About me (Kyo)
I am Assistant Professor at the Department of Psychiatry at Columbia University Irving Medical Center. Here's the lab website. Please contact me ([email protected]) if you're interested in joining the lab as a student/postdoc/RA!
I did my Ph.D. in physics (emphasis: theoretical neuroscience; thesis advisor: Stefano Fusi) at the Center for Theoretical Neuroscience and Department of Physics at Columbia University. I was a postdoc with Peter Dayan at the Gatsby Computational Neuroscience Unit, with Ray Dolan at Max Planck UCL Centre for Computational Psychiatry and Ageing at UCL, and with John O'Doherty at Caltech.
My research goal is to 1) identify computational principles underlying how humans make predictions/decisions under uncertainty, and also to 2) inform our understanding of psychiatric disorders through the study of variation in their neural realization. I build computational models and test our model's predictions in experimental data, where I often borrow ideas from behavioral economics and psychology and use tools in physics and machine learning. While I design and run behavioral/neuroimaging experiments with human participants, I have been very fortunate to work together with amazing experimental and theoretical collaborators.
I did my Ph.D. in physics (emphasis: theoretical neuroscience; thesis advisor: Stefano Fusi) at the Center for Theoretical Neuroscience and Department of Physics at Columbia University. I was a postdoc with Peter Dayan at the Gatsby Computational Neuroscience Unit, with Ray Dolan at Max Planck UCL Centre for Computational Psychiatry and Ageing at UCL, and with John O'Doherty at Caltech.
My research goal is to 1) identify computational principles underlying how humans make predictions/decisions under uncertainty, and also to 2) inform our understanding of psychiatric disorders through the study of variation in their neural realization. I build computational models and test our model's predictions in experimental data, where I often borrow ideas from behavioral economics and psychology and use tools in physics and machine learning. While I design and run behavioral/neuroimaging experiments with human participants, I have been very fortunate to work together with amazing experimental and theoretical collaborators.
Publications
Neuroscience
Kiyohito Iigaya , Sanghyun Yi, Iman A. Wahle, Koranis Tanwisuth, and John P. O’Doherty
"Aesthetic preference for art can be predicted from a mixture of low- and high-level visual features"
Nature Human Behaviour (2021)
News and Views: Beauty is in the eye of the machine
John P O'Doherty, Ueli Rutishauser, and Kiyohito Iigaya
"The Hierarchical Construction of Value"
Current Opinion in Behavioral Sciences, 41, 71 (2021)
John P O'Doherty, Sangwan Lee, Reza Tadayonnejad, Jeff Cockburn, Kiyohito Iigaya, and Caroline Charpentier
"Why and how the brain weights contributions from a mixture of experts"
Neuroscience and Biobehavioral Reviews 123, 14 (2021)
Kiyohito Iigaya, John P O’Doherty, and G. Gabrielle Starr
"Progress and Promise in Neuroaesthetics"
Neuron 108 (4), 594-596 (2020)
Kiyohito Iigaya,Tobias U Hauser, Zeb Kurth-Nelson, John P O'Doherty, Peter Dayan*, and Raymond J Dolan*
"The value of what's to come: Neural mechanisms coupling prediction error and the utility of anticipation"
Science Advances, 6, 25 (2020)
Media: The brain seeks information to boost the joy of anticipation.
*co-senior authors
(We showed how the brain generates the utility of anticipation, which can drive information-seeking and addiction.)
Kiyohito Iigaya , Sanghyun Yi, Iman A. Wahle, Koranis Tanwisuth, and John P. O’Doherty
"Aesthetic preference for art emerges from a weighted integration over hierarchically structured visual features in the brain"
bioRxiv (2020)
Media: Science: "Do you like weird art? Blame your brain"
Caroline J Charpentier, Kiyohito Iigaya, and John P O'Doherty
"A Neuro-computational Account of Arbitration between Choice Imitation and Goal Emulation during Human Observational Learning"
Neuron 106 (4) 687-699 (2020)
Kiyohito Iigaya and John P O'Doherty
"Hippocampus Is What Happens while You’re Busy Making Other Plans"
Neuron,102 (3) 517-519 (2019)
Kiyohito Iigaya, Yashar Ahmadian, Leo P Sugrue, Greg S Corrado, Yonatan Loewenstein, William T Newsome, and Stefano Fusi
"Deviation from the matching law reflects an optimal strategy involving learning over multiple timescales"
Nature Communications, 1466, 14 (2019)
Editors’ Highlights: From Brain to Behavior
(We showed how monkeys learn quickly and slowly in parallel under uncertainty.)
Kiyohito Iigaya, Madalena S Fonseda, Masayoshi Murakami, Zachary F Mainen, and Peter Dayan
"An effect of serotonergic stimulation on learning rates for rewards apparent after long intertrial intervals"
Nature Communications, 9, 2477 (2018)
F1000 Prime recommended
Media: 1, 2, ...
(We showed that mice speed up learning when serotonergic neurons are activated optogenetically.)
Kiyohito Iigaya*, Aurelie Jolivald*, Wittawat Jitkrittum, Iain Gilchrist, Peter Dayan**, Elizabeth Paul**, Mike Mendl**
"Cognitive Bias in Ambiguity Judgements: Using Computational Models to Dissect the Effects of Mild Mood Manipulation in Humans"
PLoS One 11(11): e0165840 (2016)
*equal contribution. **equal contribution.
(We showed how human's perceptual decisions can be influenced by their mood.)
Kiyohito Iigaya
"Adaptive learning and decision-making under uncertainty by metaplastic synapses guided by a surprise detection system"
eLife, 5, e18073 (2016)
(We proposed how synaptic (meta-)plasticity can help (meta-)learning.)
