Biology subjects

Roberts, J. A.

Publications and source records attributed to Roberts, J. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Cross-omics profiling reveals cortical neuronal dysfunction following neonatal intraventricular haemorrhage that is attenuated by decorin treatment

Neonatal intraventricular haemorrhage (IVH) is a form of haemorrhagic stroke which is most common in premature infants and can cause mortality and lifelong disability. The reaction of brain tissue to extraneous blood is known to trigger several complications including post-haemorrhagic hydrocephalus (PHH), furthering the likelihood of neurological disability and death. The molecular response of the neuron-rich cortex to blood within the first 24 hours of injury, and how this may precipitate secondary brain injury or neurodegeneration, remains poorly defined. This lack of understanding may reduce the development of novel therapeutics aiming to limit the injury caused by neonatal IVH. Here, we utilised a proteome and transcriptome cross-omics approach to characterise cortical responses to blood in a neonatal mouse model of IVH to improve understanding of the effects and drivers of IVH-induced brain injury. The pleiotropic proteoglycan decorin, a well-characterised modulator of the inflammatory cytokine transforming growth factor beta 1, was also studied to identify if it can have any beneficial effects in the cortex. Cross-omics analysis between the transcriptome and proteome highlighted ferroptosis-associated signatures as a key post-IVH cortical injury mechanism. IVH caused a marked depletion of cortical neurons, neurofilaments, and synaptic vesicle proteins, observed through transcriptomics, immunostaining, and proteomics, which were attenuated by decorin treatment. Decorin also produced an enhanced phagocytic response potentially through activation of microglia. These findings highlight the vulnerability of cortical neurons to early injury following IVH in neonates and support decorin as a potential neuroprotective agent. They also suggest that ferroptosis-associated pathways may contribute to early cortical injury and represent a potential therapeutic target in this context.

neuroscience↗

bioRxiv2026

Complementary frontoparietal and corticothalamic contributions to relational reasoning

Complex reasoning requires frontal, parietal, and thalamic systems to manage increasing relational demands, yet the underlying circuit mechanisms remain unclear. Here, we combined EEG with biologically grounded corticothalamic neural field modelling while participants solved relational problems of graded complexity. Successful reasoning was associated with dissociable frontoparietal dynamics. Frontal regions showed increased theta-band power, whereas parietal regions showed reduced alpha- and beta-band power. Neural field modelling linked these dynamics to complementary complexity-dependent circuit adaptations. Parietal regions showed modulation of intracortical and corticothalamic gains, intrathalamic inhibition, prolonged loop delays, and faster synaptic filtering, whereas frontal regions primarily adjusted intracortical gains in a manner consistent with maintaining local excitatory-inhibitory balance and supporting longer temporal integration windows. Together, these empirical and model-derived insights demonstrate that problem-solving under increasing reasoning demand relies not simply on greater frontoparietal engagement, but on additional, region-specific reconfigurations of cortical and corticothalamic circuits.

neuroscience↗

bioRxiv2026

Polysynaptic signal propagation in networked neural masses

The routing of information across the brain's structural network is central to its wide range of functional capabilities. However, the mechanisms underlying information routing in complex brain networks, particularly between regions that do not share a direct anatomical connection, remain poorly understood. Neural mass models (NMMs), a computational modelling framework capable of capturing complex neural dynamics across scales, can potentially be used to study the dynamical and network bases of these vital polysynaptic routing processes. In this study, we investigate polysynaptic signalling in three widely used NMMs, obeying Ornstein-Uhlenbeck, Stuart-Landau, and Jansen-Rit dynamics, by tracking the propagation of a discrete, focal, high-amplitude perturbation across the underlying network. We find that polysynaptic propagation emerges in all tested NMMs when configured within dynamical regimes that effectively enhance the persistence of perturbations. We also find distinct parameter domains that maximise signal propagation to directly connected regions and to those separated from the source by at least two hops. Finally, we benchmark in silico stimulus propagation in the brain network against an empirical dataset of direct electrical stimulation trials, to explore the relative capabilities of the NMMs in capturing signal propagation to connected versus unconnected regions. This analysis highlights the significance of dynamical repertoire in capturing stimulus propagation outcomes. Overall, this study provides insights into how dynamical and network features shape signal propagation over complex brain networks.

