Major depressive disorder (MDD) is a severe psychiatric disorder with high morbidity (Kessler et al., 2003, Lepine and Briley, 2011, Kuzior et al., 2020). Hence, the prevention and treatment of depression are a priority in the medical field. The most widely prescribed antidepressant medications affect the levels of serotonin, norepinephrine, and dopamine in some brain areas (Rapaport, 2009). However, the underlying pharmacological mechanisms and related biochemical alterations remain unclear. Thus, exploring the brain changes before and after antidepressant treatment may elucidate the potential mechanisms of MDD and treatment response to antidepressant medications.

Resting-state functional magnetic resonance imaging (rs-fMRI) (Biswal et al., 1995, Fox and Raichle, 2007) is a powerful technique for mapping intrinsic brain connectivity in individuals (Wang et al., 2015, Woodward et al., 2012). Research has consistently demonstrated that abnormal functional connectivity in the brain may be regulated by antidepressant treatment. For example, resting-state functional connectivity (RSFC) within the DMN of MDD patients was found to be modulated after 10 weeks of duloxetine treatment (Posner et al., 2013). Alterations in other neural circuits have also been identified in depression after antidepressant treatment. Anand et al. (2005) demonstrated that reduced RSFC between the dorsal anterior cingulate cortex and certain brain limbic regions was normalized after 6 weeks of sertraline treatment (Anand et al., 2005). However, only several regions or networks of interest were selected using a predefined seed-based analysis from previously reported findings rather than from their own dataset.

The brain connectivity measure of degree centrality (DC) is a graph-based measurement of network organization that reflects the number of instantaneous functional connections between a region and the rest of the brain within the entire connectivity matrix of the brain. The DC does not rely on predefined brain regions and instead views the brain as a large, whole network. It reflects how much of a node influences the whole brain and in integrating the information across those anatomically or functionally segregated brain regions (Hagmann et al., 2008, Takeuchi et al., 2015). Furthermore, the DC provides a single map for each individual, which allows for group analyses without selecting a priori regions of interest, which will also allow us to identify the specific seeds of interest from our own sample (Binnewijzend et al., 2014). A previous study has also identified that changes in brain DC could provide some insights into how functional brain activities play a role in clinical symptom relief following treatment (Yuan et al., 2018). Moreover, an elevated DC value of the hippocampus while a decrease DC value of the left insula was observed in MDD (Lin et al., 2022). However, the fundamental mechanisms underlying dysfunction in MDD are not only seen in observable brain regions but may also be affected by complex core brain networks (Menon, 2011). Thus, exploring brain connectivity changes and brain networks regulated by antidepressant medications would also be a vital step.

Consequently, we hypothesized that patients with MDD would show abnormal brain activity during depressive episodes and recover after antidepressant treatment and that the clinical improvement related to brain activity changes would be associated with alterations in more than one network. Therefore, this study used graph theory analysis to investigate changes in brain activity and hubs within the human cerebral cortex associated with the antidepressant treatment response.