Frequency-specific electrocorticographic correlates of working memory delay period fMRI activity

Abstract

Electrocorticography (ECoG) and functional MRI (BOLD-fMRI) have been used previously to measure brain activity during working memory delay periods. These studies have separately reported oscillation changes in the theta (4-8 Hz) band and BOLD-fMRI increases during delay periods when information is maintained in memory. However, it is not known how intracranial cortical field potential (CFP) changes relate to BOLD-fMRI responses during delay periods. To answer this question, fMRI was obtained from six epilepsy patients during a visual working memory task. Then, following subdural macroelectrode implant, continuous ECoG was used to record CFPs during the same task. Time-frequency analyses showed delay period gamma band oscillation amplitude increases on electrodes located near fMRI activity, while in the theta band changes were higher for electrodes located away from fMRI activation. The amplitude of the ECoG gamma band response was significantly positively correlated with the fMRI response, while a negative correlation was found for the theta band. The findings are consistent with previous reports of local field potential (LFP) coupling in the gamma band with BOLD-fMRI responses during visual stimulation in monkeys, but are novel in that the relationship reported here persists after the disappearance of visual stimuli while information is being maintained in memory. We conclude that there is a relationship between BOLD-fMRI increases and human working memory delay period gamma oscillation increases and theta decreases. The spectral profile change provides a basis for comparison of working memory delay period BOLD-fMRI with field potential recordings in animals and other human intracranial EEG studies.

Cortex-based inter-subject analysis of iEEG and fMRI data sets: Application to sustained task-related BOLD and gamma responses

“…Moreover, even in the absence of these imaging problems, the spatial precision of the iEEG remains dependent on how precisely the localization of the electrodes is performed with respect to the real (rather than modeled) brain anatomy and on how much tissue deformation (brain shift) is induced by the electrode implantation (Lachaux et al, 2003). Brain shift varies strongly from patient to patient, depending on the location and size of craniotomy, the number and placement of electrodes, and the presence and severity of any post-surgical swelling and the distortions of the tissue relative to the cortical surface reconstructions can reach the order of one centimeter (Khursheed et al, 2011). Therefore, our approach for electrode projection, which is identical to that presented by Hermes and colleagues (Hermes et al, 2010) for the special case of electrode strips, could be not as accurate as in previous works based on more advanced and precise methods (see, e. g., Dalal et al, 2008;Dykstra et al, 2012;Hermes et al, 2010;Swann et al, 2009;Tertel et al, 2011).…”

“…To empirically verify this choice, we considered two representative case subjects for which more than one electrode was located within 15 mm of an area of significant fMRI activity (Khursheed et al, 2011) and evaluated the overlap between this area and the area of significant gamma iEEG activity resulting from the cortical spread, at multiple values of d max (0.5, 1.0, 1.5 and 2.0 cm) for iEEG and multiple p-values for fMRI (p = 0.001, 0.01, 0.05). The overlap was calculated as the (percent) ratio between the vertex counts of the intersection and the vertex counts of the union, of the two patches of significant gamma iEEG (p = 0.05) and significant fMRI activity (p = 0.05, 0.01 and 0.001).…”

“…Like for EEG, locally measured electrophysiological responses, typically called local field potentials (LFP) can be either described as event-related potentials or as (de)synchronizations in predefined frequency bands, typically including delta (0-3 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) and gamma (>30 Hz) ranges (Crone et al, 1998). Many animal and human iEEG studies have previously explored the relation of these iEEG components to the BOLD signal and all have shown a close correspondence between the BOLD signal and the gamma band component of the LFP in the cerebral cortex (Conner et al, 2011;Hermes et al, 2012;Khursheed et al, 2011;Lachaux et al, 2007;Logothetis and Pfeuffer, 2004;Mukamel et al, 2005;Nir et al, 2007;Ojemann et al, 2010;Privman et al, 2007). In humans, both perceptual, motor and cognitive neural processes have been shown to be accompanied by power increases in the gamma band in brain sites matching quite precisely with the anatomical organization of the functional networks as visible with fMRI during the same (or similar) paradigms (Niessing et al, 2005), whereas the anatomical localization of other types of iEEG responses such as desynchronizations in alpha and beta bands did not match as neatly as the gamma responses with the cortical functional anatomy (Crone et al, 1998).…”

Intracranial recordings and human memory

“…Importantly, ECoG studies demonstrate that low- and high-frequency activity often share an inverse relationship [5,20,24,25,38,39,40]. Likewise, while measures of high-frequency amplitude show overlap with the BOLD measures of fMRI, low-frequency activity is anatomically dissociated with BOLD measures [41]. …”

Characteristic profiles of high gamma activity and blood oxygenation level-dependent responses in various language areas

“…Hermes et al (2011), in their study on LFP-BOLD coupling in motor function, suggested that BOLD signal change was largely induced by high gamma power increase and alpha-beta power decrease in the primary motor area. Furthermore, Khursheed et al (2011) stressed that theta power decrease had the most negative correlation with BOLD responses in working memory on the frontal lobe. On the basis of previous studies and our own, HGA-BOLD coupling is a promising key to identify complex human brain functions.…”