Neonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment

Brain dynamic functional connectivity characterises transient connections between brain regions. Features of brain dynamics have been linked to emotion and cognition in adult individuals, and atypical patterns have been associated with neurodevelopmental conditions such as autism. Although reliable functional brain networks have been consistently identified in neonates, little is known about the early development of dynamic functional connectivity. In this study we characterise dynamic functional connectivity with functional magnetic resonance imaging (fMRI) in the first few weeks of postnatal life in term-born (n = 324) and preterm-born (n = 66) individuals. We show that a dynamic landscape of brain connectivity is already established by the time of birth in the human brain, characterised by six transient states of neonatal functional connectivity with changing dynamics through the neonatal period. The pattern of dynamic connectivity is atypical in preterm-born infants, and associated with atypical social, sensory, and repetitive behaviours measured by the Quantitative Checklist for Autism in Toddlers (Q-CHAT) scores at 18 months of age.

Longitudinal neonatal brain development and socio-demographic correlates of infant outcomes following preterm birth

Preterm birth results in premature exposure of the brain to the extrauterine environment during a critical period of neurodevelopment. Consequently, infants born preterm are at a heightened risk of adverse behavioural outcomes in later life. We characterise longitudinal development of neonatal regional brain volume and functional connectivity in the first weeks following preterm birth, sociodemographic factors, and their respective relationships to psychomotor outcomes and psychopathology in toddlerhood. We study 121 infants born preterm who underwent magnetic resonance imaging shortly after birth, at term-equivalent age, or both. Longitudinal regional brain volume and functional connectivity were modelled as a function of psychopathology and psychomotor outcomes at 18 months. Better psychomotor functioning in toddlerhood was associated with greater relative right cerebellar volume and a more rapid decrease over time of sensorimotor degree centrality in the neonatal period. In contrast, increased 18-month psychopathology was associated with a more rapid decrease in relative regional subcortical volume. Furthermore, while socio-economic deprivation was related to both psychopathology and psychomotor outcomes, cognitively stimulating parenting predicted psychopathology only. Our study highlights the importance of longitudinal imaging to better predict toddler outcomes following preterm birth, as well as disparate environmental influences on separable facets of behavioural development in this population.

Tensor image registration library: Deformable registration of stand-alone histology images to whole-brain post-mortem MRI data

BACKGROUND

Accurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to assist the registration of stand-alone histology sections to whole-brain MRI data.

METHODS

Our pipeline registers stained histology sections to whole-brain post-mortem MRI in 4 stages, with the help of two photographic intermediaries: a block face image (to undistort histology sections) and coronal brain slab photographs (to insert them into MRI space). Each registration stage is implemented as a configurable stand-alone Python script using our novel platform, Tensor Image Registration Library (TIRL), which provides flexibility for wider adaptation. We report our experience of registering 87 PLP-stained histology sections from 14 subjects and perform various experiments to assess the accuracy and robustness of each stage of the pipeline.

RESULTS

All 87 histology sections were successfully registered to MRI. Histology-to-block registration (Stage 1) achieved 0.2-0.4 mm accuracy, better than commonly used existing methods. Block-to-slice matching (Stage 2) showed great robustness in automatically identifying and inserting small tissue blocks into whole brain slices with 0.2 mm accuracy. Simulations demonstrated sub-voxel level accuracy (0.13 mm) of the slice-to-volume registration (Stage 3) algorithm, which was observed in over 200 actual brain slice registrations, compensating 3D slice deformations up to 6.5 mm. Stage 4 combined the previous stages and generated refined pixelwise aligned multi-modal histology-MRI stacks.

CONCLUSIONS

Our open-source pipeline provides robust automation tools for registering stand-alone histology sections to MRI data with sub-voxel level precision, and the underlying framework makes it readily adaptable to a diverse range of microscopy-MRI studies.

