使用贝叶斯分组功能配准改进的fMRI-based疼痛预测
Improved fMRI-based Pain Prediction using Bayesian Group-wise Functional Registration
摘要：
近年来，神经影像学经历了一个范式转变，从传统的大脑映射方法转向开发集成的，多变量的大脑模型，可以预测精神事件的类别。然而，在标准解剖对齐后，大脑解剖结构和功能定位的个体间差异仍然是进行这种分析的主要限制，因为它导致后续预测模型中受试者之间的特征不对齐。
英文摘要：
In recent years, neuroimaging has undergone a paradigm shift, moving away from the traditional brain mapping approach toward developing integrated, multivariate brain models that can predict categories of mental events. However, large interindividual differences in brain anatomy and functional localization after standard anatomical alignment remain a major limitation in performing this analysis, as it leads to feature misalignment across subjects in subsequent predictive models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
