Decoding near-threshold perception of fear from distributed single-trial brain activation
Decoding near-threshold perception of fear from distributed single-trial brain activation
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DOI：
10.1093/cercor/bhk020
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发表时间：
2007-03-01
期刊：
影响因子：
3.7
通讯作者：
Padmala, Srikanth
中科院分区：
文献类型：
--
作者：
Pessoa, Luiz;Padmala, Srikanth
我们没有像神经成像中通常做的那样，对比与两种情况相关的功能性磁共振成像（fMRI）信号，而是改变了分析方向，探索大脑信号是否可以用来“预测”感知状态。我们通过在近阈值恐惧检测过程中“解码”大脑状态来探测感知决策的神经相关性。通过使用支持向量机和其他相关技术尝试解码。虽然以前的解码研究采用了相对“块”的数据，我们的目标是探索如何“时刻到时刻”的波动，在整个人口的体素的fMRI信号反映了参与者的知觉决定。准确度从考虑1个区域（类似于64%）增加到使用10个区域（类似于78%）。当对每个受试者的最佳分类进行平均时，准确率在74%到86%之间。信息理论分析表明，成对区域携带的信息可靠地超过了单个区域携带的信息之和，这表明信息是跨区域“协同”组合的。我们的结果表明，行为选择的表征“分布”在多个大脑区域。这种分布式编码可以帮助生物体做好准备，以适当地处理情绪刺激，并在有意识地决定恐惧的面孔存在时调节相关的情绪反应。此外，研究结果表明，具有挑战性的大脑状态，可以解码具有高准确性，即使是“单次试验”的数据，并建议多变量分析策略有相当大的潜力，有助于阐明视觉意识和编码的感知决策的神经相关性。
Instead of contrasting functional magnetic resonance imaging (fMRI) signals associated with 2 conditions, as customarily done in neuroimaging, we reversed the direction of analysis and probed whether brain signals could be used to "predict" perceptual states. We probed the neural correlates of perceptual decisions by "decoding" brain states during near-threshold fear detection. Decoding was attempted by using support vector machines and other related techniques. Although previous decoding studies have employed relatively "blocked" data, our objective was to probe how the "moment-to-moment" fluctuation in fMRI signals across a population of voxels reflected the participant's perceptual decision. Accuracy increased from when 1 region was considered (similar to 64%) to when 10 regions were used (similar to 78%). When the best classifications per subject were averaged, accuracy levels ranged between 74% and 86% correct. An information theoretic analysis revealed that the information carried by pairs of regions reliably exceeded the sum of the information carried by individual regions, suggesting that information was combined "synergistically" across regions. Our results indicate that the representation of behavioral choice is "distributed" across several brain regions. Such distributed encoding may help prepare the organism to appropriately handle emotional stimuli and regulate the associated emotional response upon the conscious decision that a fearful face is present. In addition, the results show that challenging brain states can be decoded with high accuracy even when "single-trial" data are employed and suggest that multivariate analysis strategies have considerable potential in helping to elucidate the neural correlates of visual awareness and the encoding of perceptual decisions.