Behavioral Systems Theory Research Articles

Testing the Disgust-Based Mechanism of Homonegative Attitudes in the Context of the COVID-19 Pandemic.

Negative attitudes and stigmatization can originate from the perception of a disease-related threat. Following the spread of the COVID-19 pandemic, it is often suggested that incidents of discriminatory behavior are the result of defense mechanisms aimed at avoiding pathogens. According to the behavioral immune system theory, people are motivated to distance themselves from individuals who show signs of infection, or who are only heuristically associated with a disease, primarily because of the disgust they evoke. In this paper we focus on negative attitudes toward gay men and lesbians who are among social groups that have been persistently framed as “unclean.” In our correlational study (N = 500 heterosexual participants; Polish sample data collected during the first COVID-19 lockdown in Poland, in March/April 2020) we tested moderation models derived from the behavioral immune system theory. Specifically, we investigated whether perceived vulnerability to disease and perceived threat of contracting COVID-19 moderate the relation between disgust and homonegativity. We found that sexual disgust (but not pathogen nor moral disgust) predicted homonegative attitudes. This effect was stronger for participants expressing higher levels of perceived vulnerability to disease but was not dependent on the perception of the COVID-19 threat. The results reaffirm previous evidence indicating a pivotal role of disgust in disease-avoidance mechanisms. They also point to functional flexibility of the behavioral immune system by demonstrating the moderating role of perceived vulnerability to disease in shaping homonegative attitudes. Finally, they show that the threat of COVID-19 does not strengthen the relationship between disgust and homonegativity.

The panic buying behavior of consumers during the COVID-19 pandemic: Examining the influences of uncertainty, perceptions of severity, perceptions of scarcity, and anxiety

The lack of a vaccine for COVID-19 and the limited amount of reliable data on the cessation of the disease have made people feel more vulnerable to the disease. As a result, people in many countries have been found to engage in panic purchasing, which has adversely affected the supply system for the retail market. Applying behavioral inhibition system theory, reactance theory, and expectancy theory, this research examines how psychological factors such as uncertainty, perceptions of severity, perceptions of scarcity, and anxiety affected the panic purchasing behavior of consumers. This study was conducted in Malaysia in light of the 2020 outbreak of the COVID-19 pandemic. The results from structural equation modeling indicate that uncertainty, and perceptions of scarcity are positively associated with anxiety but not with the panic purchasing behavior of consumers. In addition, anxiety fully mediates the relationship among these variables and the panic purchasing behavior of consumers. Taken together, these findings provide support for doing more empirical research in order to develop a more resilient retail strategy and to improve consumer service.

Condom use during COVID-19: Findings from an Australian sample of heterosexual young adults

Condoms are a valuable tool in combating the continued spread of sexually transmitted infections (STIs). Despite the fact that condoms are effective and easily accessible, young adults report inconsistent condom use and young adults represent a disproportionately large amount of new STI cases annually. The Behavioural Immune System theory suggests that health behaviours, such as condom use, are impacted by cognitive activation of perceived threat of disease. The advent of the COVID-19 pandemic may then have unforeseen impacts on condom use and the spread of STIs. The present study investigated changes in condom use during the pandemic, and any associations these changes may have had with perceived vulnerability to COVID-19. An Australian sample of 269 students completed a survey asking them to recall their condom use prior to COVID-19, and then their current condom use. Final analyses included a sample of 149 sexually active heterosexual participants. Results revealed a general decline in condom use. Single and coupled participants both reported less frequent condom use, but this decrease was more pronounced among single people. Gender did not moderate these effects. Surprisingly, diminished condom use was not significantly related to perceived threat of COVID-19. Findings of the present study have concerning implications for sexual health and sexual messaging during pandemics.

Public moral motivation during the COVID-19 pandemic: Analysis of posts on Chinese social media

As COVID-19 struck worldwide, we were inspired by behavioral immune system theory and wondered whether there would be changes to public morality brought about by the pandemic. We tracked public reactions through posts on Chinese social media to analyze the dynamics of public moral motivation. Big data analysis shows that the impact of disaster upon moral motivation was context-sensitive. The level of the severity of the disaster played a leading role in variation of moral motivation. We found that disaster increased moral motivation only when the situation was severe, and such augmentation rapidly faded when the disaster was under control and recovery began. The sentiment of news shared during the pandemic played a regulating role, such that positive or encouraging news helped augment moral motivation only when the situation was severe. Finally, we found that the pandemic increased expressions of both agency and communion in a similar way to that of moral motivation.

