Instrumental conditioning of orienting responses using positive reinforcement.

1970 ◽  
Vol 83 (3, Pt.1) ◽  
pp. 491-494 ◽  
Author(s):  
Susan R. Shnidman
Keyword(s):  
Positive Reinforcement ◽  
Instrumental Conditioning

Pavlovian and Instrumental Conditioning

2021 ◽  
Author(s):  
Federico Sanabria
Keyword(s):  
Conditional Probability ◽  
Positive Reinforcement ◽  
Negative Reinforcement ◽  
Instrumental Conditioning ◽  
Prior Experience ◽  
Time Interval ◽  
Inhibitory Conditioning ◽  
The Difference ◽  
Contextual Stimuli ◽  
Societal Problems

Conditioning is the change in the response to a stimulus either because of the relation of that stimulus to other stimuli (Pavlovian conditioning), or because of the relation between the response and other stimuli (instrumental conditioning). These relations are formulated in terms of differences in conditional probability known as contingencies. Pavlovian contingencies refer to the difference in the conditional probability of one stimulus (the outcome, or O) given the presence vs. the absence of another stimulus (the conditioned stimulus, or CS). A conditioned response (CR) may be strengthened by a positive Pavlovian contingency (excitatory conditioning) or it may be weakened by a negative Pavlovian contingency (inhibitory conditioning). CRs are anticipatory or modified responses to the O, so their topography depends on the nature of the O (appetitive vs. aversive); the proximity between and congruency of O and CS; prior experience with the CS, O, and their contingency; the magnitude of their contingency; and the characteristics of other stimuli in the environment. Instrumental contingencies refer to the relation between one stimulus (the discriminative stimulus, or SD), a response (or operant, R), and the outcome of that response (O). The nature of the O and of its contingency with the R determines whether the O strengthens or weakens the R: Os that introduce an appetitive stimulus (positive reinforcement) or remove an aversive stimulus (negative reinforcement) strengthen the R. Positive reinforcement is typically arranged on a subset of one or more Rs following a set of rules known as a schedule of reinforcement. The probability that an R is reinforced may depend on the number of Rs (ratio schedules) or the amount of time (interval schedules) since the last reinforcer. The topography and strength of instrumental Rs depend on variables that are analogous to those that affect Pavlovian CRs: the amount and nature of prior experience with the O; the proximity, congruency, and contingency of R and O; and characteristics of other stimuli in past and present environments. Contemporary quantitative models of Pavlovian and instrumental conditioning recognize the importance of contextual stimuli that compete for cognitive and behavioral resources, constraining and shaping the expression of target responses. These models have guided the bulk of recent empirical research and conceptual developments, leading to a progressively unified view of learning and motivation processes. Along the way, Pavlovian and instrumental research have demonstrated their utility in addressing a broad range of consequential societal problems.

An Empirical Test of Three Alternative Explanations for Covert Reinforcement Effects

1979 ◽  
Vol 44 (2) ◽  
pp. 611-622 ◽  
Author(s):  
Steve H. Sanders ◽  
David Hammer
Keyword(s):  
Positive Reinforcement ◽  
Alternative Explanation ◽  
Instrumental Conditioning ◽  
Empirical Test ◽  
Female Students ◽  
Behavioral Measures ◽  
Empirical Validity ◽  
Treatment Conditions ◽  
All Treatment ◽  
Assessment Results

The empirical validity of the explanations, instrumental-conditioning, counterconditioning, and exposure for covert reinforcement were tested. 45 female students, aged 19 to 35 yr., were subjects. Each was screened for level of fear toward snakes and ability to form clear images. They were randomly assigned to one of five treatment conditions and one of three categories of expectancy. Conditions were covert positive reinforcement, reversed covert positive reinforcement, neutral consequence, reversed covert positive reinforcement to nonsnake stimuli, and nondirective contact. Assessment of expectancy occurred pretreatment and posttreatment, posttreatment only, and no assessment. Results showed that assessment of expectancy did not affect performance on subjective or behavioral measures of fear. All treatment conditions except contact produced significant reductions in fear and increased expectations about ability to approach a live snake. Findings did not support the explanations of instrumental-conditioning, counterconditioning, or exposure. A cognitive-mediational account was offered as an alternative explanation for effects of covert reinforcement.

scholarly journals The use of operant instrumental conditioning with positive reinforcement for collection of saliva from marmosets (Callithrix jacchus) for research purposes

2013 ◽  
Author(s):  
Myrna Campos Ferraz ◽  
André Vicente Ruiz de Matos ◽  
Carlos Roberto Teixeira ◽  
Bruna Silva Miranda ◽  
Lygia Karla Sanches Francelino ◽  
...  
Keyword(s):  
Positive Reinforcement ◽  
Instrumental Conditioning ◽  
Callithrix Jacchus

Self-Injurious Behavior vs. Nonsuicidal Self-Injury

Crisis ◽  
2012 ◽  
Vol 33 (2) ◽  
pp. 106-112 ◽  
Author(s):  
Christopher M. Bloom ◽  
Shareen Holly ◽  
Adam M. P. Miller
Keyword(s):  
Positive Reinforcement ◽  
Empirical Investigation ◽  
High Stress ◽  
Animal Research ◽  
Stress Conditions ◽  
Human Populations ◽  
Pharmacological Interventions ◽  
Self Injury ◽  
Cns Stimulant ◽  
Nonsuicidal Self Injury