neuroscience↗

bioRxiv2026

Inferring population-level physiologically based model parameters for sleep in infancy and young childhood

The sleep patterns of infants and young children differ from adult sleep patterns, with longer duration and multiple bouts per 24 hours. There is also considerable heterogeneity in infant sleep, both between individuals and within individuals across development. While mathematical models have been used to understand the mechanisms that regulate adult sleep, the development of sleep from infancy through early childhood has remained largely unexplored. Here we used an established mathematical model for adult sleep regulation to investigate how the underlying mechanisms of sleep mature from ages 1 month to 5 years, and identify a basis for inter-individual differences at each age. Using a Bayesian approach to estimate joint distributions of model parameters at different ages, we found that: (i) decreases in the rate of accumulation of sleep homeostatic pressure captured the reduction in sleep duration across development; while (ii) increases in the time scale of the sleep homeostatic drive captured the consolidation of sleep into fewer sleep bouts per day across development. In terms of inter-individual differences, we found larger spread in the parameters within the earlier stages of infancy (<1 year). The center and boundaries of the joint distributions evolved with age through the parameter space, converging towards previously described adult parameter values. A bifurcation analysis of the homeostatic time scale parameter revealed that progressive consolidation of sleep occurs through abrupt loss of bouts one at a time, punctuated by narrow intervals of non-entrained (>24-h) cycles. These results establish plausible, population-level trajectories in physiological parameters underpinning maturation of sleep regulation through infancy and early childhood.

neuroscience↗

bioRxiv2025

NRF2 upregulation by CDDO-Me protects AC16 human cardiomyocytes against doxorubicin-induced toxicity.

Doxorubicin (DOX) is an effective anticancer therapeutic but exhibits dose-dependent, potentially life-threatening cardiotoxicity. The specific mechanisms driving this cardiotoxicity are not fully understood but can include the induction of oxidative stress and subsequent cell death mechanism activation. This has prompted the exploration of NRF2, a master co-ordinator of antioxidant and largely cytoprotective pathways, as a potential approach for the alleviation of DOX-induced cardiotoxicity. Here, NRF2 was pharmacologically activated via CDDO-Me (hitherto referred to as CDDO) to reduce the negative consequences on AC16 human cardiomyocyte cell health and functions. NRF2 intracellular dynamics were quantitatively measured using live-cell imaging, demonstrating rapid ([~]10 min) yet sustained ([≥]24 h) induction of NRF2 expression and functional downstream activity. Genetic perturbations of the NRF2-KEAP1 system highlight that CDDO acts specifically through NRF2 to exert AC16 cytoprotection from DOX whilst not promoting human lung and pancreatic cancer cell line viability. Via RNA-seq analysis, we reveal that CDDO dampens DOX-mediated effects on p53 signalling, apoptosis and ferroptosis. This study provides novel insight into NRF2 dynamics in the widely utilised AC16 cells whilst further elucidating the molecular mechanisms contributing to DOX cardiotoxicity and potential NRF2-orchestrated defence. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/675420v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@18c0bb5org.highwire.dtl.DTLVardef@154c707org.highwire.dtl.DTLVardef@d6c127org.highwire.dtl.DTLVardef@122ef0d_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2025

