What we can and cannot do with fMRI

Max Planck Institute for Biological Cybernetics, 72076 Tuebingen, Germany, and Imaging Science and Biomedical Engineering, University of Manchester, Manchester M13 9PL, UK.
Nature (Impact Factor: 41.46). 06/2008; 453(7197):869-878. DOI: 10.1038/nature06976
Source: PubMed


Functional magnetic resonance imaging (fMRI) is currently the mainstay of neuroimaging in cognitive neuroscience. Advances in scanner technology, image acquisition protocols, experimental design, and analysis methods promise to push forward fMRI from mere cartography to the true study of brain organization. However, fundamental questions concerning the interpretation of fMRI data abound, as the conclusions drawn often ignore the actual limitations of the methodology. Here I give an overview of the current state of fMRI, and draw on neuroimaging and physiological data to present the current understanding of the haemodynamic signals and the constraints they impose on neuroimaging data interpretation.

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    • "Studies using electrophysiology have provided evidence for the association between the BOLD amplitude and the components of neural activity that it best represents. Recent studies observing the correlation between the BOLD signal and local field potentials (LFPs), which reflect mass extracellular activity in a region of cortex (Logothetis 2008), indicate a strong association between the BOLD magnitude and the gamma frequency band of LFPs (Kayser et al. 2004; Scholvinck et al. 2010; Magri et al. 2012). The high-frequency gamma range has been associated with excitatory and Table 2. Time-to-peak of the temporal profile with V1 and V4 for DfMRI and BOLD. "
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    ABSTRACT: IntroductionDecreased water displacement following increased neural activity has been observed using diffusion-weighted functional MRI (DfMRI) at high b-values. The physiological mechanisms underlying the diffusion signal change may be unique from the standard blood oxygenation level-dependent (BOLD) contrast and closer to the source of neural activity. Whether DfMRI reflects neural activity more directly than BOLD outside the primary cerebral regions remains unclear.Methods Colored and achromatic Mondrian visual stimuli were statistically contrasted to functionally localize the human color center Area V4 in neurologically intact adults. Spatial and temporal properties of DfMRI and BOLD activation were examined across regions of the visual cortex.ResultsAt the individual level, DfMRI activation patterns showed greater spatial specificity to V4 than BOLD. The BOLD activation patterns were more prominent in the primary visual cortex than DfMRI, where activation was localized to the ventral temporal lobe. Temporally, the diffusion signal change in V4 and V1 both preceded the corresponding hemodynamic response, however the early diffusion signal change was more evident in V1.Conclusions DfMRI may be of use in imaging applications implementing cognitive subtraction paradigms, and where highly precise individual functional localization is required.
    Brain and Behavior 10/2015; DOI:10.1002/brb3.408 · 2.24 Impact Factor
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    • "A second model discussed, Price's model (2012), is solely based on positron emission tomography and functional magnetic resonance imaging (fMRI) data, which have no temporal resolution at the scale of single word production (i.e., often less than 1 second). Moreover, in fMRI the link between the blood-oxygenlevel dependent (BOLD) signal and underlying neuronal activity, and hence electrophysiological measures, is still poorly understood (e.g., Ekstrom, 2010; Logothetis, 2008). As such, Price's model may be difficult to assess on the basis of electrophysiological data. "

    10/2015; DOI:10.1080/23273798.2015.1100749
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    • "Nevertheless, as a voxel contains nearly a million neurons (cf. Logothetis, 2008) including both superadditive and subadditive neurons in comparable numbers and spatially intermixed, these terms are unlikely to reflect true forms of multisensory integration at the neuronal level as applied in electrophysiology research (Beauchamp, 2005; Laurienti et al., 2005). Set 2 — Visual or olfactory-related gain via OV integration (Dolan et al., 2001): 2a) Visual perceptual gain: visual negative stimuli accompanied by olfactory negative stimuli minus visual negative stimuli accompanied by olfactory neutral stimuli (O Neg V Neg À O Neut V Neg ); and 2b) Olfactory perceptual gain: olfactory negative stimuli accompanied by visual negative stimuli minus olfactory negative stimuli accompanied by visual neutral stimuli (O Neg V Neg –O Neg V Neut ). "

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