Dopamine and SEEKING: Subcortical “Reward” Systems and Appetitive Urges

2015 ◽  
Author(s):  
Jaak Panksepp ◽  
Joseph Moskal
Keyword(s):  
Reward Systems

Why a Focus on Eminence is Misguided: A Call to Return to Basic Scientific Values

2017 ◽  
Author(s):  
Katherine S. Corker
Keyword(s):  
Scientific Method ◽  
Information Source ◽  
Current Paper ◽  
Human Cognition ◽  
Reward Systems ◽  
The Moon ◽  
Eradicate Polio ◽  
And Behavior

The scientific method has been used to eradicate polio, send humans to the moon, and enrich understanding of human cognition and behavior. It produced these accomplishments not through magic or appeals to authority, but through open, detailed, and reproducible methods. To call something “science” means there are clear ways to independently and empirically evaluate research claims. There is no need to simply trust an information source. Scientific values thus prioritize transparency and universalism, emphasizing that it matters less who has made a discovery than how it was done. Yet, scientific reward systems are based on identifying individual eminence. The current paper contrasts this focus on individual eminence with reforms to scientific rewards systems that help these systems better align with scientific values.

scholarly journals Champ versus Chump: Viewing an Opponent’s Face Engages Attention but Not Reward Systems

Games ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 62
Author(s):  
Ralph S. Redden ◽  
Greg A. Gagliardi ◽  
Chad C. Williams ◽  
Cameron D. Hassall ◽  
Olave E. Krigolson
Keyword(s):  
Reinforcement Learning ◽  
Chess Player ◽  
Reward Systems ◽  
The Third ◽  
Reward Positivity ◽  
Eeg Data ◽  
Attentional Engagement ◽  
Level Of Difficulty ◽  
Competitive Games ◽  
Reinforcement Model

When we play competitive games, the opponents that we face act as predictors of the outcome of the game. For instance, if you are an average chess player and you face a Grandmaster, you anticipate a loss. Framed in a reinforcement learning perspective, our opponents can be thought of as predictors of rewards and punishments. The present study investigates whether facing an opponent would be processed as a reward or punishment depending on the level of difficulty the opponent poses. Participants played Rock, Paper, Scissors against three computer opponents while electroencephalographic (EEG) data was recorded. In a key manipulation, one opponent (HARD) was programmed to win most often, another (EASY) was made to lose most often, and the third (AVERAGE) had equiprobable outcomes of wins, losses, and ties. Through practice, participants learned to anticipate the relative challenge of a game based on the opponent they were facing that round. An analysis of our EEG data revealed that winning outcomes elicited a reward positivity relative to losing outcomes. Interestingly, our analysis of the predictive cues (i.e., the opponents’ faces) demonstrated that attentional engagement (P3a) was contextually sensitive to anticipated game difficulty. As such, our results for the predictive cue are contrary to what one might expect for a reinforcement model associated with predicted reward, but rather demonstrate that the neural response to the predictive cue was encoding the level of engagement with the opponent as opposed to value relative to the anticipated outcome.

Why Don't Public Administrators Take Productivity More Seriously?

1974 ◽  
Vol 3 (4) ◽  
pp. 318-324 ◽  
Author(s):  
Walter L. Balk
Keyword(s):  
Political Institutions ◽  
Reward Systems ◽  
Public Administrators ◽  
The Public ◽  
Low Level

“Until government managers, employees, legislators and the public become intensely involved in the processes of controls, reward systems and political institutions, motivation is liable to remain at a low level.”

scholarly journals Role of gut nutrient sensing in stimulating appetite and conditioning food preferences

2012 ◽  
Vol 302 (10) ◽  
pp. R1119-R1133 ◽  
Author(s):  
Anthony Sclafani ◽  
Karen Ackroff
Keyword(s):  
Food Preferences ◽  
Nutrient Utilization ◽  
Nutrient Sensing ◽  
Vagal Afferents ◽  
Preference Learning ◽  
Flavor Preference ◽  
Reward Systems ◽  
Additional Function ◽  
Umami Taste ◽  
Flavor Preference Conditioning

