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Frontiers in Psychology 2021We addressed an understudied topic in the literature of language disorders, that is, processing of derivational morphology, a domain which requires integration of...
We addressed an understudied topic in the literature of language disorders, that is, processing of derivational morphology, a domain which requires integration of semantic and syntactic knowledge. Current psycholinguistic literature suggests that word processing involves morpheme recognition, which occurs immediately upon encountering a complex word. Subsequent processes take place in order to interpret the combination of stem and affix. We investigated the abilities of individuals with agrammatic (PPA-G) and logopenic (PPA-L) variants of primary progressive aphasia (PPA) and individuals with stroke-induced agrammatic aphasia (StrAg) to process pseudowords which violate either the syntactic (word class) rules (*) or the semantic compatibility (argument structure specifications of the base form) rules (*). To this end, we quantified aspects of word knowledge and explored how the distinct deficits of the populations under investigation affect their performance. Thirty brain-damaged individuals and 10 healthy controls participated in a lexical decision task. We hypothesized that the two agrammatic groups (PPA-G and StrAg) would have difficulties detecting syntactic violations, while no difficulties were expected for PPA-L. Accuracy and Reaction Time (RT) patterns indicated: the PPA-L group made fewer errors but yielded slower RTs compared to the two agrammatic groups which did not differ from one another. Accuracy rates suggest that individuals with PPA-L distinguish * from *, reflecting access to and differential processing of syntactic vs. semantic violations. In contrast, the two agrammatic groups do not distinguish between * and *. The lack of difference stems from a particularly impaired performance in detecting syntactic violations, as they were equally unsuccessful at detecting * and *. Reduced grammatical abilities assessed through language measures are a significant predictor for this performance, suggesting that the "hardware" to process syntactic information is impaired. Therefore, they can only judge violations semantically where both * and * fail to pass as semantically ill-formed. This finding further suggests that impaired grammatical knowledge can affect word level processing as well. Results are in line with the psycholinguistic literature which postulates the existence of various stages in accessing complex pseudowords, highlighting the contribution of syntactic/grammatical knowledge. Further, it points to the worth of studying impaired language performance for informing normal language processes.
PubMed: 34912261
DOI: 10.3389/fpsyg.2021.701802 -
Frontiers in Human Neuroscience 2023Prior work has shown positive effects of High Definition transcranial direct current stimulation (HD-tDCS) over the dorsolateral prefrontal cortex (DLPFC) on semantic...
BACKGROUND
Prior work has shown positive effects of High Definition transcranial direct current stimulation (HD-tDCS) over the dorsolateral prefrontal cortex (DLPFC) on semantic memory performance and metamemory monitoring accuracy. However, HD-tDCS requires setup by a trained researcher, which is not always feasible. Few studies have used remotely supervised (rs) tDCS in healthy populations, and remote supervision has strong practical benefits.
OBJECTIVE/HYPOTHESIS
The goal of the current study was to test if previously shown effects of HD-tDCS over the left DLPFC on semantic memory performance and metamemory monitoring accuracy extended to conventional rs-tDCS, which is less focal than HD-tDCS, and to episodic memory and metamemory tasks.
MATERIALS AND METHODS
A total of 36 healthy participants completed 6 weeks of rs-tDCS sessions, with either active left or right anodal DLPFC stimulation, or sham. Participants completed semantic and episodic memory and metamemory tasks, which each lasted for three consecutive sessions, and session order was counterbalanced across participants.
RESULTS
Overall, there were no main effects of rs-tDCS on metamemory monitoring accuracy or memory performance for either the semantic or the episodic tasks. However, there were effects of rs-tDCS that depended on the order of completing the episodic and semantic task sessions. When participants completed the semantic task sessions after the episodic task sessions, semantic recognition was greater in the left anodal DLPFC condition. In a parallel effect, when participants completed the episodic task sessions after the semantic task sessions, episodic recognition was greater in the right anodal DLPFC condition.
