Neuronal substrates underlying the construction of value in humans

我们的个人偏好是如何产生的？我们都有许多偏好和自己的个人品味-但为什么我们会喜欢一些东西而不喜欢其他东西呢？例如，为什么一个人喜欢薯片而不喜欢爆米花，为什么一个人喜欢流行音乐而不喜欢西部乡村音乐，为什么一个人喜欢棒球而不喜欢篮球，为什么一个人喜欢伦勃朗的具象绘画而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，即大脑依赖于物体的“特征”，即构成物体的元素-例如食物中的成分，或绘画中的颜色，形状和纹理，以便决定有多少东西是喜欢或不喜欢。假设是脑细胞（神经元）对物体的这些基本特征做出反应，其他神经元整合这些特征，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中记录下来，而人们对他们喜欢的各种物品，包括食物，视觉艺术甚至服装物品进行简单的判断。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，以及正在接受难治性癫痫治疗的患者的慷慨。在进行脑外科手术切除癫痫脑组织之前，患者将小电极暂时放置在大脑中，以定位癫痫发作，作为治疗的一部分。这些患者通常愿意自愿参加研究，从而获得了直接测量神经元电活动的难得机会。了解我们大脑中的神经元如何形成我们的偏好，可以帮助我们更好地理解人们在真实的世界中是如何做出决定的。虽然我们知道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被计算出来的。在这个项目中要测试的主要假设是，从食品到消费品到艺术品的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方式构建的。虽然许多先前的研究已经使用神经成像技术（如功能性磁共振成像或fMRI）检查了价值构建，但只能通过该技术的时空分辨率获得见解，而该技术无法测量单个细胞。因此，很少有人知道刺激特征是如何由单个细胞表示的，并被整合以计算整体刺激值。在这里，可以通过在人类癫痫患者中使用颅内记录来克服这种限制，同时他们执行三种不同的任务来探索价值构建。这项研究集中在大脑价值网络的三个关键部分：杏仁核、外侧眶额和腹内侧前额叶皮层。这些方法的空间分辨率使我们能够深入了解单个特征在神经元水平上是如何表示的，而时间分辨率使我们能够识别特征被积极整合以产生整体价值信号的时间动态。杏仁核和外侧眶额皮质的特征被假设为整合在腹内侧前额叶皮质中产生价值信号。此外，该研究的目的是解决的手段，其中价值信号改变后，在一个人的总体目标的变化，比较一个模型，其中功能直接调制的变化在上下文中，对一个替代方案，其中功能神经元和价值编码神经元之间的连接调制的目标上下文，但功能表示保持不变。该项目有望产生对人类大脑中产生价值信号的神经计算的基本机械见解，以及我们个人偏好的起源和神经基础，反过来，它又在指导人类决策方面发挥着重要作用-该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查进行评估，被认为值得支持的搜索.

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.