Premature Infants Display Discriminable Behavioral, Physiological, and Brain Responses to Noxious and Nonnoxious Stimuli

Pain assessment in preterm infants is challenging as behavioral, autonomic, and neurophysiological measures of pain are reported to be less sensitive and specific than in term infants. Understanding the pattern of preterm infants’ noxious-evoked responses is vital to improve pain assessment in this group. This study investigated the discriminability and development of multimodal noxious-evoked responses in infants aged 28–40 weeks postmenstrual age. A classifier was trained to discriminate responses to a noxious heel lance from a nonnoxious control in 47 infants, using measures of facial expression, brain activity, heart rate, and limb withdrawal, and tested in two independent cohorts with a total of 97 infants. The model discriminates responses to the noxious from the nonnoxious procedure with an overall accuracy of 0.76–0.84 and an accuracy of 0.78–0.79 in the 28–31-week group. Noxious-evoked responses have distinct developmental patterns. Heart rate responses increase in magnitude with age, while noxious-evoked brain activity undergoes three distinct developmental stages, including a previously unreported transitory stage consisting of a negative event-related potential between 30 and 33 weeks postmenstrual age. These findings demonstrate that while noxious-evoked responses change across early development, infant responses to noxious and nonnoxious stimuli are discriminable in prematurity.

The impact of premature extrauterine exposure on infants' stimulus-evoked brain activity across multiple sensory systems

Prematurity can result in widespread neurodevelopmental impairment, with the impact of premature extrauterine exposure on brain function detectable in infancy. A range of neurodynamic and haemodynamic functional brain measures have previously been employed to study the neurodevelopmental impact of prematurity, with methodological and analytical heterogeneity across studies obscuring how multiple sensory systems are affected. Here, we outline a standardised template analysis approach to measure evoked response magnitudes for visual, tactile, and noxious stimulation in individual infants (n = 15) using EEG. By applying these templates longitudinally to an independent cohort of very preterm infants (n = 10), we observe that the evoked response template magnitudes are significantly associated with age-related maturation. Finally, in a cross-sectional study we show that the visual and tactile response template magnitudes differ between a cohort of infants who are age-matched at the time of study but who differ according to whether they are born during the very preterm or late preterm period (n = 10 and 8 respectively). These findings demonstrate the significant impact of premature extrauterine exposure on brain function and suggest that prematurity can accelerate maturation of the visual and tactile sensory system in infants born very prematurely. This study highlights the value of using a standardised multi-modal evoked-activity analysis approach to assess premature neurodevelopment, and will likely complement resting-state EEG and behavioural assessments in the study of the functional impact of developmental care interventions.

Functional and diffusion MRI reveal the neurophysiological basis of neonates' noxious-stimulus evoked brain activity

Understanding the neurophysiology underlying neonatal responses to noxious stimulation is central to improving early life pain management. In this neonatal multimodal MRI study, we use resting-state and diffusion MRI to investigate inter-individual variability in noxious-stimulus evoked brain activity. We observe that cerebral haemodynamic responses to experimental noxious stimulation can be predicted from separately acquired resting-state brain activity (n = 18). Applying this prediction model to independent Developing Human Connectome Project data (n = 215), we identify negative associations between predicted noxious-stimulus evoked responses and white matter mean diffusivity. These associations are subsequently confirmed in the original noxious stimulation paradigm dataset, validating the prediction model. Here, we observe that noxious-stimulus evoked brain activity in healthy neonates is coupled to resting-state activity and white matter microstructure, that neural features can be used to predict responses to noxious stimulation, and that the dHCP dataset could be utilised for future exploratory research of early life pain system neurophysiology.

Multimodal Imaging Brain Markers in Early Adolescence Are Linked with a Physically Active Lifestyle

