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Daeyeol Lee

· Bloomberg Distinguished Professor, Department of Neuroscience, School of Medicine and Department of Psychological and Brain Sciences, Krieger School of Arts and SciencesVerified

Johns Hopkins University · Psychiatry and Behavioral Sciences

Active 1972–2025

h-index62
Citations12.7k
Papers21670 last 5y
Funding$35.3M
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About

Dr. Daeyeol Lee is a Bloomberg Distinguished Professor of Neuroscience and Psychological and Brain Sciences at Johns Hopkins University. He received his bachelor’s degree in Economics from Seoul National University in Korea and his PhD in Neuroscience from the University of Illinois at Urbana-Champaign. He then completed postdoctoral training in neurophysiology at the University of Minnesota. His current research focuses on the brain mechanisms of decision making, including the role of the prefrontal cortex and basal ganglia in reinforcement learning and economic choices. His laboratory investigates how timing and numerical information is represented and transformed in the brain, employing diverse methods developed in economics, psychology, and neuroscience. He is also an expert in statistical modeling of behavioral and neurophysiological data.

Research topics

  • Artificial Intelligence
  • Computer Science
  • Cognitive science
  • Cognitive psychology
  • Psychology
  • Neuroscience

Selected publications

  • Temporal and Spatial Scales of Human Resting-state Cortical Activity Across the Lifespan

    bioRxiv (Cold Spring Harbor Laboratory) · 2025-03-30 · 1 citations

    preprintOpen accessSenior authorCorresponding

    Sensorimotor and cognitive abilities undergo substantial changes throughout the human lifespan, but the corresponding changes in the functional properties of cortical networks remain poorly understood. This can be studied using temporal and spatial scales of functional magnetic resonance imaging (fMRI) signals, which provide a robust description of the topological structure and temporal dynamics of neural activity. For example, timescales of resting-state fMRI signals can parsimoniously predict a significant amount of the individual variability in functional connectivity networks identified in adult human brains. In the present study, we quantified and compared temporal and spatial scales in resting-state fMRI data collected from 2,352 subjects between the ages of 5 and 100 in Developmental, Young Adult, and Aging datasets from Human Connectome Project. For most cortical regions, we found that both temporal and spatial scales largely decreased with age across most cortical areas throughout the lifespan, with the visual cortex and the limbic network consistently showing the largest and smallest scales, respectively. For some prefrontal regions, however, these two scales displayed non-monotonic trajectories during adolescence and peaked around the same time during adolescence and decreased throughout the rest of the lifespan. We also found that cortical myelination increased monotonically throughout the lifespan, and its rate of change was significantly correlated with the changes in both temporal and spatial scales across different cortical regions in adulthood. These findings suggest that temporal and spatial scales in fMRI signals, as well as cortical myelination, are closely coordinated during both development and aging.

  • Foraging animals use dynamic Bayesian updating to model meta-uncertainty in environment representations

    PLoS Computational Biology · 2025-04-30 · 2 citations

    articleOpen access

    Foraging theory predicts animal behavior in many contexts. In patch-based foraging behaviors, the marginal value theorem (MVT) gives the optimal strategy for deterministic environments whose parameters are fully known to the forager. In natural settings, environmental parameters exhibit variability and are only partially known to the animal based on its experience, creating uncertainty. Models of uncertainty in foraging are well established. However, natural environments also exhibit unpredicted changes in their statistics. As a result, animals must ascertain whether the currently observed quality of the environment is consistent with their internal models, or whether something has changed, creating meta-uncertainty. Behavioral strategies for optimizing foraging behavior under meta-uncertainty, and their neural underpinnings, are largely unknown. Here, we developed a novel behavioral task and computational framework for studying patch-leaving decisions in head-fixed and freely moving mice in conditions of meta-uncertainty. We stochastically varied between-patch travel time, as well as within-patch reward depletion rate. We find that, when uncertainty is minimal, mice adopt patch residence times in a manner consistent with the MVT and not explainable by simple ethologically motivated heuristic strategies. However, behavior in highly variable environments was best explained by modeling both first- and second-order uncertainty in environmental parameters, wherein local variability and global statistics are captured by a Bayesian estimator and dynamic prior, respectively. Thus, mice forage under meta-uncertainty by employing a hierarchical Bayesian strategy, which is essential for efficiently foraging in volatile environments. The results provide a foundation for understanding the neural basis of decision-making that exhibits naturalistic meta-uncertainty.

