Directional uncertainty in chase and escape dynamics.

Intercepting and avoiding collisions with moving targets are crucial skills for survival. However, little is known about how these behaviors are implemented when the trajectory of the moving target introduces variability and ambiguity into the perceptual-motor system. We developed a simple visuomotor task in which participants used a joystick to interact with a computer-controlled dot that moved along two-dimensional trajectories. This virtual system allowed us to define the role of the moving object (predator or prey) and adjust its speed and directional uncertainty (i.e., magnitude and frequency of random directional changes) during chase and escape trials. These factors had a significant impact on participants' performance in both chasing and escaping trials. We developed a simple geometrical model of potential chaser/escaper interactions to distinguish pursuit from interception chasing trajectories. We found that participants initially pursued the target but switched to a late interception strategy. The amount of late interception strategy followed an inverted U-shaped curve with the highest values at intermediate speeds. We tested the applicability of our task and methods in children who showed a robust developmental improvement in task performance and late interception strategy. Our task constitutes a flexible system in a virtual space for studying chasing and escaping behavior in adults and children. Our analytical methods allow detecting subtle changes in interception strategies, a valuable tool for studying the maturation of predictive and prospective systems, with a high potential to contribute to cognitive and developmental research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Two-stage reinforcement learning task predicts psychological traits.

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.

Response Time Distributions and the Accumulation of Visual Evidence in Freely Moving Mice.

Response time (RT) distributions are histograms of the observed RTs for discriminative choices, comprising a rich source of empirical information to study perceptual processes. The drift-diffusion model (DDM), a mathematical formulation predicting decision tasks, reproduces the RT distributions, contributing to our understanding of these processes from a theoretical perspective. Notably, although the mouse is a popular model system for studying brain function and behavior, little is known about mouse perceptual RT distributions, and their description from an information-accumulation perspective. We combined an automated visual discrimination task with pharmacological micro-infusions of targeted brain regions to acquire thousands of responses from freely-moving adult mice. Both choices and escape latencies showed a strong dependency on stimulus discriminability. By applying a DDM fit to our experimental data, we found that the rate of incoming evidence (drift rate) increased with stimulus contrast but was reversibly impaired when inactivating the primary visual cortex (V1). Other brain regions involved in the decision-making process, the posterior parietal cortex (PPC) and the frontal orienting fields (FOF), also influenced relevant parameters from the DDM. The large number of empirical observations that we collected for this study allowed us to achieve accurate convergence for the model fit. Therefore, changes in the experimental conditions were mirrored by changes in model parameters, suggesting the participation of relevant brain areas in the decision-making process. This approach could help interpret future studies involving attention, discrimination, and learning in adult mice.

Distributed processing of side-choice biases.

Psychophysics describes how variations in stimulus strength lead to changes in perceptual performance. Yet, the contribution of non-sensory information processing to perceptual decision making is still not fully understood. For instance, in two-alternative forced-choice tasks, observers can exhibit tendencies to choose more one alternative over another, with no apparent goal or function. Such choice biases are highly prevalent in mice and, in free-choice tasks, they are insensitive to changes in stimulus discriminability. Thus, a reasonable proposal is that these side-choice biases could derive from functional asymmetries in sensory processing, decision making, or both. Here, we explored how different circuits participate in the production of choice biases in adult mice. We found that the magnitude of the changes in biased choice behavior depended on the inactivated region. Indeed, contralateral, but not ipsilateral, inactivations of the primary visual and posterior parietal cortices reduced the probability of mice choosing their preferred side. In contrast, ipsilateral inactivations of the subtantia nigra pars reticulata and of the frontal orienting fields, reduced and increased the probabilities of mice choosing their preferred side, respectively. These results demonstrate that internal circuit processing contributes to side-choice behavior and illustrates how distinct brain regions could participate in producing normal to aberrant levels of choice variability.

Adaptive Choice Biases in Mice and Humans.

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.

Adrenergic Modulation of Visually-Guided Behavior.

Iontophoretic application of norepinephrine (NE) into the primary visual cortex (V1) in vivo reduces spontaneous and evoked activity, without changing the functional selectivity of cortical units. One possible consequence of this phenomenon is that adrenergic receptors (ARs) regulate the signal-to-noise ratio (SNR) of neural responses in this circuit. However, despite such strong inhibitory action of NE on neuronal firing patterns in V1, its specific action on visual behavior has not been studied. Furthermore, the majority of observations regarding cortical NE from in vivo recordings have been performed in anesthetized animals and have not been tested behaviorally. Here, we describe how micro-infusion of AR agonists/antagonists into mouse V1 influences visually-guided behavior at different contrasts and spatial frequencies. We found that cortical activation of α1- and ß-AR produced a substantial reduction in visual discrimination performance at high contrasts and low spatial frequencies, consistent with a divisive effect. This reduction was reversible and was accompanied by a rise in escape latencies as well as an increase in the group averaged choice variance as a function of stimulus contrast. We conclude that pharmacological activation of cortical AR regulates visual perception and adaptive behavior through a divisive gain control of visual responses.

MTRR A66G, RFC1 G80A, and MTHFR C677T and A1298C Polymorphisms and Disease Activity in Mexicans with Rheumatoid Arthritis Treated with Methotrexate.

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.