Decoding the dynamic perception of risk and speed using naturalistic stimuli: A multivariate, whole-brain analysis

被引:1
作者
Ju, Uijong [1 ,4 ]
Wallraven, Christian [2 ,3 ]
机构
[1] Kyung Hee Univ, Dept Informat Display, Seoul, South Korea
[2] Korea Univ, Dept Brain & Cognit Engn, Seoul, South Korea
[3] Korea Univ, Dept Artificial Intelligence, Seoul, South Korea
[4] Kyung Hee Univ, Dept Informat Display, Human Ctr Extended Real Lab, Kyungheedae Ro 26, Seoul 02447, South Korea
基金
新加坡国家研究基金会;
关键词
dynamic correlation analysis; risk; searchlight analysis; sliding window; speed; THINK-ALOUD PROTOCOL; CONNECTIVITY DYNAMICS; COGNITIVE STATES; NEURAL BASIS; MOTION; REPRESENTATIONS; NETWORK; OBJECTS; FMRI; PATHWAYS;
D O I
10.1002/hbm.26652
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Time-resolved decoding of speed and risk perception in car driving is important for understanding the perceptual processes related to driving safety. In this study, we used an fMRI-compatible trackball with naturalistic stimuli to record dynamic ratings of perceived risk and speed and investigated the degree to which different brain regions were able to decode these. We presented participants with first-person perspective videos of cars racing on the same course. These videos varied in terms of subjectively perceived speed and risk profiles, as determined during a behavioral pilot. During the fMRI experiment, participants used the trackball to dynamically rate subjective risk in a first and speed in a second session and assessed overall risk and speed after watching each video. A standard multivariate correlation analysis based on these ratings revealed sparse decodability in visual areas only for the risk ratings. In contrast, the dynamic rating-based correlation analysis uncovered frontal, visual, and temporal region activation for subjective risk and dorsal visual stream and temporal region activation for subjectively perceived speed. Interestingly, further analyses showed that the brain regions for decoding risk changed over time, whereas those for decoding speed remained constant. Overall, our results demonstrate the advantages of time-resolved decoding to help our understanding of the dynamic networks associated with decoding risk and speed perception in realistic driving scenarios. Here, we used naturalistic stimuli to investigated which different brain regions were able to decode dynamic risk and speed. The dynamic rating-based correlation analysis uncovered frontal, visual, and temporal region activation for subjective risk and dorsal visual stream and temporal region activation for subjectively perceived speed. image
引用
收藏
页数:15
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