Grapheme-color synaesthesia is associated with a distinct cognitive style

In this study we investigated whether synaesthesia is associated with a particular cognitive style. Cognitive style refers to preferred modes of information processing, such as a verbal style or a visual style. We reasoned that related to the enriched world of experiences created by synaesthesia, its association with enhanced verbal and visual memory, higher imagery and creativity, synaesthetes might show enhanced preference for a verbal as well as for a visual cognitive style compared to non-synaesthetes. In Study 1 we tested a large convenience sample of 1046 participants, who classified themselves as grapheme-color, sound-color, lexical-gustatory, sequence-space, or as non-synaesthetes. To assess cognitive style, we used the revised verbalizer-visualizer questionnaire (VVQ), which involves three independent cognitive style dimensions (verbal style, visual-spatial style, and vivid imagery style). The most important result was that those who reported grapheme-color synaesthesia showed higher ratings on the verbal and vivid imagery style dimensions, but not on the visual-spatial style dimension. In Study 2 we replicated this finding in a laboratory study involving 24 grapheme-color synaesthetes with objectively confirmed synaesthesia and a closely matched control group. Our results indicate that grapheme-color synaesthetes prefer both a verbal and a specific visual cognitive style. We suggest that this enhanced preference, probably together with the greater ease to switch between a verbal and a vivid visual imagery style, may be related to cognitive advantages associated with grapheme color synaesthesia such as enhanced memory performance and creativity.

Towards an Emergent Semantic Web

In his in uential article about the evolution of the Web, Berners-Lee [1] envisions a Semantic Web in which humans and computers alike are capable of understanding and processing information. This vision is yet to materialize. The main obstacle for the Semantic Web vision is that in today's Web meaning is rooted most often not in formal semantics, but in natural language and, in the sense of semiology, emerges not before interpretation and processing. Yet, an automated form of interpretation and processing can be tackled by precisiating raw natural language. To do that, Web agents extract fuzzy grassroots ontologies through induction from existing Web content. Inductive fuzzy grassroots ontologies thus constitute organically evolved knowledge bases that resemble automated gradual thesauri, which allow precisiating natural language [2]. The Web agents' underlying dynamic, self-organizing, and best-effort induction, enable a sub-syntactical bottom up learning of semiotic associations. Thus, knowledge is induced from the users' natural use of language in mutual Web interactions, and stored in a gradual, thesauri-like lexical-world knowledge database as a top-level ontology, eventually allowing a form of computing with words [3]. Since when computing with words the objects of computation are words, phrases and propositions drawn from natural languages, it proves to be a practical notion to yield emergent semantics for the Semantic Web. In the end, an improved understanding by computers on the one hand should upgrade human- computer interaction on the Web, and, on the other hand allow an initial version of human- intelligence amplification through the Web.

Reduplication in Mapuzungun: form and function

Mapuzungun has reduplicative structures based on elements other than verb stems that are of very limited productivity. With verb stems, however, several formal patterns can be distinguished, which consist of the repetition of the lexical verb stem plus the addition of an apparently grammaticalized version of one of three verb roots or a zero morpheme. The previous literature has attempted to identify form/function correlations for these more or less productive verbal reduplicative patterns, and the present paper contributes to the discussion by surveying older studies and exploring several cases that suggest that such form/function correspondences are substantially less straightforward than a casual observer might think.

Language context modulates reading route: an electrical neuroimaging study.

INTRODUCTION The orthographic depth hypothesis (Katz and Feldman, 1983) posits that different reading routes are engaged depending on the type of grapheme/phoneme correspondence of the language being read. Shallow orthographies with consistent grapheme/phoneme correspondences favor encoding via non-lexical pathways, where each grapheme is sequentially mapped to its corresponding phoneme. In contrast, deep orthographies with inconsistent grapheme/phoneme correspondences favor lexical pathways, where phonemes are retrieved from specialized memory structures. This hypothesis, however, lacks compelling empirical support. The aim of the present study was to investigate the impact of orthographic depth on reading route selection using a within-subject design. METHOD We presented the same pseudowords (PWs) to highly proficient bilinguals and manipulated the orthographic depth of PW reading by embedding them among two separated German or French language contexts, implicating respectively, shallow or deep orthography. High density electroencephalography was recorded during the task. RESULTS The topography of the ERPs to identical PWs differed 300-360 ms post-stimulus onset when the PWs were read in different orthographic depth context, indicating distinct brain networks engaged in reading during this time window. The brain sources underlying these topographic effects were located within left inferior frontal (German > French), parietal (French > German) and cingular areas (German > French). CONCLUSION Reading in a shallow context favors non-lexical pathways, reflected in a stronger engagement of frontal phonological areas in the shallow versus the deep orthographic context. In contrast, reading PW in a deep orthographic context recruits less routine non-lexical pathways, reflected in a stronger engagement of visuo-attentional parietal areas in the deep versus shallow orthographic context. These collective results support a modulation of reading route by orthographic depth.

