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Computers in Biology and Medicine Mar 2024Medical image inpainting holds significant importance in enhancing the quality of medical images by restoring missing areas, thereby rendering them suitable for...
Medical image inpainting holds significant importance in enhancing the quality of medical images by restoring missing areas, thereby rendering them suitable for diagnostic purposes. While several techniques have been previously proposed for medical image inpainting, they are not suitable for distorted images containing metallic implants due to their limited consideration of known shaped masking. To overcome this limitation, a novel Vectorized Box Interpolation with Arbitrary Auto-Rand Augment Masking technique has been proposed which involves scaling and vectorizing images to expand their details and generating asymmetrically shaped masking in an automatic random format. One of the challenging tasks in this regard is the precise detection of lost regions, which is addressed through the introduction of the Regional Pixel Semantic Network. This technique employs the locally shared features (LSF) based region sensing with FCN (fully convolutional network) segmentation, which performs automatic segmentation based on neighboring pixel local dependency and regional features to determine the location of masked regions. During the reconstruction of missing parts, a significant challenge posed is the inability to recognize proximity in encoding owing to the generation of shadow-like regions on the feature map. To address this issue, a novel Multilayered DRC Regularized Pyramidal Attention AE Model has been proposed which employs dilated convolution with coherent pyramidal attention for feature extraction and improves image resolution using a Laplacian convolutional layer. Moreover, the realness of the generated image is determined using the Quantile Differential Mechanism model, where in the Quantile Differential Partial Convolutional Discriminator utilizes the hyperbolic tangent activation function in the partial convolutional layer to calculate recognition accuracy. As a result, the proposed method achieves high percentages for accuracy (98 %), precision (97 %), sensitivity (96 %), recall (95 %), and F-measure (96 %) thereby outperforming existing methods. Overall, this proposed method effectively handles distorted images with metallic implants, accurately detects lost regions, and improves the reconstructed image quality.
Topics: Image Processing, Computer-Assisted; Neural Networks, Computer; Semantic Web; Brain
PubMed: 38215616
DOI: 10.1016/j.compbiomed.2023.107767 -
Brain Impairment : a Multidisciplinary... Dec 2023To examine associations between post-stroke participation and personal factors, including demographic characteristics, self- and threat appraisals, and personality...
PURPOSE
To examine associations between post-stroke participation and personal factors, including demographic characteristics, self- and threat appraisals, and personality variables.
METHODS
An exploratory cross-sectional study with purpose-designed survey was completed online or via mail. The survey was comprised of demographic and health-related questions and multiple questionnaires, including the Stroke Impact Scale Version 3.0 (SISv3) (participation/perceived recovery), Community Integration Questionnaire (CIQ) (participation), Head Injury Semantic Differential III (pre- vs post-stroke self-concept/self-discrepancy), Appraisal of Threat and Avoidance Questionnaire (threat appraisal), Life Orientation Test - Revised (optimism) and Relationships Questionnaire (adult attachment style) that measured variables of interest. Sixty-two participants, aged 24-96 years who had experienced a stroke (one or multiple events) and had returned to community living, completed the survey. Associations were examined using correlations, and univariate and multiple linear regression analyses.
RESULTS
Regression analysis showed that greater participation, measured using the CIQ, was associated with younger age, female gender, lower self-discrepancy and higher perceived recovery, explaining 69% of the variability in CIQ participation. Further, greater participation on the SISv3 was associated with lower self-discrepancy and higher perceived recovery, explaining 64% of the variability in SISv3 participation.
CONCLUSIONS
Results indicate that personal factors, particularly self-appraisals like self-concept/self-discrepancy, in combination with perceived recovery may be important in explaining a large portion of variance in post-stroke participation. Specifically, findings highlight the interrelatedness of self-concept change, perceived recovery and post-stroke participation. Further longitudinal research is needed to clarify the directionality of these associations throughout the hospital-to-home transition.
Topics: Adult; Humans; Female; Independent Living; Cross-Sectional Studies; Stroke; Self Concept; Surveys and Questionnaires
PubMed: 38167356
DOI: 10.1017/BrImp.2022.31 -
Neurology Jan 2024Prior work suggests that cognitive resilience may contribute to the heterogeneity of cognitive decline. This study examined whether distinct cortical proteins provide...
BACKGROUND AND OBJECTIVES
Prior work suggests that cognitive resilience may contribute to the heterogeneity of cognitive decline. This study examined whether distinct cortical proteins provide resilience for different cognitive abilities.
