Artículos con órdenes de acceso público - Yael NivMás información
No disponible en ningún lugar: 1
A Transdiagnostic Association Between Mood Symptoms and Mood-Learning Interaction
D Bennett, M Erickson, S Silverstein, Y Niv
Biological Psychiatry 89 (9), S214-S215, 2021
Órdenes: US National Institutes of Health
Disponibles en algún lugar: 100
Orbitofrontal cortex as a cognitive map of task space
RC Wilson, YK Takahashi, G Schoenbaum, Y Niv
Neuron 81 (2), 267-279, 2014
Órdenes: US National Institutes of Health
Hierarchically organized behavior and its neural foundations: A reinforcement learning perspective
MM Botvinick, Y Niv, AG Barto
cognition 113 (3), 262-280, 2009
Órdenes: US National Institutes of Health
Human orbitofrontal cortex represents a cognitive map of state space
NW Schuck, MB Cai, RC Wilson, Y Niv
Neuron 91 (6), 1402-1412, 2016
Órdenes: US National Institutes of Health
From fear to safety and back: reversal of fear in the human brain
D Schiller, I Levy, Y Niv, JE LeDoux, EA Phelps
Journal of Neuroscience 28 (45), 11517-11525, 2008
Órdenes: US National Institutes of Health
The effects of neural gain on attention and learning
E Eldar, JD Cohen, Y Niv
Nature neuroscience 16 (8), 1146-1153, 2013
Órdenes: US National Institutes of Health, Howard Hughes Medical Institute
Context, learning, and extinction.
SJ Gershman, DM Blei, Y Niv
Psychological review 117 (1), 197, 2010
Órdenes: US National Institutes of Health
Reinforcement learning in multidimensional environments relies on attention mechanisms
Y Niv, R Daniel, A Geana, SJ Gershman, YC Leong, A Radulescu, ...
Journal of Neuroscience 35 (21), 8145-8157, 2015
Órdenes: US National Institutes of Health
Mood as representation of momentum
E Eldar, RB Rutledge, RJ Dolan, Y Niv
Trends in cognitive sciences 20 (1), 15-24, 2016
Órdenes: Wellcome Trust
Rethinking extinction
JE Dunsmoor, Y Niv, N Daw, EA Phelps
Neuron 88 (1), 47-63, 2015
Órdenes: US National Institutes of Health
Dialogues on prediction errors
Y Niv, G Schoenbaum
Trends in cognitive sciences 12 (7), 265-272, 2008
Órdenes: US National Institutes of Health
Dynamic interaction between reinforcement learning and attention in multidimensional environments
YC Leong, A Radulescu, R Daniel, V DeWoskin, Y Niv
Neuron 93 (2), 451-463, 2017
Órdenes: US Department of Defense, US National Institutes of Health, Human Frontier …
Learning latent structure: carving nature at its joints
SJ Gershman, Y Niv
Current opinion in neurobiology 20 (2), 251-256, 2010
Órdenes: US National Institutes of Health
Learning task-state representations
Y Niv
Nature neuroscience 22 (10), 1544-1553, 2019
Órdenes: US Department of Defense, US National Institutes of Health
Expectancy-related changes in firing of dopamine neurons depend on orbitofrontal cortex
YK Takahashi, MR Roesch, RC Wilson, K Toreson, P O'donnell, Y Niv, ...
Nature neuroscience 14 (12), 1590-1597, 2011
Órdenes: US National Institutes of Health
Dopamine transients are sufficient and necessary for acquisition of model-based associations
MJ Sharpe, CY Chang, MA Liu, HM Batchelor, LE Mueller, JL Jones, ...
Nature neuroscience 20 (5), 735-742, 2017
Órdenes: US National Institutes of Health
Ventral striatum and orbitofrontal cortex are both required for model-based, but not model-free, reinforcement learning
MA McDannald, F Lucantonio, KA Burke, Y Niv, G Schoenbaum
Journal of Neuroscience 31 (7), 2700-2705, 2011
Órdenes: US National Institutes of Health
Sequential replay of nonspatial task states in the human hippocampus
NW Schuck, Y Niv
Science 364 (6447), eaaw5181, 2019
Órdenes: US Department of Defense, US National Institutes of Health
Computational approaches to fMRI analysis
JD Cohen, N Daw, B Engelhardt, U Hasson, K Li, Y Niv, KA Norman, ...
Nature neuroscience 20 (3), 304-313, 2017
Órdenes: US National Science Foundation, US National Institutes of Health
Interaction between emotional state and learning underlies mood instability
E Eldar, Y Niv
Nature communications 6 (1), 6149, 2015
Órdenes: Howard Hughes Medical Institute
La información de publicación y financiación se determina de forma automática mediante un programa informático