Search Results (35)

This contribution provides new data on Italian first language acquisition and phonological development in preschool children. In total, 104 3- to 6;4-year-old typically developing Italian children were tested with two novel nonword tasks tackling the Italian consonantal system: one for repetition (NWR) and one for discrimination (NWD). NWR data were analyzed in terms of repetition accuracy, featural characteristics, and phonological processes, while NWD was analyzed according to signal detection theory (i.e., A-prime and d-prime) and in terms of discrimination accuracy. The results show the significant role of age on children’s repetition and discrimination abilities: as the children grow older, all the scores improve and the number of errors declines. No complete overlap is found between what children can produce and what they can discriminate, which is in line with what has already been documented in other languages. The findings contribute to the state of the art on the Italian language and provide new perspectives on some methodological issues specific to this language. Full article

Background/Objectives: The Adaptive Control Hypothesis posits varying control demands across language contexts in production, but its role in comprehension is underexplored. We investigated if trilinguals, who manage three dual-language contexts (L1–L2, L2–L3, L1–L3), exhibit differential proactive and reactive control demands during comprehension across these contexts. Methods: Thirty-six Uyghur–Chinese–English trilinguals completed an auditory word-picture matching task across three dual-language contexts during EEG recording. We employed behavioral analysis, drift-diffusion modeling, event-related potential (ERP) analysis, and multivariate pattern analysis (MVPA) to examine comprehension efficiency, evidence accumulation, and neural mechanisms. The design crossed context (L1–L2, L2–L3, L1–L3) with trial type (switch vs. repetition) and switching direction (to dominant vs. non-dominant language). Results: Despite comparable behavioral performance, drift-diffusion modeling revealed distinct processing profiles across contexts, with the L1–L2 context showing the lowest comprehension efficiency due to slower evidence accumulation. In the L1–L3 context, comprehension-specific proactive control was indexed by a larger P300 and smaller N400 for L1-to-L3 switches. Notably, no reactive control (switch costs) was observed across any dual-language context. MVPA successfully classified contexts and switching directions, revealing distinct spatiotemporal neural patterns. Conclusions: Trilingual comprehension switching mechanisms differ from production. Reactive control is not essential, while proactive control is context-dependent, emerging only in the high-conflict L1–L3 context. This proactive strategy involves allocating more bottom-up attention to the weaker L3, which, unlike in production, enhances rather than hinders overall efficiency. Full article

The early detection of Alzheimer’s disease (AD) is important for effective therapeutic interventions and optimized enrollment for clinical trials. Recent studies have shown high accuracy in identifying mild AD by applying visibility graph and machine learning methods to electroencephalographic (EEG) data. We present a novel analytical framework combining Weighted Visibility Graphs (WVG) and ensemble learning to detect individuals in the “preclinical” stage of AD (preAD) using a word repetition EEG paradigm, where WVG is an advanced variant of natural Visibility Graph (VG), incorporating weighted edges based on the visibility degree between corresponding data points. The EEG signals were recorded from 40 cognitively unimpaired elderly participants (20 preclinical AD and 20 normal old) during a word repetition task. Event-related potential (ERP) and oscillatory signals were extracted from each EEG channel and transformed into a WVG network, from which relevant topological features were extracted. The features were selected using t-tests to reduce noise. Subsequent statistical analysis reveals significant disparities in the structure of WVG networks between preAD and normal subjects. Furthermore, Principal Component Analysis (PCA) was applied to condense the input data into its principal features. Leveraging these PCA components as input features, several machine learning algorithms are used to classify preAD vs. normal subjects. To enhance classification accuracy and robustness, an ensemble method is employed alongside the classifiers. Our framework achieved an accuracy of up to 92% discriminating preAD from normal old using both linear and non-linear classifiers, signifying the efficacy of combining WVG and ensemble learning in identifying very early AD from EEG signals. The framework can also improve clinical efficiency by reducing the amount of data required for effective classification and thus saving valuable clinical time. Full article

