Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6) and JARA Institute Brain Structure-Function Relationships (JBI-1 / INM-10), Jülich Research Centre, Jülich, Germany.
Bernstein Center Freiburg, Albert-Ludwig University of Freiburg, Freiburg im Breisgau, Germany.
PLoS Comput Biol. 2019 Apr 25;15(4):e1006781. doi: 10.1371/journal.pcbi.1006781. eCollection 2019 Apr.
Complexity and heterogeneity are intrinsic to neurobiological systems, manifest in every process, at every scale, and are inextricably linked to the systems' emergent collective behaviours and function. However, the majority of studies addressing the dynamics and computational properties of biologically inspired cortical microcircuits tend to assume (often for the sake of analytical tractability) a great degree of homogeneity in both neuronal and synaptic/connectivity parameters. While simplification and reductionism are necessary to understand the brain's functional principles, disregarding the existence of the multiple heterogeneities in the cortical composition, which may be at the core of its computational proficiency, will inevitably fail to account for important phenomena and limit the scope and generalizability of cortical models. We address these issues by studying the individual and composite functional roles of heterogeneities in neuronal, synaptic and structural properties in a biophysically plausible layer 2/3 microcircuit model, built and constrained by multiple sources of empirical data. This approach was made possible by the emergence of large-scale, well curated databases, as well as the substantial improvements in experimental methodologies achieved over the last few years. Our results show that variability in single neuron parameters is the dominant source of functional specialization, leading to highly proficient microcircuits with much higher computational power than their homogeneous counterparts. We further show that fully heterogeneous circuits, which are closest to the biophysical reality, owe their response properties to the differential contribution of different sources of heterogeneity.
复杂性和异质性是神经生物学系统的固有特性，表现在每个过程、每个尺度上，并且与系统的集体涌现行为和功能密不可分。然而，大多数研究生物启发的皮质微循环的动力学和计算特性的研究往往假设（通常是为了分析的可处理性）神经元和突触/连接参数具有很大程度的同质性。虽然简化和还原论对于理解大脑的功能原则是必要的，但是忽略皮质组成中的多种异质性的存在，而这些异质性可能是其计算能力的核心，将不可避免地无法解释重要的现象，并限制皮质模型的范围和普遍性。我们通过在一个具有生物物理合理性的 2/3 层微电路模型中研究神经元、突触和结构特性的个体和组合功能作用来解决这些问题，该模型是由多个来源的经验数据构建和约束的。这种方法得益于大规模、精心整理的数据库的出现，以及过去几年实验方法学的实质性改进。我们的结果表明，单个神经元参数的可变性是功能专业化的主要来源，导致具有比同质对应物更高计算能力的高度专业的微电路。我们进一步表明，最接近生物物理现实的完全异质电路的响应特性归因于不同异质源的差异贡献。