The Role of the Right Posterior Parietal Cortex in Letter Migration between Words

When briefly presented with pairs of words, skilled readers can sometimes report words with migrated letters (e.g., they report hunt when presented with the words hint and hurt). These letter migration phenomena have been often used to investigate factors that influence reading such as letter position coding. However, the neural basis of letter migration is poorly understood. Previous evidence has implicated the right posterior parietal cortex (PPC) in processing visuospatial attributes and lexical properties during word reading. The aim of this study was to assess this putative role by combining an inhibitory TMS protocol with a letter migration paradigm, which was designed to examine the contributions of visuospatial attributes and lexical factors. Temporary interference with the right PPC led to three specific effects on letter migration. First, the number of letter migrations was significantly increased only in the group with active stimulation (vs. a sham stimulation group or a control group without stimulation), and there was no significant effect on other error types. Second, this effect occurred only when letter migration could result in a meaningful word (migration vs. control context). Third, the effect of active stimulation on the number of letter migrations was lateralized to target words presented on the left. Our study thus demonstrates that the right PPC plays a specific and causal role in the phenomenon of letter migration. The nature of this role cannot be explained solely in terms of visuospatial attention, rather it involves an interplay between visuospatial attentional and word reading-specific factors.

Does Age Matter? Semantic Memory in Healthy Young and Elderly Adults

Background: Semantic memory processes have been well described in literature. However, the available findings are mostly based on relatively young subjects and concrete word material (e.g. tree). Comparatively little information exists about semantic memory for abstract words (e.g. mind) and possible age related changes in semantic retrieval. In this respect, we developed a paradigm that is useful to investigate the implicit (i.e. attentionindependent) access to concrete and abstract semantic memory. These processes were then compared between young and elderly healthy subjects. Methods: A well established tool for investigating semantic memory processes is the semantic priming paradigm, which consists both of semantically unrelated and related word pairs. In our behavioral task these noun-noun word pairs were further divided into concrete, abstract and matched pronounceable non-word conditions. With this premise, the young and elderly participants performed a lexical decision task: they were asked to press a choice of two buttons as an indication for whether the word pair contained a non-word or not. In order to minimize controlled (i.e. attention-dependent) retrieval strategies, a short stimulus onset asynchrony (SOA) of 150ms was set. Reaction time (RT) changes and accuracy to related and unrelated words (priming effect) in the abstract vs. concrete condition (concreteness effect) were the dependent variables of interest. Results and Discussion: Statistical analysis confirmed both a significant priming effect (i.e. shorter RTs in semantically related compared to unrelated words) and a concreteness effect (i.e. RT decrease for concrete compared to abstract words) in the young and elderly subjects. There was no age difference in accuracy. The only age effect was a commonly known general slowing in RT over all conditions. In conclusion, age is not a critical factor in the implicit access to abstract and concrete semantic memory.

Altered Electrophysiology of Semantic Word Processing in Alzheimer's Disease and Semantic Dementia

With the progressing course of Alzheimer's disease (AD), deficits in declarative memory increasingly restrict the patients' daily activities. Besides the more apparent episodic (biographical) memory impairments, the semantic (factual) memory is also affected by this neurodegenerative disorder. The episodic pathology is well explored; instead the underlying neurophysiological mechanisms of the semantic deficits remain unclear. For a profound understanding of semantic memory processes in general and in AD patients, the present study compares AD patients with healthy controls and Semantic Dementia (SD) patients, a dementia subgroup that shows isolated semantic memory impairments. We investigate the semantic memory retrieval during the recording of an electroencephalogram, while subjects perform a semantic priming task. Precisely, the task demands lexical (word/nonword) decisions on sequentially presented word pairs, consisting of semantically related or unrelated prime-target combinations. Our analysis focuses on group-dependent differences in the amplitude and topography of the event related potentials (ERP) evoked by related vs. unrelated target words. AD patients are expected to differ from healthy controls in semantic retrieval functions. The semantic storage system itself, however, is thought to remain preserved in AD, while SD patients presumably suffer from the actual loss of semantic representations.

