Modelling confrontation naming and discourse performance in aphasia

Background: It is well documented in the literature that the ability to produce discourse is what matters most to people with aphasia (PWA) and their families. However, quantifying discourse in typical clinical settings is a challenging task due to its dynamic and multiply determined nature. As a result, professionals often depend on confrontation naming tests to identify and measure impaired underlying cognitive mechanisms that are also hypothesised to be important for discourse production.

Aims: The main goals of the study were to investigate the extent to which confrontation naming test (CNT) scores are predictive of (i) the proportion of paraphasias in connect speech, and (ii) the amount of information PWA can effectively communicate.

Methods & Procedures: Data from 98 monolingual PWA were retrieved from AphasiaBank and analysed using structural equation modelling. Performance in CNTs was modelled as a latent variable based on the Boston Naming Test, the Western Aphasia Battery–R Naming Subtest, and the Verb Naming Test. Performance at the discourse level was modelled based on the observed proportions of paraphasias in three discourse tasks (free speech, eventcasts, and story retell). Informativeness was quantified using the percentage of Correct Information Units based on story re-tell.

Outcomes & Results: For the first question, the regression coefficient between the two latent factors was estimated to be –0.52. When the latent factor based on the CNTs was regressed on informativeness, the estimated regression coefficient was equal to 0.68.

Conclusions: Performance on CNTs was not a strong predictor of the proportion of paraphasias produced in connected speech but was substantially higher for the amount of information communicated by PWA. Clinicians are cautioned not to predict a speaker’s performance at the discourse level after establishing CNT performance. Other anomic behaviours (e.g., pauses) during discourse production may be associated with CNT performance and should be considered in future investigations.     

Networks involved in olfaction and their dynamics using independent component analysis and unified structural equation modeling

The study of human olfaction is complicated by the myriad of processing demands in conscious perceptual and emotional experiences of odors. Combining functional magnetic resonance imaging with convergent multivariate network analyses, we examined the spatiotemporal behavior of olfactory‐generated blood‐oxygenated‐level‐dependent signal in healthy adults. The experimental functional magnetic resonance imaging (fMRI) paradigm was found to offset the limitations of olfactory habituation effects and permitted the identification of five functional networks. Analysis delineated separable neuronal circuits that were spatially centered in the primary olfactory cortex, striatum, dorsolateral prefrontal cortex, rostral prefrontal cortex/anterior cingulate, and parietal‐occipital junction. We hypothesize that these functional networks subserve primary perceptual, affective/motivational, and higher order olfactory‐related cognitive processes. Results provided direct evidence for the existence of parallel networks with top‐down modulation for olfactory processing and clearly distinguished brain activations that were sniffing‐related versus odor‐related. A comprehensive neurocognitive model for olfaction is presented that may be applied to broader translational studies of olfactory function, aging, and neurological disease. Hum Brain Mapp 35:2055–2072, 2014. © 2013 Wiley Periodicals, Inc .     

Functional magnetic resonance imaging of verbal fluency and confrontation naming using compressed image acquisition to permit overt responses

Verbal fluency and confrontation naming, two tests of word retrieval, are of great utility in the field of cognitive neuroscience. However, in the context of functional magnetic resonance imaging (fMRI), movement artefact has necessitated the use of covert paradigms, which has limited clinical application. We developed two overt fMRI paradigms that allowed for performance measurement and hence were appropriate for use with patient groups. The paradigms incorporated a blocked-design and compressed-acquisition methodology where cues were presented and responses made in a "silent" period allowing for performance measurement. The slow response pace was specifically designed for older and potentially cognitively impaired participants. Verbal fluency was associated with activation in the middle frontal gyrus (Brodmann areas 46 and 9), anterior cingulate gyrus and inferior frontal gyrus (area 44 and 45). Confrontation naming activated areas of the temporo-occipital cortices (areas 18, 19, and 37) and the inferior frontal gyrus. The two paradigms successfully activated regions involved in executive and word retrieval processes and overcame the potential artefacts resulting from overt speech during image acquisition, providing useful neuropsychological tools to investigate cognitive deficits in clinical populations.     

