Biomedical subjects

W Todd Maddox

Publications and source records attributed to W Todd Maddox.

At least 19 recordsLinked to original sources

PubMed2007

Within-category discontinuity interacts with verbal rule complexity in perceptual category learning.

A test of the predicted interaction between within-category discontinuity and verbal rule complexity on information-integration and rule-based category learning was conducted. Within-category discontinuity adversely affected information-integration category learning but not rule-based category learning. Model-based analyses suggested that some information-integration participants improved performance by recruiting more "units" in the discontinuous condition. Verbal rule complexity adversely affected rule-based category learning but not information-integration category learning. Model-based analyses suggested that the rule based effect was on both decision criterion learning and variability in decision criterion placement. These results suggest that within-category discontinuity and decision rule complexity differentially impact information-integration and rule-based category learning and provide information regarding the detailed processing characteristics of these two proposed category learning systems.

Concept Formation↗

PubMed2006

Characterizing rule-based category learning deficits in patients with Parkinson's disease.

Parkinson's disease (PD) patients and normal controls were tested in three category learning experiments to determine if previously observed rule-based category learning impairments in PD patients were due to deficits in selective attention or working memory. In Experiment 1, optimal categorization required participants to base their decision on a single stimulus dimension and ignore irrelevant variation on another dimension, thus emphasizing selective attention processes. In Experiment 2, optimal categorization required participants to base their decision on both stimulus dimensions using a conjunction of unidimensional decisions. Thus, this task placed less emphasis on selective attention and more on working memory. In Experiment 3, optimal categorization again required participants to base their decision on both stimulus dimensions using a disjunction of two unidimensional decisions in which an additional verbal operation was needed, thereby placing even greater emphasis on working memory. Results indicated that PD patients were impaired in the unidimensional rule-based condition, but not the other two rule-based conditions. These results are consistent with previous studies that demonstrate that PD patients are impaired in learning rule-based categories when selective attention demands are greatest, whereas these patients are normal in learning rule-based tasks when working memory demands are emphasized. Overall, these findings help to delineate the conditions under which PD patients display rule-based category learning deficits.

Aged↗

PubMed2006

Recency effects as a window to generalization: separating decisional and perceptual sequential effects in category learning.

Accounts of learning and generalization typically focus on factors related to lasting changes in representation (i.e., long-term memory). The authors present evidence that shorter term effects also play a critical role in determining performance and that these recency effects can be subdivided into perceptual and decisional components. Experimental results based on a probabilistic category structure show that the previous stimulus exerts a contrastive effect on the current percept (perceptual recency) and that responses are biased toward or away from the previous feedback, depending on the similarity between successive stimuli (decisional recency). A method for assessing these recency effects is presented that clarifies open questions regarding stimulus generalization and perceptual contrast effects in categorization and in other domains.

Attention↗

PubMed2006

Choking and excelling under pressure.

Decrements in performance on cognitive tasks resulting from pressure to perform (i.e., choking) are thought to be caused by interference with the ability to use explicit strategies (the distraction theory). This view suggests that pressure should improve performance on tasks for which explicit strategies hamper performance. This hypothesis was tested by giving subjects one of two nearly identical learning tasks, a task that required learning a rule or one that required using a holistic information-integration strategy. Explicit rule use would hurt performance in the latter task. As predicted by the distraction theory, pressure decreased performance on the rule-based task but enhanced performance on the information-integration task.

Achievement↗

PubMed2006

Dual-task interference in perceptual category learning.

The effect of a working-memory-demanding dual task on perceptual category learning was investigated. In Experiment 1, participants learned unidimensional rule-based or information integration category structures. In Experiment 2, participants learned a conjunctive rule-based category structure. In Experiment 1, unidimensional rule-based category learning was disrupted more by the dual working memory task than was information integration category learning. In addition, rule-based category learning differed qualitatively from information integration category learning in yielding a bimodal, rather than a normal, distribution of scores. Experiment 2 showed that rule-based learning can be disrupted by a dual working memory task even when both dimensions are relevant for optimal categorization. The results support the notion of at least two systems of category learning a hypothesis-testing system that seeks verbalizable rules and relies on working memory and selective attention, and an implicit system that is procedural-learning based and is essentially automatic.

Association Learning↗

PubMed2005

Cortical and subcortical brain regions involved in rule-based category learning.

The brain regions contributing to rule-based category learning were examined using fMRI. Participants categorized single lines that varied in length and orientation into one of two categories. Category membership was based on the length of the line. Results indicated that left frontal and parietal regions were differentially activated in those participants who learned the task as compared to those who did not. Further, the head of the caudate displayed relative decreases in activation on incorrect trials relative to correct trials. The involvement of this latter structure is likely related to (1) processing an error signal, or (2) volitional switching between potential category rules. Results are consistent with theories suggesting that a frontal-striatal circuit is involved in rule-based category learning.

Adult↗

PubMed2005

The impact of irrelevant dimensional variation on rule-based category learning in patients with Parkinson's disease.

