Ovarian hormones fluctuations across the menstrual cycle are experienced by about 58% of women in their fertile age. Maladaptive brain sensitivity to these changes likely leads to the severe psychological, cognitive, and physical symptoms repeatedly experienced by women with Premenstrual Dysphoric Disorder (PMDD) during the late luteal phase of the menstrual cycle. However, the neuroanatomical correlates of these symptoms are unknown. The relationship between grey matter structure and PMDD symptom severity was delineated using structural magnetic resonance imaging during the late luteal phase of fifty-one women diagnosed with PMDD, combined with Voxel- and Surface-Based Morphometry, as well as subcortical volumetric analyses. A negative correlation was found between depression-related symptoms and grey matter volume of the bilateral amygdala. Moreover, the severity of affective and somatic PMDD symptoms correlated with cortical thickness, gyrification, sulcal depth, and complexity metrics, particularly in the prefrontal, cingulate, and parahippocampal gyri. The present findings provide the first evidence of grey matter morphological characteristics associated with PMDD symptomatology in brain regions expressing ovarian hormone receptors and of relevance to cognitive-affective functions, thus potentially having important implications for understanding how structural brain characteristics relate to PMDD symptomatology.

Numerous studies demonstrate ketamine's influence on resting-state functional connectivity (rsFC). Seed-based and static rsFC estimation methods may oversimplify FC. These limitations can be addressed with whole-brain, dynamic rsFC estimation methods. We assessed data from 27 healthy subjects who underwent two 3 T resting-state fMRI scans, once under subanesthetic, intravenous esketamine and once under placebo, in a randomized, cross-over manner. We aimed to isolate only highly robust effects of esketamine on dynamic rsFC by using eight complementary methodologies derived from two dynamic rsFC estimation methods, two functionally defined atlases and two statistical measures. All combinations revealed a negative influence of esketamine on dynamic rsFC within the left visual network and inter-hemispherically between visual networks (p < 0.05, corrected), hereby suggesting that esketamine's influence on dynamic rsFC is highly stable in visual processing networks. Our findings may be reflective of ketamine's role as a model for psychosis, a disorder associated with alterations to visual processing and impaired inter-hemispheric connectivity. Ketamine is a highly effective antidepressant and studies have shown changes to sensory processing in depression. Dynamic rsFC in sensory processing networks might be a promising target for future investigations of ketamine's antidepressant properties. Mechanistically, sensitivity of visual networks for esketamine's effects may result from their high expression of NMDA-receptors.