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    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

    A new model of decision processing in instrumental learning tasks

    Steven Miletić et al.
    A new model is presented to simultaneously study the latent cognitive processes underlying decision making and instrumental learning.
    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

    The control of tonic pain by active relief learning

    Suyi Zhang et al.
    The brain has a central cortico-striatal learning circuit that suppresses ongoing pain after injury when actively learning about things that could remove the cause of the pain.
    1. Neuroscience

    One-shot learning and behavioral eligibility traces in sequential decision making

    Marco P Lehmann et al.
    Human learning relies on short-term memories (eligibility traces) which provide a mechanism to reinforce sequences of actions from a single reward (one-shot).
    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

    Metacontrol of decision-making strategies in human aging

    Florian Bolenz et al.
    Older adults show reduced adaptation of decision-making strategies to dynamically changing situational demands.
    1. Neuroscience

    Classical conditioning drives learned reward prediction signals in climbing fibers across the lateral cerebellum

    William Heffley, Court Hull
    Cerebellar climbing fibers can generate learned reward-predictive instructional signals, suggesting a role for cerebellar learning in the reinforcement of reward-driven behaviors.
    1. Neuroscience

    The modulation of savouring by prediction error and its effects on choice

    Kiyohito Iigaya et al.
    The anticipation of rewards turns out to have its own hedonic value, on top of that of the reward itself; a wide range of behavioral and neurophysiological data suggest that this anticipation is boosted by prediction errors.
    1. Neuroscience

    Disruption of Nrxn1α within excitatory forebrain circuits drives value-based dysfunction

    Opeyemi O Alabi et al.
    Disruption of the disease-associated synaptic adhesion molecule Neurexin1a in cortical excitatory neurons perturbs decision making and disrupts value-associated neural activity in downstream striatal circuits.