A novel adaptive sampling technique for mapping brain function

诊断性认知测试用于许多临床情况；例如，评估记忆、注意力和其他过程的认知测试可用于发现痴呆症的早期迹象，并监测创伤性脑损伤后的认知障碍。这种诊断测试被认为可以激活不同的大脑系统。然而，这些测试并不是为此目的而设计的，因此可能会有更好、更灵敏的测试。我们将使用一种新的功能性脑成像技术，“自动”找到激活特定大脑系统的最佳认知测试。这项新技术被称为神经适应性贝叶斯优化。它使用神经成像（功能性核磁共振成像）在强大的机器学习算法的指导下实时评估大脑功能。这种方法可以探索许多认知测试，并找到与特定大脑系统最密切相关的测试。这是一种“闭环”方法：算法建议一个认知任务，分析它如何影响大脑，并利用这些知识更新它“知道”的关于哪个认知任务最适合激活大脑区域的信息，所有这些都是自动的；正如我们的试点数据所显示的那样，通过让人类科学家“脱离循环”，它可能会更高效、更公正，并非常迅速地搜索更多类型的认知任务。我们将利用这项技术开发一种新的诊断电池，我们希望它能比目前用于区分与神经和精神疾病相关的两个重要大脑系统的测试更敏感。如果项目成功，我们将与临床医生合作，在一系列临床情况下使用该工具来改进认知测试，并帮助更好地诊断患者的认知问题。

Diagnostic cognitive tests are used in many clinical situations; for example, cognitive tests assessing memory, attention and other processes can be used to detect early signs of dementia and monitor cognitive impairment after a traumatic brain injury. Such diagnostic tests are thought to activate different brain systems. However, the tests have not been designed for this purpose, and so there may be better, more sensitive tests. We will use a new functional brain imaging technique that "automatically" finds the best cognitive tests that activate specific brain systems. The new technique is called neuroadaptive Bayesian optmisation. It uses neuroimaging (functional MRI) to assess brain function in real-time, guided by a powerful machine learning algorithm. This approach can explore across many cognitive tests and find the ones that are most strongly associated with a specific brain system. This is a "closed-loop" approach: the algorithm suggests a cognitive task, analyses how this affects the brain, and uses this knowledge to update what it "knows" about which cognitive task is best for activating that brain region, all automatically; by taking the human scientist "out-of-the-loop", it is possible to be much more efficient and unbiased and search over many more types of cognitive task very quickly, as our pilot data shows.We will use this technique to develop a new diagnostic battery that we hope will be more sensitive than tests currently in use to distinguish between two important brain systems that have been associated with neurological and psychiatric disorders. If the project is successful, we would work with clinicians to use the tool to improve cognitive testing in a range of clinical situations and help diagnose cognitive problems better in patients.