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Frontiers in Psychology 2023Developmental stuttering is a fluency disorder that may be caused by neurological, genetic, or familial factors. However, a general perception that stuttering is caused...
PURPOSE
Developmental stuttering is a fluency disorder that may be caused by neurological, genetic, or familial factors. However, a general perception that stuttering is caused by psychological problems could lead to negative attitudes toward stuttering, causing prejudice or discrimination against people who stutter (PWS). Thus, our study aimed to investigate whether certain beliefs in etiology of stuttering are related to the negative perception of stuttering.
METHODS
A web-based survey of 413 native Japanese adults, aged 20-69, who did not suffer from stuttering, schizophrenia, or depression, was conducted in August 2021. The participants were recruited through the Web monitor panel. Participants were divided into three uniform groups based on their response to a 27-item questionnaire about their implicit belief regarding the etiology of stuttering: belief in the biological model (stuttering-biological group), belief in the psychological model (stuttering-psychological group), and the control group (those who responded to perception of healthy adult males). Participants were also asked to respond to 25 items of semantic differential scales about perception of stuttering or healthy adult males. Responses were summarized into several factors by factor analysis, and factor scores were compared among the three groups. The stuttering-biological group had the fewest participants, comprising 80 individuals. Overall, a total of 240 participants, 80 from each group, were included in the analysis.
RESULTS
Some pairs of stereotypes included in semantic differential scales revealed differences between the groups; PWS, irrespective of the participants of the biological or psychological group, were considered as having negative stereotyping properties such as being "tense," "anxious," or "afraid." Additionally, three concepts from the factor analysis of these 25 items were analyzed using an analysis of variance, and significant differences were found; the mean factor score of the "danger" stereotype was lower in the stuttering-biological group compared to the stuttering-psychological group.
CONCLUSION
Although the simplification of the biological model is not recommended, anti-stigma campaigns to educate people that stuttering is caused by multidimensional factors, not just psychological ones, could change the general public's negative perceptions of stuttering.
PubMed: 38034304
DOI: 10.3389/fpsyg.2023.1279169 -
PloS One 2023In recent years, with the development of deep learning technology, deep neural networks have been widely used in the field of medical image segmentation. U-shaped...
In recent years, with the development of deep learning technology, deep neural networks have been widely used in the field of medical image segmentation. U-shaped Network(U-Net) is a segmentation network proposed for medical images based on full-convolution and is gradually becoming the most commonly used segmentation architecture in the medical field. The encoder of U-Net is mainly used to capture the context information in the image, which plays an important role in the performance of the semantic segmentation algorithm. However, it is unstable for U-Net with simple skip connection to perform unstably in global multi-scale modelling, and it is prone to semantic gaps in feature fusion. Inspired by this, in this work, we propose a Deep Tensor Low Rank Channel Cross Fusion Neural Network (DTLR-CS) to replace the simple skip connection in U-Net. To avoid space compression and to solve the high rank problem, we designed a tensor low-ranking module to generate a large number of low-rank tensors containing context features. To reduce semantic differences, we introduced a cross-fusion connection module, which consists of a channel cross-fusion sub-module and a feature connection sub-module. Based on the proposed network, experiments have shown that our network has accurate cell segmentation performance.
Topics: Neural Networks, Computer; Algorithms; Data Compression; Reproduction; Semantic Differential; Image Processing, Computer-Assisted
PubMed: 38032913
DOI: 10.1371/journal.pone.0294727 -
Frontiers in Psychology 2023The ability to speak is grounded in general memory and control processes and likely changes across the lifespan. However, our knowledge on how word production abilities...
INTRODUCTION
The ability to speak is grounded in general memory and control processes and likely changes across the lifespan. However, our knowledge on how word production abilities naturally evolve from childhood to old age remains marginally investigated. Our aim was to shed further light on this issue by exploiting the contrast between two ways to elicit word production: referential picture naming and inferential naming from definition.
