Normative trajectories of extra-axial cerebrospinal fluid during childhood and adolescence defined in a clinically-acquired MRI dataset.

Background: Extra-axial cerebrospinal fluid (eaCSF) refers to the CSF in the subarachnoid spaces that surrounds the brain parenchyma. Benign enlargement of the subarachnoid space (BESS), a condition marked by increased eaCSF thickness, has been associated with macrocephaly and may be associated with subdural collections. However, diagnosis of BESS is complicated by the lack of age-specific normative data which hinders rigorous investigation of its clinical associations. Growth charts of eaCSF could shed light on normal CSF dynamics while also providing a normative benchmark to assist the diagnosis of BESS and other associated conditions. Methods: We accessed clinically-acquired T1w MRI scans from 1226 pediatric patients to form a clinical control cohort. Nine scans from subjects with a diagnosis of BESS from a board-certified pediatric neuroradiologist were also reviewed. SynthSeg was used to segment each T1w scan into various tissue types, including eaCSF. Growth charts of eaCSF were modeled using the clinical control cohort. The confirmed BESS cases were then benchmarked against these charts to test the performance of eaCSF growth charts. Results: eaCSF thickness varied nonlinearly with age, steadily decreasing from birth to two years, then trending upwards in early adolescence. Seven of the nine patients with a clinical diagnosis of BESS were above the 97.5 th percentile for their age for at least one eaCSF measure. Centile scores were able to distinguish BESS cases from controls with an area under curve (AUC) greater than 0.95. Discussion: eaCSF thickness evolves in a dynamic pattern throughout childhood and adolescence. Patients with BESS can be differentiated from clinical controls using computational measurements of eaCSF thickness paired with normative modeling. Our findings demonstrate the feasibility of computational extraction of eaCSF with a potential point of clinical relevance, delineation of BESS diagnosis. Enhanced understanding of normative eaCSF is critical in further investigations its clinical associations.

Tumour-infiltrated cortex participates in large-scale cognitive circuits.

The extent to which tumour-infiltrated brain tissue contributes to cognitive function remains unclear. We tested the hypothesis that cortical tissue infiltrated by diffuse gliomas participates in large-scale cognitive circuits using a unique combination of intracranial electrocorticography (ECoG) and resting-state functional magnetic resonance (fMRI) imaging in four patients. We also assessed the relationship between functional connectivity with tumour-infiltrated tissue and long-term cognitive outcomes in a larger, overlapping cohort of 17 patients. We observed significant task-related high gamma (70-250 Hz) power modulations in tumour-infiltrated cortex in response to increased cognitive effort (i.e., switch counting compared to simple counting), implying preserved functionality of neoplastic tissue for complex tasks probing executive function. We found that tumour locations corresponding to task-responsive electrodes exhibited functional connectivity patterns that significantly co-localised with canonical brain networks implicated in executive function. Specifically, we discovered that tumour-infiltrated cortex with larger task-related high gamma power modulations tended to be more functionally connected to the dorsal attention network (DAN). Finally, we demonstrated that tumour-DAN connectivity is evident across a larger cohort of patients with gliomas and that it relates to long-term postsurgical outcomes in goal-directed attention. Overall, this study contributes convergent fMRI-ECoG evidence that tumour-infiltrated cortex participates in large-scale neurocognitive circuits that support executive function in health. These findings underscore the potential clinical utility of mapping large-scale connectivity of tumour-infiltrated tissue in the care of patients with diffuse gliomas.

The molecular genetic landscape of human brain size variation.

Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.

Brain Growth Charts for Quantitative Analysis of Pediatric Clinical Brain MRI Scans with Limited Imaging Pathology.