The World Health Organization promotes physical exercise and a healthy lifestyle as means to improve youth development. However, relationships between physical lifestyle and human brain development are not fully understood. Here, we asked whether a human brain-physical latent mode of covariation underpins the relationship between physical activity, fitness, and physical health measures with multimodal neuroimaging markers. In 50 12-year old school pupils (26 females), we acquired multimodal whole-brain MRI, characterizing brain structure, microstructure, function, myelin content, and blood perfusion. We also acquired physical variables measuring objective fitness levels, 7 d physical activity, body mass index, heart rate, and blood pressure. Using canonical correlation analysis, we unravel a latent mode of brain-physical covariation, independent of demographics, school, or socioeconomic status. We show that MRI metrics with greater involvement in this mode also showed spatially extended patterns across the brain. Specifically, global patterns of greater gray matter perfusion, volume, cortical surface area, greater white matter extra-neurite density, and resting state networks activity covaried positively with measures reflecting a physically active phenotype (high fit, low sedentary individuals). Showing that a physically active lifestyle is linked with systems-level brain MRI metrics, these results suggest widespread associations relating to several biological processes. These results support the notion of close brain-body relationships and underline the importance of investigating modifiable lifestyle factors not only for physical health but also for brain health early in adolescence.SIGNIFICANCE STATEMENT An active lifestyle is key for healthy development. In this work, we answer the following question: How do brain neuroimaging markers relate with young adolescents' level of physical activity, fitness, and physical health? Combining advanced whole-brain multimodal MRI metrics with computational approaches, we show a robust relationship between physically active lifestyles and spatially extended, multimodal brain imaging-derived phenotypes. Suggesting a wider effect on brain neuroimaging metrics than previously thought, this work underlies the importance of studying physical lifestyle, as well as other brain-body relationships in an effort to foster brain health at this crucial stage in development.

Modelling brain development to detect white matter injury in term and preterm born neonates

Premature birth occurs during a period of rapid brain growth. In this context, interpreting clinical neuroimaging can be complicated by the typical changes in brain contrast, size and gyrification occurring in the background to any pathology. To model and describe this evolving background in brain shape and contrast, we used a Bayesian regression technique, Gaussian process regression, adapted to multiple correlated outputs. Using MRI, we simultaneously estimated brain tissue intensity on T1- and T2-weighted scans as well as local tissue shape in a large cohort of 408 neonates scanned cross-sectionally across the perinatal period. The resulting model provided a continuous estimate of brain shape and intensity, appropriate to age at scan, degree of prematurity and sex. Next, we investigated the clinical utility of this model to detect focal white matter injury. In individual neonates, we calculated deviations of a neonate's observed MRI from that predicted by the model to detect punctate white matter lesions with very good accuracy (area under the curve > 0.95). To investigate longitudinal consistency of the model, we calculated model deviations in 46 neonates who were scanned on a second occasion. These infants' voxelwise deviations from the model could be used to identify them from the other 408 images in 83% (T2-weighted) and 76% (T1-weighted) of cases, indicating an anatomical fingerprint. Our approach provides accurate estimates of non-linear changes in brain tissue intensity and shape with clear potential for radiological use.

EPIDEMIOLOGY OF CHLAMYDIA-INDUCED REPRODUCTIVE DISEASE IN MALE KOALAS (PHASCOLARCTOS CINEREUS) FROM SOUTHEAST QUEENSLAND, AUSTRALIA AS ASSESSED FROM PENILE URETHRAL SWABS AND SEMEN

Declining population sizes of koalas (Phascolarctos cinereus) in SE Queensland (QLD), Australia can partially be attributed to chlamydiosis, with the majority of epidemiological studies focusing on the prevalence of infection and associated pathology in female koalas, with lesser attention given to males. We aimed to explore the epidemiology of Chlamydia pecorum infection in the male urogenital tract from wild (hospitalized and free-ranging) koalas in SE QLD. Although 67% of male koalas were infected with C. pecorum in their urogenital tract and 55% were shedding the organism in their semen, only a third of the males sampled presented with overt signs of urogenital disease. Infection with C. pecorum was lower in populations from rural locations, compared with periurban locations, with a corresponding low association between urogenital infection and clinical disease. The presence of C. pecorum in penile urethral swabs was a good predictor of the presence of C. pecorum in semen, with a significant correlation (P=0.006) in 58% of males. In contrast, the C. pecorum load in penile urethral swabs was not a good predictor of the C. pecorum load in semen, with no significant correlation. In addition, 57% of male koalas had large numbers of bacterial copy numbers in the penile urethra (upper quartile) and 40% shedding into semen with no overt signs of disease. Investigation of the association of C. pecorum infection, body condition score, and age revealed that the highest incidence of urogenital infection occurred in males with the lowest body score (1 out of 10). Furthermore, 63% of sexually mature male koalas (>2 yr old) had urethral infections and 50% had C. pecorum in their semen. Our study suggested that the role of chlamydia in male koala infertility has been previously underestimated.

Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants

The infant brain is unlike the adult brain, with considerable differences in morphological, neurodynamic, and haemodynamic features. As the majority of current MRI analysis tools were designed for use in adults, a primary objective of the Developing Human Connectome Project (dHCP) is to develop optimised methodological pipelines for the analysis of neonatal structural, resting state, and diffusion MRI data. Here, in an independent neonatal dataset we have extended and optimised the dHCP fMRI preprocessing pipeline for the analysis of stimulus-response fMRI data. We describe and validate this extended dHCP fMRI preprocessing pipeline to analyse changes in brain activity evoked following an acute noxious stimulus applied to the infant's foot. We compare the results obtained from this extended dHCP pipeline to results obtained from a typical FSL FEAT-based analysis pipeline, evaluating the pipelines' outputs using a wide range of tests. We demonstrate that a substantial increase in spatial specificity and sensitivity to signal can be attained with a bespoke neonatal preprocessing pipeline through optimised motion and distortion correction, ICA-based denoising, and haemodynamic modelling. The improved sensitivity and specificity, made possible with this extended dHCP pipeline, will be paramount in making further progress in our understanding of the development of sensory processing in the infant brain.

Construction of a neonatal cortical surface atlas using Multimodal Surface Matching in the Developing Human Connectome Project

We propose a method for constructing a spatio-temporal cortical surface atlas of neonatal brains aged between 36 and 44 weeks of post-menstrual age (PMA) at the time of scan. The data were acquired as part of the Developing Human Connectome Project (dHCP), and the constructed surface atlases are publicly available. The method is based on a spherical registration approach: Multimodal Surface Matching (MSM), using cortical folding for driving the alignment. Templates have been generated for the anatomical cortical surface and for the cortical feature maps: sulcal depth, curvature, thickness, T1w/T2w myelin maps and cortical regions. To achieve this, cortical surfaces from 270 infants were first projected onto the sphere. Templates were then generated in two stages: first, a reference space was initialised via affine alignment to a group average adult template. Following this, templates were iteratively refined through repeated alignment of individuals to the template space until the variability of the average feature sets converged. Finally, bias towards the adult reference was removed by applying the inverse of the average affine transformations on the template and de-drifting the template. We used temporal adaptive kernel regression to produce age-dependant atlases for 9 weeks (36-44 weeks PMA). The generated templates capture expected patterns of cortical development including an increase in gyrification as well as an increase in thickness and T1w/T2w myelination with increasing age.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction

The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction, and cortical surface inflation, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

In vitro measurement of particle margination in the microchannel flow: effect of varying hematocrit

It has long been known that platelets undergo margination when flowing in blood vessels, such that there is an excess concentration near the vessel wall. We conduct experiments and three-dimensional boundary integral simulations of platelet-sized spherical particles in a microchannel 30 μm in height to measure the particle-concentration distribution profile and observe its margination at 10%, 20%, and 30% red blood cell hematocrit. The experiments involved adding 2.15-μm-diameter spheres into a solution of red blood cells, plasma, and water and flowing this mixture down a microfluidic channel at a wall shear rate of 1000 s(-1). Fluorescence imaging was used to determine the height and velocity of particles in the channel. Experimental results indicate that margination has largely occurred before particles travel 1 cm downstream and that hematocrit plays a role in the degree of margination. With simulations, we can track the trajectories of the particles with higher resolution. These simulations also confirm that margination from an initially uniform distribution of spheres and red blood cells occurs over the length scale of O(1 cm), with higher hematocrit showing faster margination. The results presented here, from both experiments and 3D simulations, may help explain the relationship between bleeding time in vessel trauma and red blood cell hematocrit as platelets move to a vessel wall.

Examining platelet adhesion via Stokes flow simulations and microfluidic experiments

While critically important, the platelet function at the high shear rates typical of the microcirculation is relatively poorly understood. Using a large scale Stokes flow simulation, Zhao et al. recently showed that RBC-induced velocity fluctuations cause platelets to marginate into the RBC free near-wall region [Zhao et al., Physics of Fluids, 2012, 24, 011902]. We extend their work by investigating the dynamics of platelets in shear after margination. An overall platelet adhesion model is proposed in terms of a continuous time Markov process and the transition rates are established with numerical simulations involving platelet-wall adhesion. Hydrodynamic drag and Brownian forces are calculated with the boundary element method, while the RBC collisions are incorporated through an autoregressive process. Hookean springs with first order bond kinetics are used to model receptor-ligand bonds formed between the platelet and the wall. The simulations are compared with in vitro microfluidic experiments involving platelet adhesion to Von Willebrand Factor (VWF) coated surfaces.

