Journal of the experimental analysis of behavior最新文献

Operant behavior can reflect the influence of goal-directed and habitual processes. These can be distinguished by changes to response rate following devaluation of the reinforcing outcome. Whether a response is goal directed or habitual depends on whether devaluation affects response rate. Response rate can be decomposed into frequencies of bouts and pauses by analyzing the distribution of interresponse times. This study sought to characterize goal-directed and habitual behaviors in terms of bout-initiation rate, within-bout response rate, bout length, and bout duration. Data were taken from three published studies that compared sensitivity to devaluation following brief and extended training with variable-interval schedules. Analyses focused on goal-directed and habitual responding, a comparison of a habitual response to a similarly trained response that had been converted back to goal-directed status after a surprising event, and a demonstration of contextual control of habit and goal direction in the same subjects. Across experiments and despite responses being clearly distinguished as goal directed and habitual by total response rate, analyses of bout-initiation rate, within-bout rate, bout length, and bout duration did not reveal a pattern that distinguished goal-directed from habitual responding.

Habit and motivation are thought to be separate processes, with motivated behavior often considered to be goal directed, whereas habits are defined by the absence of goal-directed control over behavior. However, there has been increasing interrogation of the binary nature of habitual versus goal-directed behavior. Furthermore, although drug and alcohol exposure can promote the formation of habits, drug seeking itself can also be highly flexible, pointing toward the need for complex consideration of the parallel processes that drive behavior. The goal of the current study was to determine whether there was a relation between motivation—as measured by progressive ratio—and habit—as measured by contingency degradation—and whether this relation was affected by ethanol exposure history and sex. The results showed that these measures were positively correlated such that greater contingency insensitivity was associated with achieving higher break points on the progressive-ratio task. However, this relation depended on reinforcement schedule history, ethanol exposure history, and sex. These point to potential relations between measures of habit and motivation and stress the importance of carefully parsing behavioral findings and assays. These findings are also expected to inform future substance use research, as drug history may affect these relations.

Goal-directed and habitual actions are clearly defined by their associative relations. Whereas goal-directed control can be confirmed via tests of outcome devaluation and contingency-degradation sensitivity, a comparable criterion for positively detecting habits has not been established. To confirm habitual responding, a test of control by the stimulus–response association is required while also ruling out goal-directed control. Here we describe an approach to developing such a test in rats using two discriminative stimuli that set the occasion for two different responses that then earn the same outcome. Performance was insensitive to outcome devaluation and showed stimulus–response specificity, indicative of stimulus-controlled behavior. The reliance of stimulus–response associations was further supported by a lack of sensitivity during the single extinction test session used here. These results demonstrate that two concurrently trained responses can come under habitual control when they share a common outcome. By reducing the ability of one stimulus to signal its corresponding response–outcome association, we found evidence for goal-directed control that can be dissociated from habits. Overall, these experiments provide evidence that tests assessing specific stimulus–response associations can be used to investigate habits.

People achieve important life outcomes of health, financial security, and productivity by repeating operant behavior. To identify whether such operants reflect goal pursuit or habit, the present research introduces a new paradigm that yields objective measures of learning and controls for the motivations of goal pursuit. In two experiments, participants practiced a sequential task of making sushi and then completed a test of the strength of cue–response (habit) associations in memory. Finally, they repeated the sushi task without instructions while under cognitive load (designed to impede deliberation about goals). As predicted, greater task practice yielded stronger cue–response associations, which in turn promoted task success. Practice did not improve performance by enhancing goal intentions or other task motivations. We conclude that repetition facilitates performance by creating mental associations that automatically activate practiced, habitual responses upon perception of recurring context cues.

Habits have garnered significant interest in studies of associative learning and maladaptive behavior. However, habit research has faced scrutiny and challenges related to the definitions and methods. Differences in the conceptualizations of habits between animal and human studies create difficulties for translational research. Here, we review the definitions and commonly used methods for studying habits in animals and humans and discuss potential alternative ways to assess habits, such as automaticity. To better understand habits, we then focus on the behavioral factors that have been shown to make or break habits in animals, as well as potential mechanisms underlying the influence of these factors. We discuss the evidence that habitual and goal-directed systems learn in parallel and that they seem to interact in competitive and cooperative manners. Finally, we draw parallels between habitual responding and compulsive drug seeking in animals to delineate the similarities and differences in these behaviors.

