Multiple sclerosis (MS) is a disease of the central nervous system where roughly 50% of patients exhibit cognitive impairment. Episodic memory defects are particularly common in MS and the California Verbal Learning Test: 2nd Edition (CVLT-II) was recommended for assessment in MS in a recently published consensus position paper. We investigated the validity of the CVLT-II in 351 MS patients and 69 demographically matched normal controls. MS patients performed significantly more poorly on 18 of the 23 measures examined. In addition to a general memory factor, factor analysis revealed five distinct factors conforming to measures of consolidation, primary/recency effect, proactive interference, and learning asymptote. The external validity of the CVLT-II was also supported by logistic regression analysis, which separated employed from work-disabled MS patients. We conclude that the CVLT-II is a valid test in MS and provides a rich constellation of verbal memory measures.

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Very few attempts have been made to apply a mathematical model to the learning curve in the California Verbal Learning Test list A immediate recall. Our rationale was to find out whether modeling of the learning curve can add additional information to the standard CVLT [corrected] measures. We applied a standard transfer function in the form Y = B3*exp(-B2*(X-1))+B4*(1-exp(-B2*(X-1))), where X is the trial number; Y is the number of recalled correct words, B2 is the learning rate, B3 is readiness to learn and B4 is ability to learn. The coefficients of the model were found to be independent measures not duplicating standard CVLT [corrected] measures. Regression analysis revealed that readiness to learn (B3) and ability to learn (B4) were significantly (p < .05) higher in a group of healthy participants than in a group of participants with type 2 diabetes mellitus (T2DM), but the learning rate (B2) did not differ (p > .2). The proposed model is appropriate for clinical application and as a guide for research and may be used as a good supplemental tool for the CVLT [corrected] and similar memory tests.

A mathematical model is proposed to measure the learning curve in the California Verbal Learning Test-Children's Version. The model is based on the first-order system transfer function in the form Y = B3*exp[-B2*(X-1)]+B4*{1-exp[-B2*(X-1)]}, where X is the trial number, Y is the number of recalled correct words, B2 is the learning rate, B3 is interpreted as readiness to learn and B4 as the ability to learn. Children's readiness to learn and ability to learn were lower than adults. Modeling revealed that girls had greater readiness to learn and ability to learn than boys.

This paper describes a mathematical model of the learning process suitable for studies of conditioning using the proboscis extension reflex (PER) in honey bees when bees are exposed to agrochemicals. Although procedural variations exist in the way laboratories use the PER paradigm, proboscis conditioning is widely used to investigate the influence of pesticides and repellents on honey bee learning. Despite the availability of several mathematical models of the learning process, no attempts have been made to apply a mathematical model to the learning curve in honey bees exposed to agrochemicals. Our model is based on the standard transfer function in the form Y = B3e−B2 (X−1) + B4 (1−e−B2 (X−1)) where X is the trial number, Y is the proportion of correct responses, B2 is the learning rate, B3 is readiness to learn, and B4 is ability to learn. We reanalyze previously published data on the effect of several classes of agrochemicals including: (1) those that are considered harmless to bees (e.g., pymetrozine, essential oils, dicofol); (2) sublethal exposure to pesticides known to harm honey bees (e.g., coumaphos, cyfluthrin, fluvalinate, permethrin); and (3) putative repellents of honey bees (e.g., butyric acid, citronella). The model revealed additional effects not detected with standard statistical tests of significance.