CONCLUSION
Prior experience with tDCS is a factor for effects of rs-tDCS on cognition. Additionally, the current experiment provides evidence for the feasibility of fully remotely supervised tDCS in healthy participants.
PubMed: 37635805
DOI: 10.3389/fnhum.2023.1239126 -
NeuroImage. Clinical 2022Multiple sclerosis (MS) is a progressive disease characterized by widespread white matter lesions in the brain and spinal cord. In addition to well-characterized motor...
Multiple sclerosis (MS) is a progressive disease characterized by widespread white matter lesions in the brain and spinal cord. In addition to well-characterized motor deficits, MS results in cognitive impairments in several domains, notably in episodic autobiographical memory. Recent studies have also revealed that patients with MS exhibit deficits in episodic future thinking, i.e., our capacity to imagine possible events that may occur in our personal future. Both episodic memory and episodic future thinking have been shown to share cognitive and neural mechanisms with a related kind of hypothetical simulation known as episodic counterfactual thinking: our capacity to imagine alternative ways in which past personal events could have occurred but did not. However, the extent to which episodic counterfactual thinking is affected in MS is still unknown. The current study sought to explore this issue by comparing performance in mental simulation tasks involving either past, future or counterfactual thoughts in relapsing-remitting MS. Diffusion weighted imaging (DWI) measures were also extracted to determine whether changes in structural pathways connecting the brain's default mode network (DMN) would be associated with group differences in task performance. Relative to controls, patients showed marked reductions in the number of internal details across all mental simulations, but no differences in the number of external and semantic-based details. It was also found that, relative to controls, patients with relapsing-remitting MS reported reduced composition ratings for episodic simulations depicting counterfactual events, but not so for actual past or possible future episodes. Additionally, three DWI measures of white matter integrity-fractional anisotropy, radial diffusivity and streamline counts-showed reliable differences between patients with relapsing-remitting MS and matched healthy controls. Importantly, DWI measures associated with reduced white matter integrity in three association tracts on the DMN-the right superior longitudinal fasciculus, the left hippocampal portion of the cingulum and the left inferior longitudinal fasciculus-predicted reductions in the number of internal details during episodic counterfactual simulations. Taken together, these results help to illuminate impairments in episodic simulation in relapsing-remitting MS and show, for the first time, a differential association between white matter integrity and deficits in episodic counterfactual thinking in individuals with relapsing-remitting MS.
Topics: Humans; Imagination; Memory, Episodic; Multiple Sclerosis; Multiple Sclerosis, Relapsing-Remitting; Nerve Net
PubMed: 35561552
DOI: 10.1016/j.nicl.2022.103033 -
Frontiers in Medicine 2022COVID-19 pandemic is disaster to public health worldwide. Better perspective on COVID's features early in its course-prior to the development of vaccines and widespread...
BACKGROUND
COVID-19 pandemic is disaster to public health worldwide. Better perspective on COVID's features early in its course-prior to the development of vaccines and widespread variants-may prove useful in the understanding of future pandemics. Ontology provides a standardized integrative method for knowledge modeling and computer-assisted reasoning. In this study, we systematically extracted and analyzed clinical phenotypes and comorbidities in COVID-19 patients found at different countries and regions during the early pandemic using an ontology-based bioinformatics approach, with the aim to identify new insights and hidden patterns of the COVID-19 symptoms.
RESULTS
A total of 48 research articles reporting analysis of first-hand clinical data from over 40,000 COVID-19 patients were surveyed. The patients studied therein were diagnosed with COVID-19 before May 2020. A total of 18 commonly-occurring phenotypes in these COVID-19 patients were first identified and then classified into different hierarchical groups based on the Human Phenotype Ontology (HPO). This meta-analytic approach revealed that fever, cough, and the loss of smell and taste were ranked as the most commonly-occurring phenotype in China, the US, and Italy, respectively. We also found that the patients from Europe and the US appeared to have more frequent occurrence of many nervous and abdominal symptom phenotypes (e.g., loss of smell, loss of taste, and diarrhea) than patients from China during the early pandemic. A total of 22 comorbidities, such as diabetes and kidney failure, were found to commonly exist in COVID-19 patients and positively correlated with the severity of the disease. The knowledge learned from the study was further modeled and represented in the Coronavirus Infectious Disease Ontology (CIDO), supporting semantic queries and analysis. Furthermore, also considering the symptoms caused by new viral variants at the later stages, a spiral model hypothesis was proposed to address the changes of specific symptoms during different stages of the pandemic.
