An update to Hippocampome.org by integrating single-cell phenotypes with circuit function in vivo.

An update to Hippocampome.org by integrating single-cell phenotypes with circuit function in vivo.
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DOI:
10.1371/journal.pbio.3001213
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发表时间:
2021-05
期刊:
影响因子:
9.8
通讯作者:
Ascoli GA
Ascoli GA
中科院分区:
生物学1区
文献类型:
--
作者:
Sanchez-Aguilera A;Wheeler DW;Jurado-Parras T;Valero M;Nokia MS;Cid E;Fernandez-Lamo I;Sutton N;García-Rincón D;de la Prida LM;Ascoli GA

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了解大脑运作需要将基本行为特征与不同大脑子电路的细胞类型特定动态联系起来。这需要一个系统来对神经元和电路的基本操作模式进行分类。体内持续振荡过程中放电行为的单细胞表型为内嗅海马功能提供了大量证据,但数据分散且多样。在这里,我们挖掘文献来搜索有关 Hippocampome.org 中定义的 100 多种海马/内嗅神经元类型的时相动态的信息。我们确定了缺失和未解决的知识片段(例如,特定神经元类型的首选 θ 相位),并用我们自己的新数据补充了数据集。通过面对大脑状态和记录方法的影响,我们强调了不同条件下的等效性和差异,并提供了许多新颖的观察结果。我们展示了基于形态识别神经元振荡特征的启发式方法如何帮助对单细胞的细胞外记录进行分类,并讨论将单细胞表型与电路功能整合的未来机遇和挑战。通过将体内振荡期间的单细胞放电行为与体外形态和分子神经元分类相结合,本研究标准化了一个框架,用于解释不同电路模块的功能作用并将细胞外记录归因于已识别的神经元类型。
Understanding brain operation demands linking basic behavioral traits to cell-type specific dynamics of different brain-wide subcircuits. This requires a system to classify the basic operational modes of neurons and circuits. Single-cell phenotyping of firing behavior during ongoing oscillations in vivo has provided a large body of evidence on entorhinal–hippocampal function, but data are dispersed and diverse. Here, we mined literature to search for information regarding the phase-timing dynamics of over 100 hippocampal/entorhinal neuron types defined in Hippocampome.org. We identified missing and unresolved pieces of knowledge (e.g., the preferred theta phase for a specific neuron type) and complemented the dataset with our own new data. By confronting the effect of brain state and recording methods, we highlight the equivalences and differences across conditions and offer a number of novel observations. We show how a heuristic approach based on oscillatory features of morphologically identified neurons can aid in classifying extracellular recordings of single cells and discuss future opportunities and challenges towards integrating single-cell phenotypes with circuit function. By integrating single-cell firing behavior during in vivo oscillations with morphological and molecular neuron classification in vitro, this study standardizes a framework for interpreting the functional roles of distinct circuit modules and ascribing extracellular recordings to identified neuron types.
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