Improved reference tracts for unsupervised brain white matter tractography

Neighbourhood tractography aims to automatically segment equivalent brain white matter tracts from diffusion magnetic resonance imaging (dMRI) data in different subjects by using a “reference tract” as a prior for the shape and length of each tract of interest. In the current work we present a means of improving the technique by using references tracts derived from dMRI data acquired from 80 healthy volunteers aged 25–64 years. The reference tracts were tested on the segmentation of 16 major white matter tracts in 50 healthy older people, aged 71.8 (±0.4) years. We found that data-generated reference tracts improved the automatic white matter tract segmentations compared to results from atlas-generated reference tracts. We also obtained higher percentages of visually acceptable segmented tracts and lower variation in water diffusion parameters using this approach

Intelligence quotient in paediatric sickle cell disease: a systematic review and meta-analysis

AIM: Sickle cell disease (SCD) is the commonest cause of childhood stroke worldwide. Magnetic resonance imaging (MRI) is routinely used to detect additional silent cerebral infarction (SCI), as IQ is lower in SCI as well as stroke. This review assesses the effect of infarction on IQ, and specifically whether, compared to healthy controls, IQ differences are seen in children with SCI with no apparent MRI abnormality. METHOD: A systematic review was conducted to include articles with an SCD paediatric population, MRI information, and Wechsler IQ. A meta-analysis of 19 articles was performed to compare IQ in three groups: stroke vs SCI; SCI vs no SCI; and no SCI vs healthy controls. RESULTS: Mean differences in IQ between all three groups were significant: stroke patients had lower IQ than patients with SCI by 10 points (six studies); patients with SCI had lower IQ than no patients with SCI by 6 points (17 studies); and no patients with SCI had lower IQ than healthy controls by 7 points (seven studies). INTERPRETATION: Children with SCD and no apparent MRI abnormality have significantly lower IQ than healthy controls. In this chronic condition, other biological, socioeconomic, and environmental factors must play a significant role in cognition

Structural connectivity of the amygdala in young adults with autism spectrum disorder

Autism spectrum disorder (ASD) is characterized by impairments in social cognition, a function associated with the amygdala. Subdivisions of the amygdala have been identified which show specificity of structure, connectivity, and function. Little is known about amygdala connectivity in ASD. The aim of this study was to investigate the microstructural properties of amygdala-cortical connections and their association with ASD behaviours, and whether connectivity of specific amygdala subregions is associated with particular ASD traits. The brains of 51 high-functioning young adults (25 with ASD; 26 controls) were scanned using MRI. Amygdala volume was measured, and amygdala-cortical connectivity estimated using probabilistic tractography. An iterative 'winner takes all' algorithm was used to parcellate the amygdala based on its primary cortical connections. Measures of amygdala connectivity were correlated with clinical scores. In comparison with controls, amygdala volume was greater in ASD (F(1,94) = 4.19; p = .04). In white matter (WM) tracts connecting the right amygdala to the right cortex, ASD subjects showed increased mean diffusivity (t = 2.35; p = .05), which correlated with the severity of emotion recognition deficits (rho = -0.53; p = .01). Following amygdala parcellation, in ASD subjects reduced fractional anisotropy in WM connecting the left amygdala to the temporal cortex was associated with with greater attention switching impairment (rho = -0.61; p = .02). This study demonstrates that both amygdala volume and the microstructure of connections between the amygdala and the cortex are altered in ASD. Findings indicate that the microstructure of right amygdala WM tracts are associated with overall ASD severity, but that investigation of amygdala subregions can identify more specific associations

Human milk feeding and cognitive outcome in preterm infants: the role of infection and NEC reduction

BACKGROUND: Breast milk has been associated with lower risk of infection and necrotising enterocolitis (NEC) and improved long-term cognitive outcomes in preterm infants but, if unsupplemented, does not meet the nutritional requirements of preterm infants. METHODS: Preterm infants were randomised to receive a high nutrient intervention diet: preterm formula (PTF) or the standard diet: term formula (TF) or banked donor breast milk (BBM), either as their sole diet or as supplement to maternal breast milk (MBM). IQ tests were performed at ages 7, 15, 20, and 30 years. RESULTS: An increase in MBM and BBM intake was associated with a lower chance of neonatal infection/NEC. Neonatal infection/NEC was associated with lower Full Scale IQ (FSIQ) and Performance IQ (PIQ) score at ages 7 and 30 years. The relationship between higher intake of MBM and PIQ at age 7 years was partly mediated by neonatal infection/NEC. The intervention diet was associated with higher Verbal IQ (VIQ) scores compared to the standard diet. There was no evidence that these effects changed from childhood through to adulthood. CONCLUSIONS: Neonatal diet is an important modifiable factor that can affect long-term cognitive outcome through a 'human milk' factor, protecting against infection/NEC, and a 'nutrient content' factor. IMPACT: This is the first study to demonstrate the effects of neonatal infection/necrotising enterocolitis (NEC) on IQ in the same cohort in childhood and adulthood. Diet can be a key factor in long-term cognitive outcome in people born preterm by preventing neonatal infection/NEC and providing adequate nutrients. Human milk, whether MBM or BBM, is associated with a reduced risk of infection/NEC. A higher nutrient diet is associated with better cognitive outcome in childhood. Performance IQ is particularly vulnerable to the effects of infection/NEC and verbal IQ to the quantity of (macro)nutrients in the diet

