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Occupational lead neurotoxicity: A behavioural and electrophysiological evaluation. study design and year one results.

To evaluate the effects of chronic lead exposure on the nervous system in adults, a set of neurobehavioural and electrophysiological tests was administered to 99 lead exposed foundry employees and 61 unexposed workers. Current and past blood lead concentrations were used to estimate the degree of lead absorption; all previous blood lead concentrations had been less than or equal to 90 micrograms/100 ml. Characteristic signs (such as wrist extensor weakness) or symptoms (such as colic) of lead poisoning were not seen. Sensory conduction in the sural nerve was not affected. By contrast, various neurobehavioural functions deteriorated with increasing lead burden. Workers with blood lead concentrations between 40 and 60 micrograms/100 ml showed impaired performance on tests of verbal concept formation, visual/motor performance, memory, and mood. Thus impairment in central nervous system function in lead exposed adults occurred in the absence of peripheral nervous system derangement and increased in severity with increasing lead dose.

Occupational lead neurotoxicity: Improvement in behavioural effects after reduction of exposure.

To evaluate critical exposure levels and the reversibility of lead neurotoxicity a group of lead exposed foundry workers and an unexposed reference population were followed up for three years. During this period, tests designed to monitor neurobehavioural function and lead dose were administered. Evaluations of 160 workers during the first year showed dose dependent decrements in mood, visual/motor performance, memory, and verbal concept formation. Subsequently, an improvement in the hygienic conditions at the plant resulted in striking reductions in blood lead concentrations over the following two years. Attendant improvement in indices of tension (20% reduction), anger (18%), depression (26%), fatigue (27%), and confusion (13%) was observed. Performance on neurobehavioural testing generally correlated best with integrated dose estimates derived from blood lead concentrations measured periodically over the study period; zinc protoporphyrin levels were less well correlated with function. This investigation confirms the importance of compliance with workplace standards designed to lower exposures to ensure that individual blood lead concentrations remain below 50 micrograms/dl.

Fuzzy ARTMAP: A Neural Network Architecture for Incremental Supervised Learning of Analog Multidimensional Maps

A new neural network architecture is introduced for incremental supervised learning of recognition categories and multidimensional maps in response to arbitrary sequences of analog or binary input vectors. The architecture, called Fuzzy ARTMAP, achieves a synthesis of fuzzy logic and Adaptive Resonance Theory (ART) neural networks by exploiting a close formal similarity between the computations of fuzzy subsethood and ART category choice, resonance, and learning. Fuzzy ARTMAP also realizes a new Minimax Learning Rule that conjointly minimizes predictive error and maximizes code compression, or generalization. This is achieved by a match tracking process that increases the ART vigilance parameter by the minimum amount needed to correct a predictive error. As a result, the system automatically learns a minimal number of recognition categories, or "hidden units", to met accuracy criteria. Category proliferation is prevented by normalizing input vectors at a preprocessing stage. A normalization procedure called complement coding leads to a symmetric theory in which the MIN operator (Λ) and the MAX operator (v) of fuzzy logic play complementary roles. Complement coding uses on-cells and off-cells to represent the input pattern, and preserves individual feature amplitudes while normalizing the total on-cell/off-cell vector. Learning is stable because all adaptive weights can only decrease in time. Decreasing weights correspond to increasing sizes of category "boxes". Smaller vigilance values lead to larger category boxes. Improved prediction is achieved by training the system several times using different orderings of the input set. This voting strategy can also be used to assign probability estimates to competing predictions given small, noisy, or incomplete training sets. Four classes of simulations illustrate Fuzzy ARTMAP performance as compared to benchmark back propagation and genetic algorithm systems. These simulations include (i) finding points inside vs. outside a circle; (ii) learning to tell two spirals apart; (iii) incremental approximation of a piecewise continuous function; and (iv) a letter recognition database. The Fuzzy ARTMAP system is also compared to Salzberg's NGE system and to Simpson's FMMC system.