Singular perturbation theory for predicting extravasation of Brownian particles

Motivated by recent studies on tumor treatments using the drug delivery of nanoparticles, we provide a singular perturbation theory and perform Brownian dynamics simulations to quantify the extravasation rate of Brownian particles in a shear flow over a circular pore with a lumped mass transfer resistance. The analytic theory we present is an expansion in the limit of a vanishing Péclet number (P), which is the ratio of convective fluxes to diffusive fluxes on the length scale of the pore. We state the concentration of particles near the pore and the extravasation rate (Sherwood number) to O(P^1/2). This model improves upon previous studies because the results are valid for all values of the particle mass transfer coefficient across the pore, as modeled by the Damköhler number (κ), which is the ratio of the reaction rate to the diffusive mass transfer rate at the boundary. Previous studies focused on the adsorption-dominated regime (i.e., κ → ∞). Specifically, our work provides a theoretical basis and an interpolation-based approximate method for calculating the Sherwood number (a measure of the extravasation rate) for the case of finite resistance [κ ~ O(1)] at small Péclet numbers, which are physiologically important in the extravasation of nanoparticles. We compare the predictions of our theory and an approximate method to Brownian dynamics simulations with reflection-reaction boundary conditions as modeled by κ. They are found to agree well at small P and for the κ ≪ 1 and κ ≫ 1 asymptotic limits representing the diffusion-dominated and adsorption-dominated regimes, respectively. Although this model neglects the finite size effects of the particles, it provides an important first step toward understanding the physics of extravasation in the tumor vasculature.

Females prefer athletes, males fear the disadvantaged: different signals used in female choice and male competition have varied consequences

The most commonly assumed cost for exaggerated male ornamentation is increased predation pressure owing to decreased locomotor performance or increased conspicuousness to predators. Despite its intuitive basis, the locomotor costs of male ornamentation are not well established. We tested the hypothesis that multiple male signals that are used independently during female choice and male competition could lead to varied locomotor costs. Multiple signals with varied costs could provide a more detailed indicator of overall male quality, as only the highest-quality individuals could support all costs. To test this idea, we investigated the burst locomotor consequences of multiple ornaments for males of the pacific blue-eye (Pseudomugil signifer). We evaluated five competing models relating body size, ornament size and performance traits to field measures of dominance and attractiveness. Non-propulsive male fin ornaments used during male competition were different from those used in female choice. First dorsal fin length was the most important predictor of male attractiveness, while dominance was only associated with anal fin length. Furthermore, first dorsal fin length was positively correlated with swim speed, while anal fin length was negatively associated with speed. Our study shows that multiple male signals that are used independently during male competition and female choice also differ in their associated costs. This provides a mechanism for understanding why locomotor costs for exaggerated male ornamentation are not often empirically demonstrated.

Cortical network dynamics during verbal working memory function

This study is an exploratory investigation of the regional timing of cortical activity associated with verbal working memory function. ERP activity was obtained from a single subject using a 124-channel sensor array during a task requiring the monitoring of imageable words for occasional targets. Distributed cortical activity was estimated every 2.5 ms with high spatial resolution using real head, boundary element modelling of non-target activity. High-resolution structural MRI was used for segmentation of tissue boundaries and co-registration to the scalp electrode array. The inverse solution was constrained to the cortical surface. Cortical activity was observed in regions commonly associated with verbal working memory function. This included: the occipital pole (early visual processing); the superior temporal and inferior parietal gyrus bilaterally and the left angular gyrus (visual and phonological word processing); the dorsal lateral occipital gyrus (spatial processing); and aspects of the bilateral superior parietal lobe (imagery and episodic verbal memory). Activity was also observed in lateral and superior prefrontal regions associated with working memory control of sensorimotor processes. The pattern of cortical activity was relatively stable over time, with variations in the extent and amplitude of contributing local source activations. By contrast, the pattern of concomitant scalp topography varied considerably over time, reflecting the linear summation effects of volume conduction that often confound dipolar source modelling.