No abstract

A classic left frontal-temporal brain network is known to support language processes. However, the level of participation of constituent regions, and the contribution of extra-canonical areas, is not fully understood; this is particularly true in children, and in individuals who have experienced early neurological insult. In the present work, we propose whole-brain connectivity and graph-theoretical analysis of magnetoencephalography (MEG) source estimates to provide robust maps of the pediatric expressive language network. We examined neuromagnetic data from a group of typically-developing young children (n = 15, ages 4–6 years) and adolescents (n = 14, 16–18 years) completing an auditory verb generation task in MEG. All source analyses were carried out using a linearly-constrained minimum-variance (LCMV) beamformer. Conventional differential analyses revealed significant (p < 0.05, corrected) low-beta (13–23 Hz) event related desynchrony (ERD) focused in the left inferior frontal region (Broca’s area) in both groups, consistent with previous studies. Connectivity analyses were carried out in broadband (3–30 Hz) on time-course estimates obtained at the voxel level. Patterns of connectivity were characterized by phase locking value (PLV), and network hubs identified through eigenvector centrality (EVC). Hub analysis revealed the importance of left perisylvian sites, i.e., Broca’s and Wernicke’s areas, across groups. The hemispheric distribution of frontal and temporal lobe EVC values was asymmetrical in most subjects; left dominant EVC was observed in 20% of young children, and 71% of adolescents. Interestingly, the adolescent group demonstrated increased critical sites in the right cerebellum, left inferior frontal gyrus (IFG) and left putamen. Here, we show that whole brain connectivity and network analysis can be used to map critical language sites in typical development; these methods may be useful for defining the margins of eloquent tissue in neurosurgical candidates.

PURPOSE: Our aim was to study the association between abnormal findings on chest and brain imaging in patients with coronavirus disease 2019 (COVID-19) and neurologic symptoms. MATERIALS AND METHODS: In this retrospective, international multicenter study, we reviewed the electronic medical records and imaging of hospitalized patients with COVID-19 from March 3, 2020, to June 25, 2020. Our inclusion criteria were patients diagnosed with Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) infection with acute neurologic manifestations and available chest CT and brain imaging. The 5 lobes of the lungs were individually scored on a scale of 0-5 (0 corresponded to no involvement and 5 corresponded to .75% involvement). A CT lung severity score was determined as the sum of lung involvement, ranging from 0 (no involvement) to 25 (maximum involvement). RESULTS: A total of 135 patients met the inclusion criteria with 132 brain CT, 36 brain MR imaging, 7 MRA of the head and neck, and 135 chest CT studies. Compared with 86 (64%) patients without acute abnormal findings on neuroimaging, 49 (36%) patients with these findings had a significantly higher mean CT lung severity score (9.9 versus 5.8, P , .001). These patients were more likely to present with ischemic stroke (40 [82%] versus 11 [13%], P , .0001) and were more likely to have either ground-glass opacities or consolidation (46 [94%] versus 73 [84%], P ¼ .01) in the lungs. A threshold of the CT lung severity score of .8 was found to be 74% sensitive and 65% specific for acute abnormal findings on neuroimaging. The neuroimaging hallmarks of these patients were acute ischemic infarct (28%), intracranial hemorrhage (10%) including microhemorrhages (19%), and leukoencephalopathy with and/or without restricted diffusion (11%). The predominant CT chest findings were peripheral ground-glass opacities with or without consolidation. CONCLUSIONS: The CT lung disease severity score may be predictive of acute abnormalities on neuroimaging in patients with COVID-19 with neurologic manifestations. This can be used as a predictive tool in patient management to improve clinical outcome. ABBREVIATIONS: COVID-19 ¼ coronavirus disease 2019; GGOs ¼ ground-glass opacities; PRES ¼ posterior reversible encephalopathy syndrome; SARS-CoV-2 ¼ Severe Acute Respiratory Syndrome coronavirus 2; TIPIC ¼ Transient Perivascular Inflammation of the Carotid artery syndrome S evere Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) began in Wuhan, China, in December 2019 and has rapidly spread around the world to become a pandemic. 1 Extensive studies have described chest and brain imaging characteristics associated with coronavirus disease 2019 (COVID-19). 2-13 The hallmarks of COVID-19 infection on chest imaging