This article argues that truth can be disclosed and found in incarnation and eucharistic repetition in a proportion between things and mind. Truth as a Christian concept is explored in the Gospel of John, and more specifically in the interaction between Jesus and Pilate, where Pilate at Jesus’ trial asks the question: ‘What is truth?’ The work of biblical commentators is examined in relation to truth in John’s Gospel. The importance of the Word made flesh and its eucharistic repetition is seen as central to truth. This is expanded using the concept of non-identical repetition, as discussed by several scholars, including David Ford and Catherine Pickstock, arguing that Jesus Christ in his incarnate form and in eucharistic repetition calls attention to truth as the proportion between things and mind. The implications of an ontological approach, as opposed to an epistemological approach are drawn in relation to eucharistic theology, with reference to signs (things of this world) and reflective processes (mind) in such a way that where there is a proportion between things and mind, truth is disclosed and found in incarnation and eucharistic repetition. Full article

This paper examines the ability of ChatGPT to generate synthetic comment datasets that mimic those produced by humans. To this end, a collection of datasets containing human comments, freely available in the Kaggle repository, was compared to comments generated via ChatGPT. The latter were based on prompts designed to provide the necessary context for approximating human results. It was hypothesized that the responses obtained from ChatGPT would demonstrate a high degree of similarity with the human-generated datasets with regard to vocabulary usage. Two categories of prompts were analyzed, depending on whether they specified the desired length of the generated comments. The evaluation of the results primarily focused on the vocabulary used in each comment dataset, employing several analytical measures. This analysis yielded noteworthy observations, which reflect the current capabilities of ChatGPT in this particular task domain. It was observed that ChatGPT typically employs a reduced number of words compared to human respondents and tends to provide repetitive answers. Furthermore, the responses of ChatGPT have been observed to vary considerably when the length is specified. It is noteworthy that ChatGPT employs a smaller vocabulary, which does not always align with human language. Furthermore, the proportion of non-stop words in ChatGPT’s output is higher than that found in human communication. Finally, the vocabulary of ChatGPT is more closely aligned with human language than the similarity between the two configurations of ChatGPT. This alignment is particularly evident in the use of stop words. While it does not fully achieve the intended purpose, the generated vocabulary serves as a reasonable approximation, enabling specific applications such as the creation of word clouds. Full article

Objectives. This study aimed to compare the audiological benefits of a non-implantable wearable option for a bone conduction (BC) implant mounted on an arch (SoundArc) to those of traditional BC hearing aids (HAs) mounted on eyeglasses (BCHAs) in patients with moderate to severe conductive or mixed hearing loss. Methods: A preliminary cross-sectional observational prospective cohort study was conducted in the Tertiary Audiological Department, University Hospital. Fourteen adults with conductive or mixed hearing loss (PTA at 0.5-1-2-4 KHz = 67 ± 15 dB HL) who had been wearing conventional BCHAs mounted on eyeglasses for at least 3 years and had declined surgical implantation of a bone conduction hearing implant (BCHI) were included in the study. Unaided and aided pure-tone air conduction (AC) and bone conduction (BC) thresholds, as well as speech tests in quiet and noise, were recorded at baseline and in two different settings: with a BCHI mounted on SoundArc^® and with their own BCHAs mounted on eyeglasses using two couplers. Participants completed questionnaires in both conditions, including the International Inventory for Hearing Aids (IOI-HA), the Hearing Handicap Inventory for Adults/Elderly (HHIA/E), the Speech, Spatial, and Qualities of Hearing Scale (SSQ), a 10-point visual analog scale (VAS), and the Fatigue Impact Scale (FIS). Results: A significant functional gain was observed in both settings (p = 0.0001). Better speech perception in quiet and noise was observed with SoundArc compared to conventional BCHAs on eyeglasses (improvements in word repetition scores in noise: +19.3 at SNR +10 dB, p = 0.002; +12.1 at SNR 0 dB, p = 0.006; and +11.4 at SNR −10 dB, p = 0.002). No significant differences were found in IOI-HA, FIS, and HHIA/E scores. However, significantly better SSQ scores were reported for SoundArc in all domains (p = 0.0038). Conclusions: Although patients were accustomed to using BCHAs mounted on eyeglasses, the bone conduction wearable option of the BCHI (SoundArc) proved to be a viable alternative for adult patients with conductive or mixed hearing loss who are unable or unwilling to undergo BCHI surgery. Full article

