Functional magnetic resonance imaging in real time (FIRE): Sliding-window correlation analysis and reference-vector optimization
New algorithms for correlation analysis are presented that allow the mapping of brain activity from functional MRI (fMRI) data in real time during the ongoing scan. They combine the computation of the correlation coefficients between measured fMRI time‐series data and a reference vector with “detren...
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| Veröffentlicht in: | Magnetic resonance in medicine 2000-02, Vol.43 (2), p.259-268 |
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| creator | Gembris, Daniel Taylor, John G. Schor, Stefan Frings, Wolfgang Suter, Dieter Posse, Stefan |
| description | New algorithms for correlation analysis are presented that allow the mapping of brain activity from functional MRI (fMRI) data in real time during the ongoing scan. They combine the computation of the correlation coefficients between measured fMRI time‐series data and a reference vector with “detrending,” a technique for the suppression of non‐stimulus‐related signal components, and the “sliding‐window technique.” Using this technique, which limits the correlation computation to the last N measurement time points, the sensitivity to changes in brain activity is maintained throughout the whole experiment. For increased sensitivity in activation detection a fast and robust optimization of the reference vector is proposed, which takes into account a realistic model of the hemodynamic response function to adapt the parameterized reference vector to the measured data. Based on the described correlation method, real‐time fMRI experiments using visual stimulation paradigms have been performed successfully on a clinical MR scanner, which was linked to an external workstation for image analysis. Magn Reson Med 43:259–268, 2000. © 2000 Wiley‐Liss, Inc. |
| doi_str_mv | 10.1002/(SICI)1522-2594(200002)43:2<259::AID-MRM13>3.0.CO;2-P |
| format | Article |
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Reson. Med</addtitle><description>New algorithms for correlation analysis are presented that allow the mapping of brain activity from functional MRI (fMRI) data in real time during the ongoing scan. They combine the computation of the correlation coefficients between measured fMRI time‐series data and a reference vector with “detrending,” a technique for the suppression of non‐stimulus‐related signal components, and the “sliding‐window technique.” Using this technique, which limits the correlation computation to the last N measurement time points, the sensitivity to changes in brain activity is maintained throughout the whole experiment. For increased sensitivity in activation detection a fast and robust optimization of the reference vector is proposed, which takes into account a realistic model of the hemodynamic response function to adapt the parameterized reference vector to the measured data. Based on the described correlation method, real‐time fMRI experiments using visual stimulation paradigms have been performed successfully on a clinical MR scanner, which was linked to an external workstation for image analysis. Magn Reson Med 43:259–268, 2000. © 2000 Wiley‐Liss, Inc.</description><subject>Adult</subject><subject>Algorithms</subject><subject>Biological and medical sciences</subject><subject>Brain - anatomy & histology</subject><subject>Brain - physiology</subject><subject>correlation analysis</subject><subject>Hemodynamics</subject><subject>Humans</subject><subject>Investigative techniques, diagnostic techniques (general aspects)</subject><subject>Magnetic Resonance Imaging - instrumentation</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Magnetic Resonance Imaging - statistics & numerical data</subject><subject>Male</subject><subject>Medical sciences</subject><subject>Nervous system</subject><subject>Photic Stimulation - methods</subject><subject>Radiodiagnosis. Nmr imagery. 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Nmr imagery. Nmr spectrometry</topic><topic>real-time fMRI</topic><topic>Reference Values</topic><topic>sensitivity optimization</topic><topic>sliding-window technique</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gembris, Daniel</creatorcontrib><creatorcontrib>Taylor, John G.</creatorcontrib><creatorcontrib>Schor, Stefan</creatorcontrib><creatorcontrib>Frings, Wolfgang</creatorcontrib><creatorcontrib>Suter, Dieter</creatorcontrib><creatorcontrib>Posse, Stefan</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Magnetic resonance in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gembris, Daniel</au><au>Taylor, John G.</au><au>Schor, Stefan</au><au>Frings, Wolfgang</au><au>Suter, Dieter</au><au>Posse, Stefan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Functional magnetic resonance imaging in real time (FIRE): Sliding-window correlation analysis and reference-vector optimization</atitle><jtitle>Magnetic resonance in medicine</jtitle><addtitle>Magn. 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| subjects | Adult Algorithms Biological and medical sciences Brain - anatomy & histology Brain - physiology correlation analysis Hemodynamics Humans Investigative techniques, diagnostic techniques (general aspects) Magnetic Resonance Imaging - instrumentation Magnetic Resonance Imaging - methods Magnetic Resonance Imaging - statistics & numerical data Male Medical sciences Nervous system Photic Stimulation - methods Radiodiagnosis. Nmr imagery. Nmr spectrometry real-time fMRI Reference Values sensitivity optimization sliding-window technique Software |
| title | Functional magnetic resonance imaging in real time (FIRE): Sliding-window correlation analysis and reference-vector optimization |
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