  • Shared and distinct cortical mechanisms for working memory and decision-making

    bioRxiv (Cold Spring Harbor Laboratory) · 2025-05-21

    preprintOpen access

    Abstract The dorsolateral prefrontal cortex (DLPFC) and lateral intraparietal cortex (LIP) in the primate brain are critically involved in working memory during tasks that require the retention of information over a delay. These same regions have also been implicated in reinforcement learning (RL), where information about an animal’s choice and its outcome is retained to update future reward expectations based on past experiences. We investigated whether spatial memory, required across different behavioral contexts, relies on a shared neural mechanism. To explore this, we analyzed neural activity recorded from rhesus monkeys engaged in three distinct tasks—the oculomotor delayed response task (ODR), a visual search task, and the matching pennies game—each requiring the retention and use of similar spatial information under different cognitive demands. The ODR task demands only prospective memory, as the selection of action is dictated by the location of visual cue, and the subject must retain this intended action for execution after a temporal delay. In contrast, the matching pennies task engages both retrospective and prospective memory: retrospective memory of previous choice and its outcome to inform decision-making, while prospective memory is needed to carry out that decision. Visual search task, by comparison, does not explicitly require either retrospective or prospective memory. Our analysis revealed that neural signals encoding retrospective memory of the animal’s choice in the visual search and matching pennies tasks were not correlated with the prospective working memory signals of visually cued locations in the ODR task, in either the DLPFC or LIP. Moreover, retrospective choice signals in the visual search and matching pennies tasks were not correlated with each other. In contrast, neural activity related to upcoming choices (prospective memory) in the LIP showed significant correlations across all three tasks. In the DLPFC, prospective choice signals were correlated between the visual search and ODR tasks, but not between those tasks and matching pennies. Additionally, in the DLPFC, neural signals representing previously rewarded choices were significantly correlated with working memory signals during the ODR task. These results suggest that the LIP supports a consistent, shared mechanism for prospective memory linking a committed action to its eventual execution. In contrast, the DLPFC might mediate the transformation of retrospective memory-integrating past choices and outcomes – into a decision and its associated prospective memory.

  • Chronic ethanol exposure produces sex-dependent impairments in value computations in the striatum

    Science Advances · 2025-04-02 · 7 citations

    articleOpen access

    Value-based decision-making relies on the striatum, where neural plasticity can be altered by chronic ethanol (EtOH) exposure, but the effects of such plasticity on striatal neural dynamics during decision-making remain unclear. This study investigated the long-term impacts of EtOH on reward-driven decision-making and striatal neurocomputations in male and female rats using a dynamic probabilistic reversal learning task. Following a prolonged withdrawal period, EtOH-exposed male rats exhibited deficits in adaptability and exploratory behavior, with aberrant outcome-driven value updating that heightened preference for chosen action. These behavioral changes were linked to altered neural activity in the dorsomedial striatum (DMS), where EtOH increased outcome-related encoding and decreased choice-related encoding. In contrast, female rats showed minimal behavioral changes with distinct EtOH-evoked alterations of neural activity, revealing significant sex differences in the impact of chronic EtOH. Our findings underscore the impact of chronic EtOH exposure on adaptive decision-making, revealing enduring changes in neurocomputational processes in the striatum underlying cognitive deficits that differ by sex.

