Measure of neurofeedback effects in an fMRI Brain-Computer Interface with support vector machine and Granger causality model
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1
Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Germany
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2
Graduate school of Neural & Behavioral Sciences, International Max Planck Research School, Germany
In a recent study, we have (Caria et al. 2007) used real-time functional magnetic resonance imaging (rtfMRI) to show that healthy subjects were able to control volitionally activity of right anterior insula. Participants voluntarily increased and decreased the bars of a graphical thermometer representing the feedback signal, which was the blood oxygen-level dependent (BOLD) signal difference between right anterior insula and reference area. However, the insula regulation based on emotional states implies that changing activity in insula could accompany changing activity in other locations. In the present study, therefore, we attempt to show how learning to regulate right anterior insula with feedback changes spatial distribution of brain activity and how this would give rise to functional connectivity of the brain. To investigate spatial interaction, support vector machine (SVM) classification was used, and a new analysis using the trained SVM model was proposed to capture spatial changes during learning. The new SVM analysis proposed, called Effect Mapping, uses information theory to measure the relation between the designed model and the input vector. In terms of temporal interaction in the brain activity, Granger causality modeling (GCM) was used to observe change of functional connectivity during learning. Our investigation revealed that with successful learning brain activation becomes more focused in the emotional network. In addition, functional connectivity analysis using GCM indicated inverted U-curve of learning with low causal connectivity in the early stage of learning followed by increased connectivity until a maximal causal connectivity is reached corresponding to peak regulation, eventually leading to reduced connectivity with more efficient regulation.
References
1. Caria, A., R. Veit, et al. (2007). "Regulation of anterior insular cortex activity using real-time fMRI." Neuroimage 35(3): 1238-46.
Conference:
10th International Conference on Cognitive Neuroscience, Bodrum, Türkiye, 1 Sep - 5 Sep, 2008.
Presentation Type:
Poster Presentation
Topic:
Abstracts
Citation:
Lee
S,
Sitaram
R,
Ruiz
S and
Birbaumer
N
(2008). Measure of neurofeedback effects in an fMRI Brain-Computer Interface with support vector machine and Granger causality model.
Conference Abstract:
10th International Conference on Cognitive Neuroscience.
doi: 10.3389/conf.neuro.09.2009.01.172
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Received:
08 Dec 2008;
Published Online:
08 Dec 2008.
*
Correspondence:
Sangkyun Lee, Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany, sangkyun.lee@student.uni-tuebingen.de