What does fMRI tell us about neuronal activity?

Heeger, David J.; Ress, David

doi:10.1038/nrn730

Cited by 878 publications

(512 citation statements)

References 111 publications

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“…Although the LFP represents the input to and intracortical activity within a neural population, it is not necessarily correlated with spike output because LFPs are not necessarily supra-threshold (Heeger and Rees, 2002). Spiking activity measured in animal studies corresponds to the highpass component (cut off >300 Hz) of the extracellular field potential and represents the output of the neural population.…”

Section: Guiding Principles From Animal Studiesmentioning

confidence: 99%

The mechanisms of tinnitus: Perspectives from human functional neuroimaging

2009

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In this review, we highlight the contribution of advances in human neuroimaging to the current understanding of central mechanisms underpinning tinnitus and explain how interpretations of neuroimaging data have been guided by animal models. The primary motivation for studying the neural subtrates of tinnitus in humans has been to demonstrate objectively its representation in the central auditory system and to develop a better understanding of its diverse pathophysiology and of the functional interplay between sensory, cognitive and affective systems. The ultimate goal of neuroimaging is to identify subtypes of tinnitus in order to better inform treatment strategies. The three neural mechanisms considered in this review may provide a basis for TI classification. While human neuroimaging evidence strongly implicates the central auditory system and emotional centres in TI, evidence for the precise contribution from the three mechanisms is unclear because the data are somewhat inconsistent. We consider a number of methodological issues limiting the field of human neuroimaging and recommend approaches to overcome potential inconsistency in results arising from poorly matched participants, lack of appropriate controls and low statistical power. AbstractIn this review, we highlight the contribution of advances in human neuroimaging to the current understanding of central mechanisms underpinning tinnitus and explain how interpretations of neuroimaging data have been guided by animal models. The primary motivation for studying the neural subtrates of tinnitus in humans has been to demonstrate objectively its representation in the central auditory system and to develop a better understanding of its diverse pathophysiology and of the functional interplay between sensory, cognitive and affective systems. The ultimate goal of neuroimaging is to identify subtypes of tinnitus in order to better inform treatment strategies. The three neural mechanisms considered in this review may provide a basis for TI classification. While human neuroimaging evidence strongly implicates the central auditory system and emotional centres in TI, evidence for the precise contribution from the three mechanisms is unclear because the data are somewhat inconsistent. We consider a number of methodological issues limiting the field of human neuroimaging and recommend approaches to overcome potential inconsistency in results arising from poorly matched participants, lack of appropriate controls and low statistical power.

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Section: Guiding Principles From Animal Studiesmentioning

confidence: 99%

The mechanisms of tinnitus: Perspectives from human functional neuroimaging

2009

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“…Assuming a linear neurovascular coupling relationship between the hemodynamic response, local field potentials and the scalp EEG phenomena (Heeger, et al, 2002;Lauritzen, et al, 2003;Logothetis, et al, 2001;Logothetis, 2003;Mukamel, et al, 2005;Shmuel, et al, 2006), this integration by prediction quantifies the covariation in the EEG-fMRI relationship and ensures some specificity with respect to the spatiotemporal inferences. In this fashion, the hemodynamic correlates of EEG rhythms (Feige, et al, 2005;Goldman, et al, 2002;Laufs, et al, 2003;Moosmann, et al, 2003), and interictal EEG phenomena in epilepsy (Gotman, et al, 2004; were first studied.…”

Section: Introductionmentioning

confidence: 99%

Joint independent component analysis for simultaneous EEG–fMRI: Principle and simulation

Moosmann

Eichele

Nordby

et al. 2008

International Journal of Psychophysiology

122

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An optimized scheme for the fusion of electroencephalography and event related potentials with functional magnetic resonance imaging (BOLD-fMRI) data should simultaneously assess all available electrophysiologic and hemodynamic information in a common data space. In doing so, it should be possible to identify features of latent neural sources whose trial-to-trial dynamics are jointly reflected in both modalities. We present a joint independent component analysis (jICA) model for analysis of simultaneous single trial EEG-fMRI measurements from multiple subjects. We outline the general idea underlying the jICA approach and present results from simulated data under realistic noise conditions. Our results indicate that this approach is a feasible and physiologically plausible data-driven way to achieve spatiotemporal mapping of event related responses in the human brain.

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“…In contrast to subcortical structures, however, cortical circuits are dominated by massive local connectivity in which most synaptic inputs originate from nearby neurons 9 and only a small minority of inputs originate from distant sites such as the thalamus. Thus, synaptic 'inputs' in cerebral cortex are mostly produced by local spiking of neighboring neurons, leading invariably to a tight coupling between synaptic and spiking activity, as well as oxygen responses 10 .…”

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confidence: 99%

BOLD and spiking activity

et al. 2008

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Viswanathan and Freeman 1 claim that oxygen concentration and, by inference, blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) reflect synaptic activity more than spiking activity. As this is a fundamental and controversial issue in fMRI research, this claim, if incorrect, may erroneously bias the interpretation of a large body of data.The authors simultaneously recorded multi-unit activity (MUA), local field potentials (LFP) and tissue oxygen concentration in primary visual cortex of anesthetized cats stimulated with moving gratings. During high temporal-frequency stimulation, when thalamic inputs were active, but few cortical neurons responded, oxygen signals were observed without MUA. Therefore, the authors concluded that oxygen responses reflect synaptic inputs more than spiking. However, careful inspection of their results leads to the opposite conclusion and supports a tight coupling between oxygen signals and local cortical spiking.Tissue oxygen responses show an initial decrease that is attributed to local oxygen consumption (negative peak) and a delayed increase that is attributed to more global changes in blood flow (positive peak). The authors showed that the initial negative peak was greater than zero during high-frequency stimulation (when spiking activity was absent), but it was in fact 80-90% smaller to high-frequency stimulation than to low-frequency stimulation (calculated from ref. 1, see red arrow in Fig. 1). Given that roughly the same thalamic input is expected on stimulation of either temporal frequency 2 , we conclude that the initial negative oxygen response depended only slightly (10-20%) on thalamocortical synaptic activity and mostly (80-90%) on cortical spiking.What about the more widespread delayed positive oxygen response? This component was evident during stimulation at high frequencies, but only in one of their two experiments that used large stimuli. A previous study demonstrated that delayed positive oxygen responses were associated with spiking outside the field of view of the electrode when using such large stimuli 3 . There is, therefore, a mismatch between the spatial extents of MUA (which

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What does fMRI tell us about neuronal activity?

Cited by 878 publications

References 111 publications

The mechanisms of tinnitus: Perspectives from human functional neuroimaging

The mechanisms of tinnitus: Perspectives from human functional neuroimaging

Joint independent component analysis for simultaneous EEG–fMRI: Principle and simulation

BOLD and spiking activity

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