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Abstract Value Encoding in Neural Populations But Not Single Neurons.
Journal of Neuroscience ( IF 4.4 ) Pub Date : 2023-05-19 , DOI: 10.1523/jneurosci.1954-22.2023
Justin M Fine 1 , David J-N Maisson 1 , Seng Bum Michael Yoo 1 , Tyler V Cash-Padgett 1 , Maya Zhe Wang 1 , Jan Zimmermann 1 , Benjamin Y Hayden 2
Affiliation  

An important open question in neuroeconomics is how the brain represents the value of offers in a way that is both abstract (allowing for comparison) and concrete (preserving the details of the factors that influence value). Here, we examine neuronal responses to risky and safe options in five brain regions that putatively encode value in male macaques. Surprisingly, we find no detectable overlap in the neural codes used for risky and safe options, even when the options have identical subjective values (as revealed by preference) in any of the regions. Indeed, responses are weakly correlated and occupy distinct (semi-orthogonal) encoding subspaces. Notably, however, these subspaces are linked through a linear transform of their constituent encodings, a property that allows for comparison of dissimilar option types. This encoding scheme allows these regions to multiplex decision related processes: they can encode the detailed factors that influence offer value (here, risky and safety) but also directly compare dissimilar offer types. Together these results suggest a neuronal basis for the qualitatively different psychological properties of risky and safe options and highlight the power of population geometry to resolve outstanding problems in neural coding.SIGNIFICANCE STATEMENT To make economic choices, we must have some mechanism for comparing dissimilar offers. We propose that the brain uses distinct neural codes for risky and safe offers, but that these codes are linearly transformable. This encoding scheme has the dual advantage of allowing for comparison across offer types while preserving information about offer type, which in turn allows for flexibility in changing circumstances. We show that responses to risky and safe offers exhibit these predicted properties in five different reward-sensitive regions. Together, these results highlight the power of population coding principles for solving representation problems in economic choice.

中文翻译:


神经群体而非单个神经元中的抽象值编码。



神经经济学中一个重要的开放问题是大脑如何以抽象(允许比较)和具体(保留影响价值因素的细节)的方式表示报价的价值。在这里,我们检查了雄性猕猴的五个大脑区域对危险和安全选择的神经元反应,这些区域被认为编码了价值。令人惊讶的是,我们发现用于风险和安全选项的神经代码没有可检测到的重叠,即使这些选项在任何区域具有相同的主观值(如偏好所揭示的)。事实上,响应是弱相关的并且占据不同的(半正交)编码子空间。然而,值得注意的是,这些子空间通过其组成编码的线性变换进行链接,这是允许比较不同选项类型的属性。这种编码方案允许这些区域复用决策相关过程:它们可以对影响报价价值(此处为风险和安全)的详细因素进行编码,但也可以直接比较不同的报价类型。这些结果共同表明了风险和安全选择的不同心理特性的神经元基础,并强调了群体几何学解决神经编码中突出问题的能力。意义声明为了做出经济选择,我们必须有某种机制来比较不同的报价。我们认为大脑使用不同的神经代码来提供有风险和安全的报价,但这些代码是线性可转换的。这种编码方案具有双重优势,即允许跨报价类型进行比较,同时保留有关报价类型的信息,从而在不断变化的情况下实现灵活性。 我们表明,对风险和安全报价的反应在五个不同的奖励敏感区域中表现出这些预测特性。总之,这些结果凸显了人口编码原则在解决经济选择中的代表性问题方面的力量。
更新日期:2023-05-17
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