Expression of estrogen receptors in the hypothalamo-pituitary-ovarian axis in middle-aged rats after re-instatement of estrus cyclicity

During reproductive aging female rats enter an anovulatory state of persistent estrus (PE). In an animal model of re-instatement of estrus cyclicity in middle-aged PE rats we injected the animals with progesterone (0.5 mg progesterone/kg body weight) at 12:00 for 4 days whereas control animals received corn oil injections. After the last injection animals were analyzed at 13:00 and 17:00. Young regular cycling rats served as positive controls and were assessed at 13:00 and 17:00 on proestrus. Progesterone treatment of middle-aged PE rats led to occurrence of luteinizing hormone (LH), follicle stimulating hormone (FSH), and prolactin surges in a subset of animals that were denoted as responders. Responding middle-aged rats displayed a reduction of ER-β mRNA in the preoptic area which was similar to the effect in young rats. Within the mediobasal hypothalamus, only young rats showed a decline of ER-α mRNA expression. A decrease of ER-α mRNA levels in the pituitary was observed in progesterone-responsive rats and in young animals. ER-β mRNA expression was reduced in young regular cycling rats. ER-β mRNA levels in the ovary were reduced following progesterone treatment in PE rats and in young rats. Taken together our data show that cyclic administration of progesterone reinstates ovulatory cycles in intact aging females which have already lost their ability to display spontaneous cyclicity. This treatment leads to the occurrence of preovulatory LH, FSH and prolactin surges which are accompanied by differential modulation of ERs in the hypothalamus, the pituitary and the ovary

A novel extended Granger Causal model approach demonstrates brain hemispheric differences during face recognition learning

Two main approaches in exploring causal relationships in biological systems using time-series data are the application of Dynamic Causal model (DCM) and Granger Causal model (GCM). These have been extensively applied to brain imaging data and are also readily applicable to a wide range of temporal changes involving genes, proteins or metabolic pathways. However, these two approaches have always been considered to be radically different from each other and therefore used independently. Here we present a novel approach which is an extension of Granger Causal model and also shares the features of the bilinear approximation of Dynamic Causal model. We have first tested the efficacy of the extended GCM by applying it extensively in toy models in both time and frequency domains and then applied it to local field potential recording data collected from in vivo multi-electrode array experiments. We demonstrate face discrimination learninginduced changes in inter- and intra-hemispheric connectivity and in the hemispheric predominance of theta and gamma frequency oscillations in sheep inferotemporal cortex. The results provide the first evidence for connectivity changes between and within left and right inferotemporal cortexes as a result of face recognition learning