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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 -
IEEE Transactions on Neural Networks... Jun 2024The task of aspect-based sentiment analysis aims to identify sentiment polarities of given aspects in a sentence. Recent advances have demonstrated the advantage of...
The task of aspect-based sentiment analysis aims to identify sentiment polarities of given aspects in a sentence. Recent advances have demonstrated the advantage of incorporating the syntactic dependency structure with graph convolutional networks (GCNs). However, their performance of these GCN-based methods largely depends on the dependency parsers, which would produce diverse parsing results for a sentence. In this article, we propose a dual GCN (DualGCN) that jointly considers the syntax structures and semantic correlations. Our DualGCN model mainly comprises four modules: 1) SynGCN: instead of explicitly encoding syntactic structure, the SynGCN module uses the dependency probability matrix as a graph structure to implicitly integrate the syntactic information; 2) SemGCN: we design the SemGCN module with multihead attention to enhance the performance of the syntactic structure with the semantic information; 3) Regularizers: we propose orthogonal and differential regularizers to precisely capture semantic correlations between words by constraining attention scores in the SemGCN module; and 4) Mutual BiAffine: we use the BiAffine module to bridge relevant information between the SynGCN and SemGCN modules. Extensive experiments are conducted compared with up-to-date pretrained language encoders on two groups of datasets, one including Restaurant14, Laptop14, and Twitter and the other including Restaurant15 and Restaurant16. The experimental results demonstrate that the parsing results of various dependency parsers affect their performance of the GCN-based models. Our DualGCN model achieves superior performance compared with the state-of-the-art approaches. The source code and preprocessed datasets are provided and publicly available on GitHub (see https://github.com/CCChenhao997/DualGCN-ABSA).
PubMed: 36374886
DOI: 10.1109/TNNLS.2022.3219615 -
Behavioural Brain Research Aug 2023Studies have shown that there are overlapping neural bases for cognitive and affective conflict control, but whether the neural activity patterns caused by the two types...
Studies have shown that there are overlapping neural bases for cognitive and affective conflict control, but whether the neural activity patterns caused by the two types of conflict are similar remains to be explored. The present study utilizes electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) to temporally and spatially analyze the differences between cognitive and affective conflict control. We employ a semantic conflict task which includes blocks of cognitive and affective judgements primed by conflicting and non-conflicting contexts. The results showed a typical neural conflict effect in the cognitive judgment blocks as reflected by greater amplitudes of P2, N400, and the late positive potential (LPP), as well as greater activation of the left pre-supplementary motor area (pre-SMA) and the right inferior frontal gyrus (IFG) in the conflict condition relative to the non-conflict condition. These patterns did not emerge in the affective judgments, but instead, showed reversed effects of the LPP and in the left SMA. Taken together, these findings suggest that cognitive and affective conflict control result in different neural activity patterns.
Topics: Humans; Male; Female; Electroencephalography; Brain Mapping; Evoked Potentials; Prefrontal Cortex; Cognition; Magnetic Resonance Imaging
PubMed: 37268253
DOI: 10.1016/j.bbr.2023.114522 -
Journal of Experimental Zoology. Part... Mar 2024The chin, a distinguishing feature of Homo sapiens, has sparked ongoing debates regarding its evolutionary origins and adaptive significance. We contend that these...
The chin, a distinguishing feature of Homo sapiens, has sparked ongoing debates regarding its evolutionary origins and adaptive significance. We contend that these controversies stem from a fundamental disagreement about what constitutes a well-defined biological trait, a problem that has received insufficient attention despite its recognized importance in biology. In this paper, we leverage paleoanthropological research on the human chin to investigate the general issue of character or trait identification. First, we examine four accounts of the human chin from the existing literature: the mandibular differential growth byproduct, the bony prominence, the inverted T-relief, and the symphyseal angle. We then generalize from these accounts and propose a three-stage framework for the process of character identification: description, detection, and justification. We use this framework to reinterpret the four accounts, elucidating key points of contention surrounding the chin as well as other morphological characters. We show that debates over the chin carry broad and important biological implications that extend beyond this trait and that are not mere semantic issues of definition.
Topics: Humans; Animals; Chin; Mandible; Biological Evolution
PubMed: 38528769
DOI: 10.1002/jez.b.23249 -
IEEE Transactions on Haptics 2023In this study, we developed the first tactile perception system for sensory evaluation based on a microelectromechanical systems (MEMS) tactile sensor with an ultrahigh...