METHODS
We collected accuracy and production latencies in a picture naming task and in a naming from definition task from 130 participants ranging from 10 to 80 years old. Measures of vocabulary size, digit span memory, semantic and phonemic fluencies and processing speed were also collected. We used multivariate adaptative regression splines and regression models to characterize lifespan patterns of the two tasks.
RESULTS
Patterns of increase in performance were similar for picture naming and naming from definition only from childhood to young adulthood. In the second half of the lifespan, significant decrease of performance was found in older adults for picture naming (from around 60 years-old) but not for naming from definition. Clearly, word production elicited with an inferential task (naming from definition) yields different age-related patterns than usually described in the literature with a referential task (picture naming).
DISCUSSION
We discuss how cognitive processes such as visual-conceptual processes and lexical prediction may explain the differential pattern of results in aging in referential and inferential production tasks. We argue for more lifespan studies and the need to investigate language production beyond picture naming, in particular with respect to aging.
PubMed: 38022984
DOI: 10.3389/fpsyg.2023.1237523 -
Language and Speech Nov 2023Constructed languages, frequently invented to support world-building in fantasy and science fiction genres, are often intended to sound similar to the characteristics of...
Constructed languages, frequently invented to support world-building in fantasy and science fiction genres, are often intended to sound similar to the characteristics of the people who speak them. The aims of this study are (1) to investigate whether some fictional languages, such as Orkish whose speakers are portrayed as villainous, are rated more negatively by listeners than, for example, the Elvish languages, even when they are all produced without emotional involvement in the voice; and (2) to investigate whether the rating results can be related to the sound structure of the languages under investigation. An online rating experiment with three 7-point semantic differential scales was conducted, in which three sentences from each of 12 fictional languages (Neo-Orkish, Quenya, Sindarin, Khuzdul, Adûnaic, Klingon, Vulcan, Atlantean, Dothraki, Na'vi, Kesh, ʕuiʕuid) were rated, spoken by a female and a male speaker. The results from 129 participants indicate that Klingon and Dothraki do indeed sound more unpleasant, evil, and aggressive than the Elvish languages Sindarin and Quenya. Furthermore, this difference in rating is predicted by certain characteristics of the sound structure, such as the percentage of non-German sounds and the percentage of voicing. The implications of these results are discussed in relation to theories of language attitude.
PubMed: 38018568
DOI: 10.1177/00238309231202944 -
Cellular and Molecular Biology... Nov 2023Diabetic foot ulcer (DFU) is the most serious and costly chronic complication that may lead to disability and even death in patients suffering from diabetes mellitus...
Diabetic foot ulcer (DFU) is the most serious and costly chronic complication that may lead to disability and even death in patients suffering from diabetes mellitus (DM). However, the clinical diagnosis and prognosis of DFU is inadequate. There is still a lack of effective biomarkers for its early diagnosis. We obtained the circRNA expression dataset GSE114248 and mRNA expression dataset GSE80178 from the GEO. R software was used to identify the differentially expressed circRNAs (DECs). The mRNAs associated with DFU were identified by a random forest algorithm and intersected with mRNAs predicted by circRNAs. Then, the circRNA-miRNA-mRNA network was established and the hub genes were screened using GO semantic similarity and were validated by the GSE199939 dataset. Meanwhile, the expression level of the biomarkers was verified by RT-PCR assays and immunohistochemistry. Finally, GSEA was conducted to determine differential immune cell infiltration and the immunological cells' relationships with hub genes. We identified three hub genes including KIAA1109, ENPP5, and NRP1 that might play an important role in DFU. ROC curve results also showed a good performance of these three genes in the validation dataset. Furthermore, RT-PCR assays and immunohistochemistry confirmed the results above. Immune infiltration analysis indicated that DFU had a significant increase in Neutrophils. Moreover, three hub genes were closely correlated with a variety of inflammatory cells. KIAA1109, ENPP5, and NRP1 are key hub genes of DFU. They might play an important role in the development of DFU and could be potential biomarkers in DFU.
