Category: Neuroscience


A Distributed Neural Network of Choice Encoding During Effort-Based Decision Making

Saturday, November 18
10:15 AM - 11:45 AM
Location: Sapphire Ballroom M & N, Level 4, Sapphire Level

Keywords: Transdiagnostic | fMRI (Function Magnetic Resonance Imaging) | Translational Research
Presentation Type: Symposium

Reduced motivation and impaired effort-based decision-making are common in psychopathology, yet the underlying neural mechanisms remain unclear. Prior work suggests that effort-based decision-making relies on a distributed network comprised of ventral medial prefrontal cortex (vmPFC), cingulate cortex, striatum, anterior insula (AI), and supplementary motor area (SMA). To date, however, it is unknown, whether computations performed by these regions are involved in comparison of effort, reward, or their integration. Elucidation of these computations may enhance our understanding of their potential contribution to motivational deficits.

To this end, 29 healthy participants completed a novel sequential effort-based decision-making task while undergoing functional magnetic resonance imaging (fMRI). This design uniquely allows for the isolation of neural responses to effort or reward alone, as well as to their subsequent integration. A two-parameter power function was fitted to each subject to determine trial-wise subjective value (SV) estimates. Across all subjects, dACC, striatum, SMA, and AI were active during choice, supporting these regions’ roles in an effort-based choice network. Further, increasing SV selectively elicited activity in vmPFC (p < 0.05, cluster-corrected), while decreasing SV elicited activity in dACC. Interestingly, we observed the same cluster within dACC involved in various processes including encoding decreasing reward and increasing effort value signals separately, as well as encoding an integrated value signal and overall choice difficulty.

Taken together, these results demonstrate a spatially distributed network of areas that respond to separate elements of effort-based decision-making. Specifically, we observed that the same area of dACC encoded both value and choice signals over the course of our sequential trial design, highlighting this region as a potentially integral hub in this network. Our findings point to the dACC as region that may be critical in furthering our understanding of disrupted decision-making and motivation so often observed in psychiatric disorders. 

Amanda Arulpragasam

Graduate Student in Clinical Psychology
Emory University


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A Distributed Neural Network of Choice Encoding During Effort-Based Decision Making

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