Abstract Background Striatal dopamine dysfunction is proposed to underlie symptoms in psychosis, yet it is not known how changes in a single neurotransmitter could underlie the heterogenous presentations that are… Click to show full abstract
Abstract Background Striatal dopamine dysfunction is proposed to underlie symptoms in psychosis, yet it is not known how changes in a single neurotransmitter could underlie the heterogenous presentations that are seen clinically. One hypothesis is that the symptomatic consequences of aberrant dopamine signalling may depend on where within the striatum dysfunction occurs. Positron emission tomography (PET) allows for the measurement of dopamine function across the striatum. However, when using typical atlas-based parcellation methods, the collinearity between measures of dopamine function within each striatal subdivision precludes investigation of this hypothesis. Methods We use a novel and data-driven parcellation method to address the above, and investigate relationships between spatial variability in dopamine synthesis capacity and psychotic symptoms. We employ a multimodal imaging approach combining 18F-DOPA PET and resting state MRI in 29 unmedicated and minimally-treated patients with first episode psychosis and 21 healthy controls. In each participant, we use resting state functional connectivity maps to quantify the functional connectivity of each striatal voxel to cortical networks. Network-specific striatal dopamine synthesis capacity (Kicer) was calculated for the resulting connectivity defined parcellations. Results Connectivity defined parcellations generated Kicer values with equivalent reliability, and significantly greater orthogonality to standard anatomical parcellation methods. Dopamine function within striatal areas connected to the default mode network is strongly associated with negative symptoms (p<0.001). Discussion These findings suggest that individual differences in the topography of striatal dopamine dysfunction contribute to shaping psychotic symptomatology.
               
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