Background Clinically acquired brain MRI scans represent a valuable but underused resource for investigating neurodevelopment due to their technical heterogeneity and lack of appropriate controls. These barriers have curtailed retrospective studies of clinical brain MRI scans compared with more costly prospectively acquired research-quality brain MRI scans. Purpose To provide a benchmark for neuroanatomic variability in clinically acquired brain MRI scans with limited imaging pathology (SLIPs) and to evaluate if growth charts from curated clinical MRI scans differed from research-quality MRI scans or were influenced by clinical indication for the scan. Materials and Methods In this secondary analysis of preexisting data, clinical brain MRI SLIPs from an urban pediatric health care system (individuals aged ≤22 years) were scanned across nine 3.0-T MRI scanners. The curation process included manual review of signed radiology reports and automated and manual quality review of images without gross pathology. Global and regional volumetric imaging phenotypes were measured using two image segmentation pipelines, and clinical brain growth charts were quantitatively compared with charts derived from a large set of research controls in the same age range by means of Pearson correlation and age at peak volume. Results The curated clinical data set included 532 patients (277 male; median age, 10 years [IQR, 5-14 years]; age range, 28 days after birth to 22 years) scanned between 2005 and 2020. Clinical brain growth charts were highly correlated with growth charts derived from research data sets (22 studies, 8346 individuals [4947 male]; age range, 152 days after birth to 22 years) in terms of normative developmental trajectories predicted by the models (median r = 0.979). Conclusion The clinical indication of the scans did not significantly bias the output of clinical brain charts. Brain growth charts derived from clinical controls with limited imaging pathology were highly correlated with brain charts from research controls, suggesting the potential of curated clinical MRI scans to supplement research data sets. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Ertl-Wagner and Pai in this issue.

Listening to Yourself and Watching Your Tongue: Distinct Abilities and Brain Regions for Monitoring Semantic and Phonological Speech Errors.

Despite the many mistakes we make while speaking, people can effectively communicate because we monitor our speech errors. However, the cognitive abilities and brain structures that support speech error monitoring are unclear. There may be different abilities and brain regions that support monitoring phonological speech errors versus monitoring semantic speech errors. We investigated speech, language, and cognitive control abilities that relate to detecting phonological and semantic speech errors in 41 individuals with aphasia who underwent detailed cognitive testing. Then, we used support vector regression lesion symptom mapping to identify brain regions supporting detection of phonological versus semantic errors in a group of 76 individuals with aphasia. The results revealed that motor speech deficits as well as lesions to the ventral motor cortex were related to reduced detection of phonological errors relative to semantic errors. Detection of semantic errors selectively related to auditory word comprehension deficits. Across all error types, poor cognitive control related to reduced detection. We conclude that monitoring of phonological and semantic errors relies on distinct cognitive abilities and brain regions. Furthermore, we identified cognitive control as a shared cognitive basis for monitoring all types of speech errors. These findings refine and expand our understanding of the neurocognitive basis of speech error monitoring.

Brain network mapping and glioma pathophysiology.

Adult diffuse gliomas are among the most difficult brain disorders to treat in part due to a lack of clarity regarding the anatomical origins and mechanisms of migration of the tumours. While the importance of studying networks of glioma spread has been recognized for at least 80 years, the ability to carry out such investigations in humans has emerged only recently. Here, we comprehensively review the fields of brain network mapping and glioma biology to provide a primer for investigators interested in merging these areas of inquiry for the purposes of translational research. Specifically, we trace the historical development of ideas in both brain network mapping and glioma biology, highlighting studies that explore clinical applications of network neuroscience, cells-of-origin of diffuse glioma and glioma-neuronal interactions. We discuss recent research that has merged neuro-oncology and network neuroscience, finding that the spatial distribution patterns of gliomas follow intrinsic functional and structural brain networks. Ultimately, we call for more contributions from network neuroimaging to realize the translational potential of cancer neuroscience.

Genomic Sequencing from Sputum for Tuberculosis Disease Diagnosis, Lineage Determination, and Drug Susceptibility Prediction.

