Compulsive behaviour may often be triggered by Pavlovian cues. Assessing how Pavlovian cues drive instrumental behaviour in obsessive-compulsive disorder (OCD) is therefore crucial to understand how compulsions develop and are maintained. An aversive Pavlovian-to-Instrumental transfer (PIT) paradigm, particularly one involving avoidance/cancellation of negative outcomes, can enable such investigation and has not previously been studied in clinical-OCD. Forty-one participants diagnosed with OCD (21 adults; 20 youths) and 44 controls (21 adults; 23 youths) completed an aversive PIT task. Participants had to prevent the delivery of unpleasant noises by moving a joystick in the correct direction. They could infer these correct responses by learning appropriate response-outcome (instrumental) and stimulus-outcome (Pavlovian) associations. We then assessed whether Pavlovian cues elicited specific instrumental avoidance responses (specific PIT) and induced general instrumental avoidance (general PIT). We investigated whether task learning and confidence indices influenced PIT strength differentially between groups. There was no overall group difference in PIT performance, although youths with OCD showed weaker specific PIT than youth controls. However, urge to avoid unpleasant noises and preference for safe over unsafe stimuli influenced specific and general PIT respectively in OCD, while PIT in controls was more influenced by confidence in instrumental and Pavlovian learning. Thus, in OCD, implicit motivational factors, but not learnt knowledge, may contribute to the successful integration of aversive Pavlovian and instrumental cues. This implies that compulsive avoidance may be driven by these automatic processes. Youths with OCD show deficits in specific PIT, suggesting cue integration impairments are only apparent in adolescence. These findings may be clinically relevant as they emphasise the importance of targeting such implicit motivational processes when treating OCD.

According to the cycle/trial (C/T) rule, the rate of associative learning is a function of the ratio between the overall rate of U.S. presentation (C) and its rate in the presence of the conditioned stimulus (CS; [T]). This rule is well supported in studies with nonhumans. The present study was conducted to test whether it also applies to human contingency learning. In Experiment 1, participants were exposed to rapid streams of trials. Sensitivity to the cue-outcome contingency varied with both intertrial interval (ITI, which captures C) and cue duration, but the C/T rule was not respected, notably because the effect of ITI was much larger than the effect of cue duration. Experiment 2 showed that mere suppression of verbal strategies did not alter the magnitude of the ITI effect. Experiment 3 replicated Experiment 1 but with cue duration and ITI varied between 1,000 and 3,000 ms instead of between 100 and 1,000 ms. Performance was insensitive to both cue duration and ITI. This was not the consequence of Experiment 3 only varying the cue duration to ITI ratio by a factor of 3; in Experiment 4 where the cue duration was 100 ms, a 300-ms ITI was sufficient to observe an ITI effect. The lack of an ITI effect with a 1,000-ms cue and an ITI varying between 1,000 and 3,000 ms was replicated in Experiment 5. These results are discussed in light of how processes underlying associative learning might break down when events occur very rapidly. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Successive negative contrast (SNC) has been used to study reward relativity, reward loss, and frustration for decades. In instrumental SNC (iSNC), the anticipatory performance of animals downshifted from a large reward to a small reward is compared to that of animals always reinforced with the small reward. iSNC involves a transient deterioration of anticipatory behavior in downshifted animals compared to unshifted controls. There is scattered information on the optimal parameters to produce this effect and even less information about its neural basis. Five experiments with rats trained in a runway to collect food pellets explored the effects of trial distribution (massed or spaced), amount of preshift training, reward disparity, and reward magnitude on the development of an iSNC effect. Start, run, and goal latencies were measured. Using spaced trials (one trial per day), evidence of the iSNC effect was observed with 24 preshift trials and a 32-to-4 pellet disparity. With massed trials (4 trials per session separated by 30-s intertrial intervals), evidence of iSNC was found with 12 preshift sessions (a total of 48 trials) and a 16-to-2 pellet disparity. The massed-training procedure was then used to assess neural activity in three prefrontal cortex areas using c-Fos expression in animals perfused after the first downshift session. There was evidence of increased activation in the anterior cingulate cortex and a trend toward increased activation in the infralimbic and prelimbic cortices. These procedures open a venue for studying the neural basis of the instrumental behavior of animals that experience reward loss.