CONCLUSIONS
Differential patterns of symptoms in COVID-19 patients were found given different locations, time, and comorbidity types during the early pandemic. The ontology-based informatics provides a unique approach to systematically model, represent, and analyze COVID-19 symptoms, comorbidities, and the factors that influence the disease outcomes.
PubMed: 35155491
DOI: 10.3389/fmed.2022.770031 -
Brain : a Journal of Neurology Sep 2019Impaired processing of emotional signals is a core feature of frontotemporal dementia syndromes, but the underlying neural mechanisms have proved challenging to...
Impaired processing of emotional signals is a core feature of frontotemporal dementia syndromes, but the underlying neural mechanisms have proved challenging to characterize and measure. Progress in this field may depend on detecting functional changes in the working brain, and disentangling components of emotion processing that include sensory decoding, emotion categorization and emotional contagion. We addressed this using functional MRI of naturalistic, dynamic facial emotion processing with concurrent indices of autonomic arousal, in a cohort of patients representing all major frontotemporal dementia syndromes relative to healthy age-matched individuals. Seventeen patients with behavioural variant frontotemporal dementia [four female; mean (standard deviation) age 64.8 (6.8) years], 12 with semantic variant primary progressive aphasia [four female; 66.9 (7.0) years], nine with non-fluent variant primary progressive aphasia [five female; 67.4 (8.1) years] and 22 healthy controls [12 female; 68.6 (6.8) years] passively viewed videos of universal facial expressions during functional MRI acquisition, with simultaneous heart rate and pupillometric recordings; emotion identification accuracy was assessed in a post-scan behavioural task. Relative to healthy controls, patient groups showed significant impairments (analysis of variance models, all P < 0.05) of facial emotion identification (all syndromes) and cardiac (all syndromes) and pupillary (non-fluent variant only) reactivity. Group-level functional neuroanatomical changes were assessed using statistical parametric mapping, thresholded at P < 0.05 after correction for multiple comparisons over the whole brain or within pre-specified regions of interest. In response to viewing facial expressions, all participant groups showed comparable activation of primary visual cortex while patient groups showed differential hypo-activation of fusiform and posterior temporo-occipital junctional cortices. Bi-hemispheric, syndrome-specific activations predicting facial emotion identification performance were identified (behavioural variant, anterior insula and caudate; semantic variant, anterior temporal cortex; non-fluent variant, frontal operculum). The semantic and non-fluent variant groups additionally showed complex profiles of central parasympathetic and sympathetic autonomic involvement that overlapped signatures of emotional visual and categorization processing and extended (in the non-fluent group) to brainstem effector pathways. These findings open a window on the functional cerebral mechanisms underpinning complex socio-emotional phenotypes of frontotemporal dementia, with implications for novel physiological biomarker development.
Topics: Affective Symptoms; Aged; Aphasia, Primary Progressive; Autonomic Nervous System; Brain Mapping; Emotions; Facial Expression; Female; Frontotemporal Dementia; Heart Rate; Humans; Limbic System; Magnetic Resonance Imaging; Male; Middle Aged; Nerve Net; Neuropsychological Tests; Pupil
PubMed: 31321407
DOI: 10.1093/brain/awz204 -
International Journal of Environmental... Dec 2021This study was designed to assess the physiological and psychological benefits of visually looking at foliage plants in adults. This study involved 30 adults in their...