Universal access to drug susceptibility testing for newly diagnosed tuberculosis patients is recommended. Access to culture-based diagnostics remains limited, and targeted molecular assays are vulnerable to emerging resistance mutations. Improved protocols for direct-from-sputum Mycobacterium tuberculosis sequencing would accelerate access to comprehensive drug susceptibility testing and molecular typing. We assessed a thermo-protection buffer-based direct-from-sample M. tuberculosis whole-genome sequencing protocol. We prospectively analyzed 60 acid-fast bacilli smear-positive clinical sputum samples in India and Madagascar. A diversity of semiquantitative smear positivity-level samples were included. Sequencing was performed using Illumina and MinION (monoplex and multiplex) technologies. We measured the impact of bacterial inoculum and sequencing platforms on genomic read depth, drug susceptibility prediction performance, and typing accuracy. M. tuberculosis was identified by direct sputum sequencing in 45/51 samples using Illumina, 34/38 were identified using MinION-monoplex sequencing, and 20/24 were identified using MinION-multiplex sequencing. The fraction of M. tuberculosis reads from MinION sequencing was lower than from Illumina, but monoplexing grade 3+ samples on MinION produced higher read depth than Illumina (P < 0.05) and MinION multiplexing (P < 0.01). No significant differences in sensitivity and specificity of drug susceptibility predictions were seen across sequencing modalities or within each technology when stratified by smear grade. Illumina sequencing from sputum accurately identified 1/8 (rifampin) and 6/12 (isoniazid) resistant samples, compared to 2/3 (rifampin) and 3/6 (isoniazid) accurately identified with Nanopore monoplex. Lineage agreement levels between direct and culture-based sequencing were 85% (MinION-monoplex), 88% (Illumina), and 100% (MinION-multiplex). M. tuberculosis direct-from-sample whole-genome sequencing remains challenging. Improved and affordable sample treatment protocols are needed prior to clinical deployment.

Transcriptomic and connectomic correlates of differential spatial patterning among gliomas.

Unravelling the complex events driving grade-specific spatial distribution of brain tumour occurrence requires rich datasets from both healthy individuals and patients. Here, we combined open-access data from The Cancer Genome Atlas, the UK Biobank and the Allen Brain Human Atlas to disentangle how the different spatial occurrences of glioblastoma multiforme and low-grade gliomas are linked to brain network features and the normative transcriptional profiles of brain regions. From MRI of brain tumour patients, we first constructed a grade-related frequency map of the regional occurrence of low-grade gliomas and the more aggressive glioblastoma multiforme. Using associated mRNA transcription data, we derived a set of differential gene expressions from glioblastoma multiforme and low-grade gliomas tissues of the same patients. By combining the resulting values with normative gene expressions from post-mortem brain tissue, we constructed a grade-related expression map indicating which brain regions express genes dysregulated in aggressive gliomas. Additionally, we derived an expression map of genes previously associated with tumour subtypes in a genome-wide association study (tumour-related genes). There were significant associations between grade-related frequency, grade-related expression and tumour-related expression maps, as well as functional brain network features (specifically, nodal strength and participation coefficient) that are implicated in neurological and psychiatric disorders. These findings identify brain network dynamics and transcriptomic signatures as key factors in regional vulnerability for glioblastoma multiforme and low-grade glioma occurrence, placing primary brain tumours within a well established framework of neurological and psychiatric cortical alterations.

High fluoroquinolone resistance proportions among multidrug-resistant tuberculosis driven by dominant L2 Mycobacterium tuberculosis clones in the Mumbai Metropolitan Region.