Structured singular value of implicit systems

Implicit systems provide a general framework in which many important properties of dynamic systems can be studied. Implicit systems are especially relevant to behavioural systems theory, the analysis and synthesis of complex interconnected systems, systems identification and robust control. By incorporating algebraic constraints, implicit models provide additional versatility relative to the standard input–output framework. Problems of robust stability in implicit systems lead in a natural way to non‐standard structured singular value (μ) formulations. In this note, it is shown that for a class of uncertainty structures involving repeated scalar parameters, these problems reduce to a standard μ problem which is well studied and for the solution of which several numerical algorithms are available. Our results are based on a matrix dilation technique and the redefinition of the uncertainty structure of the transformed problem. The main results of the paper are illustrated with a numerical example.

Stability of conformable linear differential systems: a behavioural framework with applications in fractional‐order control

The authors study the stability of linear systems whose dynamics are described by systems of conformable fractional differential equations. They provide a framework in terms of behavioural system theory to develop a general modelling specification as well as stability conditions for conformable linear systems with a fractional differential order. They also provide sufficient conditions and tests for stability based on linear matrix inequalities. To do so, they elaborate on the relationship between the conformable derivative and the traditional integer derivative as well as on a conformable Laplace transform and the use of polynomial algebra as the pivotal figure for analysis. They demonstrate the advantages of the proposed approach by designing a stabilising fractional-order controller for a DC–DC converter feeding a constant power load.

Continuous dependence of linear differential systems on polynomial modules

Linear differential systems, in Willems’ behavioral system theory, are defined to be the solution sets to systems of linear constant coefficient PDEs, and they are naturally parameterized in a bijective way by means of polynomial modules. In this article, introducing appropriate topologies, this parametrization is made continuous in both directions. Moreover, the space of linear differential systems with a given complexity polynomial is embedded into a Grassmannian.

Effects of conditioned stimulus (CS) duration, intertrial interval, and I/T ratio on appetitive Pavlovian conditioning.

Pavlovian learning is influenced by at least 2 temporal variables: The time between the onset of the conditioned stimulus (CS) and presentation of the unconditioned stimulus (US), and the time between successive conditioning trials (the intertrial interval [ITI]). Wagner's Sometimes Opponent Process (SOP) model (e.g., 1981) provides a rich account of the effects of varying the absolute durations of CS and ITI. However, other theories have contrastingly emphasized the role of the relative durations of CS (T) and ITI (I). Three experiments with rats used an appetitive conditioning preparation to separate the two approaches. They manipulated absolute values of I and T over a factor of 6 and compared the effect of varying T and I/T by the same factor. Conditioning was indexed by the rate of foodcup entry during training, during common tests conducted later with different combinations of I and T, and with a reinforcers-to-criterion measure. Experiment 1 found that learning with a 10-s CS was superior to that with a 60-s CS when the I/T ratio was the same. There was little evidence of learning with the 60-s CS. Experiment 2 replicated that result and extended it to show that a 60-s CS still supported little conditioned responding when I/T was increased from 12 to 72. Experiment 3 then examined intermediate CS durations between 10-s and 60-s while I/T was controlled. The results support a role for absolute CS duration rather than the I/T ratio. Explanations based on SOP and behavior systems theory are explored. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Data-Driven Framework to Model Identification, Event Detection, and Topology Change Location Using D-PMUs

We introduce a model-free scheme that is capable of identifying topology changes in distribution networks using data from distribution-level phasor measurement units (D-PMUs). To do so, we use algebraic tools of behavioral system theory to develop easy-to-implement algorithms. The intrinsic difficulties associated with D-PMU measurements and their proposed solution are discussed as an additional challenge for the implementation of the proposed algorithms. Experimental results using real D-PMUs and laboratory real-time hardware are provided as a proof of concept using a standard IEEE-test node feeder.

Data-Driven Tracking MPC for Changing Setpoints

We propose a data-driven tracking model predictive control (MPC) scheme to control unknown discrete-time linear time-invariant systems. The scheme uses a purely data-driven system parametrization to predict future trajectories based on behavioral systems theory. The control objective is tracking of a given input-output setpoint. We prove that this setpoint is exponentially stable for the closed loop of the proposed MPC, if it is reachable by the system dynamics and constraints. For an unreachable setpoint, our scheme guarantees closed-loop exponential stability of the optimal reachable equilibrium. Moreover, in case the system dynamics are known, the presented results extend the existing results for model-based setpoint tracking to the case where the stage cost is only positive semidefinite in the state. The effectiveness of the proposed approach is illustrated by means of a practical example.