METHODS
Participants were from the Religious Orders Study or the Rush Memory and Aging Project who had undergone annual assessments of 5 cognitive abilities and postmortem assessment of 9 Alzheimer disease and related dementia (ADRD) pathologies. Proteome-wide examination of the dorsolateral prefrontal cortex using tandem mass tag and liquid chromatography-mass spectrometry yielded 8,425 high-abundance proteins. We applied linear mixed-effect models to quantify residual cognitive change (cognitive resilience) of 5 cognitive abilities by regressing out cognitive decline related to age, sex, education, and indices of ADRD pathologies. Then we added terms for each of the individual proteins to identify cognitive resilience proteins associated with the different cognitive abilities.
RESULTS
We included 604 decedents (69% female; mean age at death = 89 years) with proteomic data. A total of 47 cortical proteins that provide cognitive resilience were identified: 22 were associated with specific cognitive abilities, and 25 were common to at least 2 cognitive abilities. NRN1 was the only protein that was associated with more than 2 cognitive abilities (semantic memory: estimate = 0.020, SE = 0.004, = 2.2 × 10; episodic memory: estimate = 0.029, SE = 0.004, = 5.8 × 10; and working memory: estimate = 0.021, SE = 0.004, = 1.2 × 10). Exploratory gene ontology analysis suggested that among top molecular pathways, mitochondrial translation was a molecular mechanism providing resilience in episodic memory, while nuclear-transcribed messenger RNA catabolic processes provided resilience in working memory.
DISCUSSION
This study identified cortical proteins associated with various cognitive abilities. Differential associations across abilities may reflect distinct underlying biological pathways. These data provide potential high-value targets for further mechanistic and drug discovery studies to develop targeted treatments to prevent loss of cognition.
Topics: Female; Humans; Aged, 80 and over; Male; Proteome; Proteomics; Resilience, Psychological; Cognition; Memory, Episodic; Neuropeptides; GPI-Linked Proteins
PubMed: 38165375
DOI: 10.1212/WNL.0000000000207816 -
Neurology Feb 2024The 3 clinical presentations of primary progressive aphasia (PPA) reflect heterogenous neuropathology, which is difficult to be recognized in vivo. Resting-state (RS)...
BACKGROUND AND OBJECTIVES
The 3 clinical presentations of primary progressive aphasia (PPA) reflect heterogenous neuropathology, which is difficult to be recognized in vivo. Resting-state (RS) EEG is promising for the investigation of brain electrical substrates in neurodegenerative conditions. In this study, we aim to explore EEG cortical sources in the characterization of the 3 variants of PPA.
METHODS
This is a cross-sectional, single-center, memory center-based cohort study. Patients with PPA and healthy controls were consecutively recruited at the Neurology Unit, IRCCS San Raffaele Scientific Institute (Milan, Italy). Each participant underwent an RS 19-channel EEG. Using standardized low-resolution brain electromagnetic tomography, EEG current source densities were estimated at voxel level and compared among study groups. Using an RS functional MRI-driven model of source reconstruction, linear lagged connectivity (LLC) values within language and extra-language brain networks were obtained and analyzed among groups.
RESULTS
Eighteen patients with logopenic PPA variant (lvPPA; mean age = 72.7 ± 6.6; % female = 52.4), 21 patients with nonfluent/agrammatic PPA variant (nfvPPA; mean age = 71.7 ± 8.1; % female = 66.6), and 9 patients with semantic PPA variant (svPPA; mean age = 65.0 ± 6.9; % female = 44.4) were enrolled in the study, together with 21 matched healthy controls (mean age = 69.2 ± 6.5; % female = 57.1). Patients with lvPPA showed a higher delta density than healthy controls ( < 0.01) and patients with nfvPPA ( < 0.05) and svPPA ( < 0.05). Patients with lvPPA also displayed a greater theta density over the left posterior hemisphere ( < 0.01) and lower alpha2 values ( < 0.05) over the left frontotemporal regions than controls. Patients with nfvPPA showed a diffuse greater theta density than controls ( < 0.05). LLC was altered in all patients relative to controls ( < 0.05); the alteration was greater at slow frequency bands and within language networks than extra-language networks. Patients with lvPPA also showed greater LLC values at theta band than patients with nfvPPA ( < 0.05).
DISCUSSION
EEG findings in patients with PPA suggest that lvPPA-related pathology is associated with a characteristic disruption of the cortical electrical activity, which might help in the differential diagnosis from svPPA and nfvPPA. EEG connectivity was disrupted in all PPA variants, with distinct findings in disease-specific PPA groups.
CLASSIFICATION OF EVIDENCE
This study provides Class IV evidence that EEG analysis can distinguish PPA due to probable Alzheimer disease from PPA due to probable FTD from normal aging.
