Amygdala and Neurogenesis Figure 5. Path analysis for the models according to the anxiety groups. A. Model fit was tested separately for the low anxiety group (x2 = 0.26, df = 1, p = 0.611; CFI = 1.00; RMSEA,0.01, p = 0.621) and B. for the high anxiety group (x2 = 0.01, df = 1, p = 0.924; CFI = 1.00; RMSEA,0.01, p = 0.927). Significant paths (p,0.05; **p,0.01) are in black and non significant in gray. The squared multiple correlations (R2) of the endogenous variables are located in their right inferior corner in gray and italics. doi:10.1371/journal.pone.0008618.g005 indirectly related to increased FST immobility via opposite regulation of Ki67 and BrdU (total and indirect effect breakdown, see Table S5). This BLA lesion model exhibited particularly high predictive power (R2 values in Fig. 4B). The joint contribution of anxiety and fluoxetine accounted for 51% of the variance of BrdU levels; and fluoxetine with anxiety, the latter indirectly through both measures of neurogenic activity (Ki67 and BrdU), also in turn successfully accounted for an important proportion of the variance of the immobility measure (58%). Path analyses for the modulatory role of anxiety: In order to test the potential modulatory role of anxiety levels over the neurogenic and behavioral actions of fluoxetine, a multiple-sample analysis was generated for the low and high anxiety groups. In this case, because most BLA lesioned subjects also exhibited low anxiety, thus yielding uneven groups precluding formal statistical compar- isons, the BLA factor was excluded. The resulting model revealed a significant overall difference in model fit between low and high anxiety groups (Figure 5; p,0.01, Table S6). A main significant difference between the anxiety groups was the influence of Ki67 on FST immobility, which exhibited a strong negative relationship in the LA group, while being absent in the HA group. Additionally, in spite of their weak strength, the opposite relationships between BrdU and FST immobility was also significant. It is finally worth noting the path from fluoxetine to FST immobility was negative in HA animals but absent in the LA group, a difference that approached significance (Table S6). For total and indirect effects see Table S7. A final stacked multi-sample model (Figure 6; Table S8) was considered next to complement the above findings, specifically addressing differences due to the drug treatment. There was an overall difference in the model fit between vehicle and fluoxetine treated groups (p,0.05). A main difference between the drug Figure 6. Path analysis for the models according to the drug treatment groups. A. Model fit was tested separately for the vehicle group (x2 = 0.07, df = 1, p = 0.784; CFI = 1.00; RMSEA,0.01, p = 0.791) and B. for the fluoxetine group (x2 = 2.00, df = 1, p = 0.157; CFI = 0.94; RMSEA = 0.17, p = 0.175). Significant paths (p,0.05; **p,0.01) are in black and non significant in gray. The squared multiple correlations (R2) of the endogenous variables are located in their right inferior corner in gray and italics. doi:10.1371/journal.pone.0008618.g006 PLoS ONE | www.plosone.org 7 January 2010 | Volume 5 | Issue 1 | e8618