From Animal Model to Human Brain Networking: Dynamic Causal Modeling of Motivational Systems

摘要

An organism's behavior is sensitive to different reinforcements in the environment. Based on extensive animal literature, the reinforcement sensitivity theory (RST) proposes three separate neurobehavioral systems to account for such context-sensitive behavior, affecting the tendency to react to punishment, reward, or goal-conflict stimuli. The translation of animal findings to complex human behavior, however, is far from obvious. To examine whether the neural networks underlying humans' motivational processes are similar to those proposed by the RST model, we conducted a functional MRI study, in which 24 healthy subjects performed an interactive game that engaged the different motivational systems using distinct time periods (states) of punishment, reward, and conflict. Crucially, we found that the different motivational states elicited activations in brain regions that corresponded exactly to the brain systems underlying RST. Moreover, dynamic causal modeling of each motivational system confirmed that the coupling strengths between the key brain regions of each system were enabled selectively by the appropriate motivational state. These results may shed light on the impairments that underlie psychopathologies associated with dysfunctional motivational processes and provide a translational validity for the RST.