Network interactions among limbic cortices, basal forebrain, and cerebellum differentiate a tone conditioned as a Pavlovian excitor or inhibitor: fluorodeoxyglucose mapping and covariance structural modeling

1994 ◽  
Vol 72 (4) ◽  
pp. 1717-1733 ◽  
Author(s):  
A. R. McIntosh ◽  
F. Gonzalez-Lima

1. The objective was to examine how opposite learned behavioral responses to the same physical tone were differentiated by the pattern of interactions between extraauditory neural regions. This was pursued using a new approach combining behavior, neuroimaging, and network analysis to integrate information about differences in regional activity with differences in the covariance relationships between brain areas. 2. A tone was used as either a Pavlovian conditioned excitor or inhibitor. Rats were conditioned with reinforced trials of a conditioned excitor (A+) intermixed with nonreinforced trials of a tone-light compound (AX-). The tone was the excitor (A+) for the tone-excitor group and was the inhibitor (X-) for the tone-inhibitor group. After conditioning, all rats were injected with [14C(U)]2-fluoro-2-deoxyglucose (FDG) and presented with the same tone. 3. FDG autoradiography was used to measure regional activity and to generate interregional correlations of activity resulting from the presentation of the tone. A stepwise discriminant analysis was used to select brain regions that differentiated the excitor from the inhibitor effects. 4. Network analysis consisted of constructing an anatomic model of the brain regions, selected by the discriminant analysis, linking the regions with their known anatomical connections. Then, functional models for the tone-excitor and -inhibitor groups were constructed using structural equation modeling. Correlations of activity between regions were decomposed to calculate numerical weights, or path coefficients, for each anatomic path. These path coefficients were used to compare the interactions for the tone-excitor and -inhibitor models. 5. Regional differences in FDG uptake were found in the sulcal frontal cortex (SFC), lateral septum (LS), medial septum/diagonal band (MS/DB), retrosplenial cortex (RS), and dentate-interpositus nuclei of the cerebellum (DEN). Discriminant analysis selected three other regions that significantly discriminated the tone-excitor and -inhibitor groups: perirhinal cortex (PRh), nucleus accumbens (ACB), and the anteroventral nucleus of the thalamus (AVN). 6. Structural equation modeling identified two functional circuits that differentiated the groups. One involved the basal forebrain regions (LS, MS/DB, ACB) and the other limbic thalamocortical structures (SFC, RS, PRh, AVN). Differences in the interactions within these circuits were mainly in sign of the covariance relationships between regions, from positive for the tone-excitor model to negative path coefficients for the tone-inhibitor model. The path coefficient between the basal forebrain circuit and the limbic thalamocortical circuit showed the largest magnitude difference. This quantitative difference was mediated by a path from the MS/DB to PRh.(ABSTRACT TRUNCATED AT 400 WORDS)

2017 ◽  
Vol 13 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Ned Kock

Recent methodological developments building on partial least squares (PLS) techniques and related ideas have significantly contributed to bridging the gap between factor-based and composite-based structural equation modeling (SEM) methods. PLS-SEM is extensively used in the field of e-collaboration, as well as in many other fields where multivariate statistical analyses are employed. The author compares results obtained with four methods: covariance-based SEM with full information maximum likelihood (FIML), factor-based SEM with common factor model assumptions (FSEM1), factor-based SEM building on the PLS Regression algorithm (FSEM2), and PLS-SEM employing the Mode A algorithm (PLSA). The comparison suggests that FSEM1 yields path coefficients and loadings that are very similar to FIML's; and that FSEM2 yields path coefficients that are very similar to FIML's and loadings that are very similar to PLSA's.