Discrimination performance in perceptual choice tasks is known to reflect both sensory discriminability and nonsensory response bias. In the framework of signal detection theory, these aspects of discrimination performance are quantified through separate measures, sensitivity (d\') for sensory discriminability and decision criterion (c) for response bias. However, it is unknown how response bias (i.e., criterion) changes at the single-trial level as a consequence of reinforcement history. We subjected rats to a two-stimulus two-response conditional discrimination task with auditory stimuli and induced response bias through unequal reinforcement probabilities for the two responses. We compared three signal-detection-theory-based criterion learning models with respect to their ability to fit experimentally observed fluctuations of response bias on a trial-by-trial level. These models shift the criterion by a fixed step (1) after each reinforced response or (2) after each nonreinforced response or (3) after both. We find that all three models fail to capture essential aspects of the data. Prompted by the observation that steady-state criterion values conformed well to a behavioral model of signal detection based on the generalized matching law, we constructed a trial-based version of this model and find that it provides a superior account of response bias fluctuations under changing reinforcement contingencies.

The partial reinforcement extinction effect (PREE) refers to the phenomenon that conditioned responding extinguishes more slowly if subjects had been inconsistently (\"partially\") reinforced than if they had been reinforced on every trial (\"continuously\" reinforced). One largely successful account of the PREE, known as sequential theory (Capaldi, 1966), suggests that, when subjects are partially reinforced, they learn that memories of sequences of nonreinforced trials are associated with subsequent reinforcement. This association helps to maintain responding (i.e., delay extinction) when the subjects experience nonreinforced trials during extinction. Sequential theory\'s explanation of the PREE hinges on subjects learning sequences of nonreinforced trials during acquisition. However, direct evidence for such sequential learning is not available in previous studies of the PREE where animals are trained with multiple sequences of different lengths that are randomly intermixed and, therefore, cannot anticipate whether a given trial will be reinforced during acquisition. The current study conducted two experiments that trained rats with a single fixed trial sequence to provide evidence of sequential learning during conditioning, and then observe its effect on the PREE. Under one condition the rats did learn about the fixed sequence but did not subsequently show a PREE, whereas other rats that did show a PREE had not learned the trial sequences during conditioning. Therefore, contrary to sequential theory\'s prediction, our result suggests that learning about the trial sequence is neither necessary nor sufficient for the PREE. We suggest that the PREE may instead depend on uncertainty about whether the conditioned stimulus will be reinforced. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Operant conditioning was shown to be a mechanism of placebo hypoalgesia; however, only verbal rewards and punishers were applied in the previous study. We aimed to induce placebo hypoalgesia using more clinically relevant consequences: token-based and social. Participants were divided into three experimental groups (with verbal, social, and token-based rewards and punishers); and two control groups (with and without placebo application). During operant conditioning, participants in the experimental groups received thermal stimuli of equal intensity and were rewarded for reporting lower pain and punished for reporting higher pain compared to their pretest pain levels. The control groups did not receive any consequences. Our results revealed placebo hypoalgesia was induced by operant conditioning only in the experimental groups with social and token-based reinforcement, compared to the control groups. The hypoalgesic effect found in the group that received verbal reinforcement did not differ significantly from the control group with the placebo application. Moreover, expectations about upcoming pain intensity were found to be a mediator, and the number of reinforcers received during conditioning was a predictor of placebo hypoalgesia. These findings highlight the potential benefits of incorporating token-based and social consequences for optimizing treatment outcomes in pain management.

Motor learning and flexibility allow animals to perform routine actions efficiently while keeping them flexible. A number of paradigms are used to test cognitive flexibility, but not many of them focus specifically on the learning of complex motor sequences and their flexibility. While many tests use operant or touchscreen boxes that offer high throughput and reproducibility, the motor actions themselves are mostly simple presses of a designated lever. To focus more on motor actions during the operant task and to probe the flexibility of these well trained actions, we developed a new operant paradigm for mice, the \"timed sequence task.\" The task requires mice to learn a sequence of lever presses that have to be emitted in precisely defined time limits. After training, the required pressing sequence and/or timing of individual presses is modified to test the ability of mice to alter their previously trained motor actions. We provide a code for the new protocol that can be used and adapted to common types of operant boxes. In addition, we provide a set of scripts that allow automatic extraction and analysis of numerous parameters recorded during each session. We demonstrate that the analysis of multiple performance parameters is necessary for detailed insight into the behavior of animals during the task. We validate our paradigm in an experiment using the valproate model of autism as a model of cognitive inflexibility. We show that the valproate mice show superior performance at specific stages of the task, paradoxically because of their propensity to more stereotypic behavior.

