Mathematical Models: Interactions Between Serotonin and Dopamine in Parkinson's Disease
Parkinson's disease (PD) has traditionally been thought of as a dysfunction in the dopamine (DA) signaling system caused primarily by cell death in the substantia nigra pars compacta (SNc) However, strong evidence has been accumulating that the serotonin (5 HT) signaling system is also involved. First, 5 HT influences normal motor function through a dense innervation of the striatum. Second, substantial cell death of serotonergic neurons occurs in PD and in some cases may occur earlier than DA cell death. And, finally, there are indications that interactions between the 5 HT system and the DA system may be responsible for some of the symptoms of PD and some of the side effects of treatment by levodopa. Some of the evidence for these assertions is reviewed below. The 5 HT system is itself very complex. The serotonergic neurons in the raphe nuclei (RN) send ascending projections to a large number of different brain regions including medial prefrontal cortex (mPFC) motor cortex, hypothalamus, hippocampus, amygdala, and the basal ganglia. And, some of these brain regions, substantia nigra, amygdala, mPFC, and hypothalamus send projections back to the RN (Monti, 2010) Thus it is not surprising that 5 HT is linked to so many behaviors including feeding and body weight regulation, social hierarchies, aggression and suicidality, obsessive compulsive disorder, alcoholism, anxiety, and affective disorders (Feldman et al. 1997) Since the pharmacology and the electrophysiology of both the serotonergic and the dopaminergic systems are only partially understood, it is a daunting task to understand how these two systems affect one another. This is particularly true in the presence of a degenerative disease that involves massive cell death in both systems. In this complicated situation, mathematical models can potentially provide insight into mechanisms and interactions. The purpose of the models is not to summarize what is already known. The purpose is to provide a platform for in silico biological experimentation. Using models one can try out ideas, validate or refute hypotheses, settle disputes in the literature, and sometimes discover new phenomena. Of course, to be useful the models have to be well grounded in real physiology and the creation of such models is not easy. However, if one 18