Habituation and consolidation of prospective memory over a week: An ERP study

Prospective memory (ProM) is the ability to remember and perform an intention in the future. If a prospective memory task is to be performed only once, it is episodic. If it is repeated, then it becomes habitual. Thus, with repetition, a task changes from episodic to habitual. The goal of this study was to investigate the transition from episodic to habitual prospective memory with event-related potentials (ERP). The ProM task was to respond to a target word which was embedded in an ongoing lexical decision task. 40 ProM trials were administered in each of two sessions that were separated by a week. The results revealed a behavioural consolidation effect with increased ProM performance after one week. The ERP-analyses showed that when the task became more habitual a difference occurred in a time-window between 450-650 ms post-stimulus in an ERP-component. In addition, a covariance analysis revealed that this transition is continued in the second session. These results demonstrate that the transition from episodic to habitual prospective memory is long-lasting and continuous.

Negative mood, self-focused attention, and the experience of physical symptoms: the joint impact hypothesis

A joint impact hypothesis on symptom experience is introduced that specifies the role of negative mood and self-focus, which have been considered independently in previous research. Accordingly, negative affect only promotes symptom experience when people simultaneously focus their attention on the self. One correlational study and 4 experiments supported this prediction: Only negative mood combined with self-focus facilitated the experience (see the self-reports in Studies 1, 2a, & 2b) and the accessibility (lexical decisions, Stroop task in Studies 3 & 4) of physical symptoms, whereas neither positive mood nor negative mood without self-focus did. Furthermore, the joint impact of negative mood and self-focused attention on momentary symptom experience remained significant after controlling for the influence of dispositional symptom reporting and neuroticism.

Bounded Seas: Island Parsing Without Shipwrecks

Imprecise manipulation of source code (semi-parsing) is useful for tasks such as robust parsing, error recovery, lexical analysis, and rapid development of parsers for data extraction. An island grammar precisely defines only a subset of a language syntax (islands), while the rest of the syntax (water) is defined imprecisely. Usually, water is defined as the negation of islands. Albeit simple, such a definition of water is naive and impedes composition of islands. When developing an island grammar, sooner or later a programmer has to create water tailored to each individual island. Such an approach is fragile, however, because water can change with any change of a grammar. It is time-consuming, because water is defined manually by a programmer and not automatically. Finally, an island surrounded by water cannot be reused because water has to be defined for every grammar individually. In this paper we propose a new technique of island parsing - bounded seas. Bounded seas are composable, robust, reusable and easy to use because island-specific water is created automatically. We integrated bounded seas into a parser combinator framework as a demonstration of their composability and reusability.

Adjectives in Thai: Implications for a functionalist typology of word classes

Tai languages are often described as “lacking” a major lexical class “adjectives”; accordingly, they and other area languages are frequently cited as evidence against adjectival universality. This article brings the putative lack under examination, arguing that a more complete distributional analysis reveals a pattern: overlap is highest among semantically peripheral adjectives and verbs and in constructions prototypically associated to both classes crosslinguistically, and lowest among semantically core adjectives and verbs and in constructions prototypically associated to only one or the other class. Rather than “lacking” adjectives, data from Thai thus in fact support functional-typological characterizations of adjectival universality such as those of Givón (1984), Croft (2001), and Dixon (2004). Finally, while data from Thai would fail to falsify an adaptation of Enfield's (2004) Lao lexical class-taxonomy (in which adjectives are treated as a verbal subclass) on its own terms, this article argues that in absence of both universally-applicable criteria for the evaluation of categorial taxonomies crosslinguistically and evidence for the cognitive reality of categorial taxonomies so stipulated, even this more limited sense of a “lack” of adjectives in Thai is less radical a challenge to adjectival universality than has sometimes been supposed.