In this study, we developed the first tactile perception system for sensory evaluation based on a microelectromechanical systems (MEMS) tactile sensor with an ultrahigh resolution exceeding than that of a human fingertip. Sensory evaluation was performed on 17 fabrics using a semantic differential method with six evaluation words such as "smooth". Tactile signals were obtained at a spatial resolution of 1 µm; the total data length of each fabric was 300 mm. The tactile perception for sensory evaluation was realized with a convolutional neural network as a regression model. The performance of the system was evaluated using data not used for training as unknown fabric. First, we obtained the relationship of the mean squared error (MSE) to the input data length [Formula: see text]. The MSE was 0.27 at [Formula: see text]300 mm. Then, the sensory evaluation and model estimated scores were compared; 89.2% of the evaluation words were successfully predicted at [Formula: see text]300 mm. A system that enables the quantitative comparison of the tactile sensation of new fabrics with existing fabrics has been realized. In addition, the region of the fabric affects each tactile sensation visualized by a heatmap, which can lead to a design policy for achieving the ideal product tactile sensation.
Topics: Humans; Touch Perception; Touch; Fingers; Neural Networks, Computer
PubMed: 37097796
DOI: 10.1109/TOH.2023.3269797 -
Current Medical Imaging Oct 2023Artificial intelligence-based aided diagnostic systems for pulmonary nodules can be divided into subtasks such as nodule detection, segmentation, and benign and...
BACKGROUND
Artificial intelligence-based aided diagnostic systems for pulmonary nodules can be divided into subtasks such as nodule detection, segmentation, and benign and malignant differentiation. Most current studies are limited to single-target tasks. However, aided diagnosis aims to distinguish benign from malignant pulmonary nodules, which requires the fusion of multiple-scale features and comprehensive discrimination based on the results of multiple learning tasks.
OBJECTIVE
This study focuses on the aspects of model design, network structure, and constraints and proposes a novel model that integrates the learning tasks of pulmonary nodule detection, segmentation, and classification under weakly supervised conditions.
METHODS
The main innovations include the following three aspects: (1) a two-dimensional sequence detection model based on a ConvLSTM (Convolutional Long Short-Term Memory) network and U-shaped structure network is proposed to obtain the context space features of image slices fully; (2) a differential diagnosis of benign and malignant pulmonary nodules based on multitask learning is proposed, which uses the annotated data of different types of tasks to mine the potential common features among tasks; and (3) an optimization strategy incorporating prior knowledge of computed tomography images and dynamic weight adjustment of multiple tasks is proposed to ensure that each task can efficiently complete training and learning.
RESULTS
Experiments on the LIDC-IDRI and LUNA16 datasets showed that our proposed method achieved a final competition performance metric score of 87.80% for nodule detection and a Dice similarity coefficient score of 83.95% for pulmonary nodule segmentation.
CONCLUSION
The cross-validation results of the LIDC-IDRI and LUNA16 datasets show that our model achieved 87.80% of the final competition performance metric score for nodule detection and 83.95% of the DSC score for pulmonary nodule segmentation, representing the optimal result for that dataset.
PubMed: 37881081
DOI: 10.2174/0115734056252399231011042326 -
Academic Radiology Mar 2024This study was designed to investigate the value of nomograms based on MRI radiomics and clinical semantic features in identifying pleomorphic xanthoastrocytoma (PXA)...
RATIONALE AND OBJECTIVES
This study was designed to investigate the value of nomograms based on MRI radiomics and clinical semantic features in identifying pleomorphic xanthoastrocytoma (PXA) and ganglioglioma (GG) as well as predicting BRAFV600E expression.
MATERIALS AND METHODS
This study included 265 patients histologically diagnosed with PXA (n = 113) and GG (n = 152). T1WI, T2WI, and CET1 sequences were utilized to extract radiomics features. Univariate analysis, Spearman correlation analysis, and the least absolute shrinkage and selection operator were used for dimensionality reduction and feature selection. Following this, logistic regression was utilized to establish the radiomics model. Univariate and multivariate analyses of clinical semantic features were applied, and clinical models were constructed. The nomograms were established by merging radiomics and clinical features. Furthermore, ROC curve analysis was used for examining the model performance, whereas the decision curve analysis (DCA) examined the clinical utility of the nomograms.
