Premenstrual syndrome (PMS) is characterized by recurrent physical, emotional, behavioral, and cognitive symptoms during the luteal phase, resolving after menstruation begins (Qiao et al., 2012; Schiola et al., 2011; Greene and Dalton, 1953). It affects approximately 20–30 % of reproductive-age women globally (Yang et al., 2023). Severe PMS premenstrual dysphoric disorder (PMDD) is defined as a depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) (Yang et al., 2023). Recent studies indicate that PMS patients are at an increased lifetime risk for depression (Cao et al., 2021), highlighting the clinical significance of early identification and intervention.

While the pathophysiology of PMS remains unclear, it is theorized that it involves the heightened sensitivity of the central nervous system to fluctuations in sex hormones (Cary and Simpson, 2024; Brinton et al., 2008; Barth et al., 2023). These hormones influence not only reproduction but also brain structure and function (Dubol et al., 2021), impacting emotional and cognitive health. Neuroimaging studies have identified altered activity in the thalamus and putamen in PMS patients by measuring the values of regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF)/fractional ALFF (fALFF), and functional connectivity (FC) (Pang et al., 2018; Liu et al., 2022; Liao et al., 2017). In a study on empathy-related abnormalities in PMDD, findings revealed a pattern similar to major depressive disorder (MDD), with PMDD patients exhibiting heightened emotional empathy but reduced cognitive empathy. These results align with clinical observations of PMDD, highlighting emotional dysregulation in response to negative stimuli (Lerner et al., 2024). These studies are limited by their sample size as well as by whole-brain neural activity; however, whether the brain networks are altered remains unreported.

The brain network functions beyond mere signal transmission, employing complex structures and a balance of segregation and integration to achieve coordinated activity across local and distant regions (Thiebaut de Schotten and Forkel, 2022). Vinod Menon proposed the triple network model, which includes the default mode network (DMN), the executive control network (ECN), and the salience network (SN), to synthesize existing findings and to better understand the pathophysiological dysfunction across psychiatric disorders (Menon, 2011). While the limbic network regulates emotion generation, triple network model offers a more integrated framework for emotional-cognitive interaction. The cerebellar network supports cognition but has limited direct relevance to PMS. Dysfunctions within the triple network model have been linked to various psychiatric disorders, including major depression, where altered connectivity affects disease severity and symptoms like anhedonia (Walter et al., 2009; Horn et al., 2010). Independent component analysis (ICA), without relying on prior assumptions, provides an effective mean to isolate the brain networks (van de Ven et al., 2004). By leveraging it, investigators have provided new insights into the relationships between the triple brain networks and the gene level (Zhao et al., 2022). Although emerging evidence has also identified abnormal FC within triple networks in PMDD (Reuveni et al., 2023; Petersen et al., 2019), there is a gap in understanding how the connectivity between these networks is altered.

This study investigates FC within and between the triple networks using ICA on resting-state functional MRI (rs-fMRI) data. We hypothesize that PMS patients will exhibit abnormal FC and functional network connectivity (FNC) compared to controls, and these abnormalities will correlate with symptom severity. By identifying network-level biomarkers, we aim to enhance understanding of brain network interactions in PMS, paving the way for targeted clinical interventions.