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Masayoshi Murakami

Researcher at Champalimaud Foundation

Publications -  28
Citations -  1205

Masayoshi Murakami is an academic researcher from Champalimaud Foundation. The author has contributed to research in topics: Neural ensemble & Serotonergic. The author has an hindex of 12, co-authored 25 publications receiving 886 citations. Previous affiliations of Masayoshi Murakami include New York University & University of Yamanashi.

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Neural antecedents of self-initiated actions in secondary motor cortex

TL;DR: Together, these results reinforce the generality of the integration-to-bound model of decision-making, which identifies the initial intention to act as the moment of threshold crossing while explaining how antecedent subthreshold neural activity can influence an action without implying a decision.
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State-Dependent Sensory Gating in Olfactory Cortex

TL;DR: A state-dependent switchover of signal processing modes in the olfactory cortex is suggested in urethane-anesthetized rats that shows robust spike responses to adequate odorants during FWS, whereas they showed only weak responses during SWS.
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Activation of Dorsal Raphe Serotonergic Neurons Promotes Waiting but Is Not Reinforcing

TL;DR: Optogenetic activation of 5-HT neurons in the dorsal raphe nucleus (DRN) produces a dose-dependent increase in mice's ability to withhold premature responding in a task that requires them to wait several seconds for a randomly delayed tone, providing strong evidence that the efficacy of DRN 5- HT neurons in promoting waiting for delayed reward is independent of appetitive or aversive effects.
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Distinct Sources of Deterministic and Stochastic Components of Action Timing Decisions in Rodent Frontal Cortex

TL;DR: Analysis of how neural circuits in the frontal cortex determine action timing in rats performing a waiting task suggests a two-stage model in which stochastic components of action timing decisions are injected by circuits downstream of those carrying deterministic bias signals.
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An effect of serotonergic stimulation on learning rates for rewards apparent after long intertrial intervals.

TL;DR: The authors report a novel analysis of a reward-based decision-making experiment, and show that 5-HT stimulation increases the learning rate, but only on a select subset of choices, which suggests that serotonin neurons modulate reinforcement learning rates, and that this influence is masked by alternate, unaffected, decision mechanisms.