Posterior Cingulate

Psychotic symptoms frequently occur in Parkinson’s disease, but their pathophysiology is poorly understood. According to the National Institute of Health RDoc programme, the pathophysiological basis of neuropsychiatric symptoms may be better understood in terms of dysfunction of underlying domains of neurocognition in a transdiagnostic fashion. Abnormal cortico-striatal reward processing has been proposed as a key domain contributing to the pathogenesis of psychotic symptoms in schizophrenia. This theory has received empirical support in the study of schizophrenia spectrum disorders and preclinical models of psychosis, but has not been tested in the psychosis associated Parkinson’s disease. We therefore investigated brain responses associated with reward expectation and prediction error signalling during reinforcement learning in Parkinson’s disease associated psychosis. An instrumental learning task with monetary gains and losses was conducted during an fMRI study in patients with Parkinson’s disease with (n=12), or without (n=17), a history of psychotic symptoms, along with a sample of healthy controls (n=24). We conducted region of interest analyses in the ventral striatum, ventromedial prefrontal and posterior cingulate cortices, and whole-brain analyses. There was reduced activation in Parkinson’s disease patients with a history of psychosis compared to those without in the posterior cingulate cortex and the ventral striatum during reward anticipation (p<0.05 small volume corrected). The results suggest that cortical and striatal abnormalities in reward processing, a putative pathophysiological mechanism of psychosis in schizophrenia, may also contribute to the pathogenesis of psychotic symptoms in Parkinson’s disease. The finding of posterior cingulate dysfunction is in keeping with prior results highlighting cortical dysfunction in the pathogenesis of Parkinson’s disease psychosis.

As different areas within the PMC have different connectivity patterns with various cortical and subcortical regions, we
hypothesized that distinct functional modules may be present within the PMC. Because the PMC appears to be the most
active region during resting state, it has been postulated to play a fundamental role in the control of baseline brain
functioning within the default mode network (DMN). Therefore one goal of this study was to explore which components of
the PMC are specifically involved in the DMN. In a sample of seventeen healthy volunteers, we performed an unsupervised
voxelwise ROI-based clustering based on resting state functional connectivity. Our results showed four clusters with
different network connectivity. Each cluster showed positive and negative correlations with cortical regions involved in the
DMN. Progressive shifts in PMC functional connectivity emerged from anterior to posterior and from dorsal to ventral ROIs.
Ventral posterior portions of PMC were found to be part of a network implicated in the visuo-spatial guidance of
movements, whereas dorsal anterior portions of PMC were interlinked with areas involved in attentional control. Ventral
retrosplenial PMC selectively correlated with a network showing considerable overlap with the DMN, indicating that it
makes essential contributions in self-referential processing, including autobiographical memory processing. Finally, ventral
posterior PMC was shown to be functionally connected with a visual network. The paper represents the first attempt to
provide a systematic, unsupervised, voxelwise clustering of the human posteromedial cortex (PMC), using resting-state
functional connectivity data. Moreover, a ROI-based parcellation was used to confirm the results.