HyungGoo R. Kim

This study shows that mesolimbic dopamine activity encodes a unified temporal derivative form of value function across both reward and aversion in mice.

The paper develops a model integrating time and reward to explain foraging decisions and identifies frontal cortex ramping dynamics as a mechanism for solving patch foraging problems.

This paper shows that dopamine neurons in mice use multiple time scales to encode reward prediction errors, suggesting cell-specific temporal discounting and implications for reinforcement learning algorithms.

The paper shows how neural gain modulation propagates from posterior to anterior brain regions to optimize orientation perception in chronic astigmatism, with effects dependent on exposure duration.

The paper develops a normative framework to distinguish need and motivation in hypothalamic neurons using computational models and experimental paradigms, showing AgRP and LHLepR neurons encode need and motivation respectively.

This study identifies distinct roles of the orbitofrontal cortex, ventral striatum, and dopamine neurons in processing counterfactual outcomes during decision-making in monkeys.

The paper shows prior expectations modulate neural activity in the sensory cortex to improve sensorimotor behavior by sharpening population tuning and reducing variability in smooth pursuit eye movements.

The paper identifies a neural mechanism in macaque area MT that detects scene-relative object motion during self-motion by responding to incongruent depth tuning for motion parallax and binocular disparity cues.

This study shows that sensory feedback causes dopamine to ramp up before reward, challenging conventional models and supporting the reward prediction error hypothesis through experimental and theoretical analysis.

This study demonstrates that ramping dopamine signals correspond to reward prediction errors rather than state values, unifying rapid phasic and slow ramping signals as derivative-like computations.