Correlation between BOLD fMRI and theta-band local field potentials in the human hippocampal area

Center for Cognitive Neuroscience, Semel Institute, Department of Psychiatry, University of California, Davis, 1544 Newton Ct., Davis, CA 95618, USA.
Journal of Neurophysiology (Impact Factor: 3.04). 03/2009; 101(5):2668-78. DOI: 10.1152/jn.91252.2008
Source: PubMed

ABSTRACT The relation between the blood-oxygen-level-dependent (BOLD) signal, which forms the basis of functional magnetic resonance imaging (fMRI), and underlying neural activity is not well understood. We performed high-resolution fMRI in patients scheduled for implantation with depth electrodes for seizure monitoring while they navigated a virtual environment. We then recorded local field potentials (LFPs) and neural firing rate directly from the hippocampal area of the same subjects during the same task. Comparing BOLD signal changes with 396 LFP and 185 neuron recordings in the hippocampal area, we found that BOLD signal changes correlated positively with LFP power changes in the theta-band (4-8 Hz). This correlation, however, was largely present for parahippocampal BOLD signal changes; BOLD changes in the hippocampus correlated weakly or not at all with LFP power changes. We did not find a significant relationship between BOLD activity and neural firing rate in either region, which could not be accounted for by a lesser tendency for neurons to respond or a greater tendency for neurons to habituate to the task. Strengthening the idea of a dissociation between LFP power and neural firing rate in their relation to the BOLD signal, simultaneously recorded LFP power and neural firing rate changes were uncorrelated across electrodes. Together, our results suggest that the BOLD signal in the human hippocampal area has a more heterogenous relationship with underlying neural activity than has been described previously in other brain regions.

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Available from: Arne D Ekstrom, Apr 08, 2015
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    • "Frequency dependence of the MEG–fMRI networks Haemodynamic signals typically show a frequency-dependent relationship with electrophysiological effects, often exhibiting negative correlations for low (b30 Hz) and positive correlations for high (N30 Hz) frequency activity (Mukamel et al., 2005). This relationship is, however, location-specific and may depend on factors such as local cytoarchitecture (Ekström et al., 2009; Kujala et al., 2014). Here, the greatest similarity between MEG and fMRI derived networks was observed at neural frequencies below 30 Hz. "
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    ABSTRACT: Large-scale networks support the dynamic integration of information across multiple functionally specialized brain regions. Network analyses of haemodynamic modulations have revealed such functional brain networks that show high consistency across subjects and different cognitive states. However, the relationship between the slowly fluctuating haemodynamic responses and the underlying neural mechanisms is not well understood. Resting state studies have revealed spatial similarities in the estimated network hub locations derived using haemodynamic and electrophysiological recordings, suggesting a direct neural basis for the widely described functional magnetic resonance imaging (fMRI) resting state networks. To truly understand the nature of the relationship between electrophysiology and haemodynamics it is important to move away from a task absent state and to establish if such networks are differentially modulated by cognitive processing. The present parallel fMRI and magnetoencephalography (MEG) experiment investigated the structural similarities between haemodynamic networks and their electrophysiological counterparts when either the stimulus or the task was varied. Connectivity patterns underlying action vs. object naming (task-driven modulations), and action vs. object images (stimulus-driven modulations) were identified in a data driven all-to-all connectivity analysis, with cross spectral coherence adopted as a metric of functional connectivity in both MEG and fMRI. We observed a striking difference in functional connectivity between conditions. The spectral profiles of the frequency-specific network similarity differed significantly for the task-driven vs. stimulus-driven connectivity modulations. While the greatest similarity between MEG and fMRI derived networks was observed at neural frequencies below 30 Hz, haemodynamic network interactions could not be attributed to a single frequency band. Instead, the entire spectral profile should be taken into account when assessing the correspondence between MEG and fMRI networks. Task-driven network hubs, evident in both MEG and fMRI, were found in cortical regions previously associated with language processing, including the posterior temporal cortex and the inferior frontal cortex. Network hubs related to stimulus-driven modulations, however, were found in regions related to object recognition and visual processing, including the lateral occipital cortex. Overall, the results depict a shift in network structure when moving from a task dependent modulation to a stimulus dependent modulation, revealing a reorganisation of large-scale functional connectivity during task performance. Copyright © 2015. Published by Elsevier Inc.
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    • "Finally, oxygen and LFP responses were correlated in both V3 and PCC. However, the nature of the linear LFP–oxygen relationship differed substantially across regions (Ekstrom et al. 2009). These results demonstrate that either hemodynamic coupling differs in PCC and V3 or that a simple (linear, single LFP band) transformation is inappropriate for predicting oxygen level from neuronal activity. "
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    Cerebral Cortex 11/2014; DOI:10.1093/cercor/bhu260 · 8.67 Impact Factor
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    • "e l s e v i e r . c o m / l o c a t e / y n i m g measures such as event-related potentials (Huettel et al., 2004) or spectral power changes (Ekstrom et al., 2009; Engell et al., 2012; Goense and Logothetis, 2008; Hermes et al., 2011, 2014; Khursheed et al., 2011; Lachaux et al., 2007; Logothetis et al., 2001; Meltzer et al., 2008; Mukamel et al., 2005; Ojemann et al., 2010; Scheeringa et al., 2011; Vansteensel et al., 2010). These studies have concluded that BOLD amplitude correlates most strongly with changes in the high frequency broadband power (HFB-power, also often referred to as 'high gamma'), a frequency range associated with local neuronal processing, and correlated with local spike rate (Crone et al., 1998; Manning et al., 2009; Miller et al., 2009a; Nir et al., 2008; Ray and Maunsell, 2011; Siero et al., 2013). "
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