  • Corrigendum to “Efficient (S)-acetoin production in Saccharomyces cerevisiae by modulating α-acetolactate decarboxylase stereospecificity”. [Bioresource Technol. 434 (2025) 132767]

    Bioresource Technology · 2025-12-31

    article
  • Temporal and Spatial Scales of Human Resting-State Cortical Activity across the Lifespan

    Journal of Neuroscience · 2025-11-17

    articleOpen accessSenior author

    Sensorimotor and cognitive abilities undergo substantial changes throughout the human lifespan, but the corresponding changes in the functional properties of cortical networks remain poorly understood. This can be studied using temporal and spatial scales of functional magnetic resonance imaging (fMRI) signals, which provide a robust description of the topological structure and temporal dynamics of neural activity. For example, timescales of resting-state fMRI signals parsimoniously predict a significant amount of the individual variability in functional connectivity networks identified in adult human brains. In the present study, we quantified and compared temporal and spatial scales in resting-state fMRI data collected from 2,352 subjects of either sex between the ages of 5 and 100 in Developmental, Young Adult, and Aging datasets from the Human Connectome Project. For most cortical regions, we found that both temporal and spatial scales decreased with age throughout the lifespan, with the visual cortex and the limbic network consistently showing the largest and smallest scales, respectively. For some prefrontal regions, however, these two scales displayed non-monotonic trajectories and peaked around the same time during adolescence and decreased throughout the rest of the lifespan. We also found that cortical myelination increased monotonically throughout the lifespan, and its rate of change was significantly correlated with the changes in both temporal and spatial scales across different cortical regions in adulthood. These findings suggest that temporal and spatial scales in fMRI signals, as well as cortical myelination, are closely coordinated during both development and aging.

  • Efficient (S)-acetoin production in Saccharomyces cerevisiae by modulating α-acetolactate decarboxylase stereospecificity

    Bioresource Technology · 2025-06-03 · 5 citations

    article
  • Efficient Production of Shinorine and Mycosporine–Glycine–Alanine in <i>Yarrowia lipolytica</i> Using Natural and Engineered Nonribosomal Peptide Synthetases

    Journal of Agricultural and Food Chemistry · 2025-06-21

    articleOpen access1st author

    biosynthesis of MG-alanine, a rare MAA previously detected only as a minor MysD byproduct. These findings demonstrate the utility of MysE engineering for expanding MAA diversity and advancing the sustainable microbial production of novel sunscreen compounds.

  • Chronic Ethanol Exposure Produces Persistent Impairment in Cognitive Flexibility and Decision Signals in the Striatum

    bioRxiv (Cold Spring Harbor Laboratory) · 2024-03-12 · 1 citations

    preprintOpen access

    Lack of cognitive flexibility is a hallmark of substance use disorders and has been associated with drug-induced synaptic plasticity in the dorsomedial striatum (DMS). Yet the possible impact of altered plasticity on real-time striatal neural dynamics during decision-making is unclear. Here, we identified persistent impairments induced by chronic ethanol (EtOH) exposure on cognitive flexibility and striatal decision signals. After a substantial withdrawal period from prior EtOH vapor exposure, male, but not female, rats exhibited reduced adaptability and exploratory behavior during a dynamic decision-making task. Reinforcement learning models showed that prior EtOH exposure enhanced learning from rewards over omissions. Notably, neural signals in the DMS related to the decision outcome were enhanced, while those related to choice and choice-outcome conjunction were reduced, in EtOH-treated rats compared to the controls. These findings highlight the profound impact of chronic EtOH exposure on adaptive decision-making, pinpointing specific changes in striatal representations of actions and outcomes as underlying mechanisms for cognitive deficits.

  • Efficient production of (S)-limonene and geraniol in Saccharomyces cerevisiae through the utilization of an Erg20 mutant with enhanced GPP accumulation capability

    Metabolic Engineering · 2024-04-15 · 22 citations

    article

Recent grants

Frequent coauthors

  • Hyojung Seo

    Yale University

    48 shared
  • Min Whan Jung

    Korea Advanced Institute of Science and Technology

    30 shared
  • Sophie Achard

    Centre National de la Recherche Scientifique

    25 shared
  • Alireza Soltani

    Dartmouth Hospital

    23 shared
  • Stephanie M. Groman

    Yale University

    21 shared
  • John D. Murray

    Yale University

    19 shared
  • Jane R. Taylor

    18 shared
  • Eun Ju Shin

    Korea Advanced Institute of Science and Technology

    18 shared

Labs

Awards & honors

  • Fellowship for Prominent Collegians from Korea Foundation fo…
  • University Fellowship from the University of Illinois
  • James S. McDonnell Foundation Cognitive Neuroscience Grant
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