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Front Hum Neurosci. 2013 Mar 11;7:64. doi: 10.3389/fnhum.2013.00064. eCollection 2013.

The Use of a priori Information in ICA-Based Techniques for Real-Time fMRI: An Evaluation of Static/Dynamic and Spatial/Temporal Characteristics.

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  • 1Center for Mind/Brain Sciences, University of Trento Trento, Italy.

Abstract

Real-time brain functional MRI (rt-fMRI) allows in vivo non-invasive monitoring of neural networks. The use of multivariate data-driven analysis methods such as independent component analysis (ICA) offers an attractive trade-off between data interpretability and information extraction, and can be used during both task-based and rest experiments. The purpose of this study was to assess the effectiveness of different ICA-based procedures to monitor in real-time a target IC defined from a functional localizer which also used ICA. Four novel methods were implemented to monitor ongoing brain activity in a sliding window approach. The methods differed in the ways in which a priori information, derived from ICA algorithms, was used to monitor a target independent component (IC). We implemented four different algorithms, all based on ICA. One Back-projection method used ICA to derive static spatial information from the functional localizer, off-line, which was then back-projected dynamically during the real-time acquisition. The other three methods used real-time ICA algorithms that dynamically exploited temporal, spatial, or spatial-temporal priors during the real-time acquisition. The methods were evaluated by simulating a rt-fMRI experiment that used real fMRI data. The performance of each method was characterized by the spatial and/or temporal correlation with the target IC component monitored, computation time, and intrinsic stochastic variability of the algorithms. In this study the Back-projection method, which could monitor more than one IC of interest, outperformed the other methods. These results are consistent with a functional task that gives stable target ICs over time. The dynamic adaptation possibilities offered by the other ICA methods proposed may offer better performance than the Back-projection in conditions where the functional activation shows higher spatial and/or temporal variability.

KEYWORDS:

ICA; a priori knowledge; adaptive algorithms; dynamic monitoring; real-time fMRI

PMID:
23483841
[PubMed]
PMCID:
PMC3593622
Free PMC Article

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