Early childhood bilingualism: effects on brain structure and function [version 2; peer review: 2 approved]

Growing up in a bilingual environment is becoming increasingly common. Yet, we know little about how this enriched language environment influences the connectivity of children’s brains. Behavioural research in children and adults has shown that bilingualism experience may boost executive control (EC) skills, such as inhibitory control and attention. Moreover, increased structural and functional (resting-state) connectivity in language-related and EC-related brain networks is associated with increased executive control in bilingual adults. However, how bilingualism factors alter brain connectivity early in brain development remains poorly understood. We will combine standardised tests of attention with structural and resting-state functional magnetic resonance imaging (MRI) in bilingual children. This study will allow us to address an important field of inquiry within linguistics and developmental cognitive neuroscience by examining the following questions: Does bilingual experience modulate connectivity in language-related and EC-related networks in children? Do differences in resting-state brain connectivity correlate with differences in EC skills (specifically attention skills)? How do bilingualism-related factors, such as age of exposure to two languages, language usage and proficiency, modulate brain connectivity? We will collect structural and functional MRI, and quantitative measures of EC and language skills from two groups of English-Greek bilingual children - 20 simultaneous bilinguals (exposure to both languages from birth) and 20 successive bilinguals (exposure to English between the ages of 3 and 5 years) - and 20 English monolingual children, 8-10 years old. We will compare connectivity measures and attention skills between monolinguals and bilinguals to examine the effects of bilingual exposure. We will also examine to what extent bilingualism factors predict brain connectivity in EC and language networks. Overall, we hypothesize that connectivity and EC will be enhanced in bilingual children compared to monolingual children, and each outcome will be modulated by age of exposure to two languages and by bilingual language usage

Anatomy and lateralization of the human corticobulbar tracts: an fMRI-guided tractography study

The left hemisphere lateralization bias for language functions, such as syntactic processing and semantic retrieval, is well known. Although several theories and clinical data indicate a link between speech motor execution and language, the functional and structural brain lateralization for these functions has never been examined concomitantly in the same individuals. Here we used functional MRI during rapid silent syllable repetition (/lalala/, /papapa/ and /pataka/, known as oral diadochokinesis or DDK) to map the cortical representation of the articulators in 17 healthy adults. In these same participants, functional lateralization for language production was assessed using the well established verb generation task. We then used DDK-related fMRI activation clusters to guide tractography of the corticobulbar tract from diffusion-weighted MRI. Functional MRI revealed a wide inter-individual variability of hemispheric asymmetry patterns (left and right dominant, as well as bilateral) for DDK in the motor cortex, despite predominantly left hemisphere dominance for language-related activity in Broca’s area. Tractography revealed no evidence for structural asymmetry (based on fractional anisotropy) within the corticobulbar tract. To our knowledge, this study is the first to reveal that motor brain activation for syllable repetition is unrelated to functional asymmetry for language production in adult humans. In addition, we found no evidence that the human corticobulbar tract is an asymmetric white matter pathway. We suggest that the predominance of dysarthria following left hemisphere infarct is probably a consequence of disrupted feedback or input from left hemisphere language and speech planning regions, rather than structural asymmetry of the corticobulbar tract itself

NODDI and Tensor-Based Microstructural Indices as Predictors of Functional Connectivity

In Diffusion Weighted MR Imaging (DWI), the signal is affected by the biophysical properties of neuronal cells and their relative placement, as well as extra-cellular tissue compartments. Typically, microstructural indices, such as fractional anisotropy (FA) and mean diffusivity (MD), are based on a tensor model that cannot disentangle the influence of these parameters. Recently, Neurite Orientation Dispersion and Density Imaging (NODDI) has exploited multi-shell acquisition protocols to model the diffusion signal as the contribution of three tissue compartments. NODDI microstructural indices, such as intra-cellular volume fraction (ICVF) and orientation dispersion index (ODI) are directly related to neuronal density and orientation dispersion, respectively. One way of examining the neurophysiological role of these microstructural indices across neuronal fibres is to look into how they relate to brain function. Here we exploit a statistical framework based on sparse Canonical Correlation Analysis (sCCA) and randomised Lasso to identify structural connections that are highly correlated with resting-state functional connectivity measured with simultaneous EEG-fMRI. Our results reveal distinct structural fingerprints for each microstructural index that also reflect their inter-relationships

Relating resting-state fMRI and EEG whole-brain connectomes across frequency bands.

