Neuronal circuits for perceptual inference

21世纪的神经科学正在经历一场引人注目的变革。在上个世纪，人们普遍认为大脑感知环境，认知过程根据接收到的感官信息进行工作，然后运动系统开始行动。一种新的观点出现了，认为真正的感觉实际上可能很少，大脑不断地对世界做出预测，并随着感觉信息的变化而更新。然而，当这些预测不准确、薄弱或不可靠时，它们就会产生异常的感觉和行为，就像现在许多脑部疾病所涉及的那样。支撑这一“感知推理”过程的基本神经元回路被认为是复杂行为的基础，需要更好地从神经生物学角度理解，以便临床团队改善患者的诊断和治疗。大脑的神经元回路能够产生预测并有力地影响我们的行为，这与繁忙的高速公路类似，车辆朝不同的方向行驶，它们的协调运动将反映出大脑神经元之间的信息流路径。然而，这种神经相互作用发生在一般可用的人脑成像扫描仪无法看到的尺度上。认识到需要更强大的脑部扫描仪，英国的资助者、大学和慈善机构已经投入了大量资金（总计约1.5亿至2亿英镑）用于强大的人体扫描仪和研究经费。这些扫描仪分布在英国各地，因为它们比以前的扫描仪具有更高的分辨率，它们提高了以所需的亚毫米分辨率可视化一些大脑信息高速公路的可能性。英国在这一领域的投资旨在从经济上刺激具有巨大社会价值问题的科学研究和创新，并支持英国生物科学的进步，从而带来更好的扫描仪、机器、技术和患者治疗。回到能够可视化大脑中信息流动的高速公路的类比，问题在于，人类扫描仪正在获得相互矛盾或令人惊讶的结果。目前还不清楚基本回路的哪些方面可以在人类中可视化。这需要在灵长类动物模型中进行基础研究，因为为了真正可视化大脑中的交通流量（大脑的交通工具），需要研究和操纵回路中的神经元。这种对复杂行为很重要的感知推理回路涉及到在人类和非人类灵长类动物中进化分化的前额皮质部分，因此需要猕猴。灵长类动物的研究也可以显示这些回路的哪些方面可以用强大的大脑扫描仪来可视化，比如那些可以用于人类的扫描仪。我们建议在非人类灵长类动物模型中推进复杂行为的神经回路研究，并通过使用脑成像技术建立与人类更直接的对应关系，该技术可以立即为人类神经成像研究提供信息和指导。实现这一目标将支持当前和未来对可用于人类患者的尖端脑成像系统和技术的投资。随着关于如何解释人类大脑成像信号所显示的信息的增长，这可能在未来也会导致对非人类动物研究的进一步减少。该提案旨在为动物研究提供不可或缺的补充，为基本神经元回路的理论和计算模型提供信息，并为如何用机器模拟这些回路功能或通过非侵入性脑刺激或脑机接口设备对患者进行潜在的康复提供重要的神经生物学信息。

Neuroscience in the 21st century is undergoing a remarkable transformation. In the prior century, a common belief was that the brain senses the environment, cognitive processes work with the sensory information that they receive, and then the motor system acts. A new view has emerged that there may actually be very little true sensation and that the brain is constantly making predictions about the world and updating them as sensory information changes. However, when these predictions are inaccurate, weak or unreliable they create abnormal sensations and behaviour, as now implicated in many brain disorders. The basic neuronal circuit that underpins this process of 'perceptual inference' is thought to be the basis for complex behaviour and needs to be better neurobiologically understood in order for clinical teams to improve patient diagnosis and treatment.An analogy for the brain's neuronal circuit that creates predictions and powerfully influences our behaviour is a busy highway where vehicles moving in different directions and coordinating their movement would reflect the pathways of information flow between neurons in the brain. However, such neural interactions occur at scales that are not visible with the commonly available human brain imaging scanners. Recognising the need for more powerful brain scanners, UK funders, universities and charities have invested substantial amounts (~£150-200M in total) into powerful human scanners and research funding to use them. These scanners are distributed throughout the UK and because they have much higher resolution capabilities than their predecessors, they raise the possibility of being able to visualise some of the brain's information highways with the required sub-millimetre resolution. The UK investment in this domain aims to economically stimulate scientific research and innovation on questions of tremendous societal value and to support UK biosciences advances leading to better scanners, machines, technology and patient treatment.The problem, returning to the analogy of being able to visualise the highways of information flow in the brain, is that conflicting or surprising results are being obtained with the human scanners. It is currently not clear which aspects of the basic circuit could be visualised in humans. This requires foundational research in a primate model, because in order to truly visualise the flow of traffic in the brain (the brain's vehicles), neurons in the circuit need to be studied and manipulated. This perceptual inference circuit important for complex behaviour involves parts of prefrontal cortex that have evolutionarily differentiated in human and nonhuman primates, thereby requiring macaque monkeys. The primate research can also show which aspects of these circuits could be visualised with powerful brain scanners, such as those available for humans. We propose to advance the study of neuronal circuits for complex behaviour in a nonhuman primate model and to establish a more direct correspondence to humans by way of using a brain imaging technique that can immediately inform and guide neuroimaging studies with humans. Achieving this will support the delivery on current and future investment in cutting-edge brain imaging systems and technology available for human patients. As information grows on how to interpret what the human brain imaging signal shows, this may in the future also lead to further reduction on the reliance on nonhuman animal research. This proposal aims to provide an indispensable complement of animal research that would inform theoretical and computational models of the fundamental neuronal circuit, and it could provide crucial neurobiological information on how such circuit functions could be emulated with machines or potentially rehabilitated with non-invasive brain stimulation or brain-machine interfacing devices in patients.