This study examined the impact of irrelevant dimensional variation on rule-based category learning in patients with Parkinson's disease (PD), older controls (OC), and younger controls (YC). Participants were presented with 4-dimensional, binary-valued stimuli and were asked to categorize each into 1 of 2 categories. Category membership was based on the value of a single dimension. Four experimental conditions were administered in which there were zero, 1, 2, or 3 randomly varying irrelevant dimensions. Results indicated that patients with PD were impacted to a greater extent than both the OC and YC participants when the number of randomly varying irrelevant dimensions increased. These results suggest that the degree of working memory and selective attention requirements of a categorization task will impact whether PD patients are impaired in rule-based category learning, and help to clarify recent discrepancies in the literature.

Aged↗

PubMed2005

Delayed feedback disrupts the procedural-learning system but not the hypothesis-testing system in perceptual category learning.

W. T. Maddox, F. G. Ashby, and C. J. Bohil (2003) found that delayed feedback adversely affects information-integration but not rule-based category learning in support of a multiple-systems approach to category learning. However, differences in the number of stimulus dimensions relevant to solving the task and perceptual similarity failed to rule out 2 single-system interpretations. The authors conducted an experiment that remedied these problems and replicated W. T. Maddox et al.'s findings. The experiment revealed a strong performance decrement for information-integration but not rule-based category learning under delayed feedback that was due to an increase in the number of observers using hypothesis-testing strategies to solve the information-integration task, and lower accuracy rates for the few observers using information-integration strategies.

Analysis of Variance↗

PubMed2005

Discontinuous categories affect information-integration but not rule-based category learning.

Three experiments were conducted that provide a direct examination of within-category discontinuity manipulations on the implicit, procedural-based learning and the explicit, hypothesis-testing systems proposed in F. G. Ashby, L. A. Alfonso-Reese, A. U. Turken, and E. M. Waldron's (1998) competition between verbal and implicit systems model. Discontinuous categories adversely affected information-integration but not rule-based category learning. Increasing the magnitude of the discontinuity did not lead to a significant decline in performance. The distance to the bound provides a reasonable description of the generalization profile associated with the hypothesis-testing system, whereas the distance to the bound plus the distance to the trained response region provides a reasonable description of the generalization profile associated with the procedural-based learning system. These results suggest that within-category discontinuity differentially impacts information-integration but not rule-based category learning and provides information regarding the detailed processing characteristics of each category learning system.

Adult↗

PubMed2005

Information-integration category learning in patients with striatal dysfunction.

Information-integration category learning was examined in patients with Parkinson's disease (PD) and in healthy control participants in 2 different conditions. In the linear condition, optimal categorization required a nonverbalizable linear integration of information from the 2 stimulus dimensions, whereas in the nonlinear condition, a nonlinear integration of information was required. Each participant completed 600 trials in each condition and was given corrective feedback following each trial. Results indicated that PD patients were not impaired in the linear condition across all trials, whereas the same patients were impaired in the nonlinear condition, but only later in training. The authors conducted model-based analyses to identify participants who used an information-integration approach, and a comparison of the accuracy rates of those individuals further revealed a specific deficit in information-integration category learning in patients with PD. These findings suggest that the striatum may be particularly involved in information-integration category learning when the rule is highly complex.

Aged↗

PubMed2005

The interaction of payoff structure and regulatory focus in classification.

This report brings together research on motivation and learning by exploring how fit of regulatory focus affects people's ability to acquire new categories. Perceptual categories were learned by people with a promotion focus (a situationally determined sensitivity to gains) or a prevention focus (a sensitivity to losses). Classification performance was closest to optimal (as determined by models fit to individual subjects' data) when the regulatory focus matched the structure of the payoffs for the categories. Promotion-focus subjects performed best when the payoffs consisted of all gains. Prevention-focus subjects performed best when the payoffs consisted of all losses.

Classification↗

PubMed2005

Human category learning.

Much recent evidence suggests some dramatic differences in the way people learn perceptual categories, depending on exactly how the categories were constructed. Four different kinds of category-learning tasks are currently popular-rule-based tasks, information-integration tasks, prototype distortion tasks, and the weather prediction task. The cognitive, neuropsychological, and neuroimaging results obtained using these four tasks are qualitatively different. Success in rule-based (explicit reasoning) tasks depends on frontal-striatal circuits and requires working memory and executive attention. Success in information-integration tasks requires a form of procedural learning and is sensitive to the nature and timing of feedback. Prototype distortion tasks induce perceptual (visual cortical) learning. A variety of different strategies can lead to success in the weather prediction task. Collectively, results from these four tasks provide strong evidence that human category learning is mediated by multiple, qualitatively distinct systems.

Attention↗

PubMed2005

Rule-based category learning is impaired in patients with Parkinson's disease but not in patients with cerebellar disorders.