Whole brain functional connectomes hold promise for understanding human brain activity across a range of cognitive, developmental and pathological states. So called resting-state (rs) functional MRI studies have contributed to the brain being considered at a macroscopic scale as a set of interacting regions. Interactions are defined as correlation-based signal measurements driven by blood oxygenation level dependent (BOLD) contrast. Understanding the neurophysiological basis of these measurements is important in conveying useful information about brain function. Local coupling between BOLD fMRI and neurophysiological measurements is relatively well defined, with evidence that gamma (range) frequency EEG signals are the closest correlate of BOLD fMRI changes during cognitive processing. However, it is less clear how whole-brain network interactions relate during rest where lower frequency signals have been suggested to play a key role. Simultaneous EEG-fMRI offers the opportunity to observe brain network dynamics with high spatio-temporal resolution. We utilize these measurements to compare the connectomes derived from rs-fMRI and EEG band limited power (BLP). Merging this multi-modal information requires the development of an appropriate statistical framework. We relate the covariance matrices of the Hilbert envelope of the source localized EEG signal across bands to the covariance matrices derived from rs-fMRI with the means of statistical prediction based on sparse Canonical Correlation Analysis (sCCA). Subsequently, we identify the most prominent connections that contribute to this relationship. We compare whole-brain functional connectomes based on their geodesic distance to reliably estimate the performance of the prediction. The performance of predicting fMRI from EEG connectomes is considerably better than predicting EEG from fMRI across all bands, whereas the connectomes derived in low frequency EEG bands resemble best rs-fMRI connectivity

Arterial Spin-Labeling Perfusion Metrics in Pediatric Posterior Fossa Tumor Surgery

BACKGROUND AND PURPOSE: Pediatric posterior fossa tumors often present with hydrocephalus; postoperatively, up to 25% of patients develop cerebellar mutism syndrome. Arterial spin-labeling is a noninvasive means of quantifying CBF and bolus arrival time. The aim of this study was to investigate how changes in perfusion metrics in children with posterior fossa tumors are modulated by cerebellar mutism syndrome and hydrocephalus requiring pre-resection CSF diversion. MATERIALS AND METHODS: Forty-four patients were prospectively scanned at 3 time points (preoperatively, postoperatively, and at 3-month follow-up) with single- and multi-inflow time arterial spin-labeling sequences. Regional analyses of CBF and bolus arrival time were conducted using coregistered anatomic parcellations. ANOVA and multivariable, linear mixed-effects modeling analysis approaches were used. The study was registered at clinicaltrials.gov (NCT03471026). RESULTS: CBF increased after tumor resection and at follow-up scanning (P = .045). Bolus arrival time decreased after tumor resection and at follow-up scanning (P = .018). Bolus arrival time was prolonged (P = .058) following the midline approach, compared with cerebellar hemispheric surgical approaches to posterior fossa tumors. Multivariable linear mixed-effects modeling showed that regional perfusion changes were more pronounced in the 6 children who presented with symptomatic obstructive hydrocephalus requiring pre-resection CSF diversion, with hydrocephalus lowering the baseline mean CBF by 20.5 (standard error, 6.27) mL/100g/min. Children diagnosed with cerebellar mutism syndrome (8/44, 18.2%) had significantly higher CBF at follow-up imaging than those who were not (P = .040), but no differences in pre- or postoperative perfusion parameters were seen. CONCLUSIONS: Multi-inflow time arterial spin-labeling shows promise as a noninvasive tool to evaluate cerebral perfusion in the setting of pediatric obstructive hydrocephalus and demonstrates increased CBF following resolution of cerebellar mutism syndrome

White matter microstructure correlates with autism trait severity in a combined clinical-control sample of high-functioning adults

Diffusion tensor imaging (DTI) studies have demonstrated white matter (WM) abnormalities in tracts involved in emotion processing in autism spectrum disorder (ASD), but little is known regarding the nature and distribution of WM anomalies in relation to ASD trait severity in adults. Increasing evidence suggests that ASD occurs at the extreme of a distribution of social abilities. We aimed to examine WM microstructure as a potential marker for ASD symptom severity in a combined clinical-neurotypical population. SIENAX was used to estimate whole brain volume. Tract-based spatial statistics (TBSS) was used to provide a voxel-wise comparison of WM microstructure in 50 high-functioning young adults: 25 ASD and 25 neurotypical. The severity of ASD traits was measured by autism quotient (AQ); we examined regressions between DTI markers of WM microstructure and ASD trait severity. Cognitive abilities, measured by intelligence quotient, were well-matched between the groups and were controlled in all analyses. There were no significant group differences in whole brain volume. TBSS showed widespread regions of significantly reduced fractional anisotropy (FA) and increased mean diffusivity (MD) and radial diffusivity (RD) in ASD compared with controls. Linear regression analyses in the combined sample showed that average whole WM skeleton FA was negatively influenced by AQ (p = 0.004), whilst MD and RD were positively related to AQ (p = 0.002; p = 0.001). Regression slopes were similar within both groups and strongest for AQ social, communication and attention switching scores. In conclusion, similar regression characteristics were found between WM microstructure and ASD trait severity in a combined sample of ASD and neurotypical adults. WM anomalies were relatively more severe in the clinically diagnosed sample. Both findings suggest that there is a dimensional relationship between WM microstructure and severity of ASD traits from neurotypical subjects through to clinical ASD, with reduced coherence of WM associated with greater ASD symptoms. General cognitive abilities were independent of the relationship between WM indices and ASD traits