No abstract

Humans demonstrate a prototypical hemispheric functional segregation pattern, with language and praxis lateralizing to the left hemisphere and spatial attention, face recognition, and emotional prosody to the right hemisphere. In this study, we used fMRI to determine laterality for all five functions in each participant. Crucially, we recruited a sample of left-handers preselected for atypical (right) language dominance (n= 24), which allowed us to characterize hemispheric asymmetry of the other functions and compare their functional segregation pattern with that of left-handers showing typical language dominance (n= 39). Our results revealed that most participants with left language dominance display the prototypical pattern of functional hemispheric segregation (44%) or deviate from this pattern in only one function (35%). Similarly, the vast majority of right language dominant participants demonstrated a completely mirrored brain organization (50%) or a reversal for all but one cognitive function (32%). Participants deviating by more than one function from the standard segregation pattern showed poorer cognitive performance, in line with an oft-presumed biological advantage of hemispheric functional segregation.

Magnetic resonance imaging was used to investigate brain structural and functional asymmetries in 15 participants with complete visceral reversal (situs inversus totalis, SIT). Language-related brain structural and functional lateralization of SIT participants, including peri-Sylvian gray and white matter asymmetries and hemispheric language dominance, was similar to those of 15 control participants individually matched for sex, age, education, and handedness. In contrast, the SIT cohort showed reversal of the brain (Yakovlevian) torque (occipital petalia and occipital bending) compared to the control group. Secondary findings suggested different asymmetry patterns between SIT participants with (n = 6) or without (n = 9) primary ciliary dyskinesia (PCD, also known as Kartagener syndrome) although the small sample sizes warrant cautious interpretation. In particular, reversed brain torque was mainly due to the subgroup with PCD-unrelated SIT and this group also included 55% left handers, a ratio close to a random allocation of handedness. We conclude that complete visceral reversal has no effect on the lateralization of brain structural and functional asymmetries associated with language, but seems to reverse the typical direction of the brain torque in particular in participants that have SIT unrelated to PCD. The observed differences in asymmetry patterns of SIT groups with and without PCD seem to suggest that symmetry breaking of visceral laterality, brain torque, and language dominance rely on different mechanisms.

Recent evidence has shown the presence of a "rich club" in the brain, which constitutes a core network of highly interconnected and spatially distributed brain regions, important for high-order cognitive processes. This study aimed to map the rich club organization in 17 young patients with moderate to severe TBI (15.71 ± 1.75 years) in the chronic stage of recovery and 17 age- and gender-matched controls. Probabilistic tractography was performed on diffusion weighted imaging data to construct the edges of the structural connectomes using number of streamlines as edge weight. In addition, the whole-brain network was divided into a rich club network, a local network and a feeder network connecting the latter two. Functional outcome was measured with a parent questionnaire for executive functioning. Our results revealed a significantly decreased rich club organization (p values < .05) and impaired executive functioning (p < .001) in young patients with TBI compared with controls. Specifically, we observed reduced density values in all three subnetworks (p values < .005) and a reduced mean strength in the rich club network (p = .013) together with an increased mean strength in the local network (p = .002) in patients with TBI. This study provides new insights into the nature of TBI-induced brain network alterations and supports the hypothesis that the local subnetwork tries to compensate for the biologically costly subnetwork of rich club nodes after TBI.

Objective Traumatic brain injury (TBI) is a heterogeneous disease with multiple neurological deficits that evolve over time. It is also associated with an increased incidence of neurodegenerative diseases. Accordingly, clinicians need better tools to predict a patient’s long‐term prognosis. Methods Diffusion‐weighted and anatomical MRI data were collected from 17 adolescents (mean age = 15y8mo) with moderate‐to‐severe TBI and 19 healthy controls. Using a network diffusion model (NDM), we examined the effect of progressive deafferentation and gray matter thinning in young TBI patients. Moreover, using a novel automated inference method, we identified several injury epicenters in order to determine the neural degenerative patterns in each TBI patient. Results We were able to identify the subject‐specific patterns of degeneration in each patient. In particular, the hippocampus, temporal cortices, and striatum were frequently found to be the epicenters of degeneration across the TBI patients. Orthogonal transformation of the predicted degeneration, using principal component analysis, identified distinct spatial components in the temporal–hippocampal network and the cortico‐striatal network, confirming the vulnerability of these networks to injury. The NDM model, best predictive of the degeneration, was significantly correlated with time since injury, indicating that NDM can potentially capture the pathological progression in the chronic phase of TBI. Interpretation These findings suggest that network spread may help explain patterns of distant gray matter thinning, which would be consistent with Wallerian degeneration of the white matter connections (i.e., “diaschisis”) from diffuse axonal injuries and multifocal contusive injuries, and the neurodegenerative patterns of abnormal protein aggregation and transmission, which are hallmarks of brain changes in TBI. NDM approaches could provide highly subject‐specific biomarkers relevant for disease monitoring and personalized therapies in TBI.