BACKGROUND: Multidrug-resistant (MDR) Mycobacterium tuberculosis complex (MTBC) strains are a serious health problem in India, also contributing to one-fourth of the global MDR tuberculosis (TB) burden. About 36% of the MDR MTBC strains are reported fluoroquinolone (FQ) resistant leading to high pre-extensively drug-resistant (pre-XDR) and XDR-TB (further resistance against bedaquiline and/or linezolid) rates. Still, factors driving the MDR/pre-XDR epidemic in India are not well defined. METHODS: In a retrospective study, we analyzed 1852 consecutive MTBC strains obtained from patients from a tertiary care hospital laboratory in Mumbai by whole genome sequencing (WGS). Univariate and multivariate statistics was used to investigate factors associated with pre-XDR. Core genome multi locus sequence typing, time scaled haplotypic density (THD) method and homoplasy analysis were used to analyze epidemiological success, and positive selection in different strain groups, respectively. RESULTS: In total, 1016 MTBC strains were MDR, out of which 703 (69.2%) were pre-XDR and 45 (4.4%) were XDR. Cluster rates were high among MDR (57.8%) and pre-XDR/XDR (79%) strains with three dominant L2 (Beijing) strain clusters (Cl 1-3) representing half of the pre-XDR and 40% of the XDR-TB cases. L2 strains were associated with pre-XDR/XDR-TB (P < 0.001) and, particularly Cl 1-3 strains, had high first-line and FQ resistance rates (81.6-90.6%). Epidemic success analysis using THD showed that L2 strains outperformed L1, L3, and L4 strains in short- and long-term time scales. More importantly, L2 MDR and MDR + strains had higher THD success indices than their not-MDR counterparts. Overall, compensatory mutation rates were highest in L2 strains and positive selection was detected in genes of L2 strains associated with drug tolerance (prpB and ppsA) and virulence (Rv2828c). Compensatory mutations in L2 strains were associated with a threefold increase of THD indices, suggesting improved transmissibility. CONCLUSIONS: Our data indicate a drastic increase of FQ resistance, as well as emerging bedaquiline resistance which endangers the success of newly endorsed MDR-TB treatment regimens. Rapid changes in treatment and control strategies are required to contain transmission of highly successful pre-XDR L2 strains in the Mumbai Metropolitan region but presumably also India-wide.

COVID-19 Vaccination Status Among Healthcare Workers and Its Effect on Disease Manifestations: A Study From Northeast India.

Background and objective Since being declared a global pandemic, coronavirus disease 2019 (COVID-19) has led to millions of cases and deaths worldwide. Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to wreak havoc on individuals, healthcare systems, and economies, the intensive vaccination strategies adopted by several countries have significantly slowed the progress and the severity of the disease. In this study, we aimed to determine the COVID-19 vaccination status among healthcare workers (HCWs) and examine the effects of vaccination on disease manifestations. Materials and methods This cross-sectional study was conducted at a teaching hospital in Northeast India from April 2021 to September 2021, during the second phase of the COVID-19 pandemic. HCWs employed in the hospital who were laboratory-confirmed cases of COVID-19 based on semiquantitative real-time reverse transcriptase-polymerase chain reaction (RT-PCR) or cartridge-based nucleic acid amplification test (CBNAAT) on oropharyngeal samples were included in the study. Data analysis was performed using Microsoft Excel (Microsoft Office Professional Plus 2019, Microsoft Corp., Redmond, WA) Results A total of 178 HCWs reported positive for COVID-19 infection during the study period. Of these, 42 (23.59%) were males and 136 were females (76.40%). Among them, 86 (48.32%) HCWs were fully vaccinated, 58 (32.58%) were partially vaccinated, and 34 (19.10%) were not vaccinated. Most of the HCWs experienced mild disease (145, 81.46%), and only four (2.24%) reported moderate to severe disease. Compared with unvaccinated HCWs, individuals who have had either one or two doses of vaccines were less likely to have moderate to severe disease or seek treatment at the hospital. On symptoms analysis, shortness of breath was found to be more common in unvaccinated individuals than in vaccinated patients, and anosmia and loss of taste were more common in vaccinated than in unvaccinated individuals. No deaths were reported among the participants included in this study. Conclusions Following the first and second waves of the COVID-19 pandemic, a substantial proportion of HCWs were infected with SARS-CoV-2, likely as a result of the acquisition of the virus in the community during the early phase of local spread. Fully vaccinated individuals with COVID-19 were more likely to be completely asymptomatic or only mildly symptomatic compared to unvaccinated HCWs.

Structural disconnection of the posterior medial frontal cortex reduces speech error monitoring.

Optimal performance in any task relies on the ability to detect and correct errors. The anterior cingulate cortex and the broader posterior medial frontal cortex (pMFC) are active during error processing. However, it is unclear whether damage to the pMFC impairs error monitoring. We hypothesized that successful error monitoring critically relies on connections between the pMFC and broader cortical networks involved in executive functions and the task being monitored. We tested this hypothesis in the context of speech error monitoring in people with post-stroke aphasia. Diffusion weighted images were collected in 51 adults with chronic left-hemisphere stroke and 37 age-matched control participants. Whole-brain connectomes were derived using constrained spherical deconvolution and anatomically-constrained probabilistic tractography. Support vector regressions identified white matter connections in which lost integrity in stroke survivors related to reduced error detection during confrontation naming. Lesioned connections to the bilateral pMFC were related to reduce error monitoring, including many connections to regions associated with speech production and executive function. We conclude that connections to the pMFC support error monitoring. Error monitoring in speech production is supported by the structural connectivity between the pMFC and regions involved in speech production, comprehension, and executive function. Interactions between pMFC and other task-relevant processors may similarly be critical for error monitoring in other task contexts.

