TY - GEN
T1 - Cost, benefit, tonic, phasic
T2 - What do response rates tell us about dopamine and motivation?
AU - Niv, Yael
PY - 2007/7
Y1 - 2007/7
N2 - The role of dopamine in decision making has received much attention from both the experimental and computational communities. However, because reinforcement learning models concentrate on discrete action selection and on phasic dopamine signals, they are silent as to how animals decide upon the rate of their actions, and they fail to account for the prominent effects of dopamine on response rates. We suggest an extension to reinforcement learning models in which response rates are optimally determined by balancing the tradeoff between the cost of fast responding and the benefit of rapid reward acquisition. The resulting behavior conforms well with numerous characteristics of free-operant responding. More importantly, this framework highlights a role for a tonic signal corresponding to the net rate of rewards, in determining the optimal rate of responding. We hypothesize that this critical quantity is conveyed by tonic levels of dopamine, explaining why dopaminergic manipulations exert a global affect on response rates. We further suggest that the effects of motivation on instrumental rates of responding are mediated through its influence on the net reward rate, implying a tight coupling between motivational states and tonic dopamine. The relationships between phasic and tonic dopamine signaling, and between directing and energizing effects of motivation, as well as the implications for motivational control of habitual and goal-directed instrumental action selection, are discussed.
AB - The role of dopamine in decision making has received much attention from both the experimental and computational communities. However, because reinforcement learning models concentrate on discrete action selection and on phasic dopamine signals, they are silent as to how animals decide upon the rate of their actions, and they fail to account for the prominent effects of dopamine on response rates. We suggest an extension to reinforcement learning models in which response rates are optimally determined by balancing the tradeoff between the cost of fast responding and the benefit of rapid reward acquisition. The resulting behavior conforms well with numerous characteristics of free-operant responding. More importantly, this framework highlights a role for a tonic signal corresponding to the net rate of rewards, in determining the optimal rate of responding. We hypothesize that this critical quantity is conveyed by tonic levels of dopamine, explaining why dopaminergic manipulations exert a global affect on response rates. We further suggest that the effects of motivation on instrumental rates of responding are mediated through its influence on the net reward rate, implying a tight coupling between motivational states and tonic dopamine. The relationships between phasic and tonic dopamine signaling, and between directing and energizing effects of motivation, as well as the implications for motivational control of habitual and goal-directed instrumental action selection, are discussed.
KW - Cost/benefit
KW - Energizing
KW - Free operant
KW - Generalized drive
KW - Motivation
KW - Phasic dopamine
KW - Reinforcement learning
KW - Response rate
KW - Tonic dopamine
UR - http://www.scopus.com/inward/record.url?scp=34447641086&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34447641086&partnerID=8YFLogxK
U2 - 10.1196/annals.1390.018
DO - 10.1196/annals.1390.018
M3 - Conference contribution
C2 - 17416928
AN - SCOPUS:34447641086
SN - 1573316741
SN - 9781573316743
T3 - Annals of the New York Academy of Sciences
SP - 357
EP - 376
BT - Reward and Decision Making in Corticobasal Ganglia Networks
PB - Blackwell Publishing Inc.
ER -