Pavlovian conditioning and rule learning

The experiment reviewed here was an attempt to show that two differential Pavlovian conditioning designs, namely positive and negative patterning, can best be understood as rule learning. First, it is shown that positive patterning is equivalent to the logical rule of conjunction (AND) and that negative patterning is equivalent to the logical rule of exclusive disjunction (XOR). It is assumed that in order to learn both kinds of discrimination subjects learn to use the according rule. If this is the case, the observed differentiation should be independent of the number of reinforcements for each individual stimulus. Second, subjects should be able to transfer the rule to new stimuli. Forty human subjects were randomly divided into four groups (N=10 each). Two factors were manipulated independently between subjects: (1) positive vs negative patterning, and (2) 2 vs 4 pairs of trained stimuli. Second interval skin conductance responses were measured. During initial acquisition positive as well as negative patterning occurred independently of number of pairs of trained stimuli (with total amount of training kept constant). Furthermore, AND as well as XOR could be transfered to new stimuli.     

Aging and implicit learning: explorations in contextual cuing

In contextual cuing, faster responses are made to repeated displays containing context-target associations than to novel displays without such covariances. We report that healthy older adults showed learning impairments in contextual cuing when compared with younger adults. The display properties in the task were altered to artificially increase younger adults' response times to match those of older adults and to produce faster responses in older participants; however, younger participants' learning remained intact, whereas older participants continued to show impairments under these conditions. These results suggest that older adults have intrinsic deficits in contextual cuing that cannot be attributed to their slower overall response speed.     

Aging and the detection of contingency in causal learning

Young and older participants' ability to detect negative, random, and positive response-outcome contingencies was evaluated using both contingency estimation and response rate adaptation tasks. Age differences in contingency estimation were consistently greater for negative than positive contingencies, and these differences, though still present, were smaller when response rate adaptation was used as the measure of contingency learning. Detecting causal contingency apparently becomes more difficult with age, especially when an oven numerical estimate of contingency must be provided and when the relationship between a causal event and an outcome is negative. A model that incorporates features of both associative and rule-based approaches to contingency learning (e.g., P. C. Price & J. F. Yates, 1995; D. R. Shanks, 1995) provides the best explanation for this pattern of findings.     

Aging and retrospective revaluation of causal learning

In a 2-stage causal learning task, young and older participants first learned which foods presented in compound were followed by an allergic reaction (e.g., STEAK-BEANS→ REACTION) and then the causal efficacy of 1 food from these compounds was revalued (e.g., BEANS→ NO REACTION). In Experiment 1, unrelated food pairs were used, and although there were no age differences in compound- or single-cue-outcome learning, older adults did not retrospectively revalue the causal efficacy of the absent target cues (e.g., STEAK). However, they had weaker within-compound associations for the unrelated foods, and this may have prevented them from retrieving the representations of these cues. In Experiment 2, older adults still showed no retrospective revaluation of absent cues even though compound food cues with pre-existing associations were used (e.g., STEAK-POTATO), and they received additional learning trials. Finally, in Experiment 3, older adults revalued the causal efficacy of the target cues when small, unobtrusive icons of these cues were present during single-cue revaluation. These findings suggest that age-related deficits in causal learning for absent cues are due to ineffective associative binding and reactivation processes.     

Reading disability: A problem in rule learning and word decoding

Traditional explanations of reading disability (e.g., perceptual, memory, and phonetic receding deficits) have encountered logical difficulties and substantial empirical disconfirmation. An alternative conceptualization of the nature of reading disability is proposed. Disabled readers are hypothesized to suffer a fundamental problem in acquiring word knowledge and word processing skills. Poor decoding skills prevent them from developing sophisticated reading comprehension skills. From this perspective, the cognitive deficits of disabled readers result from failure to acquire and generalize complex processing skills originally mastered through reading experience. Recent research of the author and of others relating to these issues is discussed.     

A parallel rule activation and rule synthesis model for generalization in category learning

This paper proposes a distinction between primary generalization (transfer from stored exemplars to perceived targets) and secondary generalization (transfer from inferred abstractions to perceived targets). This distinction is embodied in the parallel rule activation and rule synthesis (PRAS) model, a production model capable of exemplar-based and abstraction-based categorization. As an exemplar model, the PRAS model is related to the generalized context model (Nosofsky, 1984). Exemplars are stored in memory encoded as condition-action rules. Working as an exemplar-based model, rules are activated on the basis of their strength and their similarity to the current to-be-categorized instance. Similarity between a target and a stored exemplar is weighted for attention to the dimensions of the psychological space. Depending on the value of a special parameter, the PRAS model is also able to operate as an abstraction model. In the latter case, it attempts to construct generalizing productions, which are activated according to the same rules as the exemplar-specific rules. The model is described in detail. It is applied to a number of important observations described in the research literature, and an experiment is reported that tested the usefulness of the proposed secondary-generalization mechanism. Finally, the discussion elaborates on the implications of the present study for further research.     

