Studies of implicit prototype extraction in patients with mild cognitive impairment and early Alzheimer's disease

Abstract

Studies of incidental category learning support the hypothesis of an implicit prototype-extraction system that is distinct from explicit memory (Smith, 2008). In those studies, patients with explicit-memory impairments due to damage to the medial-temporal lobe performed normally in implicit categorization tasks (Bozoki, Grossman, & Smith, 2006; Knowlton & Squire, 1993). However, alternative interpretations are that (a) even people with impairments to a single memory system have sufficient resources to succeed on the particular categorization tasks that have been tested (Nosofsky & Zaki, 1998; Zaki & Nosofsky, 2001) and (b) working memory can be used at time of test to learn the categories (Palmeri & Flanery, 1999). In the present experiments, patients with amnestic mild cognitive impairment or early Alzheimer's disease were tested in prototype-extraction tasks to examine these possibilities. In a categorization task involving discrete-feature stimuli, the majority of subjects relied on memories for exceedingly few features, even when the task structure strongly encouraged reliance on broad-based prototypes. In a dot-pattern categorization task, even the memory-impaired patients were able to use working memory at time of test to extract the category structure (at least for the stimulus set used in past work). We argue that the results weaken the past case made in favor of a separate system of implicit prototype extraction.

Figure 1

Examples of the cartoon-animal stimuli used in Experiment 1. The animal at the top-left is a randomly chosen prototype stimulus. Its randomly chosen features would be the typical features for a given subject. The remaining stimuli in the figure show cartoon animals with decreasing numbers of features in common with the prototype. (Each animal is labeled in terms of the number of variable features that it has in common with the prototype.) Moving from left to right and then from the top to the bottom row, the features switched from their typical to their atypical value are: head direction, neck length, tail shape, feet shape, leg length, body markings, and body shape. The animal at the bottom right is the anti-prototype. In the present example, the feature values of ear shape and face type are held fixed across all animals. Those features might be variable features for another subject.

Figure 2

Experiment 1: Mean proportion of correct responses for each of the groups in the paired-comparison task. MCI = mild cognitive impairment; AD = Alzheimer’s disease.

Figure 3

Experiment 1: Mean proportion of correct choices for each of the groups plotted as a function of the feature-distance between the members in each pair. MCI = mild cognitive impairment; AD = Alzheimer’s disease.

Figure 4

Experiment 1: Predicted proportion of correct choices from the 2-weight EBA model plotted as a function of group and feature-distance between the members in each pair. EBA = elimination-by-aspect, MCI = mild cognitive impairment; AD = Alzheimer’s disease.

Figure 5

Experiment 2: Representative examples of the main stimulus types in the dot-pattern experiment. The top row provides examples from Dot Set 1 and the bottom row provides examples from Dot Set 2.

Figure 6

Experiment 2: Mean proportion of correct categorization decisions plotted as a function of group, training, and dot set. MCI = mild cognitive impairment; AD = Alzheimer’s disease.

Figure 7

Experiment 2: Mean proportion of category endorsements plotted as a function of group, training, dot set, and stimulus type. MCI = mild cognitive impairment; AD = Alzheimer’s disease. Proto = prototype, low = low distortion, high = high distortion.

Figure A3

Distribution of mean ratings on each of the three scales for the 25 dot sets. The ratings for Dot-Sets 1 and 2 are indicated by the vertical lines in each panel.