scholarly journals A Theoretical Investigation of the Relationship between Structural Equation Modeling and Partial Correlation in Functional MRI Effective Connectivity

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.

2021 ◽  
Author(s):  
Daniel Petrie ◽  
Sy-Miin Chow ◽  
Charles Geier

Pavlovian-to-instrumental transfer (PIT) refers to a phenomenon whereby a classically conditioned stimulus (CS) impacts the motivational salience of instrumental behavior. We examined behavioral response patterns and functional magnetic resonance imaging (fMRI) based effective connectivity during an avoidance-based PIT task. Eleven participants (8 females; Mage = 28.2, SD = 2.8, range = 25-32 years) completed the task. Effective connectivity between a priori brain regions engaged during the task was determined using hemodynamic response function group iterative multiple model estimation (HRF-GIMME). Behaviorally, participants exhibited specific PIT, a CS previously associated with a reinforcing outcome increased instrumental responding directed at the same outcome. We did not find evidence for general PIT; a CS did not significantly increase instrumental responding towards a different but related outcome. Using HRF-GIMME, we recovered effective connectivity maps among corticostriatal circuits engaged during the task. Group-level paths revealed directional effects from left putamen to right insula and from right putamen to right cingulate. Importantly, a direct effect of specific PIT stimuli on blood-oxygen-level-dependent (BOLD) activity in the left putamen was found. Results provide initial evidence of effective connectivity in key brain regions in an avoidance-based PIT task network. This study adds to the literature studying PIT effects in humans and employing GIMME models to understand how psychological phenomena are supported in the brain.


2007 ◽  
Vol 25 (8) ◽  
pp. 1181-1189 ◽  
Author(s):  
Guillaume Marrelec ◽  
Barry Horwitz ◽  
Jieun Kim ◽  
Mélanie Pélégrini-Issac ◽  
Habib Benali ◽  
...  

NeuroImage ◽  
2003 ◽  
Vol 19 (3) ◽  
pp. 751-763 ◽  
Author(s):  
Ralf Schlösser ◽  
Thomas Gesierich ◽  
Bettina Kaufmann ◽  
Goran Vucurevic ◽  
Stefan Hunsche ◽  
...  

2021 ◽  
Vol 11 (11) ◽  
pp. 1472
Author(s):  
Daniel J. Petrie ◽  
Sy-Miin Chow ◽  
Charles F. Geier

Pavlovian-to-instrumental transfer (PIT) refers to a phenomenon whereby a classically conditioned stimulus (CS) impacts the motivational salience of instrumental behavior. We examined behavioral response patterns and functional magnetic resonance imaging (fMRI) based effective connectivity during an avoidance-based PIT task. Eleven participants (8 females; Mage = 28.2, SD = 2.8, range = 25–32 years) completed the task. Effective connectivity between a priori brain regions engaged during the task was determined using hemodynamic response function group iterative multiple model estimation (HRF-GIMME). Participants exhibited behavior that was suggestive of specific PIT, a CS previously associated with a reinforcing outcome increased instrumental responding directed at the same outcome. We did not find evidence for general PIT; a CS did not significantly increase instrumental responding towards a different but related outcome. Using HRF-GIMME, we recovered effective connectivity maps among corticostriatal circuits engaged during the task. Group-level paths revealed directional effects from left putamen to right insula and from right putamen to right cingulate. Importantly, a direct effect of specific PIT stimuli on blood–oxygen-level-dependent (BOLD) activity in the left putamen was found. Results provide initial evidence of effective connectivity in key brain regions in an avoidance-based PIT task network. This study adds to the literature studying PIT effects in humans and employing GIMME models to understand how psychological phenomena are supported in the brain.


2011 ◽  
Vol 23 (12) ◽  
pp. 4082-4093 ◽  
Author(s):  
Patrick C. M. Wong ◽  
Alice H. D. Chan ◽  
Anil Roy ◽  
Elizabeth H. Margulis

Complex auditory exposures in ambient environments include systems of not only linguistic but also musical sounds. Because musical exposure is often passive, consisting of listening rather than performing, examining listeners without formal musical training allows for the investigation of the effects of passive exposure on our nervous system without active use. Additionally, studying listeners who have exposure to more than one musical system allows for an evaluation of how the brain acquires multiple symbolic and communicative systems. In the present fMRI study, listeners who had been exposed to Western-only (monomusicals) and both Indian and Western musical systems (bimusicals) since childhood and did not have significant formal musical training made tension judgments on Western and Indian music. Significant group by music interactions in temporal and limbic regions were found, with effects predominantly driven by between-music differences in temporal regions in the monomusicals and by between-music differences in limbic regions in the bimusicals. Effective connectivity analysis of this network via structural equation modeling (SEM) showed significant path differences across groups and music conditions, most notably a higher degree of connectivity and larger differentiation between the music conditions within the bimusicals. SEM was also used to examine the relationships among the degree of music exposure, affective responses, and activation in various brain regions. Results revealed a more complex behavioral–neural relationship in the bimusicals, suggesting that affective responses in this group are shaped by multiple behavioral and neural factors. These three lines of evidence suggest a clear differentiation of the effects of the exposure of one versus multiple musical systems.


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)


2018 ◽  
Vol 22 (4) ◽  
pp. 892-916 ◽  
Author(s):  
Shu Fai Cheung ◽  
Rong Wei Sun ◽  
Darius K.-S. Chan

More and more researchers use meta-analysis to conduct multivariate analysis to summarize previous findings. In the correlation-based meta-analytic structural equation modeling (cMASEM), the average sample correlation matrix is used to estimate the average population model. Using a simple mediation model, we illustrated that random effects covariation in population parameters can theoretically bias the path coefficient estimates and lead to nonnormal random effects distribution of the correlations. We developed an R function for researchers to examine by simulation the impact of random effects in other models. We then reanalyzed two real data sets and conducted a simulation study to examine the magnitude of the impact on realistic situations. Simulation results suggest parameter bias is typically negligible (less than .02), parameter bias and root mean square error do not differ across methods, 95% confident intervals are sometimes more accurate for the two-stage structural equation modeling approach with a diagonal random effects model, and power is sometimes higher for the traditional Viswesvaran-Ones approach. Given the increasing popularity of cMASEM in organizational research, these simulation results form the basis for us to make several recommendations on its application.


2014 ◽  
Vol 35 (4) ◽  
pp. 201-211 ◽  
Author(s):  
André Beauducel ◽  
Anja Leue

It is shown that a minimal assumption should be added to the assumptions of Classical Test Theory (CTT) in order to have positive inter-item correlations, which are regarded as a basis for the aggregation of items. Moreover, it is shown that the assumption of zero correlations between the error score estimates is substantially violated in the population of individuals when the number of items is small. Instead, a negative correlation between error score estimates occurs. The reason for the negative correlation is that the error score estimates for different items of a scale are based on insufficient true score estimates when the number of items is small. A test of the assumption of uncorrelated error score estimates by means of structural equation modeling (SEM) is proposed that takes this effect into account. The SEM-based procedure is demonstrated by means of empirical examples based on the Edinburgh Handedness Inventory and the Eysenck Personality Questionnaire-Revised.


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