Evaluating conventional FMRI with respect to noninvasive localization of neuronal activity

Beisteiner, Roland; Erdler, Marcus; Teichtmeister, C.; Moser, Ewald; Deecke, Lüder

doi:10.1002/ima.1850060213

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…In addition, the results indicate overadditive effects with multimethod approaches. In recent papers concerning combined MEG-FMRI approaches, several authors (Belliveau et al, 1993;NBattSinen et al, 1994Beisteiner et al, 1995b have pointed out that FMRI may help MEG to constrain the inverse problem. As we show, with certain paradigms MEG may also help FMRI to improve data analysis strategies and thus brain mapping validity.…”

Section: Discussionmentioning

confidence: 99%

Magnetoencephalography May Help to Improve Functional MRI Brain Mapping

Beisteiner

Erdler

Teichtmeister

et al. 1997

Eur J of Neuroscience

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The validity of functional magnetic resonance imaging (FMRI) brain maps with respect to the sites of neuronal activation is still unknown. One source of localization error may be pixels with large signal amplitudes, since such pixels may be expected to overlie large vessels, running remote from the centre of neuronal activation. In this study, magnetoencephalography was used to determine the centre of neuronal activation in a simple finger tapping task. The localization accuracy of conventional FMRI depending on FMRI signal enhancement was investigated relative to the magnetoencephalography reference. The results show a deterioration of FMRI localization with increasing signal amplitude related to increased contributions from large vessels. We conclude that FMRI data analysis should exclude large signal amplitudes and that magnetoencephalography may help to improve FMRI brain mapping results in a multimethod approach.

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Section: Discussionmentioning

confidence: 99%

Magnetoencephalography May Help to Improve Functional MRI Brain Mapping

Beisteiner

Erdler

Teichtmeister

et al. 1997

Eur J of Neuroscience

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Quantification of statistical type i and ii errors in correlation analysis of simulated functional magnetic resonance imaging data

Baumgartner

Backfrieder

Moser

1996

MAGMA

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The potential of statistical analyses of functional magnetic resonance images using various threshold strategies in combination with correlation analysis was studied by simulating brain activation. Differences in statistical Type I (alpha) and II (beta) errors are substantial for the various thresholds. Absolute thresholds and individualized thresholds based on the assumption of a gaussian noise distribution are producing constant alpha-errors and thus do not sufficiently improve discrimination of "truly" activated pixels even for very high contrast-to-noise ratios (CNR). Only relative threshold strategies related to the maximum correlation coefficient and thus the individual data quality and activation level, i.e., a data-driven approach, can perfectly discriminate true positives, at least for CNR > 2.5. To further improve discrimination of activated and non-activated pixel in studies with lower CNR, additional prior knowledge would be necessary. From the data presented, one would also expect that the best performing threshold strategy in this simulation study would perform best under in vivo conditions.

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