Fluoxetine Impairs GABAergic Signaling in Hippocampal Slices From Neonatal Rats.

Fluoxetine impairs GABAergic signaling in hippocampal slices from neonatal rats.

Front Cell Neurosci. 2013; 7: 63
Caiati MD, Cherubini E

Fluoxetine (Prozac), an antidepressant known to selectively inhibit serotonin reuptake, is widely used to treat mood disorders in women suffering from depression during pregnancy and postpartum period. Several lines of evidence suggest that this drug, which crosses the human placenta and is secreted into milk during lactation, exerts its action not only by interfering with serotoninergic but also with GABAergic transmission. GABA is known to play a crucial role in the construction of neuronal circuits early in postnatal development. The immature hippocampus is characterized by an early type of network activity, the so-called Giant Depolarizing Potentials (GDPs), generated by the synergistic action of glutamate and GABA, both depolarizing and excitatory. Here we tested the hypothesis that fluoxetine may interfere with GABAergic signaling during the first postnatal week, thus producing harmful effects on brain development. At micromolar concentrations fluoxetine severely depressed GDPs frequency (IC50 22 ?M) in a reversible manner and independently of its action on serotonin reuptake. This effect was dependent on a reduced GABAergic (but not glutamatergic) drive to principal cells most probably from parvalbumin-positive fast spiking neurons. Cholecystokinin-positive GABAergic interneurons were not involved since the effects of the drug persisted when cannabinoid receptors were occluded with WIN55,212-2, a CB1/CB2 receptor agonist. Fluoxetine effects on GABAergic transmission were associated with a reduced firing rate of both principal cells and interneurons further suggesting that changes in network excitability account for GDPs disruption. This may have critical consequences on the functional organization and stabilization of neuronal circuits early in postnatal development. HubMed – depression


Adult hippocampal neurogenesis reduces memory interference in humans: opposing effects of aerobic exercise and depression.

Front Neurosci. 2013; 7: 66
Déry N, Pilgrim M, Gibala M, Gillen J, Wojtowicz JM, Macqueen G, Becker S

Since the remarkable discovery of adult neurogenesis in the mammalian hippocampus, considerable effort has been devoted to unraveling the functional significance of these new neurons. Our group has proposed that a continual turnover of neurons in the DG could contribute to the development of event-unique memory traces that act to reduce interference between highly similar inputs. To test this theory, we implemented a recognition task containing some objects that were repeated across trials as well as some objects that were highly similar, but not identical, to ones previously observed. The similar objects, termed lures, overlap substantially with previously viewed stimuli, and thus, may require hippocampal neurogenesis in order to avoid catastrophic interference. Lifestyle factors such as aerobic exercise and stress have been shown to impact the local neurogenic microenvironment, leading to enhanced and reduced levels of DG neurogenesis, respectively. Accordingly, we hypothesized that healthy young adults who take part in a long-term aerobic exercise regime would demonstrate enhanced performance on the visual pattern separation task, specifically at correctly categorizing lures as “similar.” Indeed, those who experienced a proportionally large change in fitness demonstrated a significantly greater improvement in their ability to correctly identify lure stimuli as “similar.” Conversely, we expected that those who score high on depression scales, an indicator of chronic stress, would exhibit selective deficits at appropriately categorizing lures. As expected, those who scored high on the Beck Depression Inventory (BDI) were significantly worse than those with relatively lower BDI scores at correctly identifying lures as “similar,” while performance on novel and repeated stimuli was identical. Taken together, our results support the hypothesis that adult-born neurons in the DG contribute to the orthogonalization of incoming information. HubMed – depression


Do antidepressant medications work?

P T. 2013 Mar; 38(3): 162-3
Casey DA

Treatment-resistant depression is extremely common-but does that mean there is no place for antidepressants? HubMed – depression


A latent factor linear mixed model for high-dimensional longitudinal data analysis.

Stat Med. 2013 May 3;
An X, Yang Q, Bentler PM

High-dimensional longitudinal data involving latent variables such as depression and anxiety that cannot be quantified directly are often encountered in biomedical and social sciences. Multiple responses are used to characterize these latent quantities, and repeated measures are collected to capture their trends over time. Furthermore, substantive research questions may concern issues such as interrelated trends among latent variables that can only be addressed by modeling them jointly. Although statistical analysis of univariate longitudinal data has been well developed, methods for modeling multivariate high-dimensional longitudinal data are still under development. In this paper, we propose a latent factor linear mixed model (LFLMM) for analyzing this type of data. This model is a combination of the factor analysis and multivariate linear mixed models. Under this modeling framework, we reduced the high-dimensional responses to low-dimensional latent factors by the factor analysis model, and then we used the multivariate linear mixed model to study the longitudinal trends of these latent factors. We developed an expectation-maximization algorithm to estimate the model. We used simulation studies to investigate the computational properties of the expectation-maximization algorithm and compare the LFLMM model with other approaches for high-dimensional longitudinal data analysis. We used a real data example to illustrate the practical usefulness of the model. Copyright © 2013 John Wiley & Sons, Ltd. HubMed – depression