Relationship between regional hemodynamic activity and simultaneously recorded EEG-theta associated with mental arithmetic-induced workload

Abstract

Theta increases with workload and is associated with numerous processes including working memory, problem solving, encoding, or self monitoring. These processes, in turn, involve numerous structures of the brain. However, the relationship between regional brain activity and the occurrence of theta remains unclear. In the present study, simultaneous EEG-fMRI recordings were used to investigate the functional topography of theta. EEG-theta was enhanced by mental arithmetic-induced workload. For the EEG-constrained fMRI analysis, theta-reference time-series were extracted from the EEG, reflecting the strength of theta occurrence during the time course of the experiment. Theta occurrence was mainly associated with activation of the insular cortex, hippocampus, superior temporal areas, cingulate cortex, superior parietal, and frontal areas. Though observation of temporal and insular activation is in accord with the theory that theta specifically reflects encoding processes, the involvement of several other brain regions implies that surface-recorded theta represents comprehensive functional brain states rather than specific processes in the brain. The results provide further evidence for the concept that emergent theta band oscillations represent dynamic functional binding of widely distributed cortical assemblies, essential for cognitive processing. This binding process may form the source of surface-recorded EEG theta.

Figure 1

Difference maps of EEG‐power between mental arithmetic‐induced workload and a baseline task. Maps represent aggregated data for four EEG‐frequency bands in the delta range (0.5–3 Hz), the band of interest in the theta range (3.5–7.5 Hz), the lower and upper alpha bands (8–10.5 Hz; 11–13.5 Hz). Scaling is arbitrary. Red indicates increased power during workload condition in that frequency band, blue represents decreased power during workload compared to the baseline.

Figure 2

SPMs rendered on a template's brain surface are shown for both analyses (a,b). Intensity of the red color indicates proximity of the activation to the surface. The second row shows SPMs superimposed on template brain slices to illustrate the locations of the main activations. Plane z‐coordinates are given for these plots. T‐values are color‐coded (see color bar; range 0 ≤ t ≤ 7). a: fMRI results showing activated voxels for the mental arithmetic‐induced workload condition contrasted against the reference task. Threshold for activated voxels on surface‐rendered images is t > 7.27, extent threshold for above‐threshold clusters is > 26 voxels. b: Results of the EEG‐constrained fMRI‐analysis showing voxels corresponding to theta‐occurrence, which was represented by a theta‐reference time series. Threshold for activated voxels on surface‐rendered images is t > 3.59, extent threshold for above‐threshold clusters is > 26. The software packages used to produce images were SPM and MRIcro (http://www.mricro.com).

Figure 3

The theta reference time‐series. a: Line drawing represents the pooled theta energy from F3/Fz/F4, and P3/Pz/P4 averaged over subjects. a,b: x‐axis represents time in fMRI‐scans, white bars indicate epochs of workload by mental arithmetic induction, gray stem‐plots mark the onset of those epochs; black bars indicate trials of the reference task. b: Continuous wavelet transform of the averaged theta‐reference time series. Red indicates high, blue low wavelet power as indicated by the color bar. Black contour drawings mark the threshold of acceptance regions against noise background power spectrum at P < 0.05. Gray contour indicates predicted acceptance regions for the model of initial theta increase with the onsets of mental arithmetic performance. Analogously, white contour indicates predicted acceptance areas for the model of sustained theta enhancement during entire periods of mental arithmetic performance. Confidence intervals for edge effects were omitted.