Neural Basis of Decision-Making Deficits in Traumatic Brain Injury

Study Description: Deficits in decision-making are commonly found in individuals after traumatic brain injury (TBI) and can have a severe negative impact on quality of life. Converging evidence from both animal model and human studies suggest that decision-making deficits are linked with abnormal mesocorticolimbic network structure and function, and could potentially be mitigated through interventions that improve function within these neuronal circuits. Objectives: 1. Quantify differences in performance on a decision-making task between TBI patients and healthy volunteers; 2. Determine whether baseline features of mesocorticolimbic network structure and function predict subsequent decision-making performance in both TBI patients and healthy volunteers; and 3. Determine if facilitatory transcranial direct current stimulation (tDCS) applied over the dorsolateral prefrontal cortex (dlPFC), a mesocorticolimbic network region crucially involved in decision-making, improves decision-making after TBI. Endpoints: Primary Endpoint: The primary outcome measure for both Experiment 1 and 2 is performance in a computerized decision-making task. Secondary Endpoints: Secondary outcome measures will include quantitative estimates of structural and functional mesocorticolimbic network features, including MRI-based structural and functional connectivity, MEG-based functional connectivity, baseline dlPFC GABA concentration measured with magnetic resonance spectroscopy (MRS) imaging, dopamine D2 receptor binding potential within mesocorticolimbic subcortical nuclei measured with \[11C\]raclopride PET (Experiment 1). Multimodal data fusion modeling will be used to explore the predictive relationship between baseline mesocorticolimbic network features and decision-making task performance within a unified state-space framework (Experiment 1), as well as the ability of these network features to predict inter-individual differences in the effects of tDCS on decision-making task performance (Experiment 2).