Navegando por Autor "Amaral, Olavo B."
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Artigo Chronic in vivo optogenetic stimulation modulates neuronal excitability, spine morphology, and Hebbian plasticity in the mouse hippocampus(2019-02-15) Moulin, Thiago C.; Petiz, Lyvia L.; Rayêe, Danielle; Winne, Jessica; Maia, Roberto G.; Cruz, Rafael V. Lima da; Amaral, Olavo B.; Leão, Richardson NavesProlonged increases in excitation can trigger cell‐wide homeostatic responses in neurons, altering membrane channels, promoting morphological changes, and ultimately reducing synaptic weights. However, how synaptic downscaling interacts with classical forms of Hebbian plasticity is still unclear. In this study, we investigated whether chronic optogenetic stimulation of hippocampus CA1 pyramidal neurons in freely moving mice could (a) cause morphological changes reminiscent of homeostatic scaling, (b) modulate synaptic currents that might compensate for chronic excitation, and (c) lead to alterations in Hebbian plasticity. After 24 hr of stimulation with 15‐ms blue light pulses every 90 s, dendritic spine density and area were reduced in the CA1 region of mice expressing channelrhodopsin‐2 (ChR2) when compared to controls. This protocol also reduced the amplitude of mEPSCs for both the AMPA and NMDA components in ex vivo slices obtained from ChR2‐expressing mice immediately after the end of stimulation. Finally, chronic stimulation impaired the induction of LTP and facilitated that of LTD in these slices. Our results indicate that neuronal responses to prolonged network excitation can modulate subsequent Hebbian plasticity in the hippocampus.Artigo Multifactoriality in Psychiatric Disorders: A Computational Study of Schizophrenia(2015) Pavão, Rodrigo; Tort, Adriano Bretanha Lopes; Amaral, Olavo B.The search for biological causes of mental disorders has up to now met with limited success, leading to growing dissatisfaction with diagnostic classifications. However, it is questionable whether most clinical syndromes should be expected to correspond to specific microscale brain alterations, as multiple low-level causes could lead to similar symptoms in different individuals. In order to evaluate the potential multifactoriality of alterations related to psychiatric illness, we performed a parametric exploration of published computational models of schizophrenia. By varying multiple parameters simultaneously, such as receptor conductances, connectivity patterns, and background excitation, we generated 5625 different versions of an attractor-based network model of schizophrenia symptoms. Among networks presenting activity within valid ranges, 154 parameter combinations out of 3002 (5.1%) presented a phenotype reminiscent of schizophrenia symptoms as defined in the original publication. We repeated this analysis in a model of schizophrenia-related deficits in spatial working memory, building 3125 different networks, and found that 41 (4.9%) out of 834 networks with valid activity presented schizophrenia-like alterations. In isolation, none of the parameters in either model showed adequate sensitivity or specificity to identify schizophrenia-like networks. Thus, in computational models of schizophrenia, even simple network phenotypes related to the disorder can be produced by a myriad of causes at the molecular and circuit levels. This suggests that unified explanations for either the full syndrome or its behavioral and network endophenotypes are unlikely to be expected at the genetic and molecular levels.