Deniz Tuzsus

This study investigates how dopamine levels affect exploration-exploitation behavior in humans, finding that cognitive capacity and sex moderate L-DOPA effects on decision-making.

This study examines how RNN capacity affects exploration strategies in reinforcement learning, finding that higher capacity networks exhibit more human-like strategies but still differ in perseveration and switch rates.

The paper re-examines the pharmacological effects of L-DOPA on temporal discounting in a large sample and evaluates proxy measures for dopamine, finding a reliable reduction in discount rate with no credible effects from proxy measures.

This study investigates whether dopamine manipulation affects illusory pattern perception in healthy individuals, finding no significant effect of L-DOPA on false alarm rates or other measures.

This study compares human and recurrent neural network performance in restless bandit tasks, finding human-level RNN performance and distinct exploration strategies.

The paper shows that recurrent neural networks trained with medium or meta-volatility regimes adapt better to environmental volatility than those trained in low volatility.

The paper examines how erotic cues affect physiological arousal, reward discounting, and model-based reinforcement learning in healthy males.

The paper evaluates parameter and model recovery of the Kalman SMEP reinforcement learning model in restless bandit tasks using simulation and Bayesian inference.