Topics: Humans; Diabetic Foot; RNA, Circular; MicroRNAs; Computational Biology; RNA, Messenger; Diabetes Mellitus
PubMed: 38015522
DOI: 10.14715/cmb/2023.69.11.27 -
Brain Topography Jul 2024More than 10% of births are preterm, and the long-term consequences on sensory and semantic processing of non-linguistic information remain poorly understood. 17 very...
More than 10% of births are preterm, and the long-term consequences on sensory and semantic processing of non-linguistic information remain poorly understood. 17 very preterm-born children (born at < 33 weeks gestational age) and 15 full-term controls were tested at 10 years old with an auditory object recognition task, while 64-channel auditory evoked potentials (AEPs) were recorded. Sounds consisted of living (animal and human vocalizations) and manmade objects (e.g. household objects, instruments, and tools). Despite similar recognition behavior, AEPs strikingly differed between full-term and preterm children. Starting at 50ms post-stimulus onset, AEPs from preterm children differed topographically from their full-term counterparts. Over the 108-224ms post-stimulus period, full-term children showed stronger AEPs in response to living objects, whereas preterm born children showed the reverse pattern; i.e. stronger AEPs in response to manmade objects. Differential brain activity between semantic categories could reliably classify children according to their preterm status. Moreover, this opposing pattern of differential responses to semantic categories of sounds was also observed in source estimations within a network of occipital, temporal and frontal regions. This study highlights how early life experience in terms of preterm birth shapes sensory and object processing later on in life.
Topics: Humans; Female; Male; Evoked Potentials, Auditory; Child; Semantics; Auditory Perception; Electroencephalography; Acoustic Stimulation; Infant, Premature; Brain; Infant, Newborn; Recognition, Psychology
PubMed: 38010487
DOI: 10.1007/s10548-023-01022-2 -
Cognition & Emotion Nov 2023The effect of emotion on associative memory is still an open question. Our aim was to test whether discrepant findings are due to differential impact of emotion on...
The effect of emotion on associative memory is still an open question. Our aim was to test whether discrepant findings are due to differential impact of emotion on different types of associative memory or to differences in the way participants encoded stimuli across studies. We examined the effect of negative content on multiple forms of associative memory, using the same encoding task. Two registered experiments were conducted in parallel with random allocation of participants to experiments. Each experiment included 4 encoding blocks, in which participants read a neutral text comprised of 6 paragraphs, which were interleaved with neutral or negative images. Images were controlled for visual properties and semantic similarity. Memory tests included recognition memory, Remember/Know, order memory, temporal source memory and contextual memory. Analyses showed that emotion decreased contextual memory but not order memory or temporal source memory. We also found that temporal source memory and contextual memory were correlated. Recognition accuracy and subjective recollection were not impacted by emotion. In agreement with previous work, participants self-reported a reduced ability to integrate blocks containing negative images with paragraphs. In contrast to our hypothesis, results suggest that emotion does not impact all types of associative memory when stimuli are controlled.
PubMed: 37955276
DOI: 10.1080/02699931.2023.2279182 -
Journal of Neurology Mar 2024Increasing evidence implicates endo-lysosomal dysfunction in frontotemporal dementia (FTD). 18 proteins were quantified using a mass spectrometry assay panel in the...
Increasing evidence implicates endo-lysosomal dysfunction in frontotemporal dementia (FTD). 18 proteins were quantified using a mass spectrometry assay panel in the cerebrospinal fluid of 36 people with the language variant of FTD, primary progressive aphasia (PPA) (including 13 with non-fluent variant (nfvPPA), 11 with semantic variant (svPPA), and 12 with logopenic variant (lvPPA)) and 19 healthy controls. The concentrations of the cathepsins (B, D, F, L1, and Z) as well as AP-2 complex subunit beta, ganglioside GM2 activator, beta-hexosaminidase subunit beta, tissue alpha L-fucosidase, and ubiquitin were decreased in nfvPPA compared with controls. In contrast, the concentrations of amyloid beta A4 protein, cathepsin Z, and dipeptidyl peptidase 2 were decreased in svPPA compared with controls. No proteins were abnormal in lvPPA. These results indicate a differential alteration of lysosomal proteins in the PPA variants, suggesting those with non-Alzheimer's pathologies are more likely to show abnormal lysosomal function.