Assessment ◽  
2020 ◽  
pp. 107319112091109 ◽  
Author(s):  
Jay Verkuilen ◽  
Renzo Bianchi ◽  
Irvin Sam Schonfeld ◽  
Eric Laurent

Burnout has been viewed as a work-induced condition combining exhaustion, cynicism, and professional inefficacy. Using correlational analyses, an exploratory structural equation modeling bifactor analysis, structural regression analyses, and a network analysis, we examined the claim that burnout should not be mistaken for a depressive syndrome. The study involved 1,258 educational staff members. Burnout was assessed with the Maslach Burnout Inventory–General Survey and depression with the Patient Health Questionnaire–9 and the Hospital Anxiety and Depression Scale. Illegitimate work tasks and work–nonwork interferences were additionally measured. We notably found that (a) on average, exhaustion, cynicism, and professional inefficacy correlated less strongly with each other than with depression; (b) exhaustion―burnout’s core―was more strongly associated with depression than with either cynicism or professional inefficacy; (c) the Patient Health Questionnaire–9 did not correlate more strongly with the Hospital Anxiety and Depression Scale than with exhaustion; (d) exhaustion and depression loaded primarily on a general distress/dysphoria factor in the exploratory structural equation modeling bifactor analysis; (e) on average, burnout and depression were related to job stressors in a similar manner; (f) work–nonwork interferences were strongly linked to distress/dysphoria. Overall, burnout showed no syndromal unity and lacked discriminant validity. Clinicians should systematically assess depressive symptoms in individuals presenting with a complaint of “burnout.”


2009 ◽  
Vol 2009 ◽  
pp. 1-9 ◽  
Author(s):  
Guillaume Marrelec ◽  
Habib Benali

An important field of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) is the investigation of effective connectivity, that is, the actions that a given set of regions exert on one another. We recently proposed a data-driven method based on the partial correlation matrix that could provide some insight regarding the pattern of functional interaction between brain regions as represented by structural equation modeling (SEM). So far, the efficiency of this approach was mostly based on empirical evidence. In this paper, we provide theoretical fundaments explaining why and in what measure structural equation modeling and partial correlations are related. This gives better insight regarding what parts of SEM can be retrieved by partial correlation analysis and what remains inaccessible. We illustrate the different results with real data.


2014 ◽  
Vol 955-959 ◽  
pp. 1418-1422
Author(s):  
Fong Jueh Ho ◽  
Yaw Jian Lin ◽  
Hsin Yi Kuo ◽  
Yung Chuan Huang ◽  
Chung Yi Chung ◽  
...  

This study surveyed 338 the 5th and 6th grade students at an elementary school in Pingtung County, Taiwan, after they received three months education on wetland conservation. A total of 325 valid responses were received, accounting for 96.2% of the students. The data was analyzed using structural equation modeling (SEM), and the outcome showed that the structural model of wetland conservation passed the normality test and that the model had a good fit. It was understood through path coefficients that conservation attitude is a partial mediator. The total effect of conservation knowledge on conservation attitude and behavior is 0.78, and the total effect of conservation attitude on conservation behavior is 0.59.


2020 ◽  
Author(s):  
Eric-Jan Wagenmakers ◽  
Šimon Kucharský

This is the documentation for the examples contained in the JASP Data Library. The structure of this documentation follows the layout of the JASP ribbon: the first parts deal with Descriptives, T-tests, ANOVA, Regression, Frequencies, and Factor Analysis, whereas the remaining parts concern various JASP modules, namely Meta-Analysis, Network Analysis, and Structural Equation Modeling.


Jurnal Varian ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 79-90
Author(s):  
Wirajaya Kusuma ◽  
Rifani Nur Sindy Setiawan ◽  
Kirti Verma ◽  
Carina Firstca Utomo

Poverty in Papua Province in 2018 has increased from the previous year. The poverty rate in Papua Province in March 2018 reached 27,74%. This study aims to analyze the factors that influence it so that it can be handled properly. The research method used in this research is Structural Equation Modeling (SEM) with the Partial Least Squares (PLS) approach. The research variables used consisted of 4 latent variables (Poverty, Economy, Human Resources (HR), and Health) with 16 indicators (manifest variables). Based on the analysis that has been done, it is found that economic and health variables have a negative and significant effect on poverty with path coefficients of -0,421 and -0,270, respectively. The health variable has a positive and significant effect on HR with a path coefficient of 0,496. Meanwhile, the HR variable has a positive and significant effect on the economy with a path coefficient of 0,801. It can be concluded that there are two variables that have a significant effect on poverty in Papua Province, including the economy and health.


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