Introduction: The objective of the current study was two-fold. First, it aimed to estimate receptive vocabulary and expressive syntax skills in L2 Italian among early sequential/simultaneous bilingual children of migrant single-mother families with very low socioeconomic status (SES). This objective was achieved by matching the participants’ performance with normative data. Secondly, this study aimed to identify which individual and language exposure factors contributed to learning L2 vocabulary and syntax. Methods: Twenty-four early sequential/simultaneous bilingual children (age range = 5.10–12.4 years) and their mothers were enrolled. Mothers answered questions about linguistic biography and demographic information. Children completed Lexical Comprehension, Sentence Repetition, and Non-Word Repetition tasks from the Language Assessment Battery for 4–12-year-olds to, respectively, assess receptive vocabulary, expressive syntax, and phonological processing. Moreover, non-verbal intellectual functioning was evaluated by the Raven’s Test. Results/Discussion: Compared to normative data, 20 children showed lower receptive vocabulary abilities (<−1.5 SD), 24 lower expressive syntax skills (−2DS), and 7 children lower phonological processing (<−1.5 DS). Moreover, L2 phonological processing and the length of L2 exposure in an educational context positively predicted L2 receptive vocabulary as well as L2 expressive syntax skills. To date, performance in L2 among early sequential/simultaneous bilingual children from migrant households and very low SES remains underexplored. Future efforts need to be directed towards the understanding of factors that impact oral competence in L2, considering that these children will also be exposed to written L2 in the school context. Full article

The focus of the present paper is twofold; the first objective is to examine how children with dyslexia (henceforward DYS children) and typically developing children (henceforward TD children) performed in Greek (first language; L1) compared to English (second language; L2) in reading, phonological awareness (PA), rapid automatized naming (RAN), working memory (WM), and short-term memory (STM) tasks. Our second goal is to investigate DYS children’s performance compared to that of TD children in the L1 and L2 domains mentioned above. Thirty-two (DYS = 16; TD = 16) school-aged children (9;7–11;9 years old; M_age = 130.41), basic users of English (level ranging from A1 to A2), carried out a battery test in L1 and L2, respectively, including reading, PA, STM, and WM tasks. More specifically, the tasks were the following: word and nonword decoding, reading accuracy and reading fluency, word and nonword reading per minute, PA, RAN, nonword repetition, as well as forward, backward, and digit span sequencing. This is a work-in-progress study, and preliminary results reveal that DYS students exhibit important reading and memory deficits in both languages. The data analysis indicated that DYS children have particular difficulties and statistically significant differences in L1 and L2 compared to TD in all tasks. In conclusion, this is the first study, at least in Greek, which assesses both reading and memory skills of DYS children in L2. The results reveal deficits in both languages, and the overall findings contribute to theories on the transfer of difficulties of linguistic skills between L1 and L2, while memory scores also underline this co-occurrence. Future implications of this study include a combination of reading and cognitive activities in the teaching methods of English teachers to improve DYS children’s overall performance in learning English as L2. Full article

As in many other countries, baseline data concerning the linguistic development of bilingual children in Sweden are lacking, and suitable methods for identifying developmental language disorder (DLD) in bilinguals are lacking as well. This study presents reference data from 108 typically developing (TD) Turkish/Swedish-speaking children aged 4;0–8;1, for a range of language tasks developed specifically for the assessment of bilinguals (LITMUS test battery, COST Action IS0804). We report on different types of nonword repetition (NWR) tasks (language-specific and language-independent), receptive and expressive vocabulary (Cross-Linguistic Lexical Tasks, CLTs), and narrative macrostructure comprehension and production (Multilingual Assessment Instrument for Narratives, MAIN) in Turkish, the children’s home language, and in Swedish, the language of schooling and society. Performance was investigated in relation to age, language exposure, type of task, and (for NWR and narratives) vocabulary size. There was a positive development with age for all tasks, but effects of language exposure and vocabulary size differed between tasks. Six bilingual Turkish/Swedish children with DLD were individually compared to the TD children. TD/DLD performance overlapped substantially, particularly for NWR, and more so for the production than the comprehension tasks. Surprisingly, the discriminatory potential was poor for both language-specific and language-independent NWR. DLD case studies underscored the importance of interpreting language scores in relation to exposure history, and the need for an increased emphasis on functional language skills as reported by parents and teachers when assessing and diagnosing DLD in bilinguals. Full article