RESULTS
Nomograms achieved the best predictive efficacy compared to clinical and radiomics models alone. Concerning the differentiation between PXA and GG, the area under the curve (AUC) values of the nomogram were 0.879 (0.828-0.930) and 0.887 (0.805-0.969) for the training and testing cohorts, respectively. For predicting BRAFV600E expression, the AUC values of the nomogram were 0.873 (0.811-0.936) and 0.851 (0.740-0.963) for the training and testing cohorts, respectively. DCA confirmed the clinical utility of the nomograms.
CONCLUSION
Nomograms based on radiomics and clinical semantic features were noninvasive tools for differential diagnosis of PXA and GG and predicting BRAFV600E expression, which may be helpful for assessing patient prognosis and developing individualized treatment strategies.
Topics: Humans; Diagnosis, Differential; Nomograms; Ganglioglioma; Radiomics; Astrocytoma; Magnetic Resonance Imaging; Brain Neoplasms; Retrospective Studies
PubMed: 37741731
DOI: 10.1016/j.acra.2023.08.031 -
Memory & Cognition Nov 2023Recent research on item-method directed forgetting demonstrates that forget instructions not only decrease recognition for targets, but also decrease false recognition...
Recent research on item-method directed forgetting demonstrates that forget instructions not only decrease recognition for targets, but also decrease false recognition for foils from the same semantic categories as targets instructed to be forgotten. According to the selective rehearsal account of directed forgetting, this finding suggests that remember instructions may engage elaborative rehearsal of the category-level information of items. In contrast to this explanation, Reid and Jamieson (Canadian Journal of Experimental Psychology / Revue canadienne de psychologie expérimentale, 76(2), 75-86, 2022) proposed that the differential rates of false recognition may emerge at retrieval when foils from "remember" and "forget" categories are compared to traces in memory. Using MINERVA S, an instance model of memory based on MINERVA 2 that incorporates structured semantic representations, Reid and Jamieson successfully simulated lower false recognition for foils from "forget" categories without assuming rehearsal of category-level information. In this study, we extend the directed forgetting paradigm to categories consisting of orthographically related nonwords. Presumably participants would have difficulty rehearsing category-level information for these items because they would have no pre-experimental knowledge of these categories. To simulate the findings in MINERVA S, we imported structured orthographic representations rather than semantic representations. The model not only predicted differential rates of false recognition for foils from "remember" and "forget" categories, but also predicted higher rates of false recognition overall than what was observed for semantic categories. The empirical data closely matched these predictions. These data suggest that differential rates of false recognition due to remember and forget instructions emerge at retrieval when participants compare recognition probes to traces stored in memory.
Topics: Humans; Cues; Canada; Recognition, Psychology; Mental Recall; Learning
PubMed: 37308713
DOI: 10.3758/s13421-023-01433-3 -
NeuroImage Nov 2023In real-life communication, individuals use language that carries evident rewarding and punishing elements, such as praise and criticism. A common trend is to seek more...
In real-life communication, individuals use language that carries evident rewarding and punishing elements, such as praise and criticism. A common trend is to seek more praise while avoiding criticism. Furthermore, semantics is crucial for conveying information, but such semantic access to native and foreign languages is subtly distinct. To investigate how rule learning occurs in different languages and to highlight the importance of semantics in this process, we investigated both verbal and non-verbal rule learning in first (L1) and second (L2) languages using a reinforcement learning framework, including a semantic rule and a color rule. Our computational modeling on behavioral and brain imaging data revealed that individuals may be more motivated to learn and adhere to rules in an L1 compared to L2, with greater striatum activation during the outcome phase in the L1. Additionally, results on the learning rates and inverse temperature in the two rule learning tasks showed that individuals tend to be conservative and are reluctant to change their judgments regarding rule learning of semantic information. Moreover, the greater the prediction errors, the greater activation of the right superior temporal gyrus in the semantic-rule learning condition, demonstrating that such learning has differential neural correlates than symbolic rule learning. Overall, the findings provide insight into the neural mechanisms underlying rule learning in different languages, and indicate that rule learning involving verbal semantics is not a general symbolic learning that resembles a conditioned stimulus-response, but rather has its own specific characteristics.
Topics: Humans; Semantics; Learning; Language; Brain; Temporal Lobe; Brain Mapping; Magnetic Resonance Imaging
PubMed: 37820861
DOI: 10.1016/j.neuroimage.2023.120393 -
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