A unified model of cortico-hippocampal interactions through neural field theory

Numerous physical systems evolve on curved manifolds whose geometry constrains their dynamics. The human brain provides a canonical example, with large-scale neural activity evolving on distinct anatomical surfaces such as the cortex and hippocampus. Within each structure, intrinsic feedback loops and manifold geometry shape characteristic neural rhythms. However, core cognitive functions of the brain arise from reciprocal interactions between these spatially distinct neural structures. Here, we introduce a general framework for geometry-constrained coupling between spatially extended dynamical systems evolving on separate manifolds. Using quasi-conformal mapping, we construct neighbourhood-preserving interactions that enable continuous neural activity on distinct geometries to interact while preserving local neighbourhood structure. Applying this framework to neural activity evolving on cortical and hippocampal surfaces, we show that increasing inter-manifold coupling reorganises system dynamics, producing frequency shifts, mode interactions, and coupling-driven instabilities consistent with critical transitions. These effects reproduce key features of large-scale brain activity, including topographically organised synchronisation between cortex and hippocampus during healthy cognition and critical transitions to seizure-like spectral dynamics. These results identify inter-manifold coupling as a core influence on dynamics in the human brain and highlight the broader role of geometry-constrained coupling on emergent dynamics in complex spatially extended systems.

neuroscience↗

bioRxiv2025

Adult organotypic brain slice cultures recapitulate extracellular matrix remodelling in haemorrhagic stroke

1.Haemorrhagic stroke is a devastating condition characterised by vessel rupture and free blood within the brain parenchyma or cerebrospinal fluid (CSF) filled spaces. Across the major subtypes of haemorrhagic stroke (subarachnoid, intracerebral, and intraventricular haemorrhages), the presence of blood in the CSF generates significant tissue damage in the first 72 hours after the event, known as early brain injury (EBI). EBI includes neuroinflammation, blood-brain barrier breakdown and dysregulation of extracellular matrix (ECM) dynamics. ECM dysfunction has been shown to trigger fibrosis of the cortical blood vessels, limiting normal CSF circulation and resulting in the buildup of metabolic waste or the development of post-haemorrhagic hydrocephalus. Limiting or preventing this fibrosis may therefore reduce the rate of morbidity experienced by survivors, providing a potential avenue for non-surgical treatment to reduce secondary brain injury post-stroke. Despite this, current in vivo approaches fail to differentiate between the effect of blood products and secondary consequences including intracranial pressure (ICP) elevation and mass effect. Here, we describe an adult rat organotypic brain slice culture (OBSC) model of haemorrhagic stroke which enables the identification of the effect of blood products on ECM dysregulation. We demonstrate the distribution of key cell types across a time course of 0, 3 and 7 days in culture, indicating that such cultures are viable for a minimum of 7 days. Using immunofluorescence staining, Western blotting and RNA sequencing, we show that exposure of OBSCs to lysed blood markedly increases ECM deposition around cortical blood vessels. This is accompanied by dysregulation of ECM regulatory genes and upregulation of inflammation and oxidative stress-related genes, successfully recapitulating the changes seen in human stroke survivors. This versatile ex vivo model provides a translational platform to further understanding of haemorrhagic stroke pathophysiology and develop or trial novel therapeutics prior to progression to in vivo stroke studies.

neuroscience↗

bioRxiv2024

Mathematical Models of Retinal Drug Delivery

PurposeWet age-related macular degeneration (AMD) causes vision loss when vascular endothelial growth factor (VEGF) stimulates blood vessel growth into the light-sensitive retina. Anti-VEGF treatments such as ranibizumab are currently administered to treat wet AMD via intravitreal injections, which are unpleasant, expensive and risk complications. We explored the efficacy of topically administered ranibizumab, with cell penetrating peptides (CPPs). MethodsEx vivo pig eyes were divided into 3 groups and treated with 1. topical or 2. intravitreal ranibizumab and CPP, or 3. intravitreal ranibizumab. ELISAs measured ranibizumab and VEGF concentrations in the aqueous and vitreous at 20 min, 40 min, 1 hr and 3.5 hr (n = 3, per group). An ordinary differential equation model was formulated to describe the evolving concentrations of ranibizumab, VEGF and their compounds in the tear, aqueous and vitreal compartments. ResultsExperimental -- Topical: aqueous ranibizumab levels increased significantly, coincident with a significant drop in aqueous VEGF. Vitreal ranibizumab increased significantly, while vitreal VEGF remained constant. Intravitreal (with and without CPP): vitreal ranibizumab reached high concentrations, coincident with a significant drop in vitreal VEGF. Mathematical -- topical treatment may provide sustained, moderate suppression of vitreal VEGF levels, while intravitreal treatment provides strong suppression which lessens between treatments. ConclusionsCPP allows topical ranibizumab to penetrate the cornea but reduces ranibizumab availability and efficacy in neutralising VEGF for intravitreal treatment. Combined intravitreal/topical treatment presents a promising approach. Treatment efficacy would be enhanced if ranibizumabs rate of binding to VEGF or tear residence time could be increased.

