Center for Neural Informatics, Structures, & Plasticity, Krasnow Institute for Advanced Study, George Mason University, Fairfax, United States.
Bioengineering Department and Center for Neural Informatics, Structures, & Plasticity, College of Engineering and Computing, George Mason University, Fairfax, United States.
Elife. 2024 Feb 12;12:RP90597. doi: 10.7554/eLife.90597.
Hippocampome.org is a mature open-access knowledge base of the rodent hippocampal formation focusing on neuron types and their properties. Previously, Hippocampome.org v1.0 established a foundational classification system identifying 122 hippocampal neuron types based on their axonal and dendritic morphologies, main neurotransmitter, membrane biophysics, and molecular expression (Wheeler et al., 2015). Releases v1.1 through v1.12 furthered the aggregation of literature-mined data, including among others neuron counts, spiking patterns, synaptic physiology, in vivo firing phases, and connection probabilities. Those additional properties increased the online information content of this public resource over 100-fold, enabling numerous independent discoveries by the scientific community. Hippocampome.org v2.0, introduced here, besides incorporating over 50 new neuron types, now recenters its focus on extending the functionality to build real-scale, biologically detailed, data-driven computational simulations. In all cases, the freely downloadable model parameters are directly linked to the specific peer-reviewed empirical evidence from which they were derived. Possible research applications include quantitative, multiscale analyses of circuit connectivity and spiking neural network simulations of activity dynamics. These advances can help generate precise, experimentally testable hypotheses and shed light on the neural mechanisms underlying associative memory and spatial navigation.
海马体图谱组织(Hippocampome.org)是一个成熟的开放获取的啮齿动物海马体结构知识库,专注于神经元类型及其特性。此前,Hippocampome.org v1.0 建立了一个基础分类系统,根据其轴突和树突形态、主要神经递质、膜生物物理学和分子表达,确定了 122 种海马体神经元类型(Wheeler 等人,2015 年)。从 v1.1 到 v1.12 的版本进一步汇总了文献挖掘的数据,包括神经元计数、尖峰模式、突触生理学、体内放电相位和连接概率等。这些额外的特性使这个公共资源的在线信息量增加了 100 多倍,使科学界能够进行无数的独立发现。这里介绍的 Hippocampome.org v2.0 除了整合了 50 多种新的神经元类型外,现在还将其重点重新定位为扩展功能,以构建真实规模、具有详细生物学特性的数据驱动计算模拟。在所有情况下,可下载的模型参数都直接链接到从中衍生的特定经过同行评审的经验证据。可能的研究应用包括对电路连接的定量、多尺度分析和活动动力学的尖峰神经网络模拟。这些进展可以帮助生成精确的、可通过实验验证的假设,并阐明与联想记忆和空间导航相关的神经机制。