Data-driven stabilizing control of DC–DC converters with unknown active loads

We address the issue of stabilizing control design of DC–DC power converters with active loads, e.g. distributed generation systems, cascade converters, converters feeding DC buses, etc. We test the results in the presence of potential destabilizers, such as constant power loads (CPLs). The proposed approach is particularly devised for those situations where a full network dynamic model is either not available or it has an unsuitable level of complexity—in terms of number of state–space variables and equations, e.g. multiple loads, DC distribution networks, micro grids, etc. This is due to its model-free approach based on a data-driven strategy, which is able to guarantee stability using a LMI-Lyapunov approach. Elements of behavioral system theory such as linear difference systems, quadratic difference forms and Lyapunov theory, are crucial for the development of the proposed stabilizing control schemes. We also provide simulation and experimental results to corroborate the practical advantages of the proposed framework.

Bayesian Behavioral Systems Theory

Behavioral Systems Theory suggests that observable behavior is embedded in a hierarchy. A CS elicits behavior because, after learning, it activates a pathway through this hierarchy. Much of Timberlake's body of work on Behavioral Systems Theory focuses on the conditions that support the conditioning of these pathways. Most notably, his work shows that the identity of the CS, US, and the CS–US interval all help support conditioning of the system. Here, we use recent experiments in the interval timing literature to motivate a Bayesian implementation of Behavioral Systems Theory. There is a probability distribution over possible pathways through the hierarchy, and the one that maximizes reinforcement is elicited. This probability distribution is conditioned on background information, like the CS–US interval and the animal's motivational state. Lower level actions of the hierarchy, like tracking prey, are conditioned on higher level goals, like the general search for food. Our implementation of Behavioral Systems Theory captures the essential features of Timberlake's verbal model; it acts as a glue, integrating sensory, timing, and decision mechanisms with observed behavior.

William Timberlake: An Ethologist’s Psychologist

William Timberlake was one of several psychologists who, in the wake of traditional learning theory, aimed to develop an improved theoretical basis for the study of learning via greater incorporation of ecology and evolution. In this short biography, I place Timberlake’s varied work in historical context. Originally trained as a neoHullian behaviorist, Timberlake sought to integrate the laboratory approach and methodological rigor of behaviorism, with the ethologist’s interest in the animal as such. Starting at Indiana University in 1969, he stayed there his entire professional career, where he was one of the founders of the university’s internationally recognized Center for the Integrative Study of Animal Behavior. He is best known for his behavior systems theory, which characterizes animal behavior as an evolved complex hierarchically organized system. Timberlake has also made diverse contributions to the study of reinforcement, explanations of superstitious behavior and misbehavior, and the understanding of circadian rhythms and their modification, among other areas.

Timing and the transition between modes in the defensive behavior system

Antipredator defense is organized in a way that mirrors Timberlake’s feeding behavior system because the goal of defense is to thwart predatory behavior. Each predatory mode has a corresponding antipredator mode. Like appetitive behavior systems, the defensive behavior system is organized around distinct modes along a spatiotemporal continuum we call the predatory imminence continuum. Behavior systems theory directs investigation toward the factors that lead to transitions between modes. In the feeding and sex systems the time between Conditional Stimulus (CS) and Unconditional Stimulus (US; e.g., CS-US interval or CS duration) is an important factor. Short CSs elicit conditional responses (CR) characteristic of more terminal modes and long CSs provoke CRs belonging to initial modes. Therefore, we asked if short CSs (10 s) would provoke CRs like the vigorous activity bursts and escape-like responses characteristic of the terminal mode of the predatory imminence continuum (Circa-Strike Behavior). Also, via analogy to appetitive systems, long CSs (3 min) were predicted to favor the intermediate mode, post-encounter behavior, which is characterized by freezing. Instead we found that both CSs produced freezing but not activity burst CRs and that freezing was actually greater with the short CS. We suggest that this difference between behavior systems flows from selection pressure that favors moving toward terminal modes in appetitive systems but away from terminal modes in the antipredator system. In addition, since appetitive reinforcers are more likely to be repeatedly experienced than predators, the learning of timing may be less relevant to defense. We also found that shock produced activity bursts and argue that when you are in the post-encounter mode (freezing) a sudden change in stimulation causes an immediate transition to circa-strike (terminal) behavior.