The discovery of taste and nutrient receptors (chemosensors) in the gut has led to intensive research on their functions. Whereas oral sugar, fat, and umami taste receptors stimulate nutrient appetite, these and other chemosensors in the gut have been linked to digestive, metabolic, and satiating effects that influence nutrient utilization and inhibit appetite. Gut chemosensors may have an additional function as well: to provide positive feedback signals that condition food preferences and stimulate appetite. The postoral stimulatory actions of nutrients are documented by flavor preference conditioning and appetite stimulation produced by gastric and intestinal infusions of carbohydrate, fat, and protein. Recent findings suggest an upper intestinal site of action, although postabsorptive nutrient actions may contribute to flavor preference learning. The gut chemosensors that generate nutrient conditioning signals remain to be identified; some have been excluded, including sweet (T1R3) and fatty acid (CD36) sensors. The gut-brain signaling pathways (neural, hormonal) are incompletely understood, although vagal afferents are implicated in glutamate conditioning but not carbohydrate or fat conditioning. Brain dopamine reward systems are involved in postoral carbohydrate and fat conditioning but less is known about the reward systems mediating protein/glutamate conditioning. Continued research on the postoral stimulatory actions of nutrients may enhance our understanding of human food preference learning.

The effects of reward system on bank credit losses – an agent-based model

2015 ◽  
Vol 41 (9) ◽  
pp. 908-924
Author(s):  
Sara Jonsson
Keyword(s):  
Reward System ◽  
Bank Credit ◽  
Reward Systems ◽  
Risk Modeling ◽  
Agent Based Model ◽  
Credit Risk Management ◽  
Content Type ◽  
Agent Based ◽  
Loan Officer ◽  
Credit Losses

Purpose – The purpose of this paper is to investigate how the design of loan officer reward systems affects bank credit losses caused by commercial clients. Design/methodology/approach – This paper uses an agent-based model to investigate how the design of reward systems affects bank credit losses. Two different systems are compared: competitive and a cooperative. The model is designed according to the theoretically derived assumption that a cooperative reward system will make agents more likely to share knowledge with each other in the processes of granting and monitoring credit. Findings – The results show that a cooperative reward system have potential to reduce bank credit losses. The reduction of errors in evaluating company’s probability of default thus mitigates variations induced by variations in industry, region, and firm-specific returns. Practical implications – The findings imply that reward system design should be considered in credit risk management. Further, managerial issues (e.g. reward systems) should be considered in risk modeling. Originality/value – The results presented in this paper provide evidence to the value of considering the downside (e.g. loss) when designing reward systems in banks.

High Performance Teams

2016 ◽  
Vol 7 (2) ◽  
pp. 72-82 ◽  
Author(s):  
Caroline Dominguez ◽  
Isabel C. Moura ◽  
João Varajão
Keyword(s):  
High Performance ◽  
Business Environment ◽  
Reward Systems ◽  
Team Management ◽  
Key Factors ◽  
Team Members ◽  
High Performing ◽  
Exploratory Case Study ◽  
Performance Teams

Effective team management is one of the key factors that allow companies to tackle the challenges of today's demanding business environment. Although high-performing teams have been studied for some time, very little has been written on them from the construction industry's perspective. Based on the conclusions of previous work and on a project involving 44 professionals of seven teams, this exploratory case study intends to evaluate if there is a gap between what team members and leaders perceive as being (a) the most important features for managing teams into high performance and (b) the features that are present in their teams. The present study shows that, although teams under investigation had some high-performing features at the leadership dimension, there is room for improvement, in particular when it comes to empowering team members, involving them in planning the work, and creating proper reward systems.

Reward Systems

Level Design ◽  
2009 ◽  
pp. 113-154
Keyword(s):  
Reward Systems
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