Language lateralization is the most intriguing trait of functional asymmetry for cognitive functions. Nowadays, ontogenetic determinants of this trait are largely unknown, but there are efforts to find its anatomical correlates. In particular, a white matter interhemispheric connection–the corpus callosum–has been proposed as such. In the present study, we aimed to find the association between the degree of language lateralization and metrics of the callosal sub-regions. We applied a sentence completion fMRI task to measure the degree of language lateralization in a group of healthy participants balanced for handedness. We obtained the volumes and microstructural properties of callosal sub-regions with two tractography techniques, diffusion tensor imaging (DTI) and constrained spherical deconvolution (CSD). The analysis of DTI-based metrics did not reveal any significant associations with language lateralization. In contrast, CSD-based analysis revealed that the volumes of a callosal sub-region terminating in the core posterior language-related areas predict a stronger degree of language lateralization. This finding supports the specific inhibitory model implemented through the callosal fibers projecting into the core posterior language-related areas in the degree of language lateralization, with no relevant contribution of other callosal sub-regions.

We present a modified methodology for phase-resolved surface wave reconstruction from incoherent X-band marine radar images. The method is based on the linear wave theory and uses the linear dispersion relation to extract the valuable signals associated with gravity waves. A parameter optimization of the proposed modification is performed based on simulated synthetic radar images. The quantitative comparisons in the accuracy of the standard and modified reconstruction methods are made for both simulated and real radar images. The correlation coefficient between reconstructed and true wave elevations is improved up to 0.9–0.92 for the present modified method from 0.69 to 0.74 for the standard method for the simulated sea surfaces. The wave spectra reconstructed from the real X-band radar measurements are in good agreement with those obtained from the independent point measurement by Miros RangeFinder for both unimodal and bimodal seas.

We demonstrate and verify, by the use of both synthetic and real wave data, a newly developed capability of short-time phase-resolved wave prediction based on incoherent X-band marine radar measurements. An inversion algorithm is developed to convert X-band radar sea surface measurements into the phase-resolved wave field and the associated wave spectrum based on the linear gravity wave theory. The wave components obtained from the reconstruction are then used to initialize the wave propagation model that is used to provide a short-time deterministic forecast of wave field evolution downstream. Both wave spectrum and spatial-temporal wave elevation evolution obtained based on the X-band measurements are compared with the independent point wave measurements by Miros RangeFinder. The agreements between them are reasonably well, which has a significant implication on practical applications of short-time deterministic wave prediction in optimal marine operations.

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