Advanced search

Filter By:

Journal Check one or more journals to show results from those journals only.

Choose more journals

Article type Check one or more article types to show results from those article types only.
Subject Check one or more subjects to show results from those subjects only.
Date Choose a date option to show results from those dates only.

Custom date range

Clear all filters
Sort by:
Showing 1–22 of 22 results
Advanced filters: Author: Daeyeol Lee Clear advanced filters

  • Primate cortex can be organized with specialization and hierarchical principles, but presently there is little evidence for how it is organized temporally. Across six separate datasets, the authors find a hierarchical ordering of intrinsic fluctuation of spiking activity, with timescales that increase from sensory to prefrontal areas.

    • John D Murray
    • Alberto Bernacchia
    • Xiao-Jing Wang
    Research
    Nature Neuroscience
    Volume: 17, P: 1661-1663

  • Reward signals are widespread in the brain, but why? A study now identifies an important difference in the reward signals encoded by the neurons in the primate anterior cingulate and orbitofrontal cortices during decision making, suggesting that reward-related activity in these areas is shaped by different contextual factors.

    • Daeyeol Lee
    News & Views
    Nature Neuroscience
    Volume: 14, P: 1491-1492

  • How does the brain remember the consequences of our actions? Persistent activity in the prefrontal cortex and basal ganglia may be crucial for learning correct actions through experience.

    • Hyojung Seo
    • Daeyeol Lee
    News & Views
    Nature
    Volume: 461, P: 50-51

  • Donahue and Lee identify prefrontal neurons that integrate task-relevant information about past and current stimulus features and past action outcomes across trials during a probabilistic reversal task. The activity of these neurons is sensitive to past rewards and is predictive of imminent behavioral choices, suggesting that they dynamically contribute to the selection of actions that maximize reward during decision making under uncertainty.

    • Christopher H Donahue
    • Daeyeol Lee
    Research
    Nature Neuroscience
    Volume: 18, P: 295-301

  • Humans often interact without knowing the cooperative or competitive intentions of others. Here, the authors determined the neurocomputational mechanisms engaged in adapting to fluctuating intentions of others over repeated social interactions.

    • Rémi Philippe
    • Rémi Janet
    • Jean-Claude Dreher
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-15

  • While evidence is constantly changing during real-world decisions, little is known about how the brain deals with such changes. Here, the authors show that the brain strategically suppresses motor output via the frontal eye fields in response to stimulus changes.

    • Maxwell Shinn
    • Daeyeol Lee
    • Hyojung Seo
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-13

  • Comparing the behaviour of humans and monkeys, Farashahi et al. show that both species take uncertainty into account when weighing reward value and probability. Both species switch to a more flexible strategy for weighing information during learning.

    • Shiva Farashahi
    • Christopher H. Donahue
    • Alireza Soltani
    Research
    Nature Human Behaviour
    Volume: 3, P: 1215-1224

  • Individual variation in fMRI-derived brain networks is reproduced in a model using only the smoothness (autocorrelation) of the fMRI time series. Smoothness has implication for aging and can be causally manipulated by psychedelic serotonergic drugs.

    • Maxwell Shinn
    • Amber Hu
    • John D. Murray
    Research
    Nature Neuroscience
    Volume: 26, P: 867-878

  • The authors examined neuronal activity in the lateral (AGl) and medial (AGm) agranular cortex, corresponding to the primary and secondary motor cortex, respectively, in rats performing a dynamic foraging task. They find that rodent secondary motor cortex might be uniquely involved in both representing and reading out value signals for flexible action selection.

    • Jung Hoon Sul
    • Suhyun Jo
    • Min Whan Jung
    Research
    Nature Neuroscience
    Volume: 14, P: 1202-1208

  • According to reinforcement learning theory, reward expectation reflects an integration of past rewards over a fixed time scale. Here the authors extract signals about reward memory from neurons in the prefrontal, cingulate and parietal cortex, finding a wide range of time constants across the neuronal population, with a power-law distribution.

    • Alberto Bernacchia
    • Hyojung Seo
    • Xiao-Jing Wang
    Research
    Nature Neuroscience
    Volume: 14, P: 366-372

  • Learning about a rewarded outcome is complicated by the fact that a choice often incorporates multiple features with differing association with the reward. Here the authors demonstrate that feature-based learning is an efficient and adaptive strategy in dynamically changing environments.

    • Shiva Farashahi
    • Katherine Rowe
    • Alireza Soltani
    ResearchOpen Access
    Nature Communications
    Volume: 8, P: 1-16

  • Stimulus category, saliency and value all affect the subjective value estimates that guide our decisions. Here, the authors systematically vary their stimuli along these three dimensions in humans and report category independent encoding of values and saliency in the vmPFC and striatum.

    • Zhihao Zhang
    • Jennifer Fanning
    • Ifat Levy
    ResearchOpen Access
    Nature Communications
    Volume: 8, P: 1-14

  • In a changing world, how do we decide our best option? How do we settle between picking something familiar or trying out a new, possibly more rewarding, choice?

    • Daeyeol Lee
    News & Views
    Nature
    Volume: 441, P: 822-823

  • Choosing to accept enough risk, but not too much, is an important survival skill, and depending on the circumstances, animals may either seek or avoid risk. Given the choice between a sure bet and a larger but uncertain reward, a paper in this issue reports macaques consistently take the riskier option, and posterior cingulate cortex neurons represent the riskiness of those choices.

    • Daeyeol Lee
    News & Views
    Nature Neuroscience
    Volume: 8, P: 1129-1130