Topics: Humans; Female; Aged; Middle Aged; Male; Cohort Studies; Cross-Sectional Studies; Academies and Institutes; Aphasia, Primary Progressive; Electroencephalography
PubMed: 38165298
DOI: 10.1212/WNL.0000000000207993 -
Linguistics Nov 2023In this work we are presenting a database structure to encode the phenomenon of differential possession across languages, considering noun possession classes and...
In this work we are presenting a database structure to encode the phenomenon of differential possession across languages, considering noun possession classes and possessive constructions as independent but linked. We show how this structure can be used to study different dimensions of possession: semantics, noun valence, and possessive constructions. We present preliminary survey results from a global sample of 120 languages and show that there is a universal semantic core in both inalienable and non-possessible noun classes. Inalienables are centered on body parts and kinship. Non-possessibles are centered on animals, humans, and natural elements.
PubMed: 38144363
DOI: 10.1515/ling-2022-0021 -
European Journal of Investigation in... Dec 2023According to the neo-functional developmental theory, newborns and infants exhibit complex psycho-bodily functioning. The Basic Experiences of the Self (BEsS) refer to...
According to the neo-functional developmental theory, newborns and infants exhibit complex psycho-bodily functioning. The Basic Experiences of the Self (BEsS) refer to how they fulfil their essential life needs by organising their psycho-bodily functions in a typical configuration. As part of our research study, we developed a prototype psychometric tool called the BEsS Assessment Form (BAF) to assess the BEsS in infants aged zero to three years. We collected video recordings of their spontaneous behaviour and used the BAF to evaluate function polarity. In the BAF, thirty pairs of words represent functions in their dyadic polarity. To estimate the level of function polarity, we used the Osgood semantic differential scale, which ranges from seven to one. The study's results confirm that functions can be assessed by grading along the opposite polarity spectrum. Moreover, in accordance with the theory, the functions can be grouped into four domains: the emotional, postural motor, physiological, and cognitive-symbolic planes. Our findings suggest that the characteristics of BEsS are significantly influenced by the activation of the physiological and postural motor functions, which are related to the early regulation of the autonomic nervous system and can be used to evaluate infant arousal.
PubMed: 38131897
DOI: 10.3390/ejihpe13120198 -
Cognitive Science Dec 2023The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain...
The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and computational advances in neuroscience and artificial intelligence now provide unprecedented opportunities to study the human brain in action as language is read and understood. Recent contextualized language models seem to be able to capture homonymic meaning variation ("bat", in a baseball vs. a vampire context), as well as more nuanced differences of meaning-for example, polysemous words such as "book", which can be interpreted in distinct but related senses ("explain a book", information, vs. "open a book", object) whose differences are fine-grained. We study these subtle differences in lexical meaning along the concrete/abstract dimension, as they are triggered by verb-noun semantic composition. We analyze functional magnetic resonance imaging (fMRI) activations elicited by Italian verb phrases containing nouns whose interpretation is affected by the verb to different degrees. By using a contextualized language model and human concreteness ratings, we shed light on where in the brain such fine-grained meaning variation takes place and how it is coded. Our results show that phrase concreteness judgments and the contextualized model can predict BOLD activation associated with semantic composition within the language network. Importantly, representations derived from a complex, nonlinear composition process consistently outperform simpler composition approaches. This is compatible with a holistic view of semantic composition in the brain, where semantic representations are modified by the process of composition itself. When looking at individual brain areas, we find that encoding performance is statistically significant, although with differing patterns of results, suggesting differential involvement, in the posterior superior temporal sulcus, inferior frontal gyrus and anterior temporal lobe, and in motor areas previously associated with processing of concreteness/abstractness.
Topics: Humans; Artificial Intelligence; Brain Mapping; Brain; Language; Semantics
PubMed: 38103208
DOI: 10.1111/cogs.13388 -
Seizure Jan 2024A clinical decision tool for Transient Loss of Consciousness (TLOC) could reduce currently high misdiagnosis rates and waiting times for specialist assessments. Most...
OBJECTIVE
A clinical decision tool for Transient Loss of Consciousness (TLOC) could reduce currently high misdiagnosis rates and waiting times for specialist assessments. Most clinical decision tools based on patient-reported symptom inventories only distinguish between two of the three most common causes of TLOC (epilepsy, functional /dissociative seizures, and syncope) or struggle with the particularly challenging differentiation between epilepsy and FDS. Based on previous research describing differences in spoken accounts of epileptic seizures and FDS seizures, this study explored the feasibility of predicting the cause of TLOC by combining the automated analysis of patient-reported symptoms and spoken TLOC descriptions.
