Abstract
Neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNC) play central roles in reward‐related behaviours. Nonhuman animal studies suggest that these neurons also process aversive events. However, our understanding of how the human VTA and SNC responds to such events is limited and has been hindered by the technical challenge of using functional magnetic resonance imaging (fMRI) to investigate a small structure where the signal is particularly vulnerable to physiological noise. Here we show, using methods optimized specifically for the midbrain (including high‐resolution imaging, a novel registration protocol, and physiological noise modelling), a BOLD (blood‐oxygen‐level dependent) signal to both financial gain and loss in the VTA and SNC, along with a response to nil outcomes that are better or worse than expected in the VTA. Taken together, these findings suggest that the human VTA and SNC are involved in the processing of both appetitive and aversive financial outcomes in humans.
Highlights
Neurons of the ventral tegmental area (VTA) and substantia nigra pars compacta (SNC) play central roles in processing appetitive and aversive stimuli (Fields, Hjelmstad, Margolis, & Nicola, 2007; Morales & Margolis, 2017)
To explore the nil outcomes further, we conducted a region of interest (ROI) analysis to extract blood-oxygen-level dependent (BOLD) signal change values from within the significant clusters revealed by the “Gain” and “Loss” contrasts
We were able to observe a BOLD signal in the VTA and SNC associated with both financial gains and losses
Summary
Neurons of the ventral tegmental area (VTA) and substantia nigra pars compacta (SNC) play central roles in processing appetitive and aversive stimuli (Fields, Hjelmstad, Margolis, & Nicola, 2007; Morales & Margolis, 2017). Several fMRI investigations in the human have examined processing of appetitive and aversive stimuli in regions that receive dopaminergic inputs, including the striatum (Brooks & Berns, 2013; Delgado, Jou, & Phelps, 2011; Seymour, Daw, Dayan, Singer, & Dolan, 2007), but much less is known about the VTA and SNC This is largely due to technical difficulties associated with measuring a blood-oxygen-level dependent (BOLD) signal, the indirect measure of neural activity used by fMRI, in the midbrain (Düzel et al, 2009, 2015). D’Ardenne, McClure, Nystrom, and Cohen (2008), used cardiac gating (to reduce the influence of physiological noise), high-resolution data acquisition, and smoothed the data with a Gaussian filter with a small radius (to reduce partial volume effects) They observed an outcome reward-related prediction error response in the VTA (changes in the SNC were not reported). We used high-resolution imaging and a novel registration approach that we have previously optimized for use in the midbrain (Limbrick-Oldfield et al, 2012) combined with PNM (physiological noise model), which is a brainstem- optimized variant of RETROICOR (Harvey et al, 2008), to control for physiological noise
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