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 suggests 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, Miller, Mayer, Hugdahl, & Calhoun, 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 regions, and more power in the right hemisphere in the low and middle spatial frequencies. [We also find significant gender and age effects in both hemispheres consistent with (Miller et al., 2015) which analyzed a different dataset but did not evaluate lateralization. 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.

Decreased hemispheric connectivity and decreased intra- and inter- hemisphere asymmetry of resting state functional network connectivity in schizophrenia

“…Effects of diagnosis on the differences suggest that in these patients the differences are smaller, especially with connectivity involving cognitive control networks, which is consistent with a lack of lateralization in patients. Age and gender do not exhibit strong effects on the intra-hemisphere connectivity differences, which is consistent with our findings in 4D domain (Agcaoglu et al, 2015).…”

“…Differences between cerebral hemispheres were first observed by Paul Broca (Broca, 1861) and Carl Wernicke (Wernicke, 1874). Since then, there have been numerous studies noting cerebral lateralization in healthy subjects based on homodynamic activation (Agcaoglu et al, 2014; Cai et al, 2013; Clements et al, 2006; Gobbele et al, 2008) in a 4D frequency domain framework applied to resting fMRI data (Agcaoglu et al, 2015) and using FC (Gee et al, 2011; Gotts et al, 2013; Liu et al, 2009; Nielsen et al, 2013; Stark et al, 2008; Zhu et al, 2014; Zuo et al, 2010).…”

Resting state connectivity differences in eyes open versus eyes closed conditions

“…This allows rs-fMRI to be acquired from a wide range of populations including patient groups, participants with intellectual disabilities, pediatric groups, and even unconscious patients (Smitha et al, 2017). Since Biswal, Yetkin, Haughton, and Hyde (1995) initially observed that temporal correlation of low frequency fluctuations in rs-fMRI (<0.1 Hz) can provide an estimate of functional connectivity (FC), research on rs-fMRI has greatly increased (Agcaoglu et al, 2018;Agcaoglu, Miller, Mayer, Hugdahl, & Calhoun, 2016;Allen et al, 2011;Cetin et al, 2016;Haak, Marquand, & Beckmann, 2018;Hart et al, 2018;Park, Friston, Pae, Park, & Razi, 2018;Rashid et al, 2018;Smitha et al, 2017).…”

Role of inter-hemispheric connections in functional brain networks

“…An early but still cited model of interhemispheric cross-talk 23 proposed that the brain is a highly reciprocally interconnected neural network, characterized by a constantly shifting pattern of locally higher and lower activation levels. Studies using fMRI suggest that hemispherical interactions are characterized by both functional cooperation and competition [24][25][26] , and patterns of correlated brain activity at rest can be used to evaluate the extent of hemispheric asymmetry 27 . However, the exact functional mechanisms through which the hemispheres interact are still not well understood 27,28 .…”

“…Studies using fMRI suggest that hemispherical interactions are characterized by both functional cooperation and competition [24][25][26] , and patterns of correlated brain activity at rest can be used to evaluate the extent of hemispheric asymmetry 27 . However, the exact functional mechanisms through which the hemispheres interact are still not well understood 27,28 . Here, we address two outstanding questions: to what extent are brain hemispheres engaged in a competitive behaviour in terms of nodal centrality?…”