Sang Wan Lee

ssJSD improves scHiC clustering by integrating spatial interaction patterns and sparsity patterns to better distinguish cell types.

The paper shows that coupled spiking populations with distinct inhibitory timescales generate multi-frequency bursts that self-organize into patterns associated with specific information routing.

The paper shows that an optimal inhibitory-to-excitatory synaptic strength ratio enables both slow (beta) and fast (gamma) neural oscillations, enhancing communication efficiency and information capacity.

This paper introduces a computational theory called topology-aware grid coding (TAG) that enables rapid generalization of spatial navigation in environments with the same topological structure but different geometries.

This study identifies the distinct roles of ProtoGPe[->]STN neurons and astrocytes in regulating flexible reward-seeking behaviors through contextual encoding and adaptive responses.

The paper tests the hypothesis that phasic and tonic pain serve distinct functions in adaptive behavior using a virtual reality foraging task with EEG measurements.

This paper designs tasks to predict human prediction error, generating subject-independent tasks that modulate behavior and neural activity in reward learning.

This study shows that the Pavlovian fear system enables flexible and efficient exploratory decision-making by balancing safety and efficiency through uncertainty-based avoidance.

The paper describes how the brain resolves the bias-variance tradeoff during reinforcement learning through adaptive control of model-based and model-free learning, supported by behavioral, computational, and neural evidence.

This paper introduces a novel reinforcement learning model inspired by hippocampal and prefrontal cortex mechanisms, showing improved performance in uncertain environments.

The paper shows macaque monkeys use time-compressed forward replay during temporal-order judgment tasks, but lack the ability to globally compress irrelevant information.

The paper investigates how task complexity and state-space uncertainty influence the arbitration between model-based and model-free reinforcement learning at both behavioral and neural levels.

This study simulates dopamine activity transitions during reinforcement learning and finds that ramping to phasic shifts reflect cognitive resource allocation based on task complexity.

The paper investigates how systematic experience and inference order affect causal reasoning and metacognitive awareness in a cancer biology task.

This study examines how depression affects goal-directed and habitual control in the prefrontal-striatal circuitry, revealing disruptions in reinforcement learning processes.