The collective activity of a population of neurons, beyond the properties of individual cells, is crucial for many brain functions. A fundamental question is how activity correlations between neurons affect how neural populations process information. Over the past 30 years, major progress has been made on how the levels and structures of correlations shape the encoding of information in population codes. Correlations influence population coding through the organization of pairwise-activity correlations with respect to the similarity of tuning of individual neurons, by their stimulus modulation and by the presence of higher-order correlations. Recent work has shown that correlations also profoundly shape other important functions performed by neural populations, including generating codes across multiple timescales and facilitating information transmission to, and readout by, downstream brain areas to guide behaviour. Here, we review this recent work and discuss how the structures of correlations can have opposite effects on the different functions of neural populations, thus creating trade-offs and constraints for the structure–function relationships of population codes. Further, we present ideas on how to combine large-scale simultaneous recordings of neural populations, computational models, analyses of behaviour, optogenetics and anatomy to unravel how the structures of correlations might be optimized to serve multiple functions.

一群神经元的集体活动，超越了单个细胞的特性，对许多大脑功能至关重要。一个基本问题是神经元之间的活动相关性如何影响神经群体如何处理信息。在过去的 30 年里，在相关的水平和结构如何塑造人口代码中的信息编码方面取得了重大进展。相关性通过组织成对活动相关性来影响种群编码，这些相关性与调节单个神经元的相似性有关，通过它们的刺激调制和高阶相关性的存在。最近的研究表明，相关性还深刻地塑造了神经群体执行的其他重要功能，包括跨多个时间尺度生成代码，并促进信息传输到下游大脑区域并由下游大脑区域读出以指导行为。在这里，我们回顾了最近的这项工作，并讨论了相关结构如何对神经群体的不同功能产生相反的影响，从而为群体代码的结构-功能关系创造权衡和约束。此外，我们提出了关于如何结合神经群体的大规模同步记录、计算模型、行为分析、光遗传学和解剖学的想法，以揭示如何优化相关结构以服务于多种功能。我们回顾了最近的这项工作，并讨论了相关结构如何对神经群体的不同功能产生相反的影响，从而为群体代码的结构-功能关系创造权衡和约束。此外，我们提出了关于如何结合神经群体的大规模同步记录、计算模型、行为分析、光遗传学和解剖学的想法，以揭示如何优化相关结构以服务于多种功能。我们回顾了最近的这项工作，并讨论了相关结构如何对神经群体的不同功能产生相反的影响，从而为群体代码的结构-功能关系创造权衡和约束。此外，我们提出了关于如何结合神经群体的大规模同步记录、计算模型、行为分析、光遗传学和解剖学的想法，以揭示如何优化相关结构以服务于多种功能。