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Purpose: Current research has demonstrated that behavioral, emotional, and/or social difficulties often accompany developmental language disorder (DLD). It is an open question to what degrees such difficulties arise as consequence of impaired language and communicative skills, or whether they might also be driven by deficits in verbal and nonverbal emotion processing (e.g., the reduced ability to infer and verbalize emotional states from facial expressions). Regarding the existence of nonverbal deficits, previous research has yielded inconsistent findings. This study was aimed at gaining deeper knowledge of the basic aspects of emotion understanding in children with DLD by comparing their performance on nonverbal and verbal emotion categorization tasks to that of typically developing children. Method: Two verbal tasks (Lexical Decision and Valence Decision With Emotion Terms) and two nonverbal tasks (Face Decision and Valence Decision With Facial Expressions) were designed to parallel each other as much as possible, and conducted with twenty-six 6- to 10-year-old children diagnosed with DLD. The same number of typically developed children, carefully matched by age and gender, served as a control group. Results: The children with DLD showed lower performance in both verbal tasks and exhibited noticeable problems in the nonverbal emotion processing task. In particular, they achieved lower accuracy scores when they categorized faces by their valence (positive or negative), but did not differ in their ability to distinguish these faces from pictures displaying animals. Conclusions: This study provides evidence for the hypothesis that problems in emotion processing in children with DLD might be multimodal. Therefore, the results support the idea of mutual influences in the development of language and emotion skills and contribute to the current debate about the domain specificity of DLD (formerly referred to as specific language impairment).

Recent task-switching work in which paper-and-pencil administered single-task lists were compared with task-alternation lists has demonstrated large increases in task-switch costs with concurrent articulatory suppression (AS), implicating a crucial role for verbalization during switching (Baddeley, Chincotta, & Adlam, 2001; Emerson & Miyake, 2003). Experiment 1 replicated this result, using computerized assessment, albeit with much smaller effect sizes than in the original reports. In Experiment 2, AS interference was reduced when a sequential cue (spatial location) that indicated the current position in the sequence of task alternations was given. Finally, in Experiment 3, switch trials and no-switch trials were compared within a block of alternating runs of two tasks. Again, AS interference was obtained mainly when the endogenous sequencing demand was high, and it was comparable for no-switch and switch trials. These results suggest that verbalization may be critical for endogenous maintenance and updating of a sequential plan, rather than exclusively for the actual switching process.

A total of 104 six-year-old children belonging to 4 groups (English monolinguals, Chinese-English bilinguals, French-English bilinguals, Spanish-English bilinguals) were compared on 3 verbal tasks and 1 nonverbal executive control task to examine the generality of the bilingual effects on development. Bilingual groups differed in degree of similarity between languages, cultural background, and language of schooling. On the executive control task, all bilingual groups performed similarly and exceeded monolinguals; on the language tasks the best performance was achieved by bilingual children whose language of instruction was the same as the language of testing and whose languages had more overlap. Thus, executive control outcomes for bilingual children are general but performance on verbal tasks is specific to factors in the bilingual experience.

Laurence B. Leonard Robert V. Kail Purdue University, West Lafayette, IN Xuyang Zhang J. Bruce Tomblin The University of Iowa, Iowa City David J. Francis University of Houston, Houston, TX Contact author: Carol A. Miller, 110 Moore Building, Communication Sciences and Disorders, Pennsylvania State University, University Park, PA 16802-3100. E-mail: cam47{at}psu.edu PURPOSE: To determine whether children with language impairment were slower than typically developing peers at age 14, and whether slowing, if present, was similar across task domains; whether differences in response time (RT) across domains were the same for children with specific language impairment (SLI) and nonspecific language impairment (NLI); and whether RT performance at age 9 predicted performance at age 14. METHOD: Fourteen-year-old children with SLI ( n = 20), NLI ( n = 15), and typical development (NLD; n = 31) were administered several linguistic and nonlinguistic speeded tasks. The children had received the same tasks at age 9. RT performance was examined. RESULTS: Both the SLI and the NLI groups were significantly slower than the NLD group in motor, nonverbal cognitive, and language task domains, and there was no significant difference among domains. Individual analyses showed that most, but not all, children with SLI and NLI were slower than the NLD group mean. Slowing at age 9 and age 14 were moderately correlated. CONCLUSIONS: The results suggest that slow RT is a persistent characteristic of many children with language impairment; however, the nature of the relationship between RT and language performance requires further investigation. KEY WORDS: language functions and disorders, adolescents, experimental research CiteULike     Connotea     Del.icio.us     Digg     Facebook     Reddit     Technorati     Twitter     What's this?

