Unified probabilistic modelling of adaptive spatial-temporal structures in the human brain

从经验中学习并使我们的行为适应新的情况是我们日常互动的基本技能。但是，是什么样的大脑可塑性机制介导了一个人在复杂任务训练中取得进步的能力？在适应能力方面，“好”和“差”学习者的区别是什么？功能性脑成像技术的最新进展为我们提供了研究人脑如何随着学习而变化的独特机会。然而，现有的方法主要集中在对单个会话内的大脑活动数据进行建模，而不是跨训练会话。因此，这些方法不能捕获随着训练的进行而在大脑活动中出现的更大规模的依赖性。我们将开发一种新的方法，允许在学习过程中测量的一系列大脑成像数据的整体统一建模。使用这种方法，我们将研究大脑的变化，从复杂的视觉任务的广泛训练的结果。我们的工作将为科学家和从业者提供先进的工具，用于使用大脑活动测量来了解大脑学习机制以及它们如何提高我们做出复杂决策的能力。所提出的方法可能有预测能力作出推论的“原型”的学习模式，可用于预测适应性行为的个人与不同的学习策略和设计培训计划，以适应个人的能力和需求。因此，我们的研究结果有潜在的影响，设计专门的培训计划，考虑到个人的学习能力。这些方案可用于正常和病理性发育和衰老（例如中风、神经变性疾病）的教育或干预和康复。

Learning from experience and adapting our behaviour to new situations is a fundamental skill for our everyday interactions. But what are the brain plasticity mechanisms that mediate an individual's ability to make progress during training on complex tasks? What is it that differentiates `good' from `poor' learners in their ability to adapt? Recent advances in functional brain imaging technology provide us with the unique opportunity to study how the human brain changes with learning. However, the existing methods focus predominantly on modelling brain activity data within a single session rather than across training sessions. As such, these methods are not capable of capturing larger scale dependencies emerging in brain activity as training progresses. We will develop a novel methodology that allows holistic unified modelling of a series of brain imaging data measured during the course of learning. Using this methodology we will study brain changes that result from extensive training on complex visual tasks. Our work will offer scientists and practitioners advanced tools for using brain activity measurements to understand the brain learning mechanisms and how they improve our ability to make complex decisions. The proposed methodology may have predictive power for making inferences about 'prototypical' learning patterns that can be used to predict adaptive behaviour in individuals with different learning strategies and design training schemes tailored to the individuals' abilities and needs. Hence our findings have potential implications for the design of dedicated training programmes that take into account an individual's learning capacity. Such programmes may have applications in education or intervention and rehabilitation in normal and pathological development and ageing (e.g. stroke, neurodegenerative disorders).