The basal ganglia and cerebellum have both been implicated in motor skill acquisition. Recent hypotheses concerning cognitive functions of the basal ganglia and cerebellum have emphasized that these subcortical structures may also contribute to nonmotor learning. To explore this issue, patients with Parkinson's disease (PD) and patients with cerebellar lesions (CB) were tested on two category-learning tasks. Identical stimulus displays were used for the two tasks, consisting of a reference line and target line. In the length task, the two categories were defined based on the length of the target line. In the distance task, the two categories were defined by the distance between the target and reference lines. Thus, both categories could be defined by a simple rule in which attention must be restricted to a single relevant dimension. Consistent with previous results, the patients with PD were impaired on both tasks compared with neurologically healthy controls. In contrast, the CB patients performed similar to the control participants. Model-based analyses indicate that the patients with PD were able to select the appropriate categorization rule, but that they adopted suboptimal category boundaries in both conditions and were more variable in the application of the selected rule. These results provide an important neuropsychological dissociation on a non-motor-learning task between the effects of basal ganglia and cerebellar lesions. Moreover, the modeling work suggests that at least part of the Parkinson patients' impairment on these tasks reflect a tendency to exhibit strong response biases.

Aged↗

PubMed2005

Risks of drawing inferences about cognitive processes from model fits to individual versus average performance.

With the goal of drawing inferences about underlying processes from fits of theoretical models to cognitive data, we examined the tradeoff of risks of depending on model fits to individual performance versus risks of depending on fits to averaged data with respect to estimation of values of a model's parameters. Comparisons based on several models applied to experiments on recognition and categorization and to artificial, computer-generated data showed that results of using the two types of model fitting are strongly determined by two factors: model complexity and number of subjects. Reasonably accurate information about true parameter values was found only for model fits to individual performance and then only for some of the parameters of a complex model. Suggested guidelines are given for circumventing a variety of obstacles to successful recovery of useful estimates of a model's parameters from applications to cognitive data.

Cognition↗

PubMed2005

Optimal classifier feedback improves cost-benefit but not base-rate decision criterion learning in perceptual categorization.

Unequal payoffs engender separate reward- and accuracy-maximizing decision criteria; unequal base rates do not. When payoffs are unequal, observers place greater emphasis on accuracy than is optimal. This study compares objective classifier (the objectively correct response) with optimal classifier feedback (the optimal classifier's response) when payoffs or base rates are unequal. It provides a critical test of Maddox and Bohil's (1998) competition between reward and accuracy maximization (COBRA) hypothesis, comparing it with a competition between reward and probability matching (COBRM) and a competition between reward and equal response frequencies (COBRE) hypothesis. The COBRA prediction that optimal classifier feedback leads to better decision criterion leaning relative to objective classifier feedback when payoffs are unequal, but not when base rates are unequal, was supported. Model-based analyses suggested that the weight placed on accuracy was reduced for optimal classifier feedback relative to objective classifier feedback. In addition, delayed feedback affected learning of the reward-maximizing decision criterion.

Decision Making↗

PubMed2004

Dissociating explicit and procedural-learning based systems of perceptual category learning.

A fundamental question is whether people have available one category learning system, or many. Most multiple systems advocates postulate one explicit and one implicit system. Although there is much agreement about the nature of the explicit system, there is less agreement about the nature of the implicit system. In this article, we review a dual systems theory of category learning called competition between verbal and implicit systems (COVIS) developed by Ashby et al. The explicit system dominates the learning of verbalizable, rule-based category structures and is mediated by frontal brain areas such as the anterior cingulate, prefrontal cortex (PFC), and head of the caudate nucleus. The implicit system, which uses procedural learning, dominates the learning of non-verbalizable, information-integration category structures, and is mediated by the tail of the caudate nucleus and a dopamine-mediated reward signal. We review nine studies that test six a priori predictions from COVIS, each of which is supported by the data.

Caudate Nucleus↗

PubMed2004

Category number impacts rule-based but not information-integration category learning: further evidence for dissociable category-learning systems.

Category number effects on rule-based and information-integration category learning were investigated. Category number affected accuracy and the distribution of best-fitting models in the rule-based task but had no effect on accuracy and little effect on the distribution of best-fining models in the information-integration task. In the 2 category conditions, rule-based learning was better than information-integration learning, whereas in the 4 category conditions, unidimensional and conjunctive rule-based learning was worse than information-integration learning. Rule-based strategies were used in the 2-category/rule-based condition, but about half of the observers used rule-based strategies in the 4-category unidimensional and conjunctive rule-based conditions. Information-integration strategies were used in the 4-category/ information-integration condition and by the end of training were used in the 2-category/information-integration condition.

Adult↗

PubMed2004

A quantitative model-based approach to examining aging effects on information-integration category learning.

Information-integration category learning was examined in older and younger adults. Accuracy results indicated that older participants learned less well than younger participants in both linear and nonlinear conditions. Model-based analyses indicated that both groups in the linear condition tended to use information integration but that later in training younger participants were more likely to do so. In contrast, the 2 groups in the nonlinear condition were equally likely to use information integration. Further analysis indicated that younger adults were more accurate than older adults when an information-integration approach was adopted, whereas fewer age-related differences were observed when a rule-based approach was used, suggesting that age can have a negative impact on information-integration category learning processes but less impact on rule-based learning.

Adult↗