Spontaneous eye blink rate (sEBR) has been linked to striatal dopamine function and to how individuals make value-based choices after a period of reinforcement learning (RL). While sEBR is thought to reflect how individuals learn from the negative outcomes of their choices, this idea has not been tested explicitly. This study assessed how individual differences in sEBR relate to learning by focusing on the cognitive processes that drive RL. Using Bayesian latent mixture modelling to quantify the mapping between RL behaviour and its underlying cognitive processes, we were able to differentiate low and high sEBR individuals at the level of these cognitive processes. Further inspection of these cognitive processes indicated that sEBR uniquely ...
What are the neural dynamics of choice processes during reinforcement learning? Two largely separate...
Slow-timescale (tonic) changes in dopamine (DA) contribute to a wide variety of processes in reinfor...
Sequential sampling decision-making models have been successful in accounting for reaction time (RT)...
The pupil response under constant illumination can be used as a marker of cognitive processes. In th...
Cognition can reveal itself in the pupil, as latent cognitive processes map onto specific pupil resp...
Cognition can reveal itself in the pupil, as latent cognitive processes map onto specific pupil resp...
Although sequential learning and spontaneous eyeblink rate (EBR) have both been shown to be tightly ...
Recent research has shown that perceptual processing of stimuli previously associated with high-valu...
Impulsivity is defined as a trait-like tendency to engage in rash actions that are poorly thought ou...
The computational framework of reinforcement learning has been used to forward our understanding of ...
Item does not contain fulltextAlthough the existence of 'choking under pressure' is well-supported b...
In reinforcement learning (RL), an agent makes sequential decisions to maximise the reward it can ob...
Reinforcement learning (RL) in simple instrumental tasks is usually modeled as a monolithic process ...
The ventral striatum displays hyper-responsiveness to reward in adolescents relative to other age gr...
Alterations in reward processing are associated with various mental disorders. However, it is an ope...
What are the neural dynamics of choice processes during reinforcement learning? Two largely separate...
Slow-timescale (tonic) changes in dopamine (DA) contribute to a wide variety of processes in reinfor...
Sequential sampling decision-making models have been successful in accounting for reaction time (RT)...
The pupil response under constant illumination can be used as a marker of cognitive processes. In th...
Cognition can reveal itself in the pupil, as latent cognitive processes map onto specific pupil resp...
Cognition can reveal itself in the pupil, as latent cognitive processes map onto specific pupil resp...
Although sequential learning and spontaneous eyeblink rate (EBR) have both been shown to be tightly ...
Recent research has shown that perceptual processing of stimuli previously associated with high-valu...
Impulsivity is defined as a trait-like tendency to engage in rash actions that are poorly thought ou...
The computational framework of reinforcement learning has been used to forward our understanding of ...
Item does not contain fulltextAlthough the existence of 'choking under pressure' is well-supported b...
In reinforcement learning (RL), an agent makes sequential decisions to maximise the reward it can ob...
Reinforcement learning (RL) in simple instrumental tasks is usually modeled as a monolithic process ...
The ventral striatum displays hyper-responsiveness to reward in adolescents relative to other age gr...
Alterations in reward processing are associated with various mental disorders. However, it is an ope...
What are the neural dynamics of choice processes during reinforcement learning? Two largely separate...
Slow-timescale (tonic) changes in dopamine (DA) contribute to a wide variety of processes in reinfor...
Sequential sampling decision-making models have been successful in accounting for reaction time (RT)...