A unified theory of discrete and continuous responding

Understanding the cognitive processes underlying choice requires theories that can disentangle the representation of stimuli from the processes that map these representations onto observed responses. We develop a dynamic theory of how stimuli are mapped onto discrete (choice) and continuous response scales. It proposes that the mapping from stimuli to the input to an evidence accumulation process is accomplished using multiple reference points or "anchors". Evidence is accumulated until a threshold amount for a particular response is obtained, with the relative balance of support for each anchor at that time determining the response. We tested this Multiple Anchored Accumulation Theory (MAAT) using the results of two experiments requiring discrete or continuous responses to line length and color stimuli. We manipulated the number of options for discrete responses, the number of different stimuli, and the similarity amongst them, and compared the outcomes to continuous response conditions. We show that MAAT accounts for several key phenomena: more accurate choices and more skewed response distributions near the ends of a response scale; a decrease in accuracy and response speed as the number of discrete choice options increases; and longer response times and lower accuracy when discrete responses were more similar to one another. Our empirical and modeling results suggest that discrete and continuous response tasks can share a common evidence representation, and that the decision process is sensitive to the perceived similarity among the response options.

A Discrete Density Approach to Bayesian Quantile and Expectile Regression with Discrete Responses

For decades, regression models beyond the mean for continuous responses have attracted great attention in the literature. These models typically include quantile regression and expectile regression. But there is little research on these regression models for discrete responses, particularly from a Bayesian perspective. By forming the likelihood function based on suitable discrete probability mass functions, this paper introduces a discrete density approach for Bayesian inference of these regression models with discrete responses. Bayesian quantile regression for discrete responses is first developed, and then this method is extended to Bayesian expectile regression for discrete responses. The posterior distribution under this approach is shown not only coherent irrespective of the true distribution of the response, but also proper with regarding to improper priors for the unknown model parameters. The performance of the method is evaluated via extensive Monte Carlo simulation studies and one real data analysis.

Beyond single discrete responses: An integrative and multidimensional analysis of behavioral dynamics assisted by Machine Learning

Behavioral systems, understanding it as an emergent system comprising the environment and organism subsystems, includes the spatial dynamics as a basic dimension in natural settings. Nevertheless, under the standard approaches in the experimental analysis of behavior that are based on the single response paradigm and the temporal distribution of these discrete responses, the continuous analysis of spatial behavioral-dynamics has been a scarcely studied field. The technological advancements in computer vision have opened new methodological perspectives for the continuous sensing of spatial behavior. Derived from them, recent studies suggest that there are multiple features embedded in the spatial dynamics of behavior, such as entropy, and that they are affected by programmed stimuli (e.g., schedules of reinforcement), at least, as much as features related to discrete responses. Despite the progress, the characterization of behavioral systems is still segmented, and integrated data analysis and representations between discrete responses and continuous spatial behavior, are exiguous. Machine Learning advancements, such as t-SNE, variable ranking, among others, provide invaluable tools to crystallize an integrated approach for the analysis and representation of multidimensional behavioral-data. Under this rational, the present work: 1) proposes a multidisciplinary approach for the integrative and multilevel analysis of behavioral systems; 2) shows behavioral aspects usually ignored under the standard approaches in the experimental analysis of behavior; and 3) provides sensitive behavioral measures, based on spatial dynamics, and useful data representations for the study of behavioral systems. In order to exemplify and evaluate our approach, the spatial-dynamics of behavior embedded in phenomena relevant to the behavioral science, namely water-seeking behavior and motivational operations, is examined, showing aspects of behavioral systems hidden until now.