Implicit learning in rule induction and problem solving

Using the Chinese Ring Puzzle (Kotovsky & Simon, ; P. J. Reber & Kotovsky, ), we studied the effect on rule discovery of having to plan actions or not in order to reach a goal state. This was done by asking participants to predict legal moves as in implicit learning tasks (Experiment 1) and by asking participants to make legal moves as in problem-solving tasks (Experiment 2). Our hypothesis was that having a specific goal state to reach has a dual effect on rule discovery. The first effect is positive and related to feedback from moves done in order to attain the goal: generalising the results of action and associating them to the conditions in which they were obtained allows discovery of the rule and learning it. The second effect is negative. In attempting to reach a specific goal, participants first tend to reduce the distance that separates the current state from the goal state (hill climbing) and so neglect the kind of exploration that facilitates rule and procedure discovery because this would seem to be a detour from the goal. Results show that having to plan actions improved performance in implicit learning tasks (Experiment 1), yet it impaired performance in problem-solving tasks (Experiment 2). Although implicit learning and problem solving are based on rule discovery, and entail noticing regularities in the material, in both cases, rule discovery processes appear to be task-dependent.     

Sequential learning and rule abstraction in Bengalese finches

The Bengalese finch (Lonchura striata var. domestica) is a species of songbird. Males sing courtship songs with complex note-to-note transition rules, while females discriminate these songs when choosing their mate. The present study uses serial reaction time (RT) to examine the characteristics of the Bengalese finches’ sequential behaviours beyond song production. The birds were trained to produce the sequence with an “A–B–A” structure. After the RT to each key position was determined to be stable, we tested the acquisition of the trained sequential response by presenting novel and random three-term sequences (random test). We also examined whether they could abstract the embedded rule in the trained sequence and apply it to the novel test sequence (abstract test). Additionally, we examined rule abstraction through example training by increasing the number of examples in baseline training from 1 to 5. When considered as (gender) groups, training with 5 examples resulted in no statistically significant differences in the abstract tests, while statistically significant differences were observed in the random tests, suggesting that the male birds learned the trained sequences and transferred the abstract structure they had learned during the training trials. Individual data indicated that males, as opposed to females, were likely to learn the motor pattern of the sequence. The results are consistent with observations that males learn to produce songs with complex sequential rules, whereas females do not.     

An associative model of geometry learning: a modified choice rule

In a recent article, the authors (Miller & Shettleworth, 2007) showed how the apparently exceptional features of behavior in geometry learning ("reorientation") experiments can be modeled by assuming that geometric and other features at given locations in an arena are learned competitively as in the Rescorla-Wagner model and that the probability of visiting a location is proportional to the total associative strength of cues at that location relative to that of all relevant locations. Reinforced or unreinforced visits to locations drive changes in associative strengths. Dawson, Kelly, Spetch, and Dupuis (2008) have correctly pointed out that at parameter values outside the ranges the authors used to simulate a body of real experiments, our equation for choice probabilities can give impossible and/or wildly fluctuating results. Here, the authors show that a simple modification of the choice rule eliminates this problem while retaining the transparent way in which the model relates spatial choice to competitive associative learning of cue values.     

Aging, working memory, and discrimination learning

Older adults easily learn probabilistic relationships between cues and outcomes when the predictive event is the occurrence of a cue, but have greater difficulty when the predictive event is the nonoccurrence of a cue (Mutter & Pliske, 1996; Mutter & Plumlee, 2004; Mutter & Williams, 2004). This study explored whether this age-related deficit occurs in a simpler learning context and whether it might be related to working memory (WM) decline. We gave younger and older adults simultaneous discrimination tasks that allowed us to compare their ability to learn deterministic relationships when either the occurrence (feature positive; FP) or the nonoccurrence (feature negative; FN) of a distinctive feature predicted reinforcement. We also included a group of younger adults who performed the discrimination tasks under a concurrent WM load. Both age and WM load had a detrimental effect on initial FP and FN discrimination; however, these effects persisted only in FN discrimination after additional learning experience. Learning predictive relationships requires inductive reasoning processes that apparently do not operate as efficiently in individuals with reduced WM capacity. The impact of WM decline may ultimately be greater for negative cue-outcome relationships because learning these relationships requires more difficult inductive reasoning processes, which place greater demands on WM.     