•We scanned the largest cohort of children with developmental language disorder to date.•Our pre-registered predictions were not upheld.•Children with DLD who accurately performed the verb generation task showed no functional abnormality.•Proficiency on language and verbal memory factors correlated positively with activity in distinct brain areas.•Functional neural differences emerged for a subset of DLD who performed the task poorly. Developmental language disorder (DLD) is characterised by difficulties in learning one's native language for no apparent reason. These language difficulties occur in 7% of children and are known to limit future academic and social achievement. Our understanding of the brain abnormalities associated with DLD is limited. Here, we used a simple four-minute verb generation task (children saw a picture of an object and were instructed to say an action that goes with that object) to test children between the ages of 10–15 years (DLD N = 50, typically developing N = 67). We also tested 26 children with poor language ability who did not meet our criteria for DLD. Contrary to our registered predictions, we found that children with DLD did not have (i) reduced activity in language relevant regions such as the left inferior frontal cortex; (ii) dysfunctional striatal activity during overt production; or (iii) a reduction in left-lateralised activity in frontal cortex. Indeed, performance of this simple language task evoked activity in children with DLD in the same regions and to a similar level as in typically developing children. Consistent with previous reports, we found sub-threshold group differences in the left inferior frontal gyrus and caudate nuclei, but only when analysis was limited to a subsample of the DLD group (N = 14) who had the poorest performance on the task. Additionally, we used a two-factor model to capture variation in all children studied (N = 143) on a range of neuropsychological tests and found that these language and verbal memory factors correlated with activity in different brain regions. Our findings indicate a lack of support for some neurological models of atypical language learning, such as the procedural deficit hypothesis or the atypical lateralization hypothesis, at least when using simple language tasks that children can perform. These results also emphasise the importance of controlling for and monitoring task performance.

Keeping the performance of language technologies optimal as time passes is of great practical interest. We study temporal effects on model performance on downstream language tasks, establishing a nuanced terminology for such discussion and identifying factors essential to conduct a robust study. We present experiments for several tasks in English where the label correctness is not dependent on time and demonstrate the importance of distinguishing between temporal model deterioration and temporal domain adaptation for systems using pre-trained representations. We find that, depending on the task, temporal model deterioration is not necessarily a concern. Temporal domain adaptation, however, is beneficial in all cases, with better performance for a given time period possible when the system is trained on temporally more recent data. Therefore, we also examine the efficacy of two approaches for temporal domain adaptation without human annotations on new data. Self-labeling shows consistent improvement and notably, for named entity recognition, leads to better temporal adaptation than even human annotations.

Background Picture description (PD) tasks are widely used to evaluate speech and language ability. Here we describe the results of the traditional encoding condition as well the results of delayed picture description recall task designed to assess visuospatial memory for the picture. This task is computerized, automated, and normed for at‐home administration as part of the California Cognitive Assessment Battery (CCAB) [1]. Methods PARTICIPANTS: 772 healthy participants (55% female, 66.5 ± 8.5 years) completed the picture description and recall task in their homes during normative data collection for CCAB. TECHNOLOGY: The “slipper thief” (Figure 1) PD task was automated with instructions delivered using text‐to‐speech. Verbal responses were digitally recorded, transcribed with consensus automatic speech recognition, and automatically scored. Participants’ performance was remotely monitored by examiners via audio and visual feeds through the CCAB's web‐browser interface. TASK: Participants were asked to describe a visual scene (Figure 1), eliciting an average of 3.1 minutes of speech. The delayed recall trial occurred ∼30 minutes later, eliciting an average of 2.4 minutes of speech. Participants were scored based on their recall of 36 scoring elements. Results Match counts were analyzed for PD encoding, delayed recall, and the difference between these two scores. Multiple regression analysis revealed significant effects of vocabulary (< .001), age (< .05), education (p < .01), and gender (< .01) on encoding and delayed recall, accounting for 23% and 14% of the variance, respectively. Delayed recall scores correlated significantly with delayed recall performance in other verbal tasks including logical memory (.42***) and verbal list learning (.28***). Forgetting, reflected in encoding‐recall difference scores and recall scores, increased with age (p < .001) but was not significantly influenced by other demographic factors. Conclusion PD recall provides a novel measure of visuospatial memory for a complex scene that may assist in identifying individuals at risk for MCI and AD. References [1] Woods, D., Pebler, P., Johnson, D. K., Herron, T., Hall, K., Blank, M., … Baldo, J. (2024). The California Cognitive Assessment Battery (CCAB). Frontiers in Human Neuroscience, 17, 1305529.

