Confidence of probabilistic predictions modulates the cortical response to pain
Confidence of probabilistic predictions modulates the cortical response to pain
复制标题
概率预测的置信度调节皮质对疼痛的反应
DOI：
10.1101/2022.08.11.503296
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Mulders D
中科院分区：
文献类型：
--
作者：
Mulders D
疼痛通常会随着时间的推移而演变，大脑需要了解这种时间演变，以预测未来疼痛可能如何变化，并确定行为方向。这个过程被称为时间统计学习（TSL）。最近，它已被证明，TSL疼痛序列可以实现使用最佳贝叶斯推理，这是编码在体感处理区域。在这里，我们调查是否这些概率预测的信心调制的EEG反应，伤害性刺激，使用TSL任务。信心衡量的是概率预测的不确定性，而不管其实际结果如何。贝叶斯模型规定，概率预测的置信度应该与输入输入和权重学习相结合，这样它就可以调节对有害刺激的EEG反应的早期分量，并且这应该通过负相关来捕获：当置信度较高时，早期神经反应较小，因为大脑更多地依赖于预期/预测，而较少依赖于感官输入（反之亦然）。我们发现，参与者能够预测的序列转移概率使用贝叶斯推理，有一些遗忘。然后，我们发现这些概率预测的置信度与顶点电位的N2和P2分量的幅度呈负相关：参与者对他们的预测越有信心，顶点电位就越小。这些结果证实了贝叶斯学习模型的关键预测，并阐明了早期EEG对伤害性刺激的反应的功能意义，因为它与置信加权统计学习有关。
Pain typically evolves over time, and the brain needs to learn this temporal evolution to predict how pain is likely to change in the future and orient behavior. This process is termed temporal statistical learning (TSL). Recently, it has been shown that TSL for pain sequences can be achieved using optimal Bayesian inference, which is encoded in somatosensory processing regions. Here, we investigate whether the confidence of these probabilistic predictions modulates the EEG response to noxious stimuli, using a TSL task. Confidence measures the uncertainty about the probabilistic prediction, irrespective of its actual outcome. Bayesian models dictate that the confidence about probabilistic predictions should be integrated with incoming inputs and weight learning, such that it modulates the early components of the EEG responses to noxious stimuli, and this should be captured by a negative correlation: when confidence is higher, the early neural responses are smaller as the brain relies more on expectations/predictions and less on sensory inputs (and vice versa). We show that participants were able to predict the sequence transition probabilities using Bayesian inference, with some forgetting. Then, we find that the confidence of these probabilistic predictions was negatively associated with the amplitude of the N2 and P2 components of the vertex potential: the more confident were participants about their predictions, the smaller the vertex potential. These results confirm key predictions of a Bayesian learning model and clarify the functional significance of the early EEG responses to nociceptive stimuli, as being implicated in confidence-weighted statistical learning.
登录
查看更多内容
影响因子：
4.3
作者：
Meyniel F;Maheu M;Dehaene S
通讯作者：
Dehaene S
影响因子：
4.3
作者：
Meyniel F;Schlunegger D;Dehaene S
通讯作者：
Dehaene S
DOI：
10.1073/pnas.1615773114
发表时间：
2017-05-09
影响因子：
11.1
作者：
Meyniel, Florent;Dehaene, Stanislas
通讯作者：
Dehaene, Stanislas
学习疼痛的统计数据：计算和神经机制
DOI：
10.1101/2021.10.21.465270
发表时间：
2021
期刊：
--
影响因子：
--
作者：
Mancini F
通讯作者：
Mancini F
疼痛的层次模型：推理、信息寻求和适应性控制。
影响因子：
5.7
作者：
K. Sasaki;Y. Koike;H. Azehara;H. Hokari;M. Fujihira
通讯作者：
M. Fujihira