In this talk I will propose Dynamic Causal Modelling as a 'mathematical microscope' that can provide regional, laminar, neurotransmitter and receptor specific assays of brain networks. In particular, I will examine the neuromodulatory chemical, Dopamine, in the context of healthy brain circuits and in Parkinson's disease. Understanding how Dopamine interacts with primary neurotransmitters in active brain networks is an important prerequisite for understanding pathological onset and progression. How this occurs and how brain connections change downstream of Dopamine loss is the focus of my results.

In particular, from a healthy human population, I will describe how DCM was used to link behavioural improvement under pro-dopaminergic (levodopa) modulation to changes in AMPA and NMDA mediated signalling in prefrontal regions. I will present data and a DCM of steady state responses analysis of Parkinsonian animal recordings that reveal changes in connectivity in basal ganglia-thalamo cortical circuits which exhibit enhanced beta oscillations. I will also show how this analysis is supported by a human patient population where pathological oscillations are linked to a similar connectivity profile.