systems biology↗

bioRxiv2023

Influenza infected macrophages release viral ribonucleoproteins that shape the local host response

Airway epithelial cells and macrophages (M{Phi}) represent cellular targets of infection by influenza A virus (IAV). Epithelial cells support IAV infection and replication by enabling the generation and release of new viral particles (productive replication). In contrast, M{Phi} are susceptible to initial IAV infection but the release of infectious viral particles is inhibited through abortive replication. Despite the lack of infectious virions released from infected M{Phi}, we detected newly synthesised viral RNA and nucleoprotein (NP) in M{Phi} supernatants. We show that viral RNA is released from infected M{Phi} as viral ribonucleoprotein (vRNP) complexes which elicits potent inflammatory responses when exposed to uninfected cells. These vRNPs specifically induced IL-1{beta}, CXCL13, IL-32, CCL4 and CXCL10 in uninfected cells and were at least partially sensed through the RIG-I/MDA5 pathway. While M{Phi} represent a dead-end for IAV infection through abortive replication, the release of vRNPs shapes immune repsonses of uninfected cells in the local microenvironment.

microbiology↗

bioRxiv2023

Mapping the physiological changes in sleep regulation across infancy and young childhood

Sleep patterns in infancy and early childhood vary greatly and change rapidly during development. In adults, sleep patterns are regulated by interactions between neuronal populations in the brainstem and hypothalamus, driven by the circadian and sleep homeostatic processes. However, the neurophysiological mechanisms underlying the sleep patterns and their variations across infancy and early childhood are poorly understood. We investigated whether a well-established mathematical model for sleep regulation in adults can model infant sleep characteristics and explain the physiological basis for developmental changes. By fitting longitudinal sleep data spanning 2 to 540 days after birth, we inferred parameter trajectories across age. We found that the developmental changes in sleep patterns are consistent with a faster accumulation and faster clearance of sleep homeostatic pressure in infancy and a weaker circadian rhythm in early infancy. We also find greater sensitivity to phase-delaying effects of light in infancy and early childhood. These findings reveal fundamental mechanisms that regulate sleep in infancy and early childhood. Given the critical role of sleep in healthy neurodevelopment, this framework could be used to pinpoint pathophysiological mechanisms and identify ways to improve sleep quality in early life.

neuroscience↗

bioRxiv2023

A growth chart of brain function from infancy to adolescence based on electroencephalography

