Abnormalities in hemispheric lateralization of intra- and inter-hemispheric white matter connections in schizophrenia

Hemisphere lateralization of graph theoretical network in end-stage knee osteoarthritis patients

Hemisphere functional lateralization is a prominent feature of the human brain. However, it is not known whether hemispheric lateralization features are altered in end-stage knee osteoarthritis (esKOA). In this study, we performed resting-state functional magnetic imaging on 46 esKOA patients and 31 healthy controls (HCs) and compared with the global and inter-hemisphere network to clarify the hemispheric functional network lateralization characteristics of patients. A correlation analysis was performed to explore the relationship between the inter-hemispheric network parameters and clinical features of patients. The node attributes were analyzed to explore the factors changing in the hemisphere network function lateralization in patients. We found that patients and HCs exhibited "small-world" brain network topology. Clustering coefficient increased in patients compared with that in HCs. The hemisphere difference in inter-hemispheric parameters including assortativity, global efficiency, local efficiency, clustering coefficients, small-worldness, and shortest path length. The pain course and intensity of esKOA were positively correlated with the right hemispheric lateralization in local efficiency, clustering coefficients, and the small-worldness, respectively. The significant alterations of several nodal properties were demonstrated within group in pain-cognition, pain-emotion, and pain regulation circuits. The abnormal lateralization inter-hemisphere network may be caused by the destruction of regional network properties.

Hemispheric lateralization of language processing: insights from network-based symptom mapping and patient subgroups

The hemispheric laterality of language processing has become a hot topic in modern neuroscience. Although most previous studies have reported left-lateralized language processing, other studies found it to be bilateral. A previous neurocomputational model has proposed a unified framework to explain that the above discrepancy might be from healthy and patient individuals. This model posits an initial symmetry but imbalanced capacity in language processing for healthy individuals, with this imbalance contributing to language recovery disparities following different hemispheric injuries. The present study investigated this model by analyzing the lateralization patterns of language subnetworks across multiple attributes with a group of 99 patients (compared to nonlanguage processing) and examining the lateralization patterns of language subnetworks in subgroups with damage to different hemispheres. Subnetworks were identified using a whole-brain network-based lesion-symptom mapping method, and the lateralization index was quantitatively measured. We found that all the subnetworks in language processing were left-lateralized, while subnetworks in nonlanguage processing had different lateralization patterns. Moreover, diverse hemisphere-injury subgroups exhibited distinct language recovery effects. These findings provide robust support for the proposed neurocomputational model of language processing.

Brain Functional Connectivity Asymmetry: Left Hemisphere Is More Modular

Graph-theoretical approaches are increasingly used to study the brain and may enhance our understanding of its asymmetries. In this paper, we hypothesize that the structure of the left hemisphere is, on average, more modular. To this end, we analyzed resting-state functional magnetic resonance imaging data of 90 healthy subjects. We computed functional connectivity by Pearson’s correlation coefficient, turned the matrix into an unweighted graph by keeping a certain percentage of the strongest connections, and quantified modularity separately for the subgraph formed by each hemisphere. Our results show that the left hemisphere is more modular. The result is consistent across a range of binarization thresholds, regardless of whether the two hemispheres are thresholded together or separately. This illustrates that graph-theoretical analysis can provide a robust characterization of lateralization of brain functional connectivity.

Exploring brain activity for positive and negative emotions by means of EEG microstates

Microstate analysis applied to electroencephalographic signals (EEG) allows both temporal and spatial imaging exploration and represents the activity across the scalp. Despite its potential usefulness in understanding brain activity during a specific task, it has been mostly exploited at rest. We extracted EEG microstates during the presentation of emotional expressions, presented either unilaterally (a face in one visual hemifield) or bilaterally (two faces, one in each hemifield). Results revealed four specific microstate’s topographies: (i) M1 involves the temporal areas, mainly in the right hemisphere, with a higher occurrence for stimuli presented in the left than in the right visual field; (ii) M2 is localized in the left temporal cortex, with higher occurrence and coverage for unilateral than bilateral presentations; (iii) M3, with a bilateral temporo-parietal localization, shows higher coverage for bilateral than unilateral presentation; (iv) M4, mainly localized in the right fronto-parietal areas and possibly representing the hemispheric specialization for the peculiar stimulus category, shows higher occurrence and coverage for unilateral stimuli presented in the left than in the right visual field. These results suggest that microstate analysis is a valid tool to explore the cerebral response to emotions and can add new insights on the cerebral functioning, with respect to other EEG markers.