The role of ketamine in major depressive disorders: Effects on parvalbumin-positive interneurons in hippocampus

Major depressive disorder (MDD) is a complex illness that is arising as a growing public health concern. Although several brain areas are related to this type of disorders, at the cellular level, the parvalbumin-positive cells of the hippocampus interplay a very relevant role. They control pyramidal cell bursts, neuronal networks, basic microcircuit functions, and other complex neuronal tasks involved in mood disorders. In resistant depressions, the efficacy of current antidepressant treatments drops dramatically, so the new rapid-acting antidepressants (RAADs) are being postulated as novel treatments. Ketamine at subanesthetic doses and its derivative metabolites have been proposed as RAADs due to their rapid and sustained action by blocking N-methyl-d-aspartate (NMDA) receptors, which in turn lead to the release of brain-derived neurotrophic factor (BDNF). This mechanism produces a rapid plasticity activation mediated by neurotransmitter homeostasis, synapse recovery, and increased dendritic spines and therefore, it is a promising therapeutic approach to improve cognitive symptoms in MDD.Fil: Barrutieta Arberas, I.. Universidad del País Vasco; EspañaFil: Ortuzar, N.. Universidad del País Vasco; EspañaFil: Vaquero Rodríguez, A.. Universidad del País Vasco; EspañaFil: Picó-Gallardo, M.. Universidad del País Vasco; EspañaFil: Bengoetxea, H.. Universidad del País Vasco; EspañaFil: Guevara, M. A.. Universidad Nacional de Cuyo; ArgentinaFil: Gargiulo, Pascual Angel. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Lafuente, J. V.. Universidad del País Vasco; Españ

Effects of Visual Experience on Vascular Endothelial Growth Factor Expression during the Postnatal Development of the Rat Visual Cortex

The development of the cortical vascular network depends on functional maturation. External inputs are an essential requirement in the modeling of the visual cortex, mainly during the critical period, when the functional and structural properties of visual cortical neurons are particularly susceptible to alterations. Vascular endothelial growth factor (VEGF) is the major angiogenic factor, a key signal in the induction of vessel growth. Our study focused on the role of visual stimuli on the development of the vascular pattern correlated with VEGF levels. Vascular density and the expression of VEGF were examined in the primary visual cortex of rats reared under different visual environments (dark rearing, dark-rearing in conditions of enriched environment, enriched environment, and laboratory standard conditions) during postnatal development (before, during, and after the critical period). Our results show a restricted VEGF cellular expression to astroglial cells. Quantitative differences appeared during the critical period: higher vascular density and VEGF protein levels were found in the enriched environment group; both dark-reared groups showed lower vascular density and VEGF levels, which means that enriched environment without the physical exercise component does not exert effects in dark-reared rats

A review on probabilistic graphical models in evolutionary computation

Thanks to their inherent properties, probabilistic graphical models are one of the prime candidates for machine learning and decision making tasks especially in uncertain domains. Their capabilities, like representation, inference and learning, if used effectively, can greatly help to build intelligent systems that are able to act accordingly in different problem domains. Evolutionary algorithms is one such discipline that has employed probabilistic graphical models to improve the search for optimal solutions in complex problems. This paper shows how probabilistic graphical models have been used in evolutionary algorithms to improve their performance in solving complex problems. Specifically, we give a survey of probabilistic model building-based evolutionary algorithms, called estimation of distribution algorithms, and compare different methods for probabilistic modeling in these algorithms

A review of estimation of distribution algorithms in bioinformatics

Evolutionary search algorithms have become an essential asset in the algorithmic toolbox for solving high-dimensional optimization problems in across a broad range of bioinformatics problems. Genetic algorithms, the most well-known and representative evolutionary search technique, have been the subject of the major part of such applications. Estimation of distribution algorithms (EDAs) offer a novel evolutionary paradigm that constitutes a natural and attractive alternative to genetic algorithms. They make use of a probabilistic model, learnt from the promising solutions, to guide the search process. In this paper, we set out a basic taxonomy of EDA techniques, underlining the nature and complexity of the probabilistic model of each EDA variant. We review a set of innovative works that make use of EDA techniques to solve challenging bioinformatics problems, emphasizing the EDA paradigm's potential for further research in this domain

Pure phase-locking of beta/gamma oscillation contributes to the N30 frontal component of somatosensory evoked potentials

BACKGROUND: Evoked potentials have been proposed to result from phase-locking of electroencephalographic (EEG) activities within specific frequency bands. However, the respective contribution of phasic activity and phase resetting of ongoing EEG oscillation remains largely debated. We here applied the EEGlab procedure in order to quantify the contribution of electroencephalographic oscillation in the generation of the frontal N30 component of the somatosensory evoked potentials (SEP) triggered by median nerve electrical stimulation at the wrist. Power spectrum and intertrial coherence analysis were performed on EEG recordings in relation to median nerve stimulation. RESULTS: The frontal N30 component was accompanied by a significant phase-locking of beta/gamma oscillation (25-35 Hz) and to a lesser extent of 80 Hz oscillation. After the selection in each subject of the trials for which the power spectrum amplitude remained unchanged, we found pure phase-locking of beta/gamma oscillation (25-35 Hz) peaking about 30 ms after the stimulation. Transition across trials from uniform to normal phase distribution revealed temporal phase reorganization of ongoing 30 Hz EEG oscillations in relation to stimulation. In a proportion of trials, this phase-locking was accompanied by a spectral power increase peaking in the 30 Hz frequency band. This corresponds to the complex situation of 'phase-locking with enhancement' in which the distinction between the contribution of phasic neural event versus EEG phase resetting is hazardous. CONCLUSION: The identification of a pure phase-locking in a large proportion of the SEP trials reinforces the contribution of the oscillatory model for the physiological correlates of the frontal N30. This may imply that ongoing EEG rhythms, such as beta/gamma oscillation, are involved in somatosensory information processing.Comparative StudyJournal ArticleResearch Support, Non-U.S. Gov'tinfo:eu-repo/semantics/publishe