Altered microstructure of the splenium of corpus callosum is associated with neurodevelopmental impairment in preterm infants with necrotizing enterocolitis

Background Necrotizing enterocolitis (NEC) is a devastating disease in preterm infants with significant morbidities, including neurodevelopmental impairment (NDI). This study aimed to investigate whether NEC is associated with (1) brain volume expansion and white matter maturation using diffusion tensor imaging analysis and (2) NDI compared with preterm infants without NEC. Methods We included 86 preterm infants (20 with NEC and 66 without NEC) with no evidence of brain abnormalities on trans-fontanelle ultrasonography and magnetic resonance imaging at term-equivalent age (TEA). Regional brain volume analysis and white matter tractography were performed to study brain microstructure alterations. NDI was assessed using the Bayley Scales of Infant and Toddler Development-III (BSID-III) at 18 months of corrected age (CA). Results Preterm infants with NEC showed significantly high risk of motor impairment (odds ratio 58.26, 95% confidence interval 7.80–435.12, p < 0.001). We found significantly increased mean diffusivity (MD) in the splenium of corpus callosum (sCC) (p = 0.001) and the left corticospinal tract (p = 0.001) in preterm infants with NEC. The sCC with increased MD showed a negative association with the BSID-III language (p = 0.025) and motor scores (p = 0.002) at 18 months of CA, implying the relevance of sCC integrity with later NDI. Conclusion The white matter microstructure differed between preterm infants with and without NEC. The prognostic value of network parameters of sCC at TEA may provide better information for the early detection of NDI in preterm infants.

Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes

Background: Following mild traumatic brain injury (mTBI) compromised white matter structural integrity can result in alterations in functional connectivity of large-scale brain networks and may manifest in functional deficit including cognitive dysfunction . Advanced magnetic resonance neuroimaging techniques, specifically diffusion tensor imaging (DTI) and resting state functional magnetic resonance imaging (rs-fMRI), have demonstrated an increased sensitivity for detecting microstructural changes associated with mTBI. Identification of novel imaging biomarkers can facilitate early detection of these changes for effective treatment. In this study, we hypothesize that feature selection combining both structural and functional connectivity increases classification accuracy. Methods: 16 subjects with mTBI and 20 healthy controls underwent both DTI and resting state functional imaging. Structural connectivity matrices were generated from white matter tractography from DTI sequences. Functional connectivity was measured through pairwise correlations of rs-fMRI between brain regions. Features from both DTI and rs-fMRI were selected by identifying five brain regions with the largest group differences and were used to classify the generated functional and structural connectivity matrices, respectively. Classification was performed using linear support vector machines and validated with leave-one-out cross validation. Results: Group comparisons revealed increased functional connectivity in the temporal lobe and cerebellum as well as decreased structural connectivity in the temporal lobe. After training on structural connections only, a maximum classification accuracy of 78% was achieved when structural connections were selected based on their corresponding functional connectivity group differences. After training on functional connections only, a maximum classification accuracy of 69% was achieved when functional connections were selected based on their structural connectivity group differences. After training on both structural and functional connections, a maximum classification accuracy of 69% was achieved when connections were selected based on their structural connectivity. Conclusions: Our multimodal approach to ROI selection achieves at highest, a classification accuracy of 78%. Our results also implicate the temporal lobe in the pathophysiology of mTBI. Our findings suggest that white matter tractography can serve as a robust biomarker for mTBI when used in tandem with resting state functional connectivity.

Left angular gyrus disconnection impairs multiplication fact retrieval

Arithmetic fact retrieval has been suggested to recruit a left-lateralized network comprising perisylvian language areas, parietal areas such as the angular gyrus (AG), and subcortical structures such as the hippocampus. However, the underlying white matter connectivity of these areas has not been evaluated systematically so far. Using simple multiplication problems, we evaluated how disconnections in parietal brain areas affected arithmetic fact retrieval following stroke. We derived disconnectivity measures by jointly considering data from n=73 patients with acute unilateral lesions in either hemisphere and a white-matter tractography atlas (HCP-842) using the Lesion Quantification Toolbox (LQT). Whole-brain voxel-based analysis indicated a left-hemispheric cluster of white matter fibers connecting the AG and superior temporal areas to be associated with a fact retrieval deficit. Subsequent analyses of direct grey-to-grey matter disconnections revealed that disconnections of additional left-hemispheric areas (e.g., between the superior temporal gyrus and parietal areas) were significantly associated with the observed fact retrieval deficit. Results imply that disconnections of parietal areas (i.e., the AG) with language-related areas (i.e., superior and middle temporal gyri) seem specifically detrimental to arithmetic fact retrieval. This suggests that arithmetic fact retrieval recruits a widespread left-hemispheric network and emphasizes the relevance of white matter connectivity for number processing.