The present study explores comparatively the effectiveness of a cognitive (verbal short-term memory (vSTM), verbal working memory (vWM)) and of a linguistic training (10-week duration each) in the diffusion of gains in cognitive abilities (vSTM and vWM) of in school-aged Greek-speaking children with developmental language disorder (DLD). To this purpose, two computerized training programs i.e., a linguistic and a cognitive one, were developed and applied to three groups (A, B, and C) of children with DLD (N = 49, in total). There were three assessments with two vSTM tasks (non-word repetition and forward digit span) and a vWM task (backward digit span): pre-therapeutically (time 1), where no significant between-group differences were found, post-therapeutically I (time 2), and post-therapeutically II (time 3) and two training phases. In phase Ι, group A received meta-syntactic training, whereas group B vSTM/vWM training and group C received no training. In phase ΙΙ, a reversal of treatment was performed for groups A and B: group A received vSTM/vWM while group B meta-syntactic training. Again, group C received no training. Overall, the results indicated a significant performance improvement for the treatment groups and revealed beneficial far-transfer effects as language therapy can affect vSTM and vWM in addition to direct and near transfer effects. In addition, the intervention type order affected performance as follows: first, better performance on the vSTM task (non-word repetition) was shown when the linguistic treatment was delivered first; second, better performance on the vWM in Time 2 and Time 3 was shown by group B, for which the cognitive treatment was delivered first. Concluding, not only intervention type but also intervention type order can affect performance in DLD. Full article

While cognitive abilities in people with multiple sclerosis (PwMS) have been studied in detail, little is known about linguistic abilities in PwMS and their relation to cognitive impairment. In this cross-sectional explorative study, we aim to investigate the morphosyntactic abilities of PwMS alongside their cognitive performance. Furthermore, we explore the effect of clinical factors, namely, the disease duration and MS type, on the linguistic and cognitive performance of PwMS. By so doing, we aim to shed light on neurocognitive and clinical correlates of linguistic performance in PwMS. We included 78 patients and 78 age-, sex- and education-matched healthy individuals. All participants were additionally administered the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) battery, a verbal short-term memory task (non-word repetition) and questionnaires about mood, fatigue and quality of life. In addition, they underwent examinations with morphology and syntax tasks. PwMS were found to be impaired in morphology (past tense) and selectively impaired in syntax alongside cognitive impairments. Disease duration had the main impact on cognitive abilities. The MS type selectively impacted linguistic abilities, as shown by the remarkably deficient performance of the MS individuals with the progressive disease subtype. Linguistic impairments were predicted by only one measure of the BICAM test, namely, the Symbol Digit Modalities Test (SDMT), a measure of cognitive processing speed. Overall, this study contributes to the better understanding of the linguistic profile of PwMS by reporting selective deficits in their morphological and syntactical abilities. Furthermore, it provides insights into the clinical and cognitive correlates of linguistic performance. By so doing, it suggests clinical implications for the development of intervention programs for PwMS. Full article