Kiyohito Iigaya, Giles Story, Zeb Kurth-Nelson, Ray Dolan, and Peter Dayan
"The Modulation of Savouring by Prediction Error and its Effects on Choice"
eLife, 5, e13747 (2016)
(We showed how a model of the utility of anticipation can explain why people seek information.)
Kiyohito Iigaya
"Neural network models of decision making with learning on multiple timescales"
Ph.D. thesis, Columbia University (2014)
Kiyohito Iigaya and Stefano Fusi
"Dynamical regimes in neural network models of matching behavior."
Neural computation, 25:1–20 (2013).
(We showed how a simple neural network model can capture both adaptive matching and maladaptive perseverative behavior.)
"Aesthetic preference for art can be predicted from a mixture of low- and high-level visual features"
Nature Human Behaviour (2021)
News and Views: Beauty is in the eye of the machine
John P O'Doherty, Ueli Rutishauser, and Kiyohito Iigaya
"The Hierarchical Construction of Value"
Current Opinion in Behavioral Sciences, 41, 71 (2021)
John P O'Doherty, Sangwan Lee, Reza Tadayonnejad, Jeff Cockburn, Kiyohito Iigaya, and Caroline Charpentier
"Why and how the brain weights contributions from a mixture of experts"
Neuroscience and Biobehavioral Reviews 123, 14 (2021)
Kiyohito Iigaya, John P O’Doherty, and G. Gabrielle Starr
"Progress and Promise in Neuroaesthetics"
Neuron 108 (4), 594-596 (2020)
Kiyohito Iigaya,Tobias U Hauser, Zeb Kurth-Nelson, John P O'Doherty, Peter Dayan*, and Raymond J Dolan*
"The value of what's to come: Neural mechanisms coupling prediction error and the utility of anticipation"
Science Advances, 6, 25 (2020)
Media: The brain seeks information to boost the joy of anticipation.
*co-senior authors
(We showed how the brain generates the utility of anticipation, which can drive information-seeking and addiction.)
Kiyohito Iigaya , Sanghyun Yi, Iman A. Wahle, Koranis Tanwisuth, and John P. O’Doherty
"Aesthetic preference for art emerges from a weighted integration over hierarchically structured visual features in the brain"
bioRxiv (2020)
Media: Science: "Do you like weird art? Blame your brain"
Caroline J Charpentier, Kiyohito Iigaya, and John P O'Doherty
"A Neuro-computational Account of Arbitration between Choice Imitation and Goal Emulation during Human Observational Learning"
Neuron 106 (4) 687-699 (2020)
Kiyohito Iigaya and John P O'Doherty
"Hippocampus Is What Happens while You’re Busy Making Other Plans"
Neuron,102 (3) 517-519 (2019)
Kiyohito Iigaya, Yashar Ahmadian, Leo P Sugrue, Greg S Corrado, Yonatan Loewenstein, William T Newsome, and Stefano Fusi
"Deviation from the matching law reflects an optimal strategy involving learning over multiple timescales"
Nature Communications, 1466, 14 (2019)
Editors’ Highlights: From Brain to Behavior
(We showed how monkeys learn quickly and slowly in parallel under uncertainty.)
Kiyohito Iigaya, Madalena S Fonseda, Masayoshi Murakami, Zachary F Mainen, and Peter Dayan
"An effect of serotonergic stimulation on learning rates for rewards apparent after long intertrial intervals"
Nature Communications, 9, 2477 (2018)
F1000 Prime recommended
Media: 1, 2, ...
(We showed that mice speed up learning when serotonergic neurons are activated optogenetically.)
Kiyohito Iigaya*, Aurelie Jolivald*, Wittawat Jitkrittum, Iain Gilchrist, Peter Dayan**, Elizabeth Paul**, Mike Mendl**
"Cognitive Bias in Ambiguity Judgements: Using Computational Models to Dissect the Effects of Mild Mood Manipulation in Humans"
PLoS One 11(11): e0165840 (2016)
*equal contribution. **equal contribution.
(We showed how human's perceptual decisions can be influenced by their mood.)
Kiyohito Iigaya
"Adaptive learning and decision-making under uncertainty by metaplastic synapses guided by a surprise detection system"
eLife, 5, e18073 (2016)
(We proposed how synaptic (meta-)plasticity can help (meta-)learning.)
Kiyohito Iigaya, Giles Story, Zeb Kurth-Nelson, Ray Dolan, and Peter Dayan
"The Modulation of Savouring by Prediction Error and its Effects on Choice"
eLife, 5, e13747 (2016)
(We showed how a model of the utility of anticipation can explain why people seek information.)
Kiyohito Iigaya
"Neural network models of decision making with learning on multiple timescales"
Ph.D. thesis, Columbia University (2014)
Kiyohito Iigaya and Stefano Fusi
"Dynamical regimes in neural network models of matching behavior."
Neural computation, 25:1–20 (2013).
(We showed how a simple neural network model can capture both adaptive matching and maladaptive perseverative behavior.)
Physics
Kiyohito Iigaya, Satoru Konabe, Ippei Danshita, and Tetsuro Nikuni
"Landau damping: Instability mechanism of superfluid Bose gases in optical lattices"
Physical Review A 74, 053611 (2006)
(We theoretically showed how a Bose-Einstein Condensate can break down through a phonon-excitation.)
"Landau damping: Instability mechanism of superfluid Bose gases in optical lattices"
Physical Review A 74, 053611 (2006)
(We theoretically showed how a Bose-Einstein Condensate can break down through a phonon-excitation.)