This study was designed to assess the physiological and psychological benefits of visually looking at foliage plants in adults. This study involved 30 adults in their 20s (11 males, 19 females), and using a crossover design, participants looked at four different types of visual stimuli, namely, real plants, artificial plants, a photograph of plants, and no plants for 5 min. Brain waves were measured while viewing each type of plant, and a subjective evaluation of emotions was performed after each visual stimulus. Semantic differential methods (SDM) and Profile of Mood States (POMS) were used for the subjective evaluation. During the real plant visual stimulation, relative theta (RT) power spectrum was increased in the bilateral occipital lobes, while relative high beta (RHB) power spectrum was reduced in the left occipital lobe, indicating a reduction in stress, anxiety, and tension. The subjective survey results revealed that when looking at real plants, the participants exhibited significantly higher "comfort," "natural," and "relaxed" scores as well as an increase in positive mood conditions. In conclusion, among the four types of plants, visual stimulation with real plants induces physiological relaxation in adults and has a positive psychological effect.
Topics: Adult; Anxiety; Cross-Over Studies; Emotions; Female; Humans; Male; Photic Stimulation; Relaxation; Viridiplantae
PubMed: 34948539
DOI: 10.3390/ijerph182412932 -
Discover Sustainability 2021Promoting sustainable lifestyles through Education for Sustainable Development (ESD) is part of the UN's . Earlier empirical studies proved direct interactions with and...
Promoting sustainable lifestyles through Education for Sustainable Development (ESD) is part of the UN's . Earlier empirical studies proved direct interactions with and in natural environments to be effective ESD methods. Pandemic-related lockdowns rendered such courses nearly impossible, which raised concerns about achieving the Sustainable Development Goals (SDGs) in general. To evaluate what young learners know about the concept so far and how it can be taught effectively online, we designed an online learning module tackling sustainability issues and compared it with data from an on-site intervention module for Bavarian 5th graders (~ 10 years old). Cognitive learning as well as attitudinal preferences of 288 learners were monitored in a pretest-posttest design. The learning module comprised two sections: One about botany, plant characteristics, and plant families; the other about the advantages and disadvantages of traditional as well as sustainable farming methods. The customized cognitive test and semantic differentials for and produced three major findings: (1) A digital learning environment successfully and significantly increased sustainability knowledge (2) Learners clearly distinguished the concepts and (3) There is no direct correlation between semantic differential scores and learning outcome.
PubMed: 35425917
DOI: 10.1007/s43621-021-00041-y -
Computational and Mathematical Methods... 2021It is often tricky to differentiate cystic pituitary adenoma from Rathke cleft cyst with visual inspection because of similar MRI presentations between them. We aimed to...
BACKGROUND
It is often tricky to differentiate cystic pituitary adenoma from Rathke cleft cyst with visual inspection because of similar MRI presentations between them. We aimed to design an MR-based radiomics model for improving differential diagnosis between them.
METHODS
Conventional diagnostic MRI data (T1-,T2-, and postcontrast T1-weighted MR images) were obtained from 215 pathologically confirmed patients (105 cases with cystic pituitary adenoma and the other 110 cases with Rathke cleft cyst) and were divided into training ( = 172) and test sets ( = 43). MRI radiomics features were extracted from the imaging data, and semantic imaging features ( = 15) were visually estimated by two radiologists. Four classifiers were used to construct radiomics models through 5-fold crossvalidation after feature selection with least absolute shrinkage and selection operator. An integrated model by combining radiomics and semantic features was further constructed. The diagnostic performance was validated in the test set. Receiver operating characteristic curve was used to evaluate and compare the performance of the models at the background of diagnostic performance by radiologist.