Effectiveness of an inactivated virus-based SARS-CoV-2 vaccine, BBV152, in India: a test-negative, case-control study.

BACKGROUND: BBV152 is a whole-virion inactivated SARS-CoV-2 vaccine that has been deployed in India. The results of the phase 3 trial have shown clinical efficacy of BBV152. We aimed to evaluate the effectiveness of BBV152 against symptomatic RT-PCR-confirmed SARS-CoV-2 infection. METHODS: We conducted a test-negative, case-control study among employees of the All India Institute of Medical Sciences (a tertiary care hospital in New Delhi, India), who had symptoms suggestive of COVID-19 and had an RT-PCR test for SARS-CoV-2 during the peak of the second wave of the COVID-19 pandemic in India between April 15 and May 15, 2021. Cases (test-positives) and controls (test-negatives) were matched (1:1) on the basis of age and gender. The odds of vaccination with BBV152 were compared between cases and controls and adjusted for level of occupational exposure (to COVID-19), previous SARS-CoV-2 infection, and calendar time, using conditional logistic regression. The primary outcome was effectiveness of two doses of BBV152 (with the second dose received at least 14 days before testing) in reducing the odds of symptomatic RT-PCR-confirmed SARS-CoV-2 infection, expressed as (1 - odds ratio) × 100%. FINDINGS: Between April 15 and May 15, 2021, 3732 individuals had an RT-PCR test. Of these, 2714 symptomatic employees had data on vaccination status, and 1068 matched case-control pairs were available for analysis. The adjusted effectiveness of BBV152 against symptomatic COVID-19 after two doses administered at least 14 days before testing was 50% (95% CI 33-62; p<0·0001). The adjusted effectiveness of two doses administered at least 28 days before testing was 46% (95% CI 22-62) and administered at least 42 days before testing was 57% (21-76). After excluding participants with previous SARS-CoV-2 infections, the adjusted effectiveness of two doses administered at least 14 days before testing was 47% (95% CI 29-61). INTERPRETATION: This study shows the effectiveness of two doses of BBV152 against symptomatic COVID-19 in the context of a huge surge in cases, presumably dominated by the potentially immune-evasive delta (B.1.617.2) variant of SARS-CoV-2. Our findings support the ongoing roll-out of this vaccine to help control the spread of SARS-CoV-2, while continuing the emphasis on adherence to non-pharmacological measures. FUNDING: None. TRANSLATION: For the Hindi translation of the abstract see Supplementary Materials section.

Lesion covariance networks reveal proposed origins and pathways of diffuse gliomas.

Diffuse gliomas have been hypothesized to originate from neural stem cells in the subventricular zone and develop along previously healthy brain networks. Here, we evaluated these hypotheses by mapping independent sources of glioma localization and determining their relationships with neurogenic niches, genetic markers and large-scale connectivity networks. By applying independent component analysis to lesion data from 242 adult patients with high- and low-grade glioma, we identified three lesion covariance networks, which reflect clusters of frequent glioma localization. Replicability of the lesion covariance networks was assessed in an independent sample of 168 glioma patients. We related the lesion covariance networks to important clinical variables, including tumour grade and patient survival, as well as genomic information such as molecular genetic subtype and bulk transcriptomic profiles. Finally, we systematically cross-correlated the lesion covariance networks with structural and functional connectivity networks derived from neuroimaging data of over 4000 healthy UK BioBank participants to uncover intrinsic brain networks that may that underlie tumour development. The three lesion covariance networks overlapped with the anterior, posterior and inferior horns of the lateral ventricles respectively, extending into the frontal, parietal and temporal cortices. These locations were independently replicated. The first lesion covariance network, which overlapped with the anterior horn, was associated with low-grade, isocitrate dehydrogenase -mutated/1p19q-codeleted tumours, as well as a neural transcriptomic signature and improved overall survival. Each lesion covariance network significantly coincided with multiple structural and functional connectivity networks, with the first bearing an especially strong relationship with brain connectivity, consistent with its neural transcriptomic profile. Finally, we identified subcortical, periventricular structures with functional connectivity patterns to the cortex that significantly matched each lesion covariance network. In conclusion, we demonstrated replicable patterns of glioma localization with clinical relevance and spatial correspondence with large-scale functional and structural connectivity networks. These results are consistent with prior reports of glioma growth along white matter pathways, as well as evidence for the coordination of glioma stem cell proliferation by neuronal activity. Our findings describe how the locations of gliomas relate to their proposed subventricular origins, suggesting a model wherein periventricular brain connectivity guides tumour development.