METHOD
Participants completed an online web application that consisted of a 34-item medical history and symptom questionnaire (iPEP) and spoken interaction with a virtual agent (VA) that asked eight questions about the most recent experience of TLOC. Support Vector Machines (SVM) were trained using different combinations of features and nested leave-one-out cross validation. The iPEP provided a baseline performance. Inspired by previous qualitative research three spoken language based feature sets were designed to assess: (1) formulation effort, (2) the proportion of words from different semantic categories, and (3) verb, adverb, and adjective usage.
RESULTS
76 participants completed the application (Epilepsy = 24, FDS = 36, syncope = 16). Only 61 participants also completed the VA interaction (Epilepsy = 20, FDS = 29, syncope = 12). The iPEP model accurately predicted 65.8 % of all diagnoses, but the inclusion of the language features increased the accuracy to 85.5 % by improving the differential diagnosis between epilepsy and FDS.
CONCLUSION
These findings suggest that an automated analysis of TLOC descriptions collected using an online web application and VA could improve the accuracy of current clinical decisions tools for TLOC and facilitate clinical stratification processes (such as ensuring appropriate referral to cardiological versus neurological investigation and management pathways).
Topics: Humans; Seizures; Syncope; Unconsciousness; Epilepsy; Surveys and Questionnaires; Diagnosis, Differential
PubMed: 38091849
DOI: 10.1016/j.seizure.2023.11.022 -
Journal of Neuropsychology Mar 2024Glioma patients often suffer from deficits in language and executive functioning. Performance in verbal fluency (generating words within one minute according to a...
Glioma patients often suffer from deficits in language and executive functioning. Performance in verbal fluency (generating words within one minute according to a semantic category-category fluency, or given letter-letter fluency) is typically impaired in this patient group. While both language and executive functioning play a role in verbal fluency, the relative contribution of both domains remains unclear. We aim to retrospectively investigate glioma patients' performance on verbal and nonverbal fluency and to explore the influence of language and executive functioning on verbal fluency. Sixty-nine adults with gliomas in eloquent areas underwent a neuropsychological test battery (verbal fluency, nonverbal fluency, language, and executive functioning tests) before surgery (T1) and a subgroup of 31 patients also at three (T2) and twelve months (T3) after surgery. Preoperatively, patients were impaired in all verbal fluency tasks and dissociations were found based on tumour location. In contrast, nonverbal fluency was intact. Different language and executive functioning tests predicted performance on category fluency animals and letter fluency, while no significant predictors for category fluency professions were found. The longitudinal results indicated that category fluency professions deteriorated after surgery (T1-T2, T1-T3) and that nonverbal fluency improved after surgery (T1-T3, T2-T3). Verbal fluency performance can provide information on different possible underlying deficits in language and executive functioning in glioma patients, depending on verbal fluency task selection. Efficient task (order) selection can be based on complexity. Category fluency professions can be selected to detect more permanent long-term deficits.
Topics: Adult; Humans; Verbal Behavior; Retrospective Studies; Language; Executive Function; Glioma; Neuropsychological Tests
PubMed: 38087828
DOI: 10.1111/jnp.12356 -
Frontiers in Psychology 2023Alterations of verbalized thought occur frequently in psychotic disorders. We characterize linguistic findings in individuals with schizophrenia based on the current... (Review)
Review
INTRODUCTION
Alterations of verbalized thought occur frequently in psychotic disorders. We characterize linguistic findings in individuals with schizophrenia based on the current literature, including findings relevant for differential and early diagnosis.
METHODS
Review of literature published via PubMed search between January 2010 and May 2022.
RESULTS
A total of 143 articles were included. In persons with schizophrenia, language-related alterations can occur at all linguistic levels. Differentiating from findings in persons with affective disorders, typical symptoms in those with schizophrenia mainly include so-called "poverty of speech," reduced word and sentence production, impaired processing of complex syntax, pragmatic language deficits as well as reduced semantic verbal fluency. At the at-risk state, "poverty of content," pragmatic difficulties and reduced verbal fluency could be of predictive value.
DISCUSSION
The current results support multilevel alterations of the language system in persons with schizophrenia. Creative expressions of psychotic experiences are frequently found but are not in the focus of this review. Clinical examinations of linguistic alterations can support differential diagnostics and early detection. Computational methods (Natural Language Processing) may improve the precision of corresponding diagnostics. The relations between language-related and other symptoms can improve diagnostics.
PubMed: 38078276
DOI: 10.3389/fpsyg.2023.1287706