Crowdsourcing language change with smartphone applications

Crowdsourcing linguistic phenomena with smartphone applications is relatively new. In linguistics, apps have predominantly been developed to create pronunciation dictionaries, to train acoustic models, and to archive endangered languages. This paper presents the first account of how apps can be used to collect data suitable for documenting language change: we created an app, Dialäkt Äpp (DÄ), which predicts users’ dialects. For 16 linguistic variables, users select a dialectal variant from a drop-down menu. DÄ then geographically locates the user’s dialect by suggesting a list of communes where dialect variants most similar to their choices are used. Underlying this prediction are 16 maps from the historical Linguistic Atlas of German-speaking Switzerland, which documents the linguistic situation around 1950. Where users disagree with the prediction, they can indicate what they consider to be their dialect’s location. With this information, the 16 variables can be assessed for language change. Thanks to the playfulness of its functionality, DÄ has reached many users; our linguistic analyses are based on data from nearly 60,000 speakers. Results reveal a relative stability for phonetic variables, while lexical and morphological variables seem more prone to change. Crowdsourcing large amounts of dialect data with smartphone apps has the potential to complement existing data collection techniques and to provide evidence that traditional methods cannot, with normal resources, hope to gather. Nonetheless, it is important to emphasize a range of methodological caveats, including sparse knowledge of users’ linguistic backgrounds (users only indicate age, sex) and users’ self-declaration of their dialect. These are discussed and evaluated in detail here. Findings remain intriguing nevertheless: as a means of quality control, we report that traditional dialectological methods have revealed trends similar to those found by the app. This underlines the validity of the crowdsourcing method. We are presently extending DÄ architecture to other languages.

Documenting sound change with smartphone apps

Crowdsourcing linguistic phenomena with smartphone applications is relatively new. Apps have been used to train acoustic models for automatic speech recognition (de Vries et al. 2014) and to archive endangered languages (Iwaidja Inyaman Team 2012). Leemann and Kolly (2013) developed a free app for iOS—Dialäkt Äpp (DÄ) (>78k downloads)—to document language change in Swiss German. Here, we present results of sound change based on DÄ data. DÄ predicts the users’ dialects: for 16 variables, users select their dialectal variant. DÄ then tells users which dialect they speak. Underlying this prediction are maps from the Linguistic Atlas of German-speaking Switzerland (SDS, 1962-2003), which documents the linguistic situation around 1950. If predicted wrongly, users indicate their actual dialect. With this information, the 16 variables can be assessed for language change. Results revealed robustness of phonetic variables; lexical and morphological variables were more prone to change. Phonetic variables like to lift (variants: /lupfə, lʏpfə, lipfə/) revealed SDS agreement scores of nearly 85%, i.e., little sound change. Not all phonetic variables are equally robust: ladle (variants: /xælə, xællə, xæuə, xæɫə, xæɫɫə/) exhibited significant sound change. We will illustrate the results using maps that show details of the sound changes at hand.

Automatic identification of discourse markers in dialogues: An in-depth study of like and well

The lexical items like and well can serve as discourse markers (DMs), but can also play numerous other roles, such as verb or adverb. Identifying the occurrences that function as DMs is an important step for language understanding by computers. In this study, automatic classifiers using lexical, prosodic/positional and sociolinguistic features are trained over transcribed dialogues, manually annotated with DM information. The resulting classifiers improve state-of-the-art performance of DM identification, at about 90% recall and 79% precision for like (84.5% accuracy, κ = 0.69), and 99% recall and 98% precision for well (97.5% accuracy, κ = 0.88). Automatic feature analysis shows that lexical collocations are the most reliable indicators, followed by prosodic/positional features, while sociolinguistic features are marginally useful for the identification of DM like and not useful for well. The differentiated processing of each type of DM improves classification accuracy, suggesting that these types should be treated individually.

Annotating the meaning of discourse connectives in multilingual corpora

Discourse connectives are lexical items indicating coherence relations between discourse segments. Even though many languages possess a whole range of connectives, important divergences exist cross-linguistically in the number of connectives that are used to express a given relation. For this reason, connectives are not easily paired with a univocal translation equivalent across languages. This paper is a first attempt to design a reliable method to annotate the meaning of discourse connectives cross-linguistically using corpus data. We present the methodological choices made to reach this aim and report three annotation experiments using the framework of the Penn Discourse Tree Bank.