BOLD Coupling between Lesioned and Healthy Brain Is Associated with Glioma Patients' Recovery.

Predicting functional outcomes after surgery and early adjuvant treatment is difficult due to the complex, extended, interlocking brain networks that underpin cognition. The aim of this study was to test glioma functional interactions with the rest of the brain, thereby identifying the risk factors of cognitive recovery or deterioration. Seventeen patients with diffuse non-enhancing glioma (aged 22-56 years) were longitudinally MRI scanned and cognitively assessed before and after surgery and during a 12-month recovery period (55 MRI scans in total after exclusions). We initially found, and then replicated in an independent dataset, that the spatial correlation pattern between regional and global BOLD signals (also known as global signal topography) was associated with tumour occurrence. We then estimated the coupling between the BOLD signal from within the tumour and the signal extracted from different brain tissues. We observed that the normative global signal topography is reorganised in glioma patients during the recovery period. Moreover, we found that the BOLD signal within the tumour and lesioned brain was coupled with the global signal and that this coupling was associated with cognitive recovery. Nevertheless, patients did not show any apparent disruption of functional connectivity within canonical functional networks. Understanding how tumour infiltration and coupling are related to patients' recovery represents a major step forward in prognostic development.

Genome Sequences of Five SARS-CoV-2 Variants from Mumbai, India, Obtained by Nanopore Sequencing.

We report here the genome sequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants from five coronavirus disease 2019 (COVID-19) patients in Mumbai, India. Viral genomic RNA was isolated from nasopharyngeal swabs and/or respiratory particles from the masks of the patients. Genomic variant analysis determined 8 to 22 mutations, and the variants belong to lineages previously associated with Indian variants.

Pilot study on burden of fungal contamination in face masks: need for better mask hygiene in the COVID-19 era.

Risk factors which led to the outbreak of COVID-19 associated Mucormycosis still remains elusive. Face masks can become contaminated by fungal spores that are present ubiquitously in the environment. However the exact burden of such contamination is not known. Fifty masks of patients who attended the Employees Health Scheme COVID-19 facility of a tertiary healthcare centre in India were sampled by direct impression smears on Sabouraud Dextrose Agar. Agar plates were screened for any growth within five days after incubation. Growth was identified by microscopy on the Lactophenol Cotton Blue mount. Mask hygiene practices of participants was assessed using a pre-designed proforma. Out of 50 masks, fungal contamination was seen in 35/50 (70%) masks, with Aspergillus sp. being isolated from 26/50 (52%) masks and Mucorales being isolated from 9/50 (18%) of the masks. Aspergillus niger, Rhizopus a rrhizus and Syncephalastrum sp. were the most common species isolated. Same mask was worn for a median duration of 8 days (2-30 days) at a stretch with or without washing. Thirty one patients washed and re-wore their masks, with median time duration since last wash being 12 hours (4-72 hours). None of the factors assessed for mask hygiene were associated with fungal contamination. High rates of fungal contamination observed in our study emphasizes the need for better mask hygiene in the COVID-19 era.

Genetic, cellular, and connectomic characterization of the brain regions commonly plagued by glioma.

