294 genes as true antidepressant targets since their expression was altered irrespective of treatment type. However, one might also consider the alterations in var- ious gene expression induced by a single dose of a given AD as compensatory mechanisms which are triggered in the brain in response to external perturbing stimuli (e.g., drug administration). One may also suppose that such mecha- nisms are triggered each time the drug is administered, resulting in complex, reciprocal interactions at many levels, also in gene expression—therefore, different alterations are observed at various time points. The methodology employed here enables to detect very subtle changes in gene expression, which is especially impor- tant in neuroscience (Mirnics et al. 2001). Laser microdissec- tion allowed the precise excision of the specified populations of cells, and the RT-PCR arrays allowed us to investigate many genes at once. Because gene expression levels were measured in four regions of the same brains, inter-regional comparisons of the expression profiles and the finding of correlations between alterations in groups of genes and interconnected brain regions were possible. Data on multiple gene expression at sequential time points (0, 1, 3, 7, 14, and 21 days) were analyzed using SVD as a means to capture dominant trends, called characteristic modes. In this way, the data were represented by a small number of dominant modes which capture many essential features of the time pattern in gene expression. SVD analysis provided a global picture of the dynamics of gene expression and enabled the comparison of the expression of different genes across various brain regions upon treatment with different ADs. The expression patterns of the investigated genes depended on the drug (DMI or CIT), drug treatment sched- ule (repeated or acute), and the brain region studied, which strongly indicate the specificity of the observed molecular changes upon ADs treatment and confirm the biological significance of our results. Some gene expression changes were common to both drugs used, but finding a final com- mon pathway influenced by these two ADs was not possi- ble. Surprisingly, considerable periodic changes in the expression levels of many genes correlated with different time points in ADs treatment, which broadens our under- standing of ADs mechanism of action. Conclusions In conclusion, our objective was to study the alterations of gene expression with respect to time, antidepressant used, and brain region. Appropriate genes (95) were not chosen randomly but—as we clearly stated in the “Introduction” section—the choice was based on the data already pub- lished, indicating their either proved or alleged importance for the mechanism of action of antidepressants. We decided Psychopharmacology (2012) 223:281–297 to measure alterations in their expression in the same exper- iment in order to avoid any variables. What we have found is the complex picture of changes in gene expression, the picture which may help to understand discrepancies often encountered in the literature dealing with AD action. The main finding of our work is that the gene expression pattern during ADs treatment is highly dynamic, with oscillations and peaks occurring at different time points of treatment. Additionally, our study revealed a number of novel potential targets for antidepressant therapy, such as the Dbp and Id1 genes, that were not previously directly linked to antidepres- sant action. We are strongly convinced that the time has come to look at the mechanisms of action of ADs through a broader window instead of sticking to any particular mea- sure, as, e.g., one gene or one protein, and building new hypothesis which will lead us to the next dead end. A similar conclusion has been put forward recently by Kessler et al. (2011), who have analyzed the results from neuroimaging studies of depressed patients. Despite the great effort, the outcome of these studies has been “a surprising heterogeneity of results with the eventual lack of practical conclusions.” The authors suggest novel approaches using longitudinal designs of neuroimaging studies, i.e., to “take various pictures over the course of treatment.” Our studies, although preclinical, strongly support that view. Acknowledgments This work was financially supported by grant PZB-Min-2/1/2005 from the Ministry of Science and Higher Education in Poland. 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