verbs on a computer screen, while 20-channel ERP field map series were recorded separately for both word classes. Spatial microstate analysis was applied, based on the observation that series of ERP maps consist of epochs of quasi-stable map landscapes and based on the rationale that different map landscapes must have been generated by different neural generators and thus suggest different brain functions. Space-oriented segmentation of the mean map series identified nine successive, different functional microstates, i.e., steps of brain information processing characterized by quasi-stable map landscapes. In the microstate from 116 to 172 msec, noun-related maps differed significantly from verb-related maps along the left–right axis. The results indicate that different neural populations represent different grammatical word classes in language processing, in agreement with clinical observations. This word class differentiation as revealed by the spatial–temporal organization of neural activity occurred at a time after word input compatible with speed of reading.

Myth creation in textbook writing : the case of randomised controlled trials in medical research

Textbooks, across all disciplines, are prone to contain errors; grammatical, editorial, factual, or judgemental. The following is an account of one of the possible effects of such errors; how an error becomes entrenched and even exaggerated as later textbooks fail to correct the original error. The example considered here concerns the origins of one of the most basic and important tools of to­ day's medical research, the randomised controlled trial. It is the result of a systematic study of 26 British, French and German history of medicine textbooks since 1996.

Falkland Island English

This chapter examines some of the grammatical variability and non-standardness found in the English of the Falkland Islands. The Falklands are an archipelago of over 700 islands located in the western South Atlantic Ocean, 480km off the east coast of Argentina. Although the population is small – around 3000 - the islands cover an area of over 12000km2 – slightly larger than Jamaica and half the size of Wales, making them, after Greenland, the most sparsely populated political entity in the world. In political terms, the Falklands are an Overseas Territory of the United Kingdom. In contrast to the rural isolated image that the Falklands perhaps conjure up, the community is, in demographic terms, an urban and diverse one. Over 85% of the population living in the capital Stanley. The 2006 census (Government of the Falkland Islands 2007: 6) shows that 55% of the population were not born on the Islands, with the largest migrant groups coming from the UK, St Helena (another British Overseas Territory, located in the eastern South Atlantic), Chile and Australia. It also highlighted the fact that people born in 62 different countries were resident on the islands at the time (Pascoe and Pepper 2008: 38). By way of a comparison, only Monaco and Andorra, in Europe, have a higher proportion of their populations made up of migrants. In addition to the local Falkland population, there is a large military presence on the islands at the Royal Airforce Base at Mount Pleasant, 50km south-west of Stanley. The Head of State is the monarch of the UK, who is represented on the islands by a governor. The democratically elected 11-member Legislative Assembly is responsible for day-to-day government of the islands. The Falklands are perhaps most famous because of their 74 day occupation by Argentina in 1982. It is not appropriate here to go into detail about the dispute between the UK and Argentina about the sovereignty of the Islands. What is undisputed is that there has been a continuous Anglophone speech community on the islands since the early 1830s, making it one of the most recently developed ‘Inner Circle’ (Kachru 1985) Englishes in the world. This chapter examines the grammatical characteristics of Falkland Island English, drawn from a transcribed corpus of over 500,000 words of informal conversational speech, collected by Andrea Sudbury both in Stanley and in ‘Camp’ (the local name for the rest of the islands) (see Sudbury 2000, 2001 for more details about the methods used in the survey).

Beyond the tree of texts: Building an empirical model of scribal variation through graph analysis of texts and stemmata

Stemmatology, or the reconstruction of the transmission history of texts, is a field that stands particularly to gain from digital methods. Many scholars already take stemmatic approaches that rely heavily on computational analysis of the collated text (e.g. Robinson and O’Hara 1996; Salemans 2000; Heikkilä 2005; Windram et al. 2008 among many others). Although there is great value in computationally assisted stemmatology, providing as it does a reproducible result and allowing access to the relevant methodological process in related fields such as evolutionary biology, computational stemmatics is not without its critics. The current state-of-the-art effectively forces scholars to choose between a preconceived judgment of the significance of textual differences (the Lachmannian or neo-Lachmannian approach, and the weighted phylogenetic approach) or to make no judgment at all (the unweighted phylogenetic approach). Some basis for judgment of the significance of variation is sorely needed for medieval text criticism in particular. By this, we mean that there is a need for a statistical empirical profile of the text-genealogical significance of the different sorts of variation in different sorts of medieval texts. The rules that apply to copies of Greek and Latin classics may not apply to copies of medieval Dutch story collections; the practices of copying authoritative texts such as the Bible will most likely have been different from the practices of copying the Lives of local saints and other commonly adapted texts. It is nevertheless imperative that we have a consistent, flexible, and analytically tractable model for capturing these phenomena of transmission. In this article, we present a computational model that captures most of the phenomena of text variation, and a method for analysis of one or more stemma hypotheses against the variation model. We apply this method to three ‘artificial traditions’ (i.e. texts copied under laboratory conditions by scholars to study the properties of text variation) and four genuine medieval traditions whose transmission history is known or deduced in varying degrees. Although our findings are necessarily limited by the small number of texts at our disposal, we demonstrate here some of the wide variety of calculations that can be made using our model. Certain of our results call sharply into question the utility of excluding ‘trivial’ variation such as orthographic and spelling changes from stemmatic analysis.