Sociolinguistic Awareness in Galician Bilinguals: Evidence from an Accent Identification Task

The inclusion of European minority languages in public spaces such as education, administration and the media has led to the emergence of a new profile of speakers, “new speakers”, who typically acquire a minority language through education, but vary in terms of their language experience and use. The present study investigated whether a distinctive variety spoken by Galician new speakers (neofalantes) has emerged in the community and whether listeners’ language background influences accent identification abilities and patterns. Galician-Spanish bilingual listeners completed an accent identification task and were asked to comment on factors influencing their decision. Results demonstrated that all listeners could identify Galician-dominant better than Spanish-dominant bilinguals but could not identify neofalantes. Neofalantes were categorised as both Spanish- and Galician-dominant, supporting the idea that neofalantes have a hybrid variety. This finding suggests that listeners have a gradient representation of language background variation, with Galician-like and Spanish-like accents functioning as anchors and the neofalantes’ accent situated somewhere in the middle. Identification accuracy was similar for all listeners but neofalantes showed heightened sensitivity to the Galician-dominant variety, suggesting that evaluation of sociophonetic features depends on the listener’s language and social background. These findings contribute to our understanding of sociolinguistic awareness in bilingual contexts.

On the Kernel of a Polynomial of Scalar Derivations

In this paper, by using a vector variable, the procedure of characteristic systems allows us to describe the kernel of a polynomial of scalar derivations by solving Cauchy Problems for the corresponding system of ODEs. Moreover, a gradient representation for the associated Cauchy Problem solution is derived.

Bipartite functional fractionation within the default network supports disparate forms of internally oriented cognition

The ‘default network’ (DN) becomes active when the mind is steered internally towards self-generated thoughts but turns dormant when the mind is directed externally towards the outside world. While hypotheses have been proposed to characterise the association and dissociation between different component areas of the DN, it remains unclear how they coalesce into a unitary network and fractionate into different sub-networks. Here we identified two distinct subsystems within the DN – while both subsystems show common disinterest in externally-oriented visuospatial tasks, their functional profiles differ strikingly according to the preferred contents of thoughts, preferred modes of task requirement, and causative neural dynamics among network nodes. Specifically, one subsystem comprises key nodes of the frontotemporal semantic regions. This network shows moderate dislike to visuospatial tasks, shows proclivity for task-contexts with restraints on thoughts and responses, and prefers thoughts that are focused on other people. By contrast, the other subsystem comprises the cortical midline structure and angular gyri. This network shows strong aversion to visuospatial tasks, favours task-contexts allowing free self-generated thoughts without constraints, and prefers thoughts that are focused on self. Furthermore, causative connectivity reveals that task-contexts systematically alter the dynamics within and between subsystems, suggesting flexible adaption to situational demands. This ‘self/inward vs. others/outward’ separation within the broad DN resembles recent discoveries regarding a dyadic structure within the frontoparietal network that comprises regions controlling memories/thoughts vs. regions controlling sensory-motoric processes, and echoes burgeoning views that the brain is organised with a spectrum-like architecture along gradational changes of ‘inward vs. outward’ preferences.SignificanceRather than construing the default network (DN) as ‘task-negative’ regions that passively react to off-task mind-wandering, researchers have begun to acknowledge the active role of the DN in supporting internally-directed cognition. Here we found a striking dichotomy within the DN in terms of the subsystems’ task-driven functional and connectivity profiles, extending beyond previous inferences using meta-analysis and resting-state fMRI. This dichotomy reflects a local manifestation of a macro-scale gradient representation spanning across the broad cerebral cortex. This cortical gradient increases its representational complexity, from primitive sensory and motoric processing, through lexical-semantic codes for language tasks, to abstract self-generated thoughts in task-free contexts. These findings enable a framework where the separate yet related literatures of semantic cognition and default-mode processes converge.

Identifying the representational structure of affect using fMRI

The events we experience day to day can be described in terms of their affective quality: some are rewarding, others are upsetting, and still others are inconsequential. These natural distinctions reflect an underlying representational structure used to classify the affective quality of events. In affective psychology, many experiments model this representational structure with two dimensions, using either the dimensions of valence and arousal, or alternatively, the dimensions of positivity and negativity. Using an fMRI dataset, we show that these affective dimensions are not strictly linear combinations each other, and show that it is critical that all four dimensions be used to examined the data. Our findings include (1) a gradient representation of valence anatomically organized along the fusiform gyrus, and (2) distinct subregions within bilateral amygdala tracking arousal versus negativity. Importantly, these patterns would have remained concealed had either of the prevailing 2-dimensional approaches been adopted a priori.

IMAGE FUSION BASED ON MULTI-OBJECTIVE OPTIMIZATION

This paper solves the image fusion problem by using a multi-object optimization strategy and a key energy function. The energy function mainly consists of two components. One ensures injection of more correlated detailed spatial information. The detailed information is extracted from gradient representation of the image to be fused. The other one guarantees that the spectral information is preserved by a data fitting term. By minimizing the proposed energy function, the fusion result can be obtained. Moreover, a key parameter is used in the energy function to adjust the weights of the spectral and spatial information during the image fusion. In this paper, a multi-object optimization is constructed to determine such a key parameter. The image fusion performance is evaluated through visional perception and some fusion indexes. Experimental results further demonstrate advantages of the proposed technique over the conventional fusion techniques.

Children's perception of dialect variation

ABSTRACTA speaker's regional dialect is a rich source of information about that person. Two studies examined five- to six-year-old children's perception of regional dialect: Can they perceive differences among dialects? Have they made meaningful social connections to specific dialects? Experiment 1 asked children to categorize speakers into groups based on their accent; Experiment 2 asked them to match speakers to (un)familiar cultural items. Each child was tested with two of the following: the child's Home dialect, a Regional variant of that dialect, and a Second-Language variant. Results showed that children could successfully categorize only with a Home vs. Second-Language dialect contrast, but could reliably link cultural items with either a Home vs. Second-Language or a Regional vs. Second-Language dialect contrast. These results demonstrate five- to six-year-old children's developing perceptual skill with dialect, and suggest that they have a gradient representation of dialect variation.