Background: Historically, the field of self-injury has distinguished between the behaviors exhibited among individuals with a developmental disability (self-injurious behaviors; SIB) and those present within a normative population (nonsuicidal self-injury; NSSI),which typically result as a response to perceived stress. More recently, however, conclusions about NSSI have been drawn from lines of animal research aimed at examining the neurobiological mechanisms of SIB. Despite some functional similarity between SIB and NSSI, no empirical investigation has provided precedent for the application of SIB-targeted animal research as justification for pharmacological interventions in populations demonstrating NSSI. Aims: The present study examined this question directly, by simulating an animal model of SIB in rodents injected with pemoline and systematically manipulating stress conditions in order to monitor rates of self-injury. Methods: Sham controls and experimental animals injected with pemoline (200 mg/kg) were assigned to either a low stress (discriminated positive reinforcement) or high stress (discriminated avoidance) group and compared on the dependent measures of self-inflicted injury prevalence and severity. Results: The manipulation of stress conditions did not impact the rate of self-injury demonstrated by the rats. The results do not support a model of stress-induced SIB in rodents. Conclusions: Current findings provide evidence for caution in the development of pharmacotherapies of NSSI in human populations based on CNS stimulant models. Theoretical implications are discussed with respect to antecedent factors such as preinjury arousal level and environmental stress.

EFFECTS OF PUNISHMENT AS POSITIVE REINFORCEMENT FOR THE PUNISHER

1967 ◽  
Vol 24 (3) ◽  
pp. 887-898 ◽  
Author(s):  
CARL I. THOMPSON ◽  
PAUL A. GAMES ◽  
PAUL B. KOONS
Keyword(s):  
Positive Reinforcement

High dietary restraint improves performance on a food-motivated probabilistic selection task

2019 ◽  
Author(s):  
Jennifer R Sadler ◽  
Grace Elisabeth Shearrer ◽  
Nichollette Acosta ◽  
Kyle Stanley Burger
Keyword(s):  
Reinforcement Learning ◽  
Instrumental Conditioning ◽  
Food Reinforcement ◽  
Dietary Restraint ◽  
Memory Task ◽  
Brain Response ◽  
Anthropometric Measures ◽  
Instrumental Task ◽  
The Impact ◽  
Reward And Punishment

BACKGROUND: Dietary restraint represents an individual’s intent to limit their food intake and has been associated with impaired passive food reinforcement learning. However, the impact of dietary restraint on an active, response dependent learning is poorly understood. In this study, we tested the relationship between dietary restraint and food reinforcement learning using an active, instrumental conditioning task. METHODS: A sample of ninety adults completed a response-dependent instrumental conditioning task with reward and punishment using sweet and bitter tastes. Brain response via functional MRI was measured during the task. Participants also completed anthropometric measures, reward/motivation related questionnaires, and a working memory task. Dietary restraint was assessed via the Dutch Restrained Eating Scale. RESULTS: Two groups were selected from the sample: high restraint (n=29, score >2.5) and low restraint (n=30; score <1.85). High restraint was associated with significantly higher BMI (p=0.003) and lower N-back accuracy (p=0.045). The high restraint group also was marginally better at the instrumental conditioning task (p=0.066, r=0.37). High restraint was also associated with significantly greater brain response in the intracalcarine cortex (MNI: 15, -69, 12; k=35, pfwe< 0.05) to bitter taste, compared to neutral taste.CONCLUSIONS: High restraint was associated with improved performance on an instrumental task testing how individuals learn from reward and punishment. This may be mediated by greater brain response in the primary visual cortex, which has been associated with mental representation. Results suggest that dietary restraint does not impair response-dependent reinforcement learning.

The Development of an Online Tobacco Tracker Tool to Crowdsource Campus Environmental Reports for Smoke and Tobacco Free College Policies: A Mixed Methods Study (Preprint)

2020 ◽  
Author(s):  
Sabrina F. Loureiro ◽  
Kim M. Pulvers ◽  
Melissa M. Gosdin ◽  
Keavagh R. Clift ◽  
Myra J. Rice ◽  
...  
Keyword(s):  
Mixed Methods ◽  
Focus Groups ◽  
Positive Reinforcement ◽  
The United States ◽  
College Campuses ◽  
Policy Enforcement ◽  
Sequential Mixed Methods ◽  
Effective Policy ◽  
Online Tracking ◽  
One Year

BACKGROUND College campuses in the United States have begun implementing Smoke and Tobacco-Free policies to discourage the use of tobacco. Smoke and Tobacco-Free policies, however, are contingent upon effective policy enforcement. OBJECTIVE To develop an empirically-derived online tracking tool (Tracker) for crowdsourcing campus environmental reports of tobacco use and waste to support smoke and tobacco-free college policies. METHODS An exploratory sequential mixed methods approach was utilized to inform the development and evaluation of the Tracker. In October 2018, three focus groups across two California universities were conducted and themes were analyzed, guiding Tracker development. After one year of implementation, users were asked in April 2020 to complete a survey about their experience. RESULTS In the focus groups, two major themes emerged: barriers and facilitators to tool utilization. Further Tracker development was guided by focus group input to address these barriers (e.g. information, policing, and logistical concerns) and facilitators (e.g. environmental motivators, positive reinforcement). Amongst 1,163 Tracker reports, those who completed the user survey (n=316) reported the top motivations to using the tool were having a cleaner environment (79%) and health concerns (69%). CONCLUSIONS Environmental concerns, a motivator which emerged in focus groups, shaped the Tracker’s development and was cited by the majority of users surveyed as a top motivator for utilization.

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