Stuttering, a prevalent neurodevelopmental disorder, profoundly affects fluent speech, causing involuntary interruptions and recurrent sound patterns. This study addresses the critical need for the accurate classification of stuttering types. The researchers introduce “TranStutter”, a pioneering Convolution-free Transformer-based DL model, designed to excel in speech disfluency classification. Unlike conventional methods, TranStutter leverages Multi-Head Self-Attention and Positional Encoding to capture intricate temporal patterns, yielding superior accuracy. In this study, the researchers employed two benchmark datasets: the Stuttering Events in Podcasts Dataset (SEP-28k) and the FluencyBank Interview Subset. SEP-28k comprises 28,177 audio clips from podcasts, meticulously annotated into distinct dysfluent and non-dysfluent labels, including Block (BL), Prolongation (PR), Sound Repetition (SR), Word Repetition (WR), and Interjection (IJ). The FluencyBank subset encompasses 4144 audio clips from 32 People Who Stutter (PWS), providing a diverse set of speech samples. TranStutter’s performance was assessed rigorously. On SEP-28k, the model achieved an impressive accuracy of 88.1%. Furthermore, on the FluencyBank dataset, TranStutter demonstrated its efficacy with an accuracy of 80.6%. These results highlight TranStutter’s significant potential in revolutionizing the diagnosis and treatment of stuttering, thereby contributing to the evolving landscape of speech pathology and neurodevelopmental research. The innovative integration of Multi-Head Self-Attention and Positional Encoding distinguishes TranStutter, enabling it to discern nuanced disfluencies with unparalleled precision. This novel approach represents a substantial leap forward in the field of speech pathology, promising more accurate diagnostics and targeted interventions for individuals with stuttering disorders. Full article

Tier-2 reading fluency interventions are specifically tailored for struggling readers, addressing their unique needs. The aim of this study was to examine the impact of a Tier-2 reading fluency intervention on reading capabilities and motivation among third-grade students identified as at risk. The intervention employed various strategies, including non-repetitive reading, exploration of challenging words, model reading, eco-reading, assisted reading, and both self- and hetero-assessment of reading proficiency. A two-group randomized controlled trial was employed, comprising an intervention group (N n = 162) and a delayed intervention control group (N = 183). Both groups underwent pre-test and post-test evaluations in reading accuracy and fluency. Additionally, a separate cohort of students without reading difficulties was assessed (N = 225). The intervention resulted in significantly improved word reading accuracy and reading fluency scores in the intervention group compared to the control group. While the gap between the intervention and control groups was slightly reduced, no significant effects on motivation were observed. These findings underscore the relevance of Tier-2 reading fluency interventions in preventing the development of persistent reading difficulties. Full article

Compound words in psycholinguistics pose a significant challenge for researchers as their meaning involves more than the sum of their parts. The role of semantic relations in this process is crucial, and studies have reported a phenomenon known as relation priming. It suggests that previously encountered relations enhance the processing of subsequent words with the same relation. Notably, this priming effect is limited to cases where there is morpheme repetition between the priming and target words. In the present study, 33 samples from the target group were selected, and the within-subject design of 3 morphemes (modifier-shared, head-shared, non-repeated) × 2 relations (relation-same, relation-different) was adopted to explore whether the relation priming effect would occur without morpheme repetition and its time course. Significant relation priming effects were found in both behavioral and electrophysiological experimental results. These findings indicating relation priming can occur independently of morpheme repetition, and it has been activated at a very early stage (about 200 ms). As the word processing progresses, this activation gradually strengthens, indicating that the relation role is slowly increasing in the process of compound word recognition. It may first be used as context information to help determine the constituent morphemes’ meaning. After the meaning access of the constituent morphemes, they begin to play a role in the semantic composition process. This study uses electrophysiological technology to precisely describe the representation of relation and its time course for the first time, which gives us a deeper understanding of the relation priming process, and at the same time, sheds light on the meaning construction process of compounds. Full article

We present a framework for electroencephalography (EEG)-based classification between patients with Alzheimer’s Disease (AD) and robust normal elderly (RNE) via a graph theory approach using visibility graphs (VGs). This EEG VG approach is motivated by research that has demonstrated differences between patients with early stage AD and RNE using various features of EEG oscillations or cognitive event-related potentials (ERPs). In the present study, EEG signals recorded during a word repetition experiment were wavelet decomposed into 5 sub-bands ($\delta ,\theta ,\alpha ,\beta ,\gamma$). The raw and band-specific signals were then converted to VGs for analysis. Twelve graph features were tested for differences between the AD and RNE groups, and t-tests employed for feature selection. The selected features were then tested for classification using traditional machine learning and deep learning algorithms, achieving a classification accuracy of 100% with linear and non-linear classifiers. We further demonstrated that the same features can be generalized to the classification of mild cognitive impairment (MCI) converters, i.e., prodromal AD, against RNE with a maximum accuracy of 92.5%. Code is released online to allow others to test and reuse this framework. Full article