3 resultados para affective learning design

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Context: Cannabis sativa use can impair verbal learning, provoke acute psychosis, and increase the risk of schizophrenia. It is unclear where C sativa acts in the human brain to modulate verbal learning and to induce psychotic symptoms. Objectives: To investigate the effects of 2 main psychoactive constituents of C sativa, Delta 9-tetrahydrocannabinol (Delta 9-THC) and cannabidiol, on regional brain function during verbal paired associate learning. Design: Subjects were studied on 3 separate occasions using a block design functional magnetic resonance imaging paradigm while performing a verbal paired associate learning task. Each imaging session was preceded by the ingestion of Delta 9-THC (10 mg), cannabidiol (600 mg), or placebo in a double-blind, randomized, placebo-controlled, repeated-measures, within-subject design. Setting: University research center. Participants: Fifteen healthy, native English-speaking, right-handed men of white race/ethnicity who had used C sativa 15 times or less and had minimal exposure to other illicit drugs in their lifetime. Main Outcome Measures: Regional brain activation ( blood oxygen level-dependent response), performance in a verbal learning task, and objective and subjective ratings of psychotic symptoms, anxiety, intoxication, and sedation. Results: Delta 9-Tetrahydrocannabinol increased psychotic symptoms and levels of anxiety, intoxication, and sedation, whereas no significant effect was noted on these parameters following administration of cannabidiol. Performance in the verbal learning task was not significantly modulated by either drug. Administration of Delta 9-THC augmented activation in the parahippocampal gyrus during blocks 2 and 3 such that the normal linear decrement in activation across repeated encoding blocks was no longer evident. Delta 9-Tetrahydrocannabinol also attenuated the normal time-dependent change in ventrostriatal activation during retrieval of word pairs, which was directly correlated with concurrently induced psychotic symptoms. In contrast, administration of cannabidiol had no such effect. Conclusion: The modulation of mediotemporal and ventrostriatal function by Delta 9-THC may underlie the effects of C sativa on verbal learning and psychotic symptoms, respectively.

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Aging can lead to cognitive, affective, learning, memory and motor deficits. Since the cerebellum and glutamatergic neurotransmission are involved in several of those functions, the present work aimed at studying the expression of AMPA and NMDA glutamate receptor subunits in the chick cerebellum during aging. Young (30 days old) and aged (ca. 4 years old) chickens (Gallus gallus) were used in order to evaluate the expression of GluR1, GluR2/3 and NR1 subunits. The cerebella of young and aged chickens were subjected to immunohistochemical and immunoblotting techniques. Numbers of GluR1, GluR2/3 and NR1-positive cells and optical density of the immunoblotting data were analyzed and submitted to statistical analysis using ANOVA and the Bonferroni post hoc test. Mean density of Purkinje cells stained for Giemsa, GluR1, GluR2/3 and NR1 in the cerebellum all showed a statistically significant decrease in aged animals when compared to the young animals (Giemsa, P < 0.01; GluRs and NR1, P < 0.03). However, the ratio of GluR1 and GluR2/3-positive Purkinje cells in relation the total number of Purkinje cells found in each time point decreased with aging (ca. 10%), whereas the ratio of NR1-positive cells increased (ca. 9%). The immunoblotting data showed a significant decrease of GluR1 (ca. 66%) and GluR2/3 (ca. 55%) protein expression with aging, but did not reveal changes for NR1. Our data suggest that aging can lead to differential changes in the pattern of expression of glutamate receptor subunits, which can underlie at least part of the cognitive and motor disorders found in aged animals. (c) 2010 Elsevier Ireland Ltd. All rights reserved.

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The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.