Thalamic-insular dysconnectivity in schizophrenia: evidence from structural equation modeling

Structural and functional studies have shown that schizophrenia is often associated with frontolimbic abnormalities in the prefrontal and mediotemporal regions. It is still unclear, however, if such dysfunctional interaction extends as well to relay regions such as the thalamus and the anterior insula. Here, we measured gray matter volumes of five right-hemisphere regions in 68 patients with schizophrenia and 77 matched healthy subjects. The regions were amygdala, thalamus, and entorhinal cortex (identified as anomalous by prior studies on the same population) and dorsolateral prefrontal cortex and anterior insula (isolated by voxel-based morphometry analysis). We used structural equation modeling and found altered path coefficients connecting the thalamus to the anterior insula, the amygdala to the DLPFC, and the entorhinal cortex to the DLPFC. In particular, patients exhibited a stronger thalamus-insular connection than healthy controls. Instead, controls showed positive entorhinal-DLPFC and negative amygdalar-DLPFC connections, both of which were absent in the clinical population. Our data provide evidence that schizophrenia is characterized by an impaired right-hemisphere network, in which intrahemispheric communication involving relay structures may play a major role in sustaining the pathophysiology of the disease.     

Resilience and coping as predictors of general well-being in the elderly: a structural equation modeling approach

Objectives: The aims of this article are: (a) to test for the validity of the three constructs involved in the structural model; (b) to test for the effects of both coping strategies and resilient coping on well-being in a sample of elderly, by means of a structural model with latent variables; (c) to empirically study whether a brief scale of resilient coping could predict well-being over and above that predicted by the coping resources.

Methods: The research is a survey design. The sample consisted of 225 non-institutionalized elderly people living in the city of Valencia (Spain). The three constructs measured were: well-being, resilient coping, and coping strategies.

Results: The analyses consist of a series of alternative structural models with latent variables with resilience, problem-focused coping, and emotion-focused coping as the potential predictors of well-being as measured by Ryff's well-being scales. Due to parsimony reasons, the model retained is that with a single predictor of well-being: resilient coping.

Conclusion: A latent variable measuring resilient coping is able to predict a significant and large part of the variance in well-being, without the need of including coping strategies. Results impact on well-being literature of the elderly is discussed.     

Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data

The ultimate goal of brain connectivity studies is to propose, test, modify, and compare certain directional brain pathways. Path analysis or structural equation modeling (SEM) is an ideal statistical method for such studies. In this work, we propose a two-stage unified SEM plus GLM (General Linear Model) approach for the analysis of multisubject, multivariate functional magnetic resonance imaging (fMRI) time series data with subject-level covariates. In Stage 1, we analyze the fMRI multivariate time series for each subject individually via a unified SEM model by combining longitudinal pathways represented by a multivariate autoregressive (MAR) model, and contemporaneous pathways represented by a conventional SEM. In Stage 2, the resulting subject-level path coefficients are merged with subject-level covariates such as gender, age, IQ, etc., to examine the impact of these covariates on effective connectivity via a GLM. Our approach is exemplified via the analysis of an fMRI visual attention experiment. Furthermore, the significant path network from the unified SEM analysis is compared to that from a conventional SEM analysis without incorporating the longitudinal information as well as that from a Dynamic Causal Modeling (DCM) approach.     

Latent volumetric structure of the human brain: Exploratory factor analysis and structural equation modeling of gray matter volumes in healthy children and adults

Previous studies have investigated patterns of volumetric covariance (i.e. intercorrelation) among brain regions. Methodological issues, however, have limited the validity and generalizability of findings from these prior studies. Additionally, patterns of volumetric covariance have often been assumed to reflect the presence of structural networks, but this assumption has never been tested formally. We identified patterns of volumetric covariance, correlated these patterns with behavioral measures, and tested the hypothesis that the observed patterns of covariance reflect the presence of underlying networks. Specifically, we performed factor analysis on regional brain volumes of 99 healthy children and adults, and we correlated factor scores with scores on the Stroop Word-Color Interference Test. We identified four latent volumetric systems in each hemisphere: dorsal cortical, limbic, posterior, and basal ganglia. The positive correlation of the right posterior system with Stroop scores suggested that larger latent volumes are detrimental to inhibitory control. We also applied Structural Equation Modeling (SEM) to our dataset (n = 107) to test whether a model based on the anatomical pathways within cortico-striatal-thalamic-cortical (CSTC) circuits accounts for the covariances observed in our sample. The degree to which SEM predicted volumetric covariance in the CSTC circuit depended on whether we controlled for age and whole brain volume in the analyses. Removing the effects of age worsened the fit of the model, pointing to a possible developmental component in establishing connections within CSTC circuits. These modeling techniques may prove useful in the future for the study of structural networks in disease populations.     

