K
Kiyohito Iigaya
Researcher at California Institute of Technology
Publications - 26
Citations - 483
Kiyohito Iigaya is an academic researcher from California Institute of Technology. The author has contributed to research in topics: Anticipation (artificial intelligence) & Prefrontal cortex. The author has an hindex of 11, co-authored 24 publications receiving 330 citations. Previous affiliations of Kiyohito Iigaya include Max Planck Society & Columbia University Medical Center.
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The modulation of savouring by prediction error and its effects on choice.
TL;DR: This work hypothesized that this preference of advance information arises because reward prediction errors carried by such information can boost the level of anticipation, and formulated this proposal in a reinforcement-learning model.
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An effect of serotonergic stimulation on learning rates for rewards apparent after long intertrial intervals.
Kiyohito Iigaya,Kiyohito Iigaya,Madalena S. Fonseca,Masayoshi Murakami,Zachary F. Mainen,Peter Dayan +5 more
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.
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A Neuro-computational Account of Arbitration between Choice Imitation and Goal Emulation during Human Observational Learning.
TL;DR: A neuro-computational mechanism underlying arbitration between choice imitation and goal emulation is identified and the computations by which the brain decides to imitate or emulate others are illuminated.
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Adaptive learning and decision-making under uncertainty by metaplastic synapses guided by a surprise detection system.
Kiyohito Iigaya,Kiyohito Iigaya +1 more
TL;DR: This work investigates a biophysically inspired, metaplastic synaptic model within the context of a well-studied decision-making network, in which synapses can change their rate of plasticity in addition to their efficacy according to a reward-based learning rule.
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The value of what's to come: Neural mechanisms coupling prediction error and the utility of anticipation.
Kiyohito Iigaya,Kiyohito Iigaya,Tobias U. Hauser,Zeb Kurth-Nelson,John P. O'Doherty,Peter Dayan,Raymond J. Dolan +6 more
TL;DR: A previously unidentified neural underpinning for anticipation’s influence over decision-making is suggested to unify a range of phenomena associated with risk and time-delay preference.