内容来源：OpenScience

基于神经影像对幼儿认知进行个体化的预测

“预测”是科学的目标之一。近年来，随着大规模神经影像数据的出现，研究者能够将更多的比较复杂的统计方法应用于这些数据，并使用神经影像数据来预测行为、症状或者自我报告的数据。与其他领域相似，预测的结果也需要能够被重复。

在发展心理学/认知神经科学领域，预测儿童的行为/能力等尤其具有吸引力。但使用神经影像预测儿童行为/能力是否稳定？有没有需要注意的坑？本期我们邀请到了新加坡国立大学的张晗博士，为大家分享她们近期被接收的工作。注意：本次报告语言为英文，可使用中文提问和交流。

时间：北京时间8月1日(周六)21:00 ~ 21:40

Zoom：https://auckland.zoom.us/j/94791664886

Meeting ID: 947 9166 4886

 

报告人：

ZHANG Han
Research Fellow of Developmental Neuroscience,
Laboratory for Medical Image Data Sciences,
National University of Singapore

题目：Neuroimaging-based Individual Prediction of Cognition in Young Children

摘要

As we are moving towards a translational neuroscience era, more and more studies employ predictive modeling to pursue neuromarkers in predicting behaviors. People believe that neuromarkers may eventually benefit educational or clinical practices in real-world settings. However, very limited studies enrolled children or preschoolers. From a developmental perspective, is the brain-behavior prediction in children as robust as it in adults? Taking working memory as an example, we examined the predictive power of intrinsic brain functional networks from early childhood to adulthood. I will share our findings and concerns. Meanwhile, I would like to invite you to think about the effective role of predictive modeling in cognitive neuroscience.