Matthew Nassar
Matthew Nassar
Assistant Professor at Brown University
Verified email at - Homepage
Cited by
Cited by
Alternate day calorie restriction improves clinical findings and reduces markers of oxidative stress and inflammation in overweight adults with moderate asthma
JB Johnson, W Summer, RG Cutler, B Martin, DH Hyun, VD Dixit, ...
Free Radical Biology and Medicine 42 (5), 665-674, 2007
Rational regulation of learning dynamics by pupil-linked arousal systems
MR Nassar, KM Rumsey, RC Wilson, K Parikh, B Heasly, JI Gold
Nature neuroscience 15 (7), 1040, 2012
An approximately Bayesian delta-rule model explains the dynamics of belief updating in a changing environment
MR Nassar, RC Wilson, B Heasly, JI Gold
Journal of Neuroscience 30 (37), 12366-12378, 2010
Functionally dissociable influences on learning rate in a dynamic environment
JT McGuire, MR Nassar, JI Gold, JW Kable
Neuron 84 (4), 870-881, 2014
Bayesian online learning of the hazard rate in change-point problems
RC Wilson, MR Nassar, JI Gold
Neural computation 22 (9), 2452-2476, 2010
Neuroprotective actions of a histidine analogue in models of ischemic stroke
SC Tang, TV Arumugam, RG Cutler, DG Jo, T Magnus, SL Chan, ...
Journal of neurochemistry 101 (3), 729-736, 2007
Age differences in learning emerge from an insufficient representation of uncertainty in older adults
MR Nassar, R Bruckner, JI Gold, SC Li, HR Heekeren, B Eppinger
Nature Communications 7 (1), 1-13, 2016
A mixture of delta-rules approximation to bayesian inference in change-point problems
RC Wilson, MR Nassar, JI Gold
PLoS Comput Biol 9 (7), e1003150, 2013
Catecholaminergic regulation of learning rate in a dynamic environment
M Jepma, PR Murphy, MR Nassar, M Rangel-Gomez, M Meeter, ...
PLoS Computational Biology 12 (10), e1005171, 2016
Arousal-related adjustments of perceptual biases optimize perception in dynamic environments
K Krishnamurthy, MR Nassar, S Sarode, JI Gold
Nature human behaviour 1 (6), 1-11, 2017
Chunking as a rational strategy for lossy data compression in visual working memory.
MR Nassar, JC Helmers, MJ Frank
Psychological review 125 (4), 486, 2018
The mitochondrial uncoupler DNP triggers brain cell mTOR signaling network reprogramming and CREB pathway up‐regulation
D Liu, Y Zhang, R Gharavi, HR Park, J Lee, S Siddiqui, R Telljohann, ...
Journal of neurochemistry 134 (4), 677-692, 2015
Positive reward prediction errors during decision-making strengthen memory encoding
AI Jang, MR Nassar, DG Dillon, MJ Frank
Nature human behaviour 3 (7), 719-732, 2019
Taming the beast: extracting generalizable knowledge from computational models of cognition
MR Nassar, MJ Frank
Current opinion in behavioral sciences 11, 49-54, 2016
A healthy fear of the unknown: perspectives on the interpretation of parameter fits from computational models in neuroscience
MR Nassar, JI Gold
PLoS Computational Biology 9 (4), e1003015, 2013
Statistical context dictates the relationship between feedback-related EEG signals and learning
MR Nassar, R Bruckner, MJ Frank
Elife 8, e46975, 2019
A control theoretic model of adaptive learning in dynamic environments
H Ritz, MR Nassar, MJ Frank, A Shenhav
Journal of cognitive neuroscience 30 (10), 1405-1421, 2018
Dissociable forms of uncertainty-driven representational change across the human brain
MR Nassar, JT McGuire, H Ritz, JW Kable
Journal of Neuroscience 39 (9), 1688-1698, 2019
Computational neuroscience across the lifespan: Promises and pitfalls
W van den Bos, R Bruckner, MR Nassar, R Mata, B Eppinger
Developmental cognitive neuroscience 33, 42-53, 2018
Individual neurons in the cingulate cortex encode action monitoring, not selection, during adaptive decision-making
YS Li, MR Nassar, JW Kable, JI Gold
Journal of Neuroscience 39 (34), 6668-6683, 2019
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