An examination of innate behavior and its possible origins suggests parallels with the formation of habitual behavior. Inflexible but adaptive responses—innate reflexive behavior, Pavlovian conditioned responses, and operant habits—may have evolved from variable behavior in phylogeny and ontogeny. This form of “plasticity-first” scientific narrative was unpopular post-Darwin but has recently gained credibility in evolutionary biology. The present article seeks to identify originating events and contingencies contributing to such inflexible but adaptive behavior at both phylogenic and ontogenic levels of selection. In ontogeny, the development of inflexible performance (i.e., habit) from variable operant behavior is reminiscent of the genetic accommodation of initially variable phylogenic traits. The effects characteristic of habit (e.g., unresponsiveness to reinforcer devaluation) are explicable as the result of a conflict between behaviors at distinct levels of selection. The present interpretation validates the practice of seeking hard analogies between evolutionary biology and operant behavior. Finding such parallels implies the validity of a claim that organismal behavior, both innate and learned, is a product of selection by consequences. A complete and coherent account of organismal behavior may ultimately focus on functional selective histories in much the same way evolutionary biology does with its subject matter.

We examine whether cigarettes serve as substitutes for electronic nicotine delivery systems (ENDS) among ENDS users and demonstrate methodological extensions of data from a cross-price purchase task to inform policies and interventions. During a clinical laboratory study, n = 19 exclusive ENDS users and n = 17 dual cigarette/ENDS users completed a cross-price purchase task with cigarettes available at a fixed price while prices of own-brand ENDS increased. We estimated cross-price elasticity using linear models to examine substitutability. We defined five additional outcomes: nonzero cross-price intensity (purchasing cigarettes if ENDS were free), constant null demand (not purchasing cigarettes at any ENDS price), cross-product crossover point (first price where participants purchased more cigarettes than ENDS), dual-demand score (percentage of prices where both products were purchased), and dual-use break point (minimum relative price to force complete substitution). The cross-price elasticity results indicated that cigarettes could serve as substitutes for ENDS among ENDS users on average, but this average effect masked substantial heterogeneity in profiles of demand (here, a measure of the drug's reinforcement potential). Policies and regulations that increase ENDS prices appear unlikely to steer most exclusive ENDS users toward cigarette use, as most would not purchase cigarettes at any ENDS price, but they could prompt some dual users to substitute cigarettes completely while others remain dual users. This heterogeneity in consumer responses suggests additional indices of cross-product demand are useful to characterize the anticipated and unanticipated effects of tobacco price policies more fully.

The rate of discounting future goods is a crucial factor in intertemporal trade-offs, upon which depends not only individual well-being but also that of our planet: How much privation now for a temperate future for our grandchildren? What is the best way to measure how the value of future goods decreases with its delay? The most accurate discount functions involve several covarying parameters, making interpretation equivocal. A universal and robust measure is the area under the discount curve, the AuC. The AuC of a hyperbolic discount function is a logarithmic function of the discount rate, k. The same integral also approximates the area under a hyperboloid function. A simple technique converts each datum into estimates of the discount rate, eliminating rogue data points in the process. These trimmed estimates are converted into areas and tested against data, where they succeed at predicting the AuC and its relation to log(k).

Many researchers have tackled the question of how behavior is influenced by its outcomes. Some have adopted a nonmechanistic (functional) perspective that attempts to describe the influence of outcomes on behavior. Others have adopted a mechanistic (cognitive) perspective that attempts to explain the influence of outcomes on behavior. Orthogonal to this distinction, some have focused on the influence of outcomes that a behavior had in the past, whereas others also consider the influence of outcomes that a behavior might have in the future. In this article, we relate these different perspectives with the goal of reducing misunderstandings and fostering collaborations between researchers who adopt different perspectives on the common question of how behavior is influenced by its outcomes.

Delayed matching to sample (DMTS) increases the probability of equivalence class formation. Precurrent responses can mediate the retention interval in DMTS trials and control the selection of comparisons. In human participants, precurrent responses usually consist of naming the experimental stimuli based on their similarities to meaningful stimuli with preexperimental history. We tested whether precurrents expand classes by serving as nodes between experimental and meaningful stimuli. A DMTS (2 s) was used throughout the entire experiment. Eleven undergraduates learned A1B1 and A2B2 relations and then were submitted to ArC trials that required them to answer math problems presented during the DMTS interval: when the sample was A1, the problems resulted in 12 and C1 was correct; when the sample was A2, they resulted in 9 and C2 was correct. Response-as-node tests assessed whether participants would relate B1 and C1 to the printed number 12 and B2 and C2 to the printed number 9. Ten participants responded accordingly to this pattern, showing that the responses to the problems expanded the classes. Parity tests using the words “even” and “odd” further confirmed this hypothesis. These results contribute to understanding why DMTS enhances equivalence performances. Implications of using this procedure in stimulus-equivalence studies are discussed.