Statistical analysis tool for time/frequency state spaces.

时间/频率状态空间的统计分析工具。

• 批准号: BB/K01420X/1
• 负责人: Cyril Pernet
• 金额: $ 13.04万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FK01420X%2F1
• 关键词: Statistical; analysis; tool; time; frequency

The electroencephalogram, or EEG, consists of fluctuations in brain electrical activity; it can be measured whilst people are doing cognitive tasks (e.g. seeing objects, reading, listening). Recordings consist in time-series and are collected via multiple electrodes at the surface of the skull. Mathematical operations allow decomposing those recordings into more easy interpretable signals to examine, for instance, different frequencies (e.g. slow and fast fluctuations of the signal). There is currently no tool allowing the statistical assessment of all the EEG dimensions simultaneously (all electrodes, all time points and all frequencies together). Our project aims at providing a freely distributed toolbox allowing such analyses, therefore providing a new way to investigate a lot of research data and potentially generating important new knowledge about the brain.

脑电图，或EEG，由脑电活动的波动组成;它可以在人们进行认知任务（例如看物体，阅读，听）时测量。记录包括时间序列，并通过颅骨表面的多个电极收集。数学运算允许将这些记录分解为更容易解释的信号，以检查例如不同频率（例如信号的缓慢和快速波动）。目前没有工具允许同时对所有EEG维度进行统计评估（所有电极、所有时间点和所有频率）。我们的项目旨在提供一个免费分发的工具箱，允许进行此类分析，从而提供一种新的方法来调查大量研究数据，并可能产生有关大脑的重要新知识。

项目成果

Cluster-based computational methods for mass univariate analyses of event-related brain potentials/fields: A simulation study.

• DOI: 10.1016/j.jneumeth.2014.08.003
• 发表时间: 2015-07-30
• 期刊: Journal of neuroscience methods
• 影响因子: 3
• 作者: Pernet CR;Latinus M;Nichols TE;Rousselet GA
• 通讯作者: Rousselet GA