scholarly journals Critical role for the mediodorsal thalamus in permitting rapid reward-guided updating in stochastic reward environments

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Subhojit Chakraborty ◽  
Nils Kolling ◽  
Mark E Walton ◽  
Anna S Mitchell

Adaptive decision-making uses information gained when exploring alternative options to decide whether to update the current choice strategy. Magnocellular mediodorsal thalamus (MDmc) supports adaptive decision-making, but its causal contribution is not well understood. Monkeys with excitotoxic MDmc damage were tested on probabilistic three-choice decision-making tasks. They could learn and track the changing values in object-reward associations, but they were severely impaired at updating choices after reversals in reward contingencies or when there were multiple options associated with reward. These deficits were not caused by perseveration or insensitivity to negative feedback though. Instead, monkeys with MDmc lesions exhibited an inability to use reward to promote choice repetition after switching to an alternative option due to a diminished influence of recent past choices and the last outcome to guide future behavior. Together, these data suggest MDmc allows for the rapid discovery and persistence with rewarding options, particularly in uncertain or changing environments.

2018 ◽  
Vol 49 (8) ◽  
pp. 1041-1054 ◽  
Author(s):  
Subhojit Chakraborty ◽  
Zakaria Ouhaz ◽  
Stuart Mason ◽  
Anna S. Mitchell

2009 ◽  
Vol 21 (7) ◽  
pp. 1332-1345 ◽  
Author(s):  
Thorsten Kahnt ◽  
Soyoung Q Park ◽  
Michael X Cohen ◽  
Anne Beck ◽  
Andreas Heinz ◽  
...  

It has been suggested that the target areas of dopaminergic midbrain neurons, the dorsal (DS) and ventral striatum (VS), are differently involved in reinforcement learning especially as actor and critic. Whereas the critic learns to predict rewards, the actor maintains action values to guide future decisions. The different midbrain connections to the DS and the VS seem to play a critical role in this functional distinction. Here, subjects performed a dynamic, reward-based decision-making task during fMRI acquisition. A computational model of reinforcement learning was used to estimate the different effects of positive and negative reinforcements on future decisions for each subject individually. We found that activity in both the DS and the VS correlated with reward prediction errors. Using functional connectivity, we show that the DS and the VS are differentially connected to different midbrain regions (possibly corresponding to the substantia nigra [SN] and the ventral tegmental area [VTA], respectively). However, only functional connectivity between the DS and the putative SN predicted the impact of different reinforcement types on future behavior. These results suggest that connections between the putative SN and the DS are critical for modulating action values in the DS according to both positive and negative reinforcements to guide future decision making.


2009 ◽  
Author(s):  
Robert J. Pleban ◽  
Jennifer S. Tucker ◽  
Vanessa Johnson Katie /Gunther ◽  
Thomas R. Graves

2000 ◽  
Vol 86 (1) ◽  
pp. 295-300 ◽  
Author(s):  
John E. Barbuto ◽  
Susan M. Fritz ◽  
David Marx

Relationships between motivation and transformational leadership were examined in this study. 56 leaders and 234 followers from a variety of organizations were sampled. Leaders were administered the Motivation Sources Inventory and the Job Choice Decision-making Exercise, while followers reported leaders' behaviors using the Multifactor Leadership Questionnaire (MLQ–rater version). Scores on the Motivation Sources Inventory subscales subsequently correlated with the Multifactor Leadership Questionnaire subscales of inspirational motivation, idealized influence (behavior), and individualized consideration (range, r = .13 to .23). There were no significant correlations among any of the Job Choice Decision-making Exercise subscales with any of the variables measured.


1997 ◽  
Vol 24 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Jennifer Gregan‐Paxton ◽  
Deborah Roedder John

2014 ◽  
Vol 40 (11) ◽  
pp. 825-833 ◽  
Author(s):  
Yiwei Chen ◽  
Jiaxi Wang ◽  
Robert M. Kirk ◽  
Olivia L. Pethtel ◽  
Allison E. Kiefner

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