2020/10/23
The computational and neural underpinning of human confidence reports in perceptual decisions and visual working memory
【演講公告】
系上很榮幸地邀請紐約大學心理系黎信宏博士至系上演講，
演講相關內容如下：
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時間：10/23（五）13：10
地點：社科院北棟2樓心理系階梯教室
講者：黎信宏博士，紐約大學心理系博士後研究員。主要研究領域為視覺、注意力、決策以及計算神經科學。
主要著作：
Li, H. H., & Ma, W. J. (2020). Confidence reports in decision-making with multiple alternatives violate the Bayesian confidence hypothesis. Nature Communications, 11(1), 1-11.
Li, H. H., Rankin, J., Rinzel, J., Carrasco, M., & Heeger, D. J. (2017). Attention model of binocular rivalry. Proceedings of the National Academy of Sciences, 114(30), E6192-E6201.
Li, H. H., Barbot, A., & Carrasco, M. (2016). Saccade preparation reshapes sensory tuning. Current Biology, 26(12), 1564-1570.
講題：The computational and neural underpinning of human confidence reports in perceptual decisions and visual working memory
演講摘要：
Confidence is “the sense of knowing” that comes with a decision. Confidence guides planning of subsequent actions after a decision, learning, and cooperation in group decision making. By utilizing decision tasks with confidence reports or uncertainty judgements, numerous studies have demonstrated that people are capable of tracking the quality of their perception and decisions. However, the computation and the neural underpinning of confidence reports are still contentious issues in the field. In the talk, I will present two studies addressing these issues: (1) We studied human confidence reports in a novel multiple alternative perceptual decision task. We argue that tasks with multiple alternatives not only resemble the choices we face in the real world, but are critical for distinguishing different computational models of confidence. We showed that humans' confidence reports systematically deviated from the conventional theory assuming that confidence simply follows the percentage correct in decisions. (2) In neuroimaging experiments, we studied confidence reports in decisions that required the utilization of visual working memory information. By applying Bayesian decoding methods to the fMRI BOLD signals, we demonstrate that human visual cortex contains neural population code that reflects participants’ confidence in their visual working memory.
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敬請準時出席，謝謝。