Shuo Wang

Dr. Shuo Wang

orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2014 in Journal of Vision
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Journal Article
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JXJuan Xu
Juan Xu
MJMing Jiang
Ming Jiang
SWShuo Wang
Shuo Wang
MKMohan S. Kankanhalli
Mohan S. Kankanhalli
QZQ. Zhao
Q. Zhao
A large body of previous models to predict where people look in natural scenes focused on pixel-level image attributes. To bridge the semantic gap between the predictive power of computational saliency models and human behavior, we propose a new saliency architecture that incorporates information at three layers: pixel-level image attributes, object-level attributes, and semantic-level attributes. Object- and semantic-level information is frequently ignored, or only a few sample object categories are discussed where scaling to a large number of object categories is not feasible nor neurally plausible. To address this problem, this work constructs a principled vocabulary of basic attributes to describe object- and semantic-level information thus not restricting to a limited number of object categories. We build a new dataset of 700 images with eye-tracking data of 15 viewers and annotation data of 5,551 segmented objects with fine contours and 12 semantic attributes (publicly available with the paper). Experimental results demonstrate the importance of the object- and semantic-level information in the prediction of visual attention.

3 February 2020 in Nature Human Behaviour
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DRDobromir Rahnev
Dobromir Rahnev
KDKobe Desender
Kobe Desender
ALAlan L. F. Lee
Alan L. F. Lee
WAWilliam T. Adler
William T. Adler
DADavid Aguilar-Lleyda
David Aguilar-Lleyda
AZAriel Zylberberg
Ariel Zylberberg

21 April 2017 in Nature Communications
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Journal Article
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SWShuo Wang
Shuo Wang
RYRongjun Yu
Rongjun Yu
JTJ. Michael Tyszka
J. Michael Tyszka
SZShanshan Zhen
Shanshan Zhen
CKChristopher Kovach
Christopher Kovach
URUeli Rutishauser
Ueli Rutishauser
The human amygdala is a key structure for processing emotional facial expressions, but it remains unclear what aspects of emotion are processed. We investigated this question with three different approaches: behavioural analysis of 3 amygdala lesion patients, neuroimaging of 19 healthy adults, and single-neuron recordings in 9 neurosurgical patients. The lesion patients showed a shift in behavioural sensitivity to fear, and amygdala BOLD responses were modulated by both fear and emotion ambiguity (the uncertainty that a facial expression is categorized as fearful or happy). We found two populations of neurons, one whose response correlated with increasing degree of fear, or happiness, and a second whose response primarily decreased as a linear function of emotion ambiguity. Together, our results indicate that the human amygdala processes both the degree of emotion in facial expressions and the categorical ambiguity of the emotion shown and that these two aspects of amygdala processing can be most clearly distinguished at the level of single neurons.

31 May 2021 in Nature Communications
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MPMichael Pereira
Michael Pereira
PMPierre Megevand
Pierre Megevand
MTMi Xue Tan
Mi Xue Tan
WCWenwen Chang
Wenwen Chang
SWShuo Wang
Shuo Wang
NFNathan Faivre
Nathan Faivre
A fundamental scientific question concerns the neural basis of perceptual consciousness and perceptual monitoring resulting from the processing of sensory events. Although recent studies identified neurons reflecting stimulus visibility, their functional role remains unknown. Here, we show that perceptual consciousness and monitoring involve evidence accumulation. We recorded single-neuron activity in a participant with a microelectrode in the posterior parietal cortex, while they detected vibrotactile stimuli around detection threshold and provided confidence estimates. We find that detected stimuli elicited neuronal responses resembling evidence accumulation during decision-making, irrespective of motor confounds or task demands. We generalize these findings in healthy volunteers using electroencephalography. Behavioral and neural responses are reproduced with a computational model considering a stimulus as detected if accumulated evidence reaches a bound, and confidence as the distance between maximal evidence and that bound. We conclude that gradual changes in neuronal dynamics during evidence accumulation relates to perceptual consciousness and perceptual monitoring in humans.

28 October 2023 in Translational Psychiatry
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Journal Article
Open access
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SSSai Sun
Sai Sun
HYHongbo Yu
Hongbo Yu
RYRongjun Yu
Rongjun Yu
SWShuo Wang
Shuo Wang
Processing facial expressions of emotion draws on a distributed brain network. In particular, judging ambiguous facial emotions involves coordination between multiple brain areas. Here, we applied multimodal functional connectivity analysis to achieve network-level understanding of the neural mechanisms underlying perceptual ambiguity in facial expressions. We found directional effective connectivity between the amygdala, dorsomedial prefrontal cortex (dmPFC), and ventromedial PFC, supporting both bottom-up affective processes for ambiguity representation/perception and top-down cognitive processes for ambiguity resolution/decision. Direct recordings from the human neurosurgical patients showed that the responses of amygdala and dmPFC neurons were modulated by the level of emotion ambiguity, and amygdala neurons responded earlier than dmPFC neurons, reflecting the bottom-up process for ambiguity processing. We further found parietal-frontal coherence and delta-alpha cross-frequency coupling involved in encoding emotion ambiguity. We replicated the EEG coherence result using independent experiments and further showed modulation of the coherence. EEG source connectivity revealed that the dmPFC top-down regulated the activities in other brain regions. Lastly, we showed altered behavioral responses in neuropsychiatric patients who may have dysfunctions in amygdala-PFC functional connectivity. Together, using multimodal experimental and analytical approaches, we have delineated a neural network that underlies processing of emotion ambiguity.

1 August 2017 in NeuroImage
Verified
Journal Article
Closed access
SSSai Sun
Sai Sun
SZShanshan Zhen
Shanshan Zhen
ZFZhongzheng Fu
Zhongzheng Fu
DWDaw-An Wu
Daw-An Wu
SSShinsuke Shimojo
Shinsuke Shimojo
SWShuo Wang
Shuo Wang