Mild cognitive impairment in prediagnosed Huntington disease.

BACKGROUND: Cognitive decline has been reported in Huntington disease (HD), as well as in the period before diagnosis of motor symptoms (i.e., pre-HD). However, the severity, frequency, and characterization of cognitive difficulties have not been well-described. Applying similar cutoffs to those used in mild cognitive impairment (MCI) research, the current study examined the rates of subtle cognitive dysfunction (e.g., dysfunction that does not meet criteria for dementia) in pre-HD. METHODS: Using baseline data from 160 non-gene-expanded comparison participants, normative data were established for cognitive tests of episodic memory, processing speed, executive functioning, and visuospatial perception. Cutoff scores at 1.5 standard deviations below the mean of the comparison group were then applied to 575 gene-expanded pre-HD participants from the observational study, PREDICT-HD, who were stratified by motor signs and genetic risk for HD. RESULTS: Nearly 40% of pre-HD individuals met criteria for MCI, and individuals closer to HD diagnosis had higher rates of MCI. Nonamnestic MCI was more common than amnestic MCI. Single-domain MCI was more common than multiple-domain MCI. Within the nonamnestic single-domain subtype, impairments in processing speed were most frequent. CONCLUSIONS: Consistent with the Alzheimer disease literature, MCI as a prodromal period is a valid concept in pre-HD, with nearly 40% of individuals showing this level of impairment before diagnosis. Future studies should examine the utility of MCI as a marker of cognitive decline in pre-HD.

On the dominance of unidimensional rules in unsupervised categorization.

In several experiments, observers tried to categorize stimuli constructed from two separable stimulus dimensions in the absence of any trial-by-trial feedback. In all of the experiments, the observers were told the number of categories (i.e., two), they were told that perfect accuracy was possible, and they were given extensive experience in the task (i.e., 800 trials). When the boundary separating the contrasting categories was unidimensional, the accuracy of all observers improved significantly over blocks (i.e., learning occurred), and all observers eventually responded optimally. When the optimal boundary was diagonal, none of the observers responded optimally. Instead they all used some sort of suboptimal unidimensional rule. In a separate feedback experiment, all observers responded optimally in the diagonal condition. These results contrast with those for supervised category learning; they support the hypothesis that in the absence of feedback, people are constrained to use unidimensional rules.