Aging,working memory,and discrimination learning

Older adults easily learn probabilistic relationships between cues and outcomes when the predictive event is the occurrence of a cue, but have greater difficulty when the predictive event is the nonoccurrence of a cue (Mutter & Pliske, 1996; Mutter & Plumlee, 2004; Mutter & Williams, 2004). This study explored whether this age-related deficit occurs in a simpler learning context and whether it might be related to working memory (WM) decline. We gave younger and older adults simultaneous discrimination tasks that allowed us to compare their ability to learn deterministic relationships when either the occurrence (feature positive; FP) or the nonoccurrence (feature negative; FN) of a distinctive feature predicted reinforcement. We also included a group of younger adults who performed the discrimination tasks under a concurrent WM load. Both age and WM load had a detrimental effect on initial FP and FN discrimination; however, these effects persisted only in FN discrimination after additional learning experience. Learning predictive relationships requires inductive reasoning processes that apparently do not operate as efficiently in individuals with reduced WM capacity. The impact of WM decline may ultimately be greater for negative cue–outcome relationships because learning these relationships requires more difficult inductive reasoning processes, which place greater demands on WM.     

Aging affects motor learning but not savings at transfer of learning

Two important components of skill learning are the learning process itself (motor acquisition) and the ability to transfer what has been learned to new task variants (motor transfer). Many studies have documented age-related declines in the ability to learn new manual motor skills. In this study, I tested whether the degree of savings at transfer of learning is similarly affected by advancing age. Young and older adults made aiming movements with a joystick to hit targets presented on a computer screen, with real-time feedback display of their movement. They adapted to three different rotations of the feedback display in a sequential fashion, with return to the normal feedback display between each. Adaptation performance was better when it was preceded by other adaptive experiences, regardless of age.     

Aging affects acquisition and reversal of reward-based associative learning

Reward-based associative learning is mediated by a distributed network of brain regions that are dependent on the dopaminergic system. Age-related changes in key regions of this system, the striatum and the prefrontal cortex, may adversely affect the ability to use reward information for the guidance of behavior. The present study investigated the effects of healthy aging on different components of reward learning, such as acquisition, reversal, effects of reward magnitude, and transfer of learning. A group of 30 young (mean age = 24.2 yr) and a group of 30 older subjects (mean age = 64.1 yr) completed two probabilistic reward-based stimulus association learning tasks. Older subjects showed poorer overall acquisition and impaired reversal learning, as well as deficits in transfer learning. When only those subjects who showed evidence of significant learning were considered, younger subjects showed equivalently fast learning irrespective of reward magnitude, while learning curves in older subjects were steeper for high compared to low reward magnitudes. Acquired equivalence learning, which requires generalization across stimuli and transfer of learned contingencies to new stimuli, was mildly impaired in older subjects.     

The power law repealed: The case for an exponential law of practice

The power function is treated as the law relating response time to practice trials. However, the evidence for a power law is flawed, because it is based on averaged data. We report a survey that assessed the form of the practice function for individual learners and learning conditions in paradigms that have shaped theories of skill acquisition. We fit power and exponential functions to 40 sets of data representing 7,910 learning series from 475 subjects in 24 experiments. The exponential function fit better than the power function in all the unaveraged data sets. Averaging produced a bias in favor of the power function. A new practice function based on the exponential, the APEX function, fit better than a power function with an extra, preexperimental practice parameter. Clearly, the best candidate for the law of practice is the exponential or APEX function, not the generally accepted power function. The theoretical implications are discussed.     

Relevance of education and intelligence for the political development of nations: Democracy, rule of law and political liberty

Political theory has described a positive linkage between education, cognitive ability and democracy. This assumption is confirmed by positive correlations between education, cognitive ability, and positively valued political conditions (N = 183 − 130). Longitudinal studies at the country level (N = 94 − 16) allow the analysis of causal relationships. It is shown that in the second half of the 20th century, education and intelligence had a strong positive impact on democracy, rule of law and political liberty independent from wealth (GDP) and chosen country sample. One possible mediator of these relationships is the attainment of higher stages of moral judgment fostered by cognitive ability, which is necessary for the function of democratic rules in society. The other mediators for citizens as well as for leaders could be the increased competence and willingness to process and seek information necessary for political decisions due to greater cognitive ability. There are also weaker and less stable reverse effects of the rule of law and political freedom on cognitive ability.     

Incorporating prior biases innetwork models of conceptual rule learning

A series of simulations is reported in which extant formal categorization models are applied to human rule-learning data (Salatas & Bourne, 1974). These data show that there are clear differences in the ease with which humans learn rules, with the conjunctive the easiest and the biconditional the hardest. The original ALCOVE model (an exemplar-based model), a configuralcue model, and two-layer backpropagation models did not fit the rule-learning data. ALCOVE successfully fit the data, however, when prior biases observed in human rule learning were implemented into weights of the network. Thus, current empirical learning models may not fare well in situations in which learners enter the concept-formation situation with preconceived biases regarding the kinds of concepts that are possible, but such biases might nevertheless be captured within these models. By incorporating preexperimental biases, ALCOVE may hold promise as a comprehensive category-learning model.