Investigating reward systems in the human midbrain with fMRI

Abstract

Localising activity in the human midbrain with conventional functional MRI (fMRI) is challenging because the midbrain nuclei are small and located in an area that is prone to physiological artefacts. In the first section of this thesis I present a replicable and automated method to improve the detection and localisation of midbrain fMRI signals. I designed a visual fMRI task that was predicted would activate the superior colliculi bilaterally. A novel anatomical registration pathway was used to optimise the localisation of the small midbrain nuclei in stereotactic space. This pathway was compared to conventional registration pathways, and was shown to significantly improve midbrain registration. To reduce the physiological artefacts in the functional data, I estimated and removed structured noise using a modified version of a previously described physiological noise model (PNM). Whereas a conventional analysis revealed only unilateral colliculi activity, the PNM analysis revealed the predicted bilateral activity. I then used these methods to investigate the role of the midbrain dopaminergic system in reward. Midbrain dopamine neurons play central roles in positive reward prediction errors (PEs). Non-human studies now indicate that dopamine neurons also code for aversive, punishing events, and may code negative PEs. However, our understanding of how such events are coded in the human dopaminergic midbrain is limited, and has been hindered by the technical challenge of using fMRI in this region. Here I show that during a financial reward and punishment task the ventral tegmental area (VTA) codes for both positive and negative PEs. The fMRI data from the midbrain contained a significant amount of physiological noise, but once I applied the PNM responses were also observed in the substantia nigra pars compacta (SNc), with negative PE signals extending more laterally. These findings indicate that both the human VTA and SNc code for both positive and negative PEs.