Low-frequency EEG correlates of fMRI in the resting state

Grooms, Joshua Koehler; Thompson, Garth J.; Schwarb, Hillary; Schumacher, Eric H.; Schmidt, Regina; Epstein, Charles M.; Keilholz, Shella

doi:10.1186/1471-2202-13-s1-p107

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…In humans, the relationship between the BOLD signal and neural activity was studied using either separate or simultaneous recordings of EEG/ECoG/MEG and fMRI ( Grooms et al, 2012 ; Tagliazucchi et al, 2012b ; Chang et al, 2013 ; Allen et al, 2018 ). For example, Kucyi and his colleagues studied the correspondence between the temporal profiles of ECoG frequencies and functional brain networks detected by fMRI ( Kucyi et al, 2018 ).…”

Section: Applicationsmentioning

confidence: 99%

Functional Connectivity of the Brain Across Rodents and Humans

LaGrow

Anumba

et al. 2022

Front. Neurosci.

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Resting-state functional magnetic resonance imaging (rs-fMRI), which measures the spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal, is increasingly utilized for the investigation of the brain’s physiological and pathological functional activity. Rodents, as a typical animal model in neuroscience, play an important role in the studies that examine the neuronal processes that underpin the spontaneous fluctuations in the BOLD signal and the functional connectivity that results. Translating this knowledge from rodents to humans requires a basic knowledge of the similarities and differences across species in terms of both the BOLD signal fluctuations and the resulting functional connectivity. This review begins by examining similarities and differences in anatomical features, acquisition parameters, and preprocessing techniques, as factors that contribute to functional connectivity. Homologous functional networks are compared across species, and aspects of the BOLD fluctuations such as the topography of the global signal and the relationship between structural and functional connectivity are examined. Time-varying features of functional connectivity, obtained by sliding windowed approaches, quasi-periodic patterns, and coactivation patterns, are compared across species. Applications demonstrating the use of rs-fMRI as a translational tool for cross-species analysis are discussed, with an emphasis on neurological and psychiatric disorders. Finally, open questions are presented to encapsulate the future direction of the field.

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Section: Applicationsmentioning

confidence: 99%

Functional Connectivity of the Brain Across Rodents and Humans

LaGrow

Anumba

et al. 2022

Front. Neurosci.

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“…Second, using the same rat model as Thompson et al and using electrodes and amplifiers that could record fluctuations down to the DC (0 Hz) component of the signal (Pan et al, 2013 ), correlations between infraslow LFP and fMRI matched the QPP observed in fMRI alone, and changes in strength of these patterns over time weakly but significantly correlated with the LFP signal directly (Thompson et al, 2013b ). Preliminary evidence from an infraslow EEG study suggests that the correlation between the infraslow electrical signal and QPP in fMRI may exist in humans as well (Grooms et al, 2012 ).…”

Section: Introductionmentioning

confidence: 99%

Phase-amplitude coupling and infraslow (<1 Hz) frequencies in the rat brain: relationship to resting state fMRI

Thompson

Pan

Billings

et al. 2014

Front. Integr. Neurosci.

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Resting state functional magnetic resonance imaging (fMRI) can identify network alterations that occur in complex psychiatric diseases and behaviors, but its interpretation is difficult because the neural basis of the infraslow BOLD fluctuations is poorly understood. Previous results link dynamic activity during the resting state to both infraslow frequencies in local field potentials (LFP) (<1 Hz) and band-limited power in higher frequency LFP (>1 Hz). To investigate the relationship between these frequencies, LFPs were recorded from rats under two anesthetics: isoflurane and dexmedetomidine. Signal phases were calculated from low-frequency LFP and compared to signal amplitudes from high-frequency LFP to determine if modulation existed between the two frequency bands (phase-amplitude coupling). Isoflurane showed significant, consistent phase-amplitude coupling at nearly all pairs of frequencies, likely due to the burst-suppression pattern of activity that it induces. However, no consistent phase-amplitude coupling was observed in rats that were anesthetized with dexmedetomidine. fMRI-LFP correlations under isoflurane using high frequency LFP were reduced when the low frequency LFP's influence was accounted for, but not vice-versa, or in any condition under dexmedetomidine. The lack of consistent phase-amplitude coupling under dexmedetomidine and lack of shared variance between high frequency and low frequency LFP as it relates to fMRI suggests that high and low frequency neural electrical signals may contribute differently, possibly even independently, to resting state fMRI. This finding suggests that researchers take care in interpreting the neural basis of resting state fMRI, as multiple dynamic factors in the underlying electrophysiology could be driving any particular observation.

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Low-frequency EEG correlates of fMRI in the resting state

Cited by 2 publications

References 3 publications

Functional Connectivity of the Brain Across Rodents and Humans

Functional Connectivity of the Brain Across Rodents and Humans

Phase-amplitude coupling and infraslow (<1 Hz) frequencies in the rat brain: relationship to resting state fMRI

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