Disentangling age‐ and disease‐related alterations in schizophrenia brain network using structural equation modeling: A graph theoretical study based on minimum spanning tree

Functional brain networks have been shown to undergo fundamental changes associated with aging or schizophrenia. However, the mechanism of how these factors exert influences jointly or interactively on brain networks remains elusive. A unified recognition of connectomic alteration patterns was also hampered by heterogeneities in network construction and thresholding methods. Recently, an unbiased network representation method regardless of network thresholding, so called minimal spanning tree algorithm, has been applied to study the critical skeleton of the brain network. In this study, we aimed to use minimum spanning tree (MST) as an unbiased network reconstruction and employed structural equation modeling (SEM) to unravel intertwined relationships among multiple phenotypic and connectomic variables in schizophrenia. First, we examined global and local brain network properties in 40 healthy subjects and 40 schizophrenic patients aged 21–55 using resting‐state functional magnetic resonance imaging (rs‐fMRI). Global network alterations are measured by graph theoretical metrics of MSTs and a connectivity‐transitivity two‐dimensional approach was proposed to characterize nodal roles. We found that networks of schizophrenic patients exhibited a more star‐like global structure compared to controls, indicating excessive integration, and a loss of regional transitivity in the dorsal frontal cortex (corrected p <.05). Regional analysis of MST network topology revealed that schizophrenia patients had more network hubs in frontal regions, which may be linked to the “overloading” hypothesis. Furthermore, using SEM, we found that the level of MST integration mediated the influence of age on negative symptom severity (indirect effect 95% CI [0.026, 0.449]). These findings highlighted an altered network skeleton in schizophrenia and suggested that aging‐related enhancement of network integration may undermine functional specialization of distinct neural systems and result in aggravated schizophrenic symptoms.     

Brain structural connectivity,anhedonia, and phenotypes of major depressive disorder: A structural equation model approach

Aberrant brain structural connectivity in major depressive disorder (MDD) has been repeatedly reported, yet many previous studies lack integration of different features of MDD with structural connectivity in multivariate modeling approaches. In n = 595 MDD patients, we used structural equation modeling (SEM) to test the intercorrelations between anhedonia, anxiety, neuroticism, and cognitive control in one comprehensive model. We then separately analyzed diffusion tensor imaging (DTI) connectivity measures in association with those clinical variables, and finally integrated brain connectivity associations, clinical/cognitive variables into a multivariate SEM. We first confirmed our clinical/cognitive SEM. DTI analyses (FWE‐corrected) showed a positive correlation of anhedonia with fractional anisotropy (FA) in the right anterior thalamic radiation (ATR) and forceps minor/corpus callosum, while neuroticism was negatively correlated with axial diffusivity (AD) in the left uncinate fasciculus (UF) and inferior fronto‐occipital fasciculus (IFOF). An extended SEM confirmed the associations of ATR FA with anhedonia and UF/IFOF AD with neuroticism impacting on cognitive control. Our findings provide evidence for a differential impact of state and trait variables of MDD on brain connectivity and cognition. The multivariate approach shows feasibility of explaining heterogeneity within MDD and tracks this to specific brain circuits, thus adding to better understanding of heterogeneity on the biological level.     

Attachment insecurities,maladaptive perfectionism,and eating disorder symptoms: A latent mediated and moderated structural equation modeling analysis across diagnostic groups

Although 96–100% of individuals with eating disorders (EDs) report insecure attachment, the specific mechanisms by which adult insecure attachment dimensions affect ED symptomatology remain to date largely unknown. This study examined maladaptive perfectionism as both a mediator and a moderator of the relationship between insecure attachment (anxiety and avoidance) and ED symptomatology in a clinical, treatment seeking, sample. Insecure anxious and avoidant attachment, maladaptive perfectionism, and ED symptomatology were assessed in 403 participants from three medium size specialized care centres for EDs in Italy. Structural equation modeling indicated that maladaptive perfectionism served as mediator between both insecure attachment patterns and ED symptomatology. It also interacted with insecure attachment to predict higher levels of ED symptoms – highlighting the importance of both insecure attachment patterns and maladaptive aspects of perfectionism as treatment targets. Multiple-group comparison analysis did not reveal differences across diagnostic groups (AN, BN, EDNOS) in mediating, main and interaction effects of perfectionism. These findings are consistent with recent discussions on the classification and treatment of EDs that have highlighted similarities between ED diagnostic groups and could be viewed through the lens of the Trans-theoretical Model of EDs. Implications for future research and intervention are discussed.     

Functional and effective connectivity of visuomotor control systems demonstrated using generalized partial least squares and structural equation modeling

