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Gianaros, P. J.

Publications and source records attributed to Gianaros, P. J..

2 recordsLinked to original sources

D2 dopamine receptor expression, sensitivity to rewards, and reinforcement learning in a complex value-based decision-making task

In the basal ganglia, different dopamine subtypes have opposing dynamics at post-synaptic receptors, with the ratio of D1 to D2 receptors determining the relative sensitivity to gains and losses, respectively, during value-based learning. This effective sensitivity to reward feedback interacts with phasic dopamine levels to determine the effectiveness of learning, particularly in dynamic feedback situations where frequency and magnitude of rewards need to be integrated over time to make optimal decisions. Using both simulations and behavioral data in humans, we evaluated how reduced sensitivity to losses, relative to gains, leads to suboptimal learning in the Iowa Gambling Task (IGT), a complex value-learning task. In the behavioral data, we tested individuals with a variant of the human dopamine receptor D2 (DRD2; -141C Ins/Del and Del/Del) gene that associates with lower levels of D2 receptor expression (N=119) and compared their performance to non-carrier controls (N=319). The magnitude of the reward response was measured by looking at ventral striatal (VS) reactivity to rewards in the Cards task using fMRI. DRD2 variant carriers had generally lower performance in the IGT than non-carriers, consistent with reduced sensitivity to losses. There was also a positive association between VS reactivity and performance in the IGT, however, we found no statistically significant difference in this effect between DRD2 carriers and non-carriers. Thus, while reduced D2 receptor expression was associated with less efficient learning in the IGT, we did not find evidence for the moderation of this effect by the magnitude of the reward response.

neuroscience↗

Similarity in evoked responses does not imply similarity in macroscopic network states across tasks

There is an ongoing debate as to whether cognitive processes arise from a group of functionally specialized brain modules (modularism) or as the result of distributed nonlinear processes (dynamical systems theory). The former predicts that tasks recruiting similar local brain areas should be equally similar in their network profiles. The latter allows for differential connectivity, even when the areas recruited are largely the same. Here we evaluated both views at the macroscopic level by comparing region-wise activation patterns and functional correlation profiles from a large sample of healthy subjects (N=242) that performed two executive control tasks known to recruit nearly identical brain areas, the color-word Stroop task and the Multi-Source Interference Task (MSIT). Using a measure of instantaneous functional correlations, based on edge time series, we estimated the task-related networks that differed between incongruent and congruent conditions. At the group level, the two tasks were much more different in their network profiles than in their evoked activity patterns. This is found even when matching the degrees of freedom of both activation patterns and functional correlation profiles, when considering subject-level differences, after changing brain parcellations, and if employing alternative methods for defining task-related network profiles. Our results are consistent with the perspective of the brain as a dynamical system, suggesting that task representations should be independently evaluated at both node and edge (connectivity) levels. Significant StatementIf the brain is strictly modular at the macroscopic scale, then recruiting the same brain regions should result in the same functional interactions between regions. However, if the brain is a dynamical system, with information represented at both the node and edge levels, then two tasks could have the same pattern of activation, but largely different functional correlation profiles. Here we tested this contrastive prediction using two tasks with overlapping cognitive demands, but different sensory signals. Despite being nearly identical in their activation patterns, we found that the tasks produced largely different functional correlation profiles. These findings reinforce the view of the brain as a dynamical system, with task states represented both within and across regions.

neuroscience↗