Fixel-Based Analysis Effectively Identifies White Matter Tract Degeneration in Huntington’s Disease

Microstructure damage in white matter might be linked to regional and global atrophy in Huntington’s Disease (HD). We hypothesize that degeneration of subcortical regions, including the basal ganglia, is associated with damage of white matter tracts linking these affected regions. We aim to use fixel-based analysis to identify microstructural changes in the white matter tracts. To further assess the associated gray matter damage, diffusion tensor-derived indices were measured from regions of interest located in the basal ganglia. Diffusion weighted images were acquired from 12 patients with HD and 12 healthy unrelated controls using a 3 Tesla scanner. Reductions in fixel-derived metrics occurs in major white matter tracts, noticeably in corpus callosum, internal capsule, and the corticospinal tract, which were closely co-localized with the regions of increased diffusivity in basal ganglia. These changes in diffusion can be attributed to potential axonal degeneration. Fixel-based analysis is effective in studying white matter tractography and fiber changes in HD.

Preoperative Repetitive Navigated TMS and Functional White Matter Tractography in a Bilingual Patient with a Brain Tumor in Wernike Area

Awake surgery and intraoperative neuromonitoring represent the gold standard for surgery of lesion located in language-eloquent areas of the dominant hemisphere, enabling the maximal safe resection while preserving language function. Nevertheless, this functional mapping is invasive; it can be executed only during surgery and in selected patients. Moreover, the number of neuro-oncological bilingual patients is constantly growing, and performing awake surgery in this group of patients can be difficult. In this scenario, the application of accurate, repeatable and non-invasive preoperative mapping procedures is needed, in order to define the anatomical distribution of both languages. Repetitive navigated transcranial magnetic stimulation (rnTMS) associated with functional subcortical fiber tracking (nTMS-based DTI-FT) represents a promising and comprehensive mapping tool to display language pathway and function reorganization in neurosurgical patients. Herein we report a case of a bilingual patient affected by brain tumor in the left temporal lobe, who underwent rnTMS mapping for both languages (Romanian and Italian), disclosing the true eloquence of the anterior part of the lesion in both tests. After surgery, language abilities were intact at follow-up in both languages. This case represents a preliminary application of nTMS-based DTI-FT in neurosurgery for brain tumor in eloquent areas in a bilingual patient.

Entrack: Probabilistic Spherical Regression with Entropy Regularization for Fiber Tractography

White matter tractography, based on diffusion-weighted magnetic resonance images, is currently the only available in vivo method to gather information on the structural brain connectivity. The low resolution of diffusion MRI data suggests to employ probabilistic methods for streamline reconstruction, i.e., for fiber crossings. We propose a general probabilistic model for spherical regression based on the Fisher-von-Mises distribution, which efficiently estimates maximum entropy posteriors of local streamline directions with machine learning methods. The optimal precision of posteriors for streamlines is determined by an information-theoretic technique, the expected log-posterior agreement concept. It relies on the requirement that the posterior distributions of streamlines, inferred on retest measurements of the same subject, should yield stable results within the precision determined by the noise level of the data source.

Visual information routes in the posterior dorsal and ventral face network studied with intracranial neurophysiology, and white matter tract endpoints

ABSTRACTOccipito-temporal regions within the face network process perceptual and socio-emotional information, but the dynamics and interactions between different nodes within this network remain unknown. Here, we analyzed intracerebral EEG from 11 epileptic patients viewing a stimulus sequence beginning with a neutral face with direct gaze. The gaze could avert or remain direct, while the emotion changed to fearful or happy. N200 field potential peak latencies indicated that face processing begins in inferior occipital cortex and proceeds anteroventrally to fusiform and inferior temporal cortices, in parallel. The superior temporal sulcus responded preferentially to gaze changes with augmented field potential amplitudes for averted versus direct gaze, and large effect sizes relative to other regions of the network. An overlap analysis of posterior white matter tractography endpoints (from 1066 healthy brains) relative to active intracerebral electrodes from the 11 patients showed likely involvement of both dorsal and ventral posterior white matter pathways. The inferior occipital and temporal sulci likely broadcast their information - the former dorsally to intraparietal sulcus, and the latter between fusiform and superior temporal cortex. Overall, our data call for inclusion of inferior temporal cortex in face processing models, and anchor the superior temporal cortex in dynamic gaze processing.