Topics: Humans; Aphasia, Primary Progressive; Amyloid beta-Peptides; Frontotemporal Dementia; Language; Lysosomes
PubMed: 37917233
DOI: 10.1007/s00415-023-12063-9 -
Frontiers in Neurology 2023Frontotemporal dementia (FTD) is a spectrum of clinically and pathologically heterogenous neurodegenerative dementias. Clinical and anatomical variants of FTD have been...
Frontotemporal dementia (FTD) is a spectrum of clinically and pathologically heterogenous neurodegenerative dementias. Clinical and anatomical variants of FTD have been described and associated with underlying frontotemporal lobar degeneration (FTLD) pathology, including tauopathies (FTLD-tau) or TDP-43 proteinopathies (FTLD-TDP). FTD patients with predominant degeneration of anterior temporal cortices often develop a language disorder of semantic knowledge loss and/or a social disorder often characterized by compulsive rituals and belief systems corresponding to predominant left or right hemisphere involvement, respectively. The neural substrates of these complex social disorders remain unclear. Here, we present a comparative imaging and postmortem study of two patients, one with FTLD-TDP (subtype C) and one with FTLD-tau (subtype Pick disease), who both developed new rigid belief systems. The FTLD-TDP patient developed a complex set of values centered on positivity and associated with specific physical and behavioral features of pigs, while the FTLD-tau patient developed compulsive, goal-directed behaviors related to general themes of positivity and spirituality. Neuroimaging showed left-predominant temporal atrophy in the FTLD-TDP patient and right-predominant frontotemporal atrophy in the FTLD-tau patient. Consistent with antemortem cortical atrophy, histopathologic examinations revealed severe loss of neurons and myelin predominantly in the anterior temporal lobes of both patients, but the FTLD-tau patient showed more bilateral, dorsolateral involvement featuring greater pathology and loss of projection neurons and deep white matter. These findings highlight that the regions within and connected to anterior temporal lobes may have differential vulnerability to distinct FTLD proteinopathies and serve important roles in human belief systems.
PubMed: 37900607
DOI: 10.3389/fneur.2023.1245886 -
Frontiers in Artificial Intelligence 2023In recent years, with the rapid development of deep learning technology, great progress has been made in computer vision, image recognition, pattern recognition, and... (Review)
Review
In recent years, with the rapid development of deep learning technology, great progress has been made in computer vision, image recognition, pattern recognition, and speech signal processing. However, due to the black-box nature of deep neural networks (DNNs), one cannot explain the parameters in the deep network and why it can perfectly perform the assigned tasks. The interpretability of neural networks has now become a research hotspot in the field of deep learning. It covers a wide range of topics in speech and text signal processing, image processing, differential equation solving, and other fields. There are subtle differences in the definition of interpretability in different fields. This paper divides interpretable neural network (INN) methods into the following two directions: model decomposition neural networks, and semantic INNs. The former mainly constructs an INN by converting the analytical model of a conventional method into different layers of neural networks and combining the interpretability of the conventional model-based method with the powerful learning capability of the neural network. This type of INNs is further classified into different subtypes depending on which type of models they are derived from, i.e., mathematical models, physical models, and other models. The second type is the interpretable network with visual semantic information for user understanding. Its basic idea is to use the visualization of the whole or partial network structure to assign semantic information to the network structure, which further includes convolutional layer output visualization, decision tree extraction, semantic graph, etc. This type of method mainly uses human visual logic to explain the structure of a black-box neural network. So it is a post-network-design method that tries to assign interpretability to a black-box network structure afterward, as opposed to the pre-network-design method of model-based INNs, which designs interpretable network structure beforehand. This paper reviews recent progress in these areas as well as various application scenarios of INNs and discusses existing problems and future development directions.
PubMed: 37899962
DOI: 10.3389/frai.2023.974295