147 results found
    1. Neuroscience

    Effects of dopamine on reinforcement learning and consolidation in Parkinson’s disease

    John P Grogan et al.
    Memory over 24 hours was impaired in Parkinson's patients off, rather than on, dopaminergic medication during reinforcement learning, whereas dopamine did not affect positive and negative reinforcement, in contrast to previous studies.
    1. Neuroscience

    Neural computations underlying inverse reinforcement learning in the human brain

    Sven Collette et al.
    The human brain is capable of implementing inverse reinforcement learning, where an observer infers the hidden reward structure of a decision problem solely through observing another individual take actions.
    1. Computational and Systems Biology
    2. Neuroscience

    A cholinergic feedback circuit to regulate striatal population uncertainty and optimize reinforcement learning

    Nicholas T Franklin, Michael J Frank
    Computational modeling suggests that feedback between striatal cholinergic neurons and spiny neurons dynamically adjusts learning rates to optimize behavior in a variable world.
    1. Neuroscience

    Homeostatic reinforcement learning for integrating reward collection and physiological stability

    Mehdi Keramati, Boris Gutkin
    A mathematical model built around the assumption that the desire to maintain internal homeostasis drives the behavior of animals, by affecting their learning processes, can explain many real-world behaviors, including some that might otherwise appear irrational.
    1. Neuroscience

    DYT1 dystonia increases risk taking in humans

    David Arkadir et al.
    Patients with DYT1 dystonia show aberrant risk-aversion in a simple decision-making task, in accordance with predictions of a reinforcement learning model of corticostriatal trial-and-error learning.
    1. Neuroscience

    Mesolimbic confidence signals guide perceptual learning in the absence of external feedback

    Matthias Guggenmos et al.
    Neural confidence signals can take the role of reward signals and explain perceptual learning without external feedback as a form of internal reinforcement learning.
    1. Neuroscience

    Learning the specific quality of taste reinforcement in larval Drosophila

    Michael Schleyer et al.
    The finding that fly maggots, equipped with only 10,000 neurons, process reinforcement not only by value but also by specific quality reveals a basic operating principle of brains and challenges current models of memory organization.
    1. Neuroscience

    Associability-modulated loss learning is increased in posttraumatic stress disorder

    Vanessa M Brown et al.
    Veterans with PTSD show increased attention to a history of unexpected outcomes during loss learning, both as measured by computational model-derived behavioral parameters and in increased neural signaling in amygdala and insula.
    1. Neuroscience

    Reward-based training of recurrent neural networks for cognitive and value-based tasks

    H Francis Song et al.
    A two-part neural network models reward-based training and provides a unified framework in which to study diverse computations that can be compared to electrophysiological recordings from behaving animals.
    1. Neuroscience

    Complementary contributions of basolateral amygdala and orbitofrontal cortex to value learning under uncertainty

    Alexandra Stolyarova, Alicia Izquierdo
    Rat orbitofrontal cortex is required to accurately represent outcome distributions, whereas basolateral amygdala is necessary for the facilitation of learning in response to surprising events.

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