Data-Driven Model Predictive Control With Stability and Robustness Guarantees

We propose a robust data-driven model predictive control (MPC) scheme to control linear time-invariant (LTI) systems. The scheme uses an implicit model description based on behavioral systems theory and past measured trajectories. In particular, it does not require any prior identification step, but only an initially measured input-output trajectory as well as an upper bound on the order of the unknown system. First, we prove exponential stability of a nominal data-driven MPC scheme with terminal equality constraints in the case of no measurement noise. For bounded additive output measurement noise, we propose a robust modification of the scheme, including a slack variable with regularization in the cost. We prove that the application of this robust MPC scheme in a multi-step fashion leads to practical exponential stability of the closed loop w.r.t. the noise level. The presented results provide the first (theoretical) analysis of closed-loop properties, resulting from a simple, purely data-driven MPC scheme.

Interbehavioral psychology and the behavior systems framework: A brief reply

The present commentary considers a paper by Silva, Silva, and Machado (2019) published in this special issue, which describes some relations between Behavior Systems Theory and Interbehavioral Psychology. In particular, the systems aspects, field orientation, and role of experimentation in both Behavior Systems Theory and Interbehavioral Psychology are discussed. Similarities and differences among the two perspectives are highlighted, and misconceptions about Interbehavioral Psychology are addressed.

A unifying theoretical framework for clinical psychology

Clinical psychology lacks a theoretical framework through which to interpret and apply research findings. This comment explains the theoretical framework of ethology, a discipline that is extinct in the United States. Ethologists, Lorenze and Tinbergen developed behavioral systems theory as a means to place the proximal causes of behaviors within the context of adaptive goals. This comment asserts there are four adaptive goals that motivate human social behavior: attachment/affiliation, caregiving, dominance and sex. Tinbergen developed the 4 questions of ethology as a complete explanation for behavior. The articles in this volume are discussed in terms of behavioral systems theory and the 4 questions of ethology.

Causal reasoning in rats' behaviour systems.

Conceiving of stimuli and responses as causes and effects, and assuming that rats acquire representational models of causal relations from Pavlovian procedures, previous work by causal model theory proponents attempted to train rat subjects to represent stimulus A as a cause of both stimulus B and food. By these assumptions, with formal help from Bayesian networks, self-production of stimulus B should reduce expectation of alternative causes, including stimulus A, and their effects, including food. Reduced feeder-directed responding to stimulus B when self-produced has been taken as evidence for a general causal reasoning capacity among rats involving mental maps of causal relations. Critics have rejoined that response competition can explain these effects. The present research replicates the key effect, but uses continuous and finer-grained measurement of a broader range of behaviours. Behaviours not recorded in previous studies contradict both prior explanations. Even results cited in support of these explanations, when measured in finer detail and continuously over longer periods, show patterns not expected by either view, but supportive of a specific-process approach with attention to motivational factors. Still, the abstract prediction from Bayesian networks holds, providing a potentially complementary normative analysis. Behaviour systems theory provides firmer framing for such theories than representational-map alternatives.

Deterministic Finite-Automata Abstractions of Time-Variant Sequential Behaviours

A sequential behaviour is a set of infinite length words. Following J.C. Willems behavioural systems theory, we interpret the behaviour as the relevant outcome when modelling a phenomenon w.r.t. the progress of discrete time. We propose the notion of an experiment as a particular form of inspecting a provided behaviour and ask for a strongest model that can be derived therefrom. The overall construct establishes a behavioural abstraction from the original model which, for finite signal ranges, can be realised as a deterministic finite automaton. The proposed method includes a flexible scheme for abstraction refinement that can be tailored to meet application requirements.

A common heritage of behaviour systems

Abstract Behaviour systems theory had its beginnings with Nikolaas Tinbergen’s “hierarchical systems”, an aspect of his thinking and writing that he conspicuously left out of his very memorable 1963 manifesto. This starting point has since been developed within psychology, where it has provided numerous advances. Tinbergen’s aspiration for behaviour systems had been principled integration of ethology with physiology, but the bridge among sciences it ultimately provided led to psychology. To an ethology audience, this paper attempts to reintroduce behaviour systems as a part of Tinbergen’s legacy to make accessible the theoretical developments of behaviour systems theory that have occurred outside of ethology over the last several decades. To a psychology audience, the paper serves as a reminder of the ethological origins of behaviour systems. Both sciences and their integration stand to benefit from recognising this point of common heritage.