Negative reinforcement examples youtube11/11/2023 ![]() We modified the task further so that two decks varied only in the magnitude of gains and losses, and two decks varied in the frequency of gains and losses. Subjects had to learn to increase specific behaviors to minimize loss (negative reinforcement) and maximize gain (positive reinforcement). We adopted a modified version of the IGT (mIGT) used in previous studies that required an active response to avoid cards from disadvantageous decks ( Cauffman et al., 2010 Tanabe et al., 2007). The purpose of this study was to examine the effects of negative and positive reinforcement in SDI while controlling for frequency and magnitude information using a decision making task based on the IGT. This type of learning has not been studied in SDI so it is not known whether SDI are similar to, worse than, or better than normal controls in their negative reinforcement learning. Examples of negatively reinforced behaviors in everyday life include wearing a seatbelt to avoid an aversive sound, stopping at a Stop sign to avoid a ticket or accident, and saying no to a “get rich quick” scheme to avoid losing one's money. This theory suggests that SDI's continued maladaptive behavior may be influenced significantly by negative reinforcement, in which a behavior is acquired and maintained by the escape or avoidance of an aversive consequence. In this scenario, unpleasant physical or psychological conditions serve as negative reinforcers to reinitiate drug use ( Koob and Le Moal, 2001). SDI may persist or reinitiate using drugs, not because of positive effects, but rather to escape or avoid withdrawal symptoms and/or negative affective states. While initial drug use is largely driven by positive reinforcement, the positive reinforcing effects of drugs decrease over time ( Ahmed et al., 2002 Volkow et al., 1997). The original IGT evaluates the effects of positive reinforcement and punishment on behavior, but another form of learning, negative reinforcement, may play an important role in the persistence of addiction. However, no empirical study to date has used a procedure that disentangles the influences of magnitude and frequency of gains and losses on the IGT. Further, Frank and Claus (2006) proposed that performance on the IGT relies on the integration of magnitude and frequency information, which is represented across distinct neural regions. (2004) found cocaine abusers to be less influenced by losses and more sensitive to gains, and Fridberg and colleagues (2010) found that cannabis users were under-influenced by loss magnitude compared to controls. Mathematical models have also been used to better understand factors that influence performance on the IGT for example, Stout et al. (2006) found that manipulating relative reward magnitude of good and bad decks led to different choice behavior in control subjects. Previous research suggests that magnitude and frequency information may be important variables. The IGT payment schedule is complex ( Fellows, 2007), with the contingencies of each deck confounded by the size and frequency of gains and losses in an intermittent reinforcement paradigm. (See Buelow and Suhr (2009) for a review of studies on the IGT in SDI.) Individuals dependent on stimulants perform worse than other SDI ( Gonzalez et al., 2007) and pharmacologic therapies for drug dependence may further influence performance ( Pirastu et al., 2006). Substance dependent individuals (SDI) often fail to learn to ignore the decks with negative long-term consequences ( Bechara et al., 2001 Bechara and Damasio, 2002 Bolla et al., 2003 Grant et al., 2000 Verdejo et al., 2004, 2006, 2007). To be successful, participants must learn to play the advantageous decks instead of the disadvantageous decks this involves focusing on the long-term expected value of the decks, not just on short-term rewards. The decks vary in the magnitude and probability of short-term and long-term monetary gains and losses, such that over time, two decks result in a net gain and two result in a net loss. In this task, participants decide on each trial which one of four decks of cards to play. ![]() ![]() A laboratory task used to assess such decision making is the Iowa Gambling Task (IGT Bechara et al., 1994). Failure to learn from negative feedback may be manifested as poor decision making in the face of choices that involve ambiguity and risk. ![]()
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