MOBBED: a computational data infrastructure for handling large collections of event-rich time series datasets in MATLAB.
MOBBED: a computational data infrastructure for handling large collections of event-rich time series datasets in MATLAB.
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DOI：
10.3389/fninf.2013.00020
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发表时间：
2013
影响因子：
3.5
通讯作者：
Robbins KA
中科院分区：
文献类型：
--
作者：
Cockfield J;Su K;Robbins KA
监测主动行为期间人脑活动的实验记录了各种模式（例如脑电图、眼动追踪、动作捕捉、呼吸监测）并捕获复杂的环境背景，从而产生大量事件丰富的时间序列数据集。在更现实的行为场景中，受试者内部和受试者之间的反应存在相当大的可变性，需要通过实验在更长的时间内评估更多的受试者。数据的爆炸需要更好的计算基础设施来更系统地探索和处理这些集合。 MOBBED 是一个轻量级、易于使用、可扩展的工具包，允许用户将计算数据库合并到正常的 MATLAB 工作流程中。虽然能够存储相当通用类型的注释数据，但 MOBBED 特别面向多通道时间序列，例如 EEG，其事件流覆盖有传感器数据。 MOBBED 直接支持访问单个事件、数据帧和带时间戳的特征向量，允许用户提出诸如在各种实验条件下同时发生什么类型的事件或特征等问题。数据库提供了从本地文件系统一次处理一个数据集的用户所无法获得的多项优势。除了将主要数据存档在中央位置以节省空间并避免不一致之外，此类数据库还允许用户跨多个数据集管理、搜索和检索事件，而无需读取整个数据集。该数据库还提供用于处理更复杂的事件模式（包括环境和上下文条件）的基础设施。该数据库还可以用作昂贵的中间结果的缓存，这些结果可以在机器学习算法的交叉验证等活动中重用。 MOBBED 是通过 PostgreSQL（一种广泛使用的开源数据库）实现的，并且可以根据 GNU 通用公共许可证在 http://visual.cs.utsa.edu/mobbed 上免费获得。 MOBBED 的源代码和问题报告维护在 http://vislab.github.com/MobbedMatlab/
Experiments to monitor human brain activity during active behavior record a variety of modalities (e.g., EEG, eye tracking, motion capture, respiration monitoring) and capture a complex environmental context leading to large, event-rich time series datasets. The considerable variability of responses within and among subjects in more realistic behavioral scenarios requires experiments to assess many more subjects over longer periods of time. This explosion of data requires better computational infrastructure to more systematically explore and process these collections. MOBBED is a lightweight, easy-to-use, extensible toolkit that allows users to incorporate a computational database into their normal MATLAB workflow. Although capable of storing quite general types of annotated data, MOBBED is particularly oriented to multichannel time series such as EEG that have event streams overlaid with sensor data. MOBBED directly supports access to individual events, data frames, and time-stamped feature vectors, allowing users to ask questions such as what types of events or features co-occur under various experimental conditions. A database provides several advantages not available to users who process one dataset at a time from the local file system. In addition to archiving primary data in a central place to save space and avoid inconsistencies, such a database allows users to manage, search, and retrieve events across multiple datasets without reading the entire dataset. The database also provides infrastructure for handling more complex event patterns that include environmental and contextual conditions. The database can also be used as a cache for expensive intermediate results that are reused in such activities as cross-validation of machine learning algorithms. MOBBED is implemented over PostgreSQL, a widely used open source database, and is freely available under the GNU general public license at http://visual.cs.utsa.edu/mobbed. Source and issue reports for MOBBED are maintained at http://vislab.github.com/MobbedMatlab/
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影响因子：
14.9
作者：
Galperin MY;Fernández-Suárez XM
通讯作者：
Fernández-Suárez XM
影响因子：
3
作者：
Marcus, Daniel S.;Olsen, Timothy R.;Buckner, Randy L.
通讯作者：
Buckner, Randy L.
影响因子：
3.5
作者：
Bellec P;Lavoie-Courchesne S;Dickinson P;Lerch JP;Zijdenbos AP;Evans AC
通讯作者：
Evans AC
影响因子：
3.5
作者：
Poline JB;Breeze JL;Ghosh S;Gorgolewski K;Halchenko YO;Hanke M;Haselgrove C;Helmer KG;Keator DB;Marcus DS;Poldrack RA;Schwartz Y;Ashburner J;Kennedy DN
通讯作者：
Kennedy DN
影响因子：
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作者：
Oostenveld R;Fries P;Maris E;Schoffelen JM
通讯作者：
Schoffelen JM