RESUMO
External sources of information influence human actions. However, psychological traits (PTs), considered internal variables, also play a crucial role in decision making. PTs are stable across time and contexts and define the set of behavioral repertoires that individuals express. Here, we explored how multiple metrics of adaptive behavior under uncertainty related to several PTs. Participants solved a reversal-learning task with volatile contingencies, from which we characterized a detailed behavioral profile based on their response sequences. We then tested the relationship between this multimetric behavioral profile and scores obtained from self-report psychological questionnaires. The PT measurements were based on the Hierarchical Taxonomy Of Psychopathology (HiTOP) model. By using multiple linear regression models (MLRMs), we found that the learning curves predicted important differences in the PTs and task response times. We confirmed the significance of these relationships by using random permutations of the predictors of the MLRM. Therefore, the behavioral profile configurations predicted the PTs and served as a "fingerprint" to identify participants with a high certainty level. We discuss briefly how this characterization and approach could contribute to better nosological classifications.
Assuntos
Reforço Psicológico , Reversão de Aprendizagem , Humanos , Reversão de Aprendizagem/fisiologia , Adaptação Psicológica , IncertezaRESUMO
The contribution of non-sensory information processing to perceptual decision making is not fully understood. Choice biases have been described for mice and humans and are highly prevalent even if they decrease rewarding outcomes. Choice biases are usually reduced by discriminability because stimulus strength directly enables the adjustments in the decision strategies used by decision-makers. However, choice biases could also derive from functional asymmetries in sensory processing, decision making, or both. Here, we tested how particular experimental contingencies influenced the production of choice biases in mice and humans. Our main goal was to establish the tasks and methods to jointly characterize psychometric performance and innate side-choice behavior in mice and humans. We implemented forced and un-forced visual tasks and found that both species displayed stable levels of side-choice biases, forming continuous distributions from low to high levels of choice stereotypy. Interestingly, stimulus discriminability reduced the side-choice biases in forced-choice, but not in free-choice tasks. Choice biases were stable in appearance and intensity across experimental days and could be employed to identify mice and human participants. Additionally, side- and alternating choices could be reinforced for both mice and humans, implying that choice biases were adaptable to non-visual manipulations. Our results highlight the fact that internal and external elements can influence the production of choice biases. Adaptations of our tasks could become a helpful diagnostic tool to detect aberrant levels of choice variability.
RESUMO
AIM: To investigate the relationships of polymorphisms in genes whose protein products are related in the metabolic pathway of folic acid, particularly MTRR A66G, RFC1 G80A, and MTHFR C677T and A1298C, and disease activity in Mexican patients with rheumatoid arthritis (RA) treated with methotrexate (MTX). MATERIALS AND METHODS: Sixty-eight patients with RA were included in the study who were being treated with MTX, either with or without other drugs. In addition to general data, disease activity was measured by the disease activity score 28 (DAS28). Single nucleotide polymorphisms (SNPs) genotyping was performed by allelic discrimination using real-time polymerase chain reaction. RESULTS: Differences in genotype (homozygotic or heterozygotic for each allele), allele distributions, and phenotype were not statistically different between the RA group and control populations. We did not find any association between the studied polymorphisms and disease activity nor with the intragroup variables (e.g., clinical activity, body mass index, and single- or combined-drug treatment) or between genetic markers; we also did not find any association within the RA group or between the RA group and control populations. CONCLUSION: Additional studies of more polymorphisms related to this or other metabolic pathways are required to determine the influence of genetics on disease activity in RA.