NEURAL DYNAMICS OF SHORT AND MEDIUM-TERM MOTOR CONTROL EFFECTS OF LEVODOPA THERAPY IN PARKINSONS-DISEASE

A neural network model of movement control in normal and Parkinson's d isease (PD) conditions is proposed to simulate the time-varying dose-r esponse relationship underlying the effects of levodopa on movement am plitude and movement duration in PD patients. Short and long-term dyna mics of cell activations and neurotransmitter mechanisms underlying th e differential expression of neuropeptide messenger RNA within the bas al ganglia striatum are modeled to provide a mechanistic account for t he effects of levodopa medication on motor performance (e.g. the pharm acodynamics). Experimental and neural network simulation data suggest that levodopa therapy in Parkinson's disease has differential effects on cell activities, striatal neuropeptides, and motor behavior. In par ticular, it is shown how dopamine depletion in the striatum may modula te differentially the level of substance P and enkephalin messenger RN A in the direct and indirect basal ganglia pathways. This dissociation in the magnitude and timing of peptide expression causes an imbalance in the opponently organized basal ganglia pathways which results in P arkinsonian motor deficits. The model is validated with experimental d ata obtained from handwriting movements performed by PD subjects befor e and after medication intake. The results suggest that fine motor con trol analysis and network modeling of the effects of dopamine in motor control are useful tools in drug development and in the optimization of pharmacological therapy in PD patients, (C) 1998 Elsevier Science B .V, All rights reserved.