BackgroundIn children, objective, quantitative tools that determine functional neurodevelopment are scarce and rarely scalable for clinical use. Direct recordings of cortical activity using routinely acquired electroencephalography (EEG) offer reliable measures of brain function. MethodsWe developed and validated a measure of functional brain age (FBA) using a residual neural network-based interpretation of the paediatric EEG. In this cross-sectional study, we included 1056 children with typical development ranging in age from 1 month to 18 years. We analyzed a 10 to 15 minute segment of 18-channel EEG recorded during light sleep (N1 and N2 states). FindingsThe FBA obtained from EEG had a weighted mean absolute error (wMAE) of 0.85 years (95%CI: 0.69-1.02; n = 1056). A two-channel version of the FBA had a wMAE of 1.51 years (95%CI: 1.30-1.73; n = 1056) and was validated on an independent set of EEG recordings (wMAE = 2.27 years, 95%CI: 1.90-2.65; n = 723). Group-level maturational delays were also detected in a small cohort of children with Trisomy 21 (Cohens d = 0.36, p = 0.028). InterpretationAn FBA, based on EEG, is an accurate, practical and scalable automated tool to track brain function maturation throughout childhood with accuracy comparable to widely used physical growth charts. FundingThis research was supported by the National Health and Medical Research Council, Australia, Helsinki University Diagnostic Center Research Funds, Finnish Academy, Finnish Paediatric Foundation, and Sigrid Juselius Foundation. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSTools for objectively tracking neurodevelopment in paediatric populations using direct measurement of the brain are rare. Prior to conducting this study, we explored multiple databases (Google Scholar, PubMed, Web of Science) with search strategies that combined one or more of the terms "paediatric brain development", "brain age", "age estimation", "MRI measurements", "EEG measurements", "machine learning", "artificial intelligence", "advanced ageing", "neurodevelopmental delays" and "growth charts" with no restrictions on language and dates. In screening over 500 publications, 7 studies evaluated brain age in children using MRI and only a single study investigated maturation in EEG activity across discrete age bins. Added value of this studyWe formulated a measure of functional brain age (FBA) using state-of-the-art machine learning (ML) algorithms trained on a large, unique database consisting of multichannel clinical EEG recorded from N1/N2 sleep (n = 1056 children; 1 month to 17 years), with typical neurodevelopment confirmed at a 4-year follow-up. The FBA showed a high correlation with age and detected group-level differences associated with conditions of neurodevelopmental delay. Implications of all the available evidenceAge is prominent within EEG recordings of N1/N2 sleep and is readily extracted using ML. Public release of the FBA estimator and the use of EEG, commonly delivered in outpatient settings, as the basis of age prediction enables clear translation of measures of brain age to the clinic. Future work on EEG datasets across various neurodevelopmental profiles will enhance generalisability and user confidence in the clinical application of brain age.

neuroscience↗

bioRxiv2023

Neuropsychology of cognitive aging in rhesus monkeys

Aged rhesus monkeys, like aged humans, show declines in cognitive function. We present cognitive test data from a large sample of male and female rhesus monkeys, 34 young (3.5-13.6 years) and 71 aged (19.9-32.5 years of age at the start of cognitive testing). Monkeys were tested on spatiotemporal working memory (delayed response), visual recognition memory (delayed nonmatching-to-sample), and stimulus-reward association learning (object discrimination), tasks with an extensive evidence base in nonhuman primate neuropsychology. On average, aged monkeys performed worse than young on all three tasks. Acquisition of delayed response and delayed nonmatching-to-sample was more variable in aged monkeys than in young. Performance scores on delayed nonmatching-to-sample and object discrimination were associated with each other, but neither was associated with performance on delayed response. Sex and chronological age were not reliable predictors of individual differences in cognitive outcome among the aged monkeys. These data establish population norms for cognitive tests in young and aged rhesus monkeys in the largest sample reported to date. They also illustrate independence of cognitive aging in task domains dependent on the prefrontal cortex and medial temporal lobe. (181 words)

neuroscience↗

bioRxiv2022

Evolutionary shaping of human brain dynamics

The human brain is distinct from those of other species in terms of size, organization, and connectivity. How do these structural evolutionary differences drive patterns of neural activity enabling brain function? Here, we combine brain imaging and biophysical modeling to show that the anatomical wiring of the human brain distinctly shapes neural dynamics. This shaping is characterized by a narrower distribution of dynamic ranges across brain regions compared with that of chimpanzees, our closest living primate relatives. We find that such a sharp dynamic range distribution supports faster integration between regions, particularly in transmodal systems. Conversely, a broad dynamic range distribution as seen in chimpanzees facilitates brain processes relying more on neural interactions within specialized local brain systems. These findings suggest that human brain dynamics have evolved to foster rapid associative processes in service of complex cognitive functions and behavior.

neuroscience↗

bioRxiv2022

Seasonal changes in membrane structure and excitability in central neurons of goldfish (Carassius auratus) under constant environmental conditions

Seasonal modifications in the structure of cellular membranes occur as an adaