Retrospective revaluation— learning about implied but unpresented cues— poses one of the greatest challenges to classical learning theories. Whereas theorists have revised their models to accommodate revaluation, the empirical reliability of the phenomenon remains contentious. I present two sets of experiments that examine revaluative learning under different but analogous experimental protocols. Results provided mixed empirical evidence that is difficult to interpret in isolation. To address the issue, I apply two computational models to the experiments. An instance-based model of associative learning (Jamieson et al., 2012) predicts retrospective revaluation and anticipates participant behaviour in one set of experiments. An updated classical learning model (Ghirlanda, 2005) fails to predict retrospective revaluation, but anticipates participant behaviour in the other set of experiments. I argue that retrospective revaluation emerges as a corollary of basic memorial processes and discuss the empirical and theoretical implications.

No description available.

Retrospective revaluation— learning about implied but unpresented cues— poses one of the greatest challenges to classical learning theories. Whereas theorists have revised their models to accommodate revaluation, the empirical reliability of the phenomenon remains contentious. I present two sets of experiments that examine revaluative learning under different but analogous experimental protocols. Results provided mixed empirical evidence that is difficult to interpret in isolation. To address the issue, I apply two computational models to the experiments. An instance-based model of associative learning (Jamieson et al., 2012) predicts retrospective revaluation and anticipates participant behaviour in one set of experiments. An updated classical learning model (Ghirlanda, 2005) fails to predict retrospective revaluation, but anticipates participant behaviour in the other set of experiments. I argue that retrospective revaluation emerges as a corollary of basic memorial processes and discuss the empirical and theoretical implications.

The present research sought to describe and explain age related changes to associative learning processes. Eleven experiments were conducted using a human conditional learning paradigm. Background data on health, lifestyle, and cognitive ability were collected and used as predictor variables in multiple regression analyses. Experiments 1 to 8 were formative, and found that older participants showed an overall age related decline in learning ability exacerbated by the number of stimuli and outcomes used, and the concurrent presentation of different problem types. Configural models of learning (e.g. Pearce, 1994, 2002) best predicted young participants’ learning whereas older people’s learning was more consistent with elemental models (e.g. Rescorla-Wagner, 1972), suggesting an age related change in generalisation processes. Those who learned problems better were also more likely to be able to articulate a rule that had helped them learn the problem. Age itself was the most predominant predictor of accuracy in these experiments. Experiments 9, 10, and 11 were multiple stage experiments that looked at the extent of pro- and retro-active interference in learning. Experiments 9 and 10 used easy and hard HCL problems to examine the role of rule induction in learning. Older participants who had learned initial discriminations better were more prone to pro-active interference in both experiments, the extent of which was predicted most reliably by fluid intelligence. Rule learning had a profound effect on participants’ predictions during the unreinforced test stage. In Experiment 9 (Easy-Hard) younger participants suffered from more retroactive interference than older people. This pattern was far less pronounced in Experiment 10, (Hard-Easy) suggesting that problem order affected the way participants generalised from rule-based knowledge. This observation is inexplicable by associative learning theories, and explanation may require a problem solving approach. Experiment 11 examined feature-based generalisation. Again older participants suffered more proactive and retroactive interference and elemental theories predicted their responses best, whereas younger participants responses were consistent with configural models of learning. In this instance, resistance to pro- and retro-active interference was predicted by fluid intelligence. Overall the research concluded that there is a demonstrable, complexity dependent change in associative learning processes in later life. It appears that humans have an increasing tendency to rely on elemental, rather than configural processes of generalisation in later life, and this leads to overgeneralisation between stimuli and an inability to resist pro- and retroactive interference in learning. This may be as a result of an inhibitory or source monitoring failure as a consequence of atrophy in the frontal lobes of the brain, although some of the learning deficits are explicable through mnemonic decline.

The experiments reported in this thesis were conducted to examine the effects of executive-control and associative-learning processes on performance in conventional executive-control paradigms. For this purpose, I developed comparative task-switching and response-inhibition paradigms, which were used to assess the performance of pigeons, whose behaviour is presumably based purely on associative processes, and of humans, whose behaviour may be guided by executive control and by associative processes. Pigeons were able to perform accurately in the comparative paradigms; hence, associative-learning processes are sufficient to account for successful performance. However, some task-specific effects that can be attributed to executive-control processes, and which were found in humans applying executive control, were absent or greatly reduced in pigeons. Those effects either reflect the mental operations that are performed to ensure that a specific set of stimulus-response-contingencies is applied and any contingencies belonging to a different set are suppressed, or reflect mental preparations for the possibility that the requirement to execute a certain response suddenly changes. In particular, in Chapter 3, it is shown that the benefits of repeatedly applying the same set of stimulus-response contingencies (or, in reverse, the costs of switching from one set to another) do not apply when Pavlovian processes dominate learning, which is likely the case for pigeons. Furthermore, as shown in Chapters 4 and 5, the behavioural effects of preparing for an unpredicted change in response requirements appeared to be absent when behaviour was based purely on associative processes. Instead, associatively mediated performance was primarily influenced by the stimulus-response contingencies that were effective in each paradigm. Repeating the same response in consecutive trials facilitated the performance of pigeons and associatively learning human participants in the task-switching paradigms, and performing a particular Go response increased the pigeons' likelihood of executing that response in the following trial in two response-inhibition paradigms. In summary, any behavioural effects that can be observed at the level of abstract task requirements reflect the influence of executive-control processes, both in task-switching paradigms and in response-inhibition paradigms.

Using an allergist task, Uengoer, Lotz and Pearce (2013) found that in a design A+/AX+/BY+/CY-, the blocked cue X was indicated to cause the outcome to a greater extent than the uncorrelated cue Y. This finding has been termed “the redundancy effect” by Pearce and Jones (2015). According to Vogel and Wagner (2017), the redundancy effect “presents a serious challenge for those theories of conditioning that compute learning through a global error-term” (p. 119). One such theory is the Rescorla-Wagner (1972) model, which predicts the opposite result, that Y will have a stronger association with the outcome than X. This thesis explored the basis of the redundancy effect in human causal learning. Evidence from Chapter 2 suggested that the redundancy effect was unlikely to have been due to differences in attention between X and Y. Chapter 3 explored whether differences in participants’ certainty about the causal status of X and of Y contributed to the redundancy effect. Manipulations aimed at disambiguating the effects that X had on the outcome, including outcome-additivity training and low outcome rate, resulted in lower ratings for this cue and a smaller redundancy effect. However, the redundancy effect was still significant with both manipulations, suggesting that while participants’ uncertainty about the causal status of X contributed to it, there may have been other factors. Chapter 4 investigated whether another factor was a lack of inhibition for cue C. In a scenario where inhibition was more plausible than in an allergist task, a negative correlation between causal ratings for C and for Y, and a positive correlation between ratings for C and the magnitude of the redundancy effect, were found. In addition, establishing C as inhibitory resulted in a smaller redundancy effect than establishing C as neutral. Overall, findings of this thesis suggest that the redundancy effect in human causal learning is the result of participants’ uncertainty about the causal status of X, and a lack of inhibition for C. Further work is recommended to explore whether combining manipulations targeting X and Y would reverse the redundancy effect, whether effects of outcome additivity and outcome rate on X are the result of participants’ uncertainty about this cue, and the extent to which participants rely on single versus summed error.

abstract: Watanabe, Náñez, and Sasaki (2001) introduced a phenomenon they named “task-irrelevant perceptual learning” in which near-threshold stimuli that are not essential to a given task can be associatively learned when consistently and concurrently paired with the focal task. The present study employs a visual paired-shapes recognition task, using colored polygon targets as salient attended focal stimuli, with the goal of comparing the increases in perceptual sensitivity observed when near-threshold stimuli are temporally paired in varying manners with focal targets. Experiment 1 separated and compared the target-acquisition and target-recognition phases and revealed that sensitivity improved most when the near-threshold motion stimuli were paired with the focal target-acquisition phase. The parameters of sensitivity improvement were motion detection, critical flicker fusion threshold (CFFT), and letter-orientation decoding. Experiment 2 tested perceptual learning of near-threshold stimuli when they were offset from the focal stimuli presentation by ±350 ms. Performance improvements in motion detection, CFFT, and decoding were significantly greater for the group in which near-threshold motion was presented after the focal target. Experiment 3 showed that participants with reading difficulties who were exposed to focal target-acquisition training improved in sensitivity in all visual measures. Experiment 4 tested whether near-threshold stimulus learning occurred cross-modally with auditory stimuli and served as an active control for the first, second, and third experiments. Here, a tone was paired with all focal stimuli, but the tone was 1 Hz higher or lower when paired with the targeted focal stimuli associated with recognition. In Experiment 4, there was no improvement in visual sensitivity, but there was significant improvement in tone discrimination. Thus, this study, as a whole, confirms that pairing near-threshold stimuli with focal stimuli can improve performance in just tone discrimination, or in motion detection, CFFT, and letter decoding. Findings further support the thesis that the act of trying to remember a focal target also elicited greater associative learning of correlated near-threshold stimulus than the act of recognizing a target. Finally, these findings support that we have developed a visual learning paradigm that may potentially mitigate some of the visual deficits that are often experienced by the reading disabled. / Dissertation/Thesis / Doctoral Dissertation Psychology 2016

No description available.

La dopamine du cortex préfrontal (PFC) est impliquée dans l’apprentissage et dans la prise de décision liée à l’effort. Comme l’apprentissage ne peut se faire sans effort, il n’est pas clair aujourd’hui si la dopamine est nécessaire pour l’apprentissage, ou pour l’engagement de l’effort pour apprendre. Dans ce travail, les rats apprenaient à pousser un levier pour obtenir de la nourriture, soit avec (apprentissage par observation, LeO) ou sans (essai-et-erreur, TE) observation préalable d’un congénère exécutant la tâche. TE et la phase d’exécution de LeO nécessitent l’effort physique (overt learning), l’observation dans LeO ne requiert pas d’effort physique (covert learning). Avant chaque session, les rats recevaient des injections de SCH23390 ou de la saline dans le cingulaire antérieur (ACC) ou l’orbitofrontal (OFC). Si la dopamine est nécessaire à l’apprentissage, le blocage des récepteurs D1 affecterait aussi bien l’apprentissage overt que covert. Si la dopamine n’est pas requise pour l’apprentissage mais pour l’engagement de l’effort, le blocage affecterait l’apprentissage overt, et non covert. Les résultats montrent que le blocage de la dopamine dans ACC ou OFC supprime l’apprentissage overt, laissant intact l’apprentissage covert. Une fois les injections arrêtées, les rats récupèrent la capacité d’apprendre, mais dans le cas de ACC, pas la tolérance à l’effort. Ces résultats suggèrent que la dopamine dans ACC et OFC n’est pas nécessaire pour l’apprentissage, et que les déficits d’apprentissage pourraient reflèter une réduction de la tolérance effort à l’effort liée au blocage de la dopamine. / Because prefrontal cortex (PFC) dopamine plays a pivotal role in associative learning and in effort-related decision making, it is not clear as of today whether PFC dopamine activity is required for learning per se, or rather for engaging the effort necessary to learn. In this work, we used observational learning (LeO) and trial-and-error (TE) learning to dissociate learning from physical effort. Both TE and the execution phase of LeO require physical effort (overt learning). Observation does not require physical effort (covert learning). Rats learned to push a lever for food rewards either with or without prior observation of an expert conspecific performing the same task. Before daily testing sessions, the rats received bilateral ACC or OFC microinfusions of SCH23390, or saline-control infusions. If dopamine activity is required for task acquisition, its blockade should impair both overt and covert learning. If dopamine is not required for task acquisition, but solely for regulating effort tolerance, blockade should impair overt learning but spare covert learning. We found that dopamine blockade in ACC or OFC suppressed overt learning selectively, leaving covert learning intact. In subsequent testing sessions without dopamine blockade, rats recovered their overt-learning capacity but, in ACC experiments, the animals did not recover their normal level of effort tolerance. These results suggest that ACC and OFC dopamine is not required for the acquisition of conditioned behaviours and that apparent learning impairments could instead reflect a reduced level of effort tolerance due to cortical dopamine blockade.

<div>While cognitive control enables the selection of goal-relevant responses, metacontrol enables the selection of context-appropriate control operations. In task switching, metacontrol modulates task-switching efficiency by retrieving the associations between a contextual cue and a particular cognitive control demand. While the automatic retrieval of cognitive control is appealing due to its time and energy efficiency, the effects of different contextual cues have been shown in separate studies and appear to have different characteristics. Here, we devised a single task-switching paradigm to test whether we can observe both list-wide and item-specific metacontrol within subjects. In two experiments, we demonstrated reduced switch costs in lists associated with a high probability of switching as compared with lists with a low probability of switching (i.e., a list-wide switch probability [LWSP] effect). Similarly, we observed an analogous item-specific switch probability (ISSP) effect such that items associated with a high probability of switching incurred smaller switch costs as compared with items associated with a low probability of switching. We also confirmed that both list-wide and item-specific switch probability effects were not dependent on lower-level stimulus-response associations. However, the LWSP and the ISSP effects were uncorrelated, suggesting a lack of dependence. Together, these findings suggest that there are two distinct modes of metacontrol that are deployed in a context-sensitive manner in order to adapt to specific cognitive demands.</div>