RESULTS
In test set, the combined radiomics and semantic model using ANN classifier obtained the best classification performance with an AUC of 0.848 (95% CI: 0.750-0.946), accuracy of 76.7% (95% CI: 64.1-89.4%), sensitivity of 73.9% (95% CI: 56.0-91.9%), and specificity of 80.0% (95% CI: 62.5-97.5%) and performed better than multiparametric model (AUC = 0.792, 95% CI: 0.674-0.910) or semantic model (AUC = 0.823, 95% CI: 0.705-0.941). The two radiologists had an accuracy of 69.8% and 74.4%, respectively, sensitivity of 69.6% and 73.9%, and specificity of 70.0% and 75.0%.
CONCLUSIONS
The MR-based radiomics model had technical feasibility and good diagnostic performance in the differential diagnosis between cystic pituitary adenoma and Rathke cleft cyst.
Topics: Adenoma; Adult; Central Nervous System Cysts; Computational Biology; Diagnosis, Computer-Assisted; Diagnosis, Differential; Female; Humans; Image Interpretation, Computer-Assisted; Machine Learning; Magnetic Resonance Imaging; Male; Middle Aged; Neural Networks, Computer; Pituitary Neoplasms; Retrospective Studies; Semantics
PubMed: 34422095
DOI: 10.1155/2021/6438861 -
Cortex; a Journal Devoted To the Study... Sep 2021Naming of nouns and verbs can be selectively impaired in neurological disorders, but the specificity of the neural and cognitive correlates of such dissociation remains...
Naming of nouns and verbs can be selectively impaired in neurological disorders, but the specificity of the neural and cognitive correlates of such dissociation remains unclear. Functional imaging and stroke research sought to identify cortical regions selectively recruited for nouns versus verbs, yet findings are inconsistent. The present study investigated this issue in neurodegenerative diseases known to selectively affect different brain networks, thus providing new critical evidence of network specificity. We examined naming performances on nouns and verbs in 146 patients with different neurodegenerative syndromes (Primary Progressive Aphasia - PPA, Alzheimer's disease - AD, and behavioral variant Frontotemporal Dementia - FTD) and 30 healthy adults. We then correlated naming scores with MRI-derived cortical thickness values as well as with performances in semantic and syntactic tasks, across all subjects. Results indicated that patients with the semantic variant PPA named significantly fewer nouns than verbs. Instead, nonfluent/agrammatic PPA patients named fewer verbs than nouns. Across all subjects, performance on nouns (adjusted for verbs) specifically correlated with cortical atrophy in left anterior temporal regions, and performance on verbs (adjusted for nouns) with atrophy in left inferior and middle frontal, inferior parietal and posterior temporal regions. Furthermore, lower lexical-semantic abilities correlated with deficits in naming both nouns and verbs, while lower syntactic abilities only correlated with naming verbs. Our results show that different neural and cognitive mechanisms underlie naming of specific grammatical categories in neurodegenerative diseases. Importantly, our findings showed that verb processing depends on a widespread perisylvian networks, suggesting that some regions might be involved in processing different types of action knowledge. These findings have important implications for early differential diagnosis of neurodegenerative disorders.
Topics: Adult; Aphasia, Primary Progressive; Humans; Language; Neurodegenerative Diseases; Semantics; Temporal Lobe
PubMed: 34182153
DOI: 10.1016/j.cortex.2021.05.006 -
Frontiers in Digital Health 2021Semantic similarity is a useful approach for comparing patient phenotypes, and holds the potential of an effective method for exploiting text-derived phenotypes for...
Semantic similarity is a useful approach for comparing patient phenotypes, and holds the potential of an effective method for exploiting text-derived phenotypes for differential diagnosis, text and document classification, and outcome prediction. While approaches for context disambiguation are commonly used in text mining applications, forming a standard component of information extraction pipelines, their effects on semantic similarity calculations have not been widely explored. In this work, we evaluate how inclusion and disclusion of negated and uncertain mentions of concepts from text-derived phenotypes affects similarity of patients, and the use of those profiles to predict diagnosis. We report on the effectiveness of these approaches and report a very small, yet significant, improvement in performance when classifying primary diagnosis over MIMIC-III patient visits.
PubMed: 34939069
DOI: 10.3389/fdgth.2021.781227