MOTIVATION Structural connectomics supports understanding aspects of neuronal dynamics and brain functions. Conducting metastudies of tract-tracing publications is one option to generate connectome databases by collating neuronal connectivity data. Meanwhile, it is a common practice that the neuronal connections and their attributes of such retrospective data collations are extracted from tract-tracing publications manually by experts. As the description of tract-tracing results is often not clear-cut and the documentation of interregional connections is not standardized, the extraction of connectivity data from tract-tracing publications could be complex. This might entail that different experts interpret such non-standardized descriptions of neuronal connections from the same publication in variable ways. Hitherto, no investigation is available that determines the variability of extracted connectivity information from original tract-tracing publications. A relatively large variability of connectivity information could produce significant misconstructions of adjacency matrices with faults in network and graph analyzes. The objective of this study is to investigate the inter-rater and inter-observation variability of tract-tracing-based documentations of neuronal connections. To demonstrate the variability of neuronal connections, data of 16 publications which describe neuronal connections of subregions of the hypothalamus have been assessed by way of example. RESULTS A workflow is proposed that allows detecting variability of connectivity at different steps of data processing in connectome metastudies. Variability between three blinded experts was found by comparing the connection information in a sample of 16 publications that describe tract-tracing-based neuronal connections in the hypothalamus. Furthermore, observation scores, matrix visualizations of discrepant connections and weight variations in adjacency matrices are analyzed. AVAILABILITY The resulting data and software are available at http://neuroviisas.med.uni-rostock.de/neuroviisas.shtml.

中文翻译：

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Connectome验证：基于道追踪的固有下丘脑连通性的评估者和连接可靠性。

动机结构性连接学支持理解神经元动力学和脑功能的各个方面。进行管道追踪出版物的荟萃研究是通过整理神经元连通性数据来生成连接基因组数据库的一种选择。同时，通常的做法是由专家手动从道追踪出版物中提取这种追溯性数据归类的神经元联系及其属性。由于对域跟踪结果的描述通常不清晰，区域间连接的文档也不是标准化的，因此从域跟踪出版物中提取连通性数据可能很复杂。这可能需要不同的专家以可变的方式解释来自同一出版物的神经元连接的非标准化描述。到目前为止，没有调查可以确定从原始管道跟踪出版物中提取的连通性信息的可变性。连接性信息的相对较大的可变性可能会导致邻接矩阵的严重错误构造，并在网络和图形分析中出现故障。这项研究的目的是调查基于道追踪的神经元连接文献的评分者和观察者之间的变异性。为了证明神经元连接的可变性，已经通过实例评估了描述下丘脑子区域的神经元连接的16种出版物的数据。结果提出了一种工作流，该工作流允许在连接组元研究中检测数据处理不同步骤的连接性变化。通过比较16个出版物的样本中的连接信息发现三位盲专家之间的差异，这些出版物描述了下丘脑中基于道追踪的神经元连接。此外，分析了观察分数，邻接关系的矩阵可视化以及邻接矩阵的权重变化。可用性结果数据和软件可从http://neuroviisas.med.uni-rostock.de/neuroviisas.shtml获得。