•This study employs advanced meta-analytic methods to revisit language production networks and map four key language processing components.•We identified a distinct speech control network separate from the domain-general and high-level language networks.•The left ventral precentral cortex is shown to play a central role in language production, beyond Broca's area.•Our research proposes a novel framework for a language production network.•Propose a two-pathway process, emphasizing the speech control system's central coordination role in language tasks. In recent decades, converging evidence has reached a consensus that human speech production is carried out by large-scale hierarchical network comprising both language-selective and domain-general systems. However, it remains unclear how these systems interact during speech production and the specific contributions of their component regions. By utilizing a series of meta-analytic approaches based on various language tasks, we dissociated four major systems in this study: domain-general, high-level language, motor-perception, and speech-control systems. Using meta-analytic connectivity modeling, we found that while the domain-general system is coactivated with high-level language regions and speech-control networks, only the speech-control network at the ventral precentral gyrus is coactivated with other systems during different speech-related tasks, including motor perception. In summary, this study revisits the previously proposed language models using meta-analytic approaches and highlights the contribution of the speech-control network to the process of speech production independent of articulatory motor.

Background The early detection of amnestic mild cognitive impairment (aMCI) is essential for effective preventive interventions. Artificial Intelligence (AI) offers innovative methods to identify markers of aMCI, complementing traditional approaches. However, research in this field remains in its early stages. In this context, this study focuses on designing AI multimodal neuropsychological instruments to differentiate healthy individuals from aMCI subjects, emphasizing local data calibration and validation. Method We recruited 59 participants from Fleni, Argentina, including 30 healthy controls and 29 individuals diagnosed with aMCI based on Petersen's criteria (2020). All participants underwent comprehensive assessments, including neuropsychological testing (Uniform Data Set 3) and magnetic resonance imaging (MRI) following the ADNI 3 protocol. Participants were video‐ and audio‐recorded while performing language tasks on a web platform, which involved describing two target images (“Cookie Theft” and “Firefighter‐Oasis”) and completing two additional tasks without images (describing their favorite sandwich and reading a story). Multimodal markers were extracted from five modalities: language processing (automated speech transcription), speech acoustics (audio), face mesh analysis (video), blend shapes (video), and emotion recognition (video). Each modality provided a variety of features, including expert‐derived metrics and embedding representations. These features were used to train machine learning classifiers to differentiate individuals with aMCI from healthy controls. Result Participants ranged in age from 60 to 89 years (mean ± SD: 70.95 ± 6.8). Unimodal analysis was performed to study shared information between proposed AI‐markers and traditional neurocognitive tests. We obtained 204 significantly correlated AI‐markers to traditional tests of a total of 432 (47%). Univariate AUC for aMCI diagnosis was measured for all markers, yielding an average above chance performance (0.57 ± 0.062). However, combining all modalities using a multivariate random forest classifier achieved an outstanding AUC of 0.91, highlighting its excellent diagnostic performance. Conclusion This study demonstrates that AI‐based multimodal markers, including language, speech acoustics, facial analysis, and emotion recognition, can effectively differentiate aMCI from healthy controls in an Argentine population. Validating these tools using Spanish‐language data and cost‐effective, non‐invasive methods is crucial for their broader applicability.

Background Emerging research suggests that behavioral‐variant frontotemporal dementia (bvFTD) involves distinct deficits in processing social concepts –units that denote interpersonal traits, events, and circumstances. Recent findings indicate that assessments of these domains could contribute to differential diagnosis and predict syndrome‐specific neural alterations. However, unlike other semantic categories, social concepts lack normative datasets for under‐represented languages, which hinders strategic stimulus selection for much‐needed experiments on under‐served populations. To tackle this gap, we created a normative psycholinguistic database of social and non‐social concepts for Spanish‐speaking Latinos, aimed to fuel groundbreaking research on this population. Methods Healthy subjects over 18 years old completed an online form, rating 600 Spanish words (nouns, verbs, adjectives) in terms of their meanings’ social relevance. Subsets of 100 words with high and low sociality (e.g., “friendship” and “button”, respectively) were randomly presented. After rating their comprehension of the instructions, participants assessed the sociality of each word using a Likert scale (1 = no sociality, 7 = high sociality). Stimuli selection was made based on Diveica et al. (Behav Res Methods 2023, 54:461‐73), who achieved strong validity in categorizing social and non‐social English words, and socialness‐driven variance in lexical tasks. Participants were recruited through flyers in online educational platforms and social media. Result Socialness ratings averaged 5.997 (SD = 0.873) for social words and 1.75 (SD = 0.909) for non‐social words. Participants provided more consistent responses at the extremes of the scale. These findings suggest strong face validity and a clear distinction between categories. Conclusions Focusing on linguistic tools, we aim for a comprehensive study of social concepts and their potential as markers of cerebral dysfunction. In particular, we hope to enhance clinical investigation and diagnoses for populations with bvFTD, while fostering a fertile ground for novel translational research. This Spanish database is crucial for data collection in underrepresented populations and contributes to equity in dementia research and, more broadly, in behavioral neurology, by incorporating the Latin American perspective.