Previous nonhuman studies have reported that sign-tracking to a conditioned stimulus (CS) is increased when the intertrial interval (ITI) duration is increased. Separate studies indicate that individual differences in sign-tracking (vs. goal-tracking) at a fixed ITI (and CS duration) is predictive of the conditioned reinforcer efficacy of the CS. The present study evaluates, for the first time, if increasing the ITI increases rats\' sign-tracking and the conditioned reinforcing efficacy of the CS. Forty-five female rats were randomly assigned to one of three groups that completed appetitive Pavlovian training with ITIs of 14, 24, or 96 s. Subsequently, they completed tests of conditioned reinforcement. Replicating previous findings, longer ITIs increased sign-tracking to a lever-CS and, extending the literature, conditioned reinforcer efficacy of that CS was highest at the longest ITI used during Pavlovian training. Implications for behavioral interventions using conditioned reinforcement are discussed.

The modulation of instrumental action by conditioned Pavlovian cues is hypothesized to play a role in the emergence and maintenance of maladaptive behavior. The Pavlovian to Instrumental transfer task (PIT) is designed to examine the magnitude of the influence of cues on behavior and we aim to manipulate the motivational value of Pavlovian cues to reduce their effect on instrumental responding. To this end, we utilized a joystick-based modification of approach and avoidance propensities that has shown success in clinical populations. To examine changes in PIT, we subjected 35 healthy participants to a series of experimental procedures: (1) Instrumental training was followed by (2) Pavlovian conditioning of neutral stimuli that were associated with monetary reward or loss. (3) In a subsequent joystick task, approach and avoidance tendencies toward conditioned cues were assessed. (4) In a transfer test, the PIT effect as the impact of conditioned cues on instrumental behavior was measured. (5) The explicit knowledge of cue-reward contingencies was assessed in a forced-choice phase. (6, 7) systematic joystick training was followed by a posttest (8) the transfer task and forced-choice test were repeated. We found no effect of training on approach-avoidance propensities in the context of this proof of concept study. A higher response rate towards negative stimuli during PIT after systematic training compared to sham training was seen. On the other hand, we saw an increased PIT effect after sham training. These results contribute to the understanding of the strength of the influence of cues on instrumental behavior. Our findings further stress the importance of context, instructions and operationalization of instrumental behavior in the framework of transfer effects.

BACKGROUND: The incidence of adolescent depressive disorder is globally skyrocketing in recent decades, albeit the causes and the decision deficits depression incurs has yet to be well-examined. With an instrumental learning task, the aim of the current study is to investigate the extent to which learning behavior deviates from that observed in healthy adolescent controls and track the underlying mechanistic channel for such a deviation.
METHODS: We recruited a group of adolescents with major depression and age-matched healthy control subjects to carry out the learning task with either gain or loss outcome and applied a reinforcement learning model that dissociates valence (positive v. negative) of reward prediction error and selection (chosen v. unchosen).
RESULTS: The results demonstrated that adolescent depressive patients performed significantly less well than the control group. Learning rates suggested that the optimistic bias that overall characterizes healthy adolescent subjects was absent for the depressive adolescent patients. Moreover, depressed adolescents exhibited an increased pessimistic bias for the counterfactual outcome. Lastly, individual difference analysis suggested that these observed biases, which significantly deviated from that observed in normal controls, were linked with the severity of depressive symoptoms as measured by HAMD scores.
CONCLUSIONS: By leveraging an incentivized instrumental learning task with computational modeling within a reinforcement learning framework, the current study reveals a mechanistic decision-making deficit in adolescent depressive disorder. These findings, which have implications for the identification of behavioral markers in depression, could support the clinical evaluation, including both diagnosis and prognosis of this disorder.