For decades, it has been known that gliomas follow a non-random spatial distribution, appearing more often in some brain regions (e.g. the insula) compared to others (e.g. the occipital lobe). A better understanding of the localization patterns of gliomas could provide clues to the origins of these types of tumours, and consequently inform treatment targets. Following hypotheses derived from prior research into neuropsychiatric disease and cancer, gliomas may be expected to localize to brain regions characterized by functional hubness, stem-like cells, and transcription of genetic drivers of gliomagenesis. We combined neuroimaging data from 335 adult patients with high- and low-grade glioma to form a replicable tumour frequency map. Using this map, we demonstrated that glioma frequency is elevated in association cortex and correlated with multiple graph-theoretical metrics of high functional connectedness. Brain regions populated with putative cells of origin for glioma, neural stem cells and oligodendrocyte precursor cells, exhibited a high glioma frequency. Leveraging a human brain atlas of post-mortem gene expression, we found that gliomas were localized to brain regions enriched with expression of genes associated with chromatin organization and synaptic signalling. A set of glioma proto-oncogenes was enriched among the transcriptomic correlates of glioma distribution. Finally, a regression model incorporating connectomic, cellular, and genetic factors explained 58% of the variance in glioma frequency. These results add to previous literature reporting the vulnerability of hub regions to neurological disease, as well as provide support for cancer stem cell theories of glioma. Our findings illustrate how factors of diverse scale, from genetic to connectomic, can independently influence the anatomic localization of brain dysfunction.

Brain structures and cognitive abilities important for the self-monitoring of speech errors.

The brain structures and cognitive abilities necessary for successful monitoring of one's own speech errors remain unknown. We aimed to inform self-monitoring models by examining the neural and behavioral correlates of phonological and semantic error detection in individuals with post-stroke aphasia. First, we determined whether detection related to other abilities proposed to contribute to monitoring according to various theories, including naming ability, fluency, word-level auditory comprehension, sentence-level auditory comprehension, and executive function. Regression analyses revealed that fluency and executive scores were independent predictors of phonological error detection, while a measure of word-level comprehension related to semantic error detection. Next, we used multivariate lesion-symptom mapping to determine lesion locations associated with reduced error detection. Reduced overall error detection related to damage to a region of frontal white matter extending into dorsolateral prefrontal cortex (DLPFC). Detection of phonological errors related to damage to the same areas, but the lesion-behavior association was stronger, suggesting the localization for overall error detection was driven primarily by phonological error detection. These findings demonstrate that monitoring of different error types relies on distinct cognitive functions, and provide causal evidence for the importance of frontal white matter tracts and DLPFC for self-monitoring of speech.

Behavioral Effects of Chronic Gray and White Matter Stroke Lesions in a Functionally Defined Connectome for Naming.

BACKGROUND: In functional magnetic resonance imaging studies, picture naming engages widely distributed brain regions in the parietal, frontal, and temporal cortices. However, it remains unknown whether those activated areas, along with white matter pathways between them, are actually crucial for naming. OBJECTIVE: We aimed to identify nodes and pathways implicated in naming in healthy older adults and test the impact of lesions to the connectome on naming ability. METHODS: We first identified 24 cortical nodes activated by a naming task and reconstructed anatomical connections between these nodes using probabilistic tractography in healthy adults. We then used structural scans and fractional anisotropy (FA) maps in 45 patients with left hemisphere stroke to assess the relationships of node and pathway integrity to naming, phonology, and nonverbal semantic ability. RESULTS: We found that mean FA values in 13 left hemisphere white matter tracts within the dorsal and ventral streams and 1 interhemispheric tract significantly related to naming scores after controlling for lesion size and demographic factors. In contrast, lesion loads in the cortical nodes were not related to naming performance after controlling for the same variables. Among the identified tracts, the integrity of 4 left hemisphere ventral stream tracts related to nonverbal semantic processing and 1 left hemisphere dorsal stream tract related to phonological processing. CONCLUSIONS: Our findings reveal white matter structures vital for naming and its subprocesses. These findings demonstrate the value of multimodal methods that integrate functional imaging, structural connectivity, and lesion data to understand relationships between brain networks and behavior.