RbDT: A computerized task system based on transposition for the continuous analysis of relational behavior dynamics in humans

The most extensively paradigm employed for the analysis of relational behavior is the transposition task. Nevertheless, It has two important limitations for its use in humans. The first one is the “ceiling effect” reported in linguistic participants. The second limitation is that the standard transposition task, being a simple choice task between two stimuli, does not include active behavioral patterns, and its record, as relevant factors in emergence of relational behavior. In the present work, a challenging multi-object task based on transposition integrated with recording software is presented. This paradigm requires behavioral active patterns to form stimuli compounds with a given relational criteria. The paradigm is composed of three arrangements: a) a bank of stimuli, b) sample relational compounds, and c) comparison relational compounds. The task consists of the participant constructing two comparison relational compounds by dragging figures of a bank of stimuli with the same relation shown by the sample relational compounds. These factors conform an integrated system that can be manipulated in an individual or in integrative manner. The software records discrete responses (e.g. stimuli selections, placements) and continuous responses (e.g. tracking of cursor movements, figure dragging). The obtained data, data analysis and graphical representations proposed are compatible with frameworks that assume an active nature of the attentional and perceptual processes and an integrated and continuous system between the perceiver and the environment. The proposed paradigm deepens the systematic study of relational behavior in humans in the framework of the transposition paradigm and expands it to continuous analysis of interaction between active patterns and the dynamics of relational behavior.

Monuments to the Impossible

What tools do cultural interventions offer us to face and speak back to the horrors of a colonial archive that continues to grow and expand in its mechanisms of dehumanizing and silencing the populations it targets? How do we respond to a horizon of reality that seems surreal? What weapons do we have left to fight or speak back when we know that the walking and living archive—officers, policymakers, schoolteachers, corporate investors, and the people successfully disciplined by them—denies the lives of the people who tirelessly labor for it? Facts, research, and logical argument barely hold up against the almost surreal arsenal of deliberately woven lies and institutional racism we face. This article briefly analyzes three discrete responses linked by unfathomable horror, beauty, and anger (a song, a cry of rage, and a sacrificial act of self-assertion) to the horrors of anti-Black brutality.

Nontuberculous Mycobacterial Disease and Molybdenum in Colorado Watersheds

Nontuberculous mycobacteria (NTM) are environmental bacteria that may cause chronic lung disease. Environmental factors that favor NTM growth likely increase the risk of NTM exposure within specific environments. We aimed to identify water-quality constituents (Al, As, Cd, Ca, Cu, Fe, Pb, Mg, Mn, Mo, Ni, K, Se, Na, Zn, and pH) associated with NTM disease across Colorado watersheds. We conducted a geospatial, ecological study, associating data from patients with NTM disease treated at National Jewish Health and water-quality data from the Water Quality Portal. Water-quality constituents associated with disease risk were identified using generalized linear models with Poisson-distributed discrete responses. We observed a highly robust association between molybdenum (Mo) in the source water and disease risk. For every 1- unit increase in the log concentration of molybdenum in the source water, disease risk increased by 17.0%. We also observed a statistically significant association between calcium (Ca) in the source water and disease risk. The risk of NTM varied by watershed and was associated with watershed-specific water-quality constituents. These findings may inform mitigation strategies to decrease the overall risk of exposure.

Engrafted parenchymal brain macrophages differ from host microglia in transcriptome, epigenome and response to challenge

Microglia are yolk sac-derived macrophages residing in the parenchyma of brain and spinal cord, where they interact with neurons and other glial cells by constantly probing their surroundings with dynamic extensions. Following different conditioning paradigms and bone marrow (BM) / hematopoietic stem cell (HSC) transplantation, graft-derived cells seed the brain and persistently contribute to the parenchymal brain macrophage compartment. Here we establish that these cells acquire over time microglia characteristics, including ramified morphology, longevity, radio-resistance and clonal expansion. However, even following prolonged CNS residence, transcriptomes and epigenomes of engrafted HSC-derived macrophages remain distinct from yolk sac-derived host microglia. Furthermore, BM graft-derived cells display discrete responses to peripheral endotoxin challenge, as compared to host microglia. Also in human HSC transplant recipients, engrafted cells remain distinct from host microglia, extending our finding to clinical settings. Collectively, our data emphasize the molecular and functional heterogeneity of parenchymal brain macrophages and highlight potential clinical implications for patients treated by HSC gene therapy.