Yuelu Liu
Affiliations: | Center for Mind and Brain |
Area:
Visual Attention, Top-down Control, Affective ProcessingGoogle:
"Yuelu Liu"Mean distance: 13.45 (cluster 29) | S | N | B | C | P |
Parents
Sign in to add mentorMingzhou Ding | grad student | 2008-2013 | UF Gainesville | |
(Single-trial analysis and its applications in EEG and simultaneous EEG-fMRI studies.) | ||||
George R. Mangun | post-doc | 2013- | UC Davis | |
W Martin Usrey | post-doc | 2013- | UC Davis |
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Publications
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Rajan A, Meyyappan S, Liu Y, et al. (2021) The Microstructure of Attentional Control in the Dorsal Attention Network. Journal of Cognitive Neuroscience. 33: 965-983 |
Bo K, Yin S, Liu Y, et al. (2021) Decoding Neural Representations of Affective Scenes in Retinotopic Visual Cortex. Cerebral Cortex (New York, N.Y. : 1991) |
Yin S, Bo K, Liu Y, et al. (2020) Fear conditioning prompts sparser representations of conditioned threat in primary visual cortex. Social Cognitive and Affective Neuroscience |
Yin S, Bo K, Liu Y, et al. (2020) Fear conditioning prompts sparser representations of conditioned threat in primary visual cortex. Social Cognitive and Affective Neuroscience |
Bengson JJ, Liu Y, Khodayari N, et al. (2019) Gating by inhibition during top-down control of willed attention. Cognitive Neuroscience. 1-11 |
Meyyappan S, Rajan A, Walker H, et al. (2019) Cue-evoked pupillary response reveals a left visual field bias in covert spatial visual attention Journal of Vision. 19: 319a |
Bo K, Yin S, Liu Y, et al. (2019) EEG and fMRI Decoding of Emotional States: Temporal Dynamics and Neural Substrate Journal of Vision. 19: 285 |
Rajan A, Siegel SN, Liu Y, et al. (2018) Theta Oscillations Index Frontal Decision-Making and Mediate Reciprocal Frontal-Parietal Interactions in Willed Attention. Cerebral Cortex (New York, N.Y. : 1991) |
Yin S, Liu Y, Petro NM, et al. (2018) Amygdala Adaptation and Temporal Dynamics of the Salience Network in Conditioned Fear: A Single-Trial fMRI Study. Eneuro. 5 |
Liu Y, Hong X, Bengson JJ, et al. (2017) Deciding Where to Attend: Large-scale Network Mechanisms Underlying Attention and Intention Revealed by Graph-theoretic Analysis. Neuroimage |