Increased spatial granularity of left brain activation and unique age/gender signatures: a 4D frequency domain approach to cerebral lateralization at rest

Abstract

Cerebral lateralization is a well-studied topic. However, most of the research to date in functional magnetic resonance imaging (fMRI) has been carried out on hemodynamic fluctuations of voxels, networks, or regions of interest (ROIs). For example, cerebral differences can be revealed by comparing the temporal activation of an ROI in one hemisphere with the corresponding homotopic region in the other hemisphere. While this approach can reveal significant information about cerebral organization, it does not provide information about the full spatiotemporal organization of the hemispheres. The cerebral differences revealed in literature suggest that hemispheres have different spatiotemporal organization in the resting state. In this study, we evaluate cerebral lateralization in the 4D spatiotemporal frequency domain to compare the hemispheres in the context of general activation patterns at different spatial and temporal scales. We use a gender-balanced resting fMRI dataset comprising over 600 healthy subjects ranging in age from 12 to 71, that have previously been studied with a network specific voxel-wise and global analysis of lateralization (Agcaoglu, et al. NeuroImage, 2014). Our analysis elucidates significant differences in the spatiotemporal organization of brain activity between hemispheres, and generally more spatiotemporal fluctuation in the left hemisphere especially in the high spatial frequency bands, and more power in the right hemisphere in the low and middle spatial frequencies. Importantly, the identified effects are not visible in the context of a typical assessment of voxelwise, regional, or even global laterality, thus our study highlights the value of 4D spatiotemporal frequency domain analyses as a complementary and powerful tool for studying brain function.

Keywords: 4D Fourier transform; Aging; Frequency domain; Gender differences; Laterality; Resting state.

Figure 1

Flowchart of data processing.

Figure 2

Group averages of hemisphere SSBPs, Left hemisphere (on left) and Right hemisphere (on right) displayed in log10 format (unit is decibel-Watt). In each image; left bottom represents the low temporal and low spatial frequencies; on the x-axis from left to right, temporal frequencies increase from 0 Hz to 0.25 Hz; on the y-axis from bottom to top, spatial frequencies increases from 0 cycles/mm to 0.17 cycles/mm.

Figure 3

Paired t-test results for hemisphere SSBPs, P-values (on left) and 0.01 level FDR corrected p-values (on right [maybe indicate FDR corrected in the figure titles as well, so its easy to see without reading the caption, same for figs below…also for this one would say “Left – Right (paired T-test)” or something like this in the figure titles]) are presented in –sign(t)*log(p) format (where sign(t) is the sign of corresponding beta value). Red color represents the regions favoring left hemisphere, while blue color represents region favoring right hemisphere. Overall, regions favoring right hemisphere occupies a larger area and includes low and middle spatial frequencies, left hemisphere has more power in high spatial frequencies.

Figure 4

Regression analysis result on subject SSBPs for age effects on Left hemisphere. P-values (on left) and 0.01 level FDR corrected p-values (on right) are presented in –sign(t)*log(p) format (where sign(t) is the sign of corresponding beta value). Overall, temporal frequencies determine the direction of the age effects, from 0.016 (3^rd index) Hz to 0.14 (19^th index) Hz and in all spatial frequencies, show a decrease in power with increasing age, while other temporal and spatial frequencies increases in power with aging.

Figure 5

Regression analysis result on subject SSBPs for age effects on Right hemisphere. P-values (on left) and 0.01 level FDR corrected p-values (on right) are presented in –sign(t)*log(p) format (where sign(t) is the sign of corresponding beta value). Generally, the age effects on right hemisphere are very similar to the effect on left hemisphere.

Figure 6

Regression analysis result on subject SSBPs for gender effects on Left hemisphere. P-values (on left) and 0.01 level FDR corrected p-values (on right) are presented in –sign(t)*log(p) format (where sign(t) is the sign of corresponding beta value); blue color shows the region favors males while red color shows the region favors females. Gender patterns are complicated and dependent on both spatial and temporal frequencies.

Figure 7

Regression analysis result on subject SSBPs for gender effects on Right hemisphere. P-values (on left) and 0.01 level FDR corrected p-values (on right) are presented in –sign(t)*log(p) format (where sign(t) is the sign of corresponding beta value); blue color shows the region favors males while red color shows the region favors females. Overall, the gender effects on right hemisphere are very similar to the effect on left hemisphere.