Tasks employing parametric variation in movement rate are associated with predictable modulations in neural activity and provide a convenient context for developing new techniques for system identification. Using a multistage approach, we explored the functional and effective connectivity of a visuomotor control system by combining generalized partial least squares (gPLS) with subsequent structural equation modeling (SEM) to reveal the relationships between neural activity and finger movement rate in an experiment involving visually paced left or right thumb flexion. The gPLS in the first analysis stage automatically identified spatially distributed sets of BOLD‐contrast signal changes using linear combinations of sigmoidal basis functions parameterized by kinematic variables. The gPLS provided superior sensitivity in detecting task‐related functional activity patterns via a step‐wise comparison with both classical linear modeling and behavior correlation analysis. These activity patterns were used in the second analysis stage, which employed SEM to characterize the areal regional interactions. The hybrid gPLS/SEM procedure allowed modeling of complex regional interactions in a network including primary motor cortex, premotor areas, cerebellum, thalamus, and basal ganglia, with differential activity modulations with respect to rate observed in the corticocerebellar and corticostriate subsystems. This effective connectivity analysis of visuomotor control circuits showed that both the left and right corticocerebellar and corticostriate circuits exhibited movement rate‐related modulation. The identification of the functional connectivity among regions participating particular classes of behavior using gPLS, followed by the estimation of the effective connectivity using SEM is an efficient means to characterize the neural interactions underlying variations in sensorimotor behavior. Hum Brain Mapp, 2009. © 2009 Wiley‐Liss, Inc.     

Age-Related Enhancements in Positive Emotionality across The Life Span: Structural Equation Modeling of Brain and Behavior

Aging is associated with a bias in attention and memories toward positive and away from negative emotional content. In addition, emotion regulation appears to improve with age, despite concomitant widespread cognitive decline coupled with gray matter volume loss in cortical and subcortical regions thought to subserve emotion regulation. Here, we address this emotion-aging paradox using the behavioral data of an emotion regulation task from a population-derived, male and female, human sample (CamCAN) and use structural equation modeling together with multivariate analysis of structural MRI images of the same sample to investigate brain–behavior relationships. In a series of measurement models, we show the relationship between age and emotionality is best explained by a four-factor model, compared with single and hierarchical factor models. These four latent factors are interpreted as Basal Negative Affect, Positive Reactivity, Negative Reactivity and Positive Regulation (upregulating positive emotion to negative content). Increasing age uniquely contributes to increased Basal Negative Affect, Positive Reactivity, and Positive Regulation, but not Negative Reactivity. Furthermore, we show gray matter volumes, namely in the bilateral frontal operculum, medial frontal gyrus, bilateral hippocampal complex, bilateral middle temporal gyri, and bilateral angular gyrus, are distinctly related to these four latent factors. Finally, we show that a subset of these brain–behavior relationships remain significant when accounting for age and demographic data. Our results support the notion of an age-related increase in positivity and are interpreted in the context of the socioemotional selectivity theory of improved emotion regulation in older age.SIGNIFICANCE STATEMENT Aging is associated with a paradoxical increase in well-being and improved emotion regulation despite widespread cognitive decline and gray matter volume loss in neural regions that underlie emotion regulation. Using a population-derived sample, we test the theories behind this emotion/aging paradox with an emotion regulation task and structural MRI data. We report robust age-related increases in positivity across the life span and show structural neural integrity influences this relationship with increasing age. Several brain–behavior relationships remained unaffected by age and may represent empirically derived neural markers to explore the paradox of increased well-being in old age. The results support the predictions of socioemotional selectivity theory of improved emotion regulation in older age and challenge the amygdala-focused neural predictions of the aging brain model.     

Schizophrenic outpatient perceptions of psychiatric treatment and psychotic symptomatology: An investigation using structural equation modeling

Schizophrenic patient perceptions of treatment have clinical value and deserve detailed psychiatric investigation. The present study sought a model indicating statistically estimated cause-effect relationships of perceptions and psychotic symptomatology of outpatients with schizophrenia by applying a method of structural equation modeling. The perceptions included in this model were patient satisfaction with treatment, perceptions of their treating psychiatrists, and patient-role perception. Scores of Positive and Negative Syndrome Scale and poor insight measures were added to the model as possible influential factors. The constructed model revealed that the poor insight exerted a major influence on the patient-role perception that had small effects on the reliable therapist perception and the satisfaction. It was also shown that satisfaction was chiefly determined by the reliable therapist perception that was formed in the treatment relationship, rather independently of the other construct. These findings were valuable in terms of their implications for understanding the makeup of the perceptions and the strategy for interventions to improve them.     

Development and validation of the Rasch-based depression screening (DESC) using Rasch analysis and structural equation modelling

Questionnaires for the assessment of depression benefit from modern test construction like item-response-modelling. We developed two parallel 10 item depression questionnaires, the Rasch-based Depression Screening version 1 (DESC-I) and 2 (DESC-II), by combining Rasch analysis and structural equation modelling on patient samples suffering primarily from a mental disorder or from somatic diseases. Both scales base upon a Rasch homogeneous item bank and proved unidimensionality and good model fit. Cut-off scores with good sensitivity and specificity were developed using ROC analyses. Results suggest that DESC may be appropriately used to screen for depression and may be beneficial for repeated measurements.