Neuronal substrates underlying the construction of value in humans

我们的个人偏好是如何产生的？我们都有很多喜好，对自己的品味也有自己的看法--但为什么我们喜欢一些东西，而不喜欢另一些东西呢？例如，为什么一个人可能喜欢薯片但不喜欢爆米花、流行音乐而不是西部乡村音乐、棒球而不是篮球，或者喜欢伦勃朗的具象绘画但不喜欢杰克逊·波洛克的抽象现代艺术？我们在这个项目中要解决的主要问题是，我们的偏好是如何在大脑中形成的？研究人员的目标是测试一种理论，即大脑依赖于组成物体的元素--比如食物中的成分，或者画中的颜色、形状和纹理--的物体的“特征”，以决定人们对某物的喜好程度。假设是脑细胞(神经元)对物体的这些基本特征做出反应，其他神经元对这些特征进行整合，形成整体偏好判断。为了测试这一点，神经元的反应直接从人脑记录下来，同时人们对他们对包括食物、视觉艺术甚至服装在内的各种物品的喜好做出简单的判断。这项研究之所以成为可能，是因为脑外科手术的安全技术进步，以及正在接受顽固性癫痫治疗的患者的慷慨。在切除癫痫脑组织的脑部手术之前，患者会在大脑中临时放置小电极，以定位癫痫发作，作为治疗的一部分。这些患者往往愿意自愿参加研究，这为直接测量神经元的电活动提供了难得的机会。了解我们大脑中的神经元是如何形成我们的偏好的，可以帮助我们更好地理解人们在现实世界中是如何做出决定的。虽然价值信号是在大脑中编码的，但一个基本的问题仍然是，这些信号最初是如何计算出来的。这个项目要检验的主要假设是，从食物到消费品再到艺术，刺激的价值信号是由大脑通过整合刺激的组成特征或属性以动态的方式构建的。虽然之前的一些研究已经检验了使用神经成像技术(如功能磁共振成像或功能磁共振成像)来构建价值，但只能通过该技术的时空分辨率来获得洞察力，因为该技术不能测量单个细胞。因此，关于刺激特征是如何由单个细胞表示并结合起来计算整体刺激值的，人们知之甚少。在这里，这一限制可以通过使用人类癫痫患者的颅内记录来克服，同时他们执行三种不同的探测值构建任务。这项研究集中在大脑价值网络的三个关键部分：杏仁核、外侧眶前叶和腹内侧前额叶皮质中的神经元群体。这些方法的空间分辨率使我们能够深入了解单个特征是如何在神经元水平上表示的，而时间分辨率允许我们识别特征被主动整合以产生整体价值信号的时间动力学。杏仁核和外侧眼眶前额叶皮质的功能被假设为整合在一起，以在腹内侧额前皮质产生价值信号。此外，这项研究的目的是解决价值信号在一个人的总体目标改变后被改变的方式，将特征直接被语境变化调制的模型与特征神经元和价值编码神经元之间的连通性被目标语境调制但特征表征保持不变的替代模型进行比较。这个项目承诺对人类大脑中产生价值信号的神经计算以及我们个人偏好的起源和神经基础产生基本的机械性见解，这些偏好反过来在指导人类决策方面发挥着基础性作用。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

How do our personal preferences arise? We all have a multitude of preferences and a sense of our own individual taste – but why do we come to like some things and not like others? For instance, why might a person like potato chips but not like popcorn, pop music rather than country-western, baseball rather than basketball, or come to like a representational painting by Rembrandt, but dislike abstract, modern art of Jackson Pollock? The major question we are addressing in this project is how are our preferences formed in the brain? The researchers aim to test a theory that the brain relies on “features” of objects which are the elements that make up an object – such as the ingredients in a food item, or the color, shapes and textures in a painting, in order to make a decision about how much something is liked or not. The hypothesis is that the brain cells (neurons) respond to these elementary features of an object, and that other neurons integrate over these features to form an overall preference judgment. To test for this, the responses of neurons are recorded directly from the human brain, while people make simple judgements about how much they like a variety of items including food, visual art and even clothing items. This research is made possible because of safe technological advances in brain surgery, and the generosity of patients who are being treated for intractable epilepsy. Prior to brain surgery to remove the epileptic brain tissue, patients have small electrodes temporarily placed into their brain to locate their seizures as part of their treatment. These patients are often willing to volunteer to take part in research studies, yielding a rare opportunity to measure electrical activity from neurons directly. Understanding how neurons in our brain form our preferences could help us better understand how people make decisions in the real world.While value signals are known to be encoded in the brain, a fundamental question remains about how such signals come to be computed in the first place. The major hypothesis to be tested in this project is that value signals for stimuli ranging from foods to consumer goods through to art, are constructed by the brain in a dynamic fashion by integrating over the component features or attributes of a stimulus. While a number of prior studies have examined value construction using neuroimaging techniques (such as functional magnetic resonance imaging or fMRI), insights can only be gained over the spatiotemporal resolution of the technique, which cannot measure single cells. As a consequence, little is known about how stimulus features are represented by individual cells and integrated to compute an overall stimulus-value. Here, this limitation can be overcome through the use of intracranial recordings in human epilepsy patients while they perform three different tasks probing value construction. The research focuses on neuronal populations in the three key parts of the value network in the brain: the amygdala, lateral orbitofrontal, and ventromedial prefrontal cortex. The spatial resolution of these methods enables insight into how individual features are represented at the neuronal level, while the temporal resolution allows us to identify the temporal dynamics by which features are actively integrated to yield an overall value signal. Features in the amygdala and lateral orbitofrontal cortex are hypothesized to be integrated to yield value signals in the ventromedial prefrontal cortex. Furthermore, the research aims to address the means by which value signals are altered following a change in one’s overall goals, comparing a model in which features are modulated directly by a change in context, against an alternative in which the connectivity between feature neurons and value coding neurons are modulated by goal context, yet feature representations remain unchanged. This project promises to yield fundamental mechanistic insights into the neural computations underlying the production of value signals in the human brain, and the origin and neural basis of our individual preferences, which in turn serve a fundamental role in guiding human decision-making.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.