Revisiting brain rewiring and plasticity in children born without corpus callosum.

The corpus callosum is the largest white matter pathway connecting homologous structures of the two cerebral hemispheres. Remarkably, children and adults with developmental absence of the corpus callosum (callosal dysgenesis, CD) show typical interhemispheric integration, which is classically impaired in adult split-brain patients, for whom the corpus callosum is surgically severed. Tovar-Moll and colleagues (2014) proposed alternative neural pathways involved in the preservation of interhemispheric transfer. In a sample of six adults with CD, they revealed two homotopic bundles crossing the midline via the anterior and posterior commissures and connecting parietal cortices, and the microstructural properties of these aberrant bundles were associated with functional connectivity of these regions. The aberrant bundles were specific to CD and not visualised in healthy brains. We extended this study in a developmental cohort of 20 children with CD and 29 typically developing controls (TDC). The two anomalous white-matter bundles were visualised using tractography. Associations between structural properties of these bundles and their regional functional connectivity were explored. The proposed atypical bundles were observed in 30% of our CD cohort crossing via the anterior commissure, and in 30% crossing via the posterior commissure (also observed in 6.9% of TDC). However, the structural property measures of these bundles were not associated with parietal functional connectivity, bringing into question their role and implication for interhemispheric functional connectivity in CD. It is possible that very early disruption of embryological callosal development enhances neuroplasticity and facilitates the formation of these proposed alternative neural pathways, but further evidence is needed.

Structural Neuroplastic Responses Preserve Functional Connectivity and Neurobehavioural Outcomes in Children Born Without Corpus Callosum.

The corpus callosum is the largest white matter pathway in the brain connecting the two hemispheres. In the context of developmental absence (agenesis) of the corpus callosum (AgCC), a proposed candidate for neuroplastic response is strengthening of intrahemispheric pathways. To test this hypothesis, we assessed structural and functional connectivity in a uniquely large cohort of children with AgCC (n = 20) compared with typically developing controls (TDC, n = 29), and then examined associations with neurobehavioral outcomes using a multivariate data-driven approach (partial least squares correlation, PLSC). For structural connectivity, children with AgCC showed a significant increase in intrahemispheric connectivity in addition to a significant decrease in interhemispheric connectivity compared with TDC, in line with the aforementioned hypothesis. In contrast, for functional connectivity, children with AgCC and TDC showed a similar pattern of intrahemispheric and interhemispheric connectivity. In conclusion, we observed structural strengthening of intrahemispheric pathways in children born without corpus callosum, which seems to allow for functional connectivity comparable to a typically developing brain, and were relevant to explain neurobehavioral outcomes in this population. This neuroplasticity might be relevant to other disorders of axonal guidance, and developmental disorders in which corpus callosum alteration is observed.

On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke.

Recent tract-based analyses provided evidence for the exploitability of 3D-SHORE microstructural descriptors derived from diffusion MRI (dMRI) in revealing white matter (WM) plasticity. In this work, we focused on the main open issues left: (1) the comparative analysis with respect to classical tensor-derived indices, i.e., Fractional Anisotropy (FA) and Mean Diffusivity (MD); and (2) the ability to detect plasticity processes in gray matter (GM). Although signal modeling in GM is still largely unexplored, we investigated their sensibility to stroke-induced microstructural modifications occurring in the contralateral hemisphere. A more complete picture could provide hints for investigating the interplay of GM and WM modulations. Ten stroke patients and ten age/gender-matched healthy controls were enrolled in the study and underwent diffusion spectrum imaging (DSI). Acquisitions at three and two time points (tp) were performed on patients and controls, respectively. For all subjects and acquisitions, FA and MD were computed along with 3D-SHORE-based indices [Generalized Fractional Anisotropy (GFA), Propagator Anisotropy (PA), Return To the Axis Probability (RTAP), Return To the Plane Probability (RTPP), and Mean Square Displacement (MSD)]. Tract-based analysis involving the cortical, subcortical and transcallosal motor networks and region-based analysis in GM were successively performed, focusing on the contralateral hemisphere to the stroke. Reproducibility of all the indices on both WM and GM was quantitatively proved on controls. For tract-based, longitudinal group analyses revealed the highest significant differences across the subcortical and transcallosal networks for all the indices. The optimal regression model for predicting the clinical motor outcome at tp3 included GFA, PA, RTPP, and MSD in the subcortical network in combination with the main clinical information at baseline. Region-based analysis in the contralateral GM highlighted the ability of anisotropy indices in discriminating between groups mainly at tp1, while diffusivity indices appeared to be altered at tp2. 3D-SHORE indices proved to be suitable in probing plasticity in both WM and GM, further confirming their viability as a novel family of biomarkers in ischemic stroke in WM and revealing their potential exploitability in GM. Their combination with tensor-derived indices can provide more detailed insights of the different tissue modulations related to stroke pathology.

Ensemble average propagator-based detection of microstructural alterations after stroke.

PURPOSE: New analytical reconstruction techniques of diffusion weighted signal have been proposed. A previous work evidenced the exploitability of some indices derived from the simple harmonic oscillator-based reconstruction and estimation (3D-SHORE) model as numerical biomarkers of neural plasticity after stroke. Here, the analysis is extended to two additional indices: return to the plane/origin (RTPP/RTOP) probabilities. Moreover, several motor networks were introduced and the results were analyzed at different time scales. METHODS: Ten patients underwent three diffusion spectrum imaging (DSI) scans [1 week (tp1), 1 month (tp2) and 6 months (tp3) after stroke]. Ten matched controls underwent two DSI scans 1 month apart. 3D-SHORE was used for reconstructing the signal and the microstructural indices were derived. Tract-based analysis was performed along motor cortical, subcortical and transcallosal networks in the contralesional area. RESULTS: The optimal intra-class correlation coefficient (ICC) was obtained in the subcortical loop for propagator anisotropy (ICC [Formula: see text] 0.96), followed by generalized fractional anisotropy (ICC [Formula: see text] 0.94). The new indices reached the highest stability in the transcallosal network and performed well in the cortical and subcortical networks with the exception of RTOP in the cortical loop (ICC [Formula: see text] 0.59). They allowed discriminating patients from controls at the majority of the timescales. Finally, the regression model using indices calculated along the subcortical loop at tp1 resulted in the best prediction of clinical outcome. CONCLUSIONS: The whole set of microstructural indices provide measurements featuring high precision. The new indices allow discriminating patients from controls in all networks, except for RTPP in the cortical loop. Moreover, the 3D-SHORE indices in subcortical connections constitute a good regression model for predicting the clinical outcome at 6 months, supporting their suitability as numerical biomarkers for neuronal plasticity after stroke.