Prediction of treatment response in major depression: The relationship between the serotonin-related LDAEP and the unspecific prediction related to anterior cingulate cortex activity

2004 ◽  
Vol 36 (05) ◽  
Author(s):  
C Mulert ◽  
O Pogarell ◽  
M Brunnmeier ◽  
G Juckel ◽  
U Hegerl
2003 ◽  
Vol 47 (2) ◽  
pp. 175-183 ◽  
Author(s):  
Christoph Mulert ◽  
Jürgen Gallinat ◽  
Hans Dorn ◽  
Werner M. Herrmann ◽  
Georg Winterer

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
M. Lotze ◽  
M. Domin ◽  
C. O. Schmidt ◽  
N. Hosten ◽  
H. J. Grabe ◽  
...  

Abstract Income and education are both elements of a person’s socioeconomic status, which is predictive of a broad range of life outcomes. The brain’s gray matter volume (GMV) is influenced by socioeconomic status and mediators related to an unhealthy life style. We here investigated two independent general population samples comprising 2838 participants (all investigated with the same MRI-scanner) with regard to the association of indicators of the socioeconomic status and gray matter volume. Voxel-based morphometry without prior hypotheses revealed that years of education were positively associated with GMV in the anterior cingulate cortex and net-equivalent income with gray matter volume in the hippocampus/amygdala region. Analyses of possible mediators (alcohol, cigarettes, body mass index (BMI), stress) revealed that the relationship between income and GMV in the hippocampus/amygdala region was partly mediated by self-reported stressors, and the association of years of education with GMV in the anterior cingulate cortex by BMI. These results corrected for whole brain effects (and therefore not restricted to certain brain areas) do now offer possibilities for more detailed hypotheses-driven approaches.


2020 ◽  
Vol 1 (1) ◽  
Author(s):  
José V Pardo ◽  
Shantal M Nyabwari ◽  
Joel T Lee ◽  

Abstract The anterior cingulate cortex (ACC) shows the most aging-related brain metabolic dysfunction that correlates with decreasing executive processing in otherwise healthy, cognitively intact volunteers. Here, data from ADNI are used to elucidate potential pathophysiological mechanisms involved in cognitive aging, that is, age-related decline in cognitive performance in the absence of known neurodegenerative disease. Amyloid-negative volunteers showed statistically significant mediation of ACC metabolism in the relationship between age and verbal fluency. A nonlinguistic task of executive function, Trails B, showed also negative correlation between performance and age, albeit weaker, but was not significant in the mediation analysis. Recall of story items, minimizing attentional demands compared with learning of word lists, did not correlate with age. ADNI subjects selected for low vascular risks also showed correlation between age and declining ACC metabolism. In the whole-brain amyloid-negative subset, ACC amyloid was not correlated with age. As expected, the metabolism in an arbitrary region such as motor cortex that was not expected to decline with cognitive aging showed no correlation with age or ACC metabolism suggesting regional specificity. These findings motivate the search for the pathophysiology of aging-related ACC dysfunction to prevent, diagnose, and treat the decline in executive function associated with cognitive aging.


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