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Jure Demšar1,2, Aleksij Kraljič2, Andraž Matkovič2,3,4

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此摘要是机器生成的。

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关键词:
数据分析数据分析数据分析处理数据的数据处理.神经成像是一种神经成像.可复制性的可复制性

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科学领域:

  • 神经成像是一种神经成像.
  • 计算神经科学是一种神经科学.
  • 数据科学数据科学数据科学

背景情况:

  • 神经成像数据的预处理和分析是复杂的,需要多种工具和参数调整.
  • 目前的方法往往缺乏足够的细节来实现完全的透明度和可重复性.
  • 这种复杂性阻碍了神经成像工作流程的共享和复制.

研究的目的:

  • 介绍QuNex配方,定义和执行完整的神经成像工作流程的框架.
  • 提高神经成像数据处理中的透明度,可复制性和标准化.
  • 为了促进各种工具和自定义脚本在一个统一的平台内无集成.

主要方法:

  • 开发了QuNex配方作为定量神经成像环境和工具箱 (QuNex) 的综合功能.
  • 配方定义和执行端到端的神经成像工作流程,以机器和人类可读的格式.
  • 该框架捕捉了所有处理步骤和参数设置,以获得完整的文档.

主要成果:

  • QuNex配方使神经成像工作流程的透明,机器和人类可读的定义成为可能.
  • 该框架允许无集成QuNex命令,自定义脚本和外部工具.
  • 分享QuNex版本,配方文件和数据可以通过一个命令复制研究.

结论:

  • QuNex配方标准化了工作流程规范,并提高了神经成像研究的透明度.
  • 这一框架有助于复杂的神经成像分析的可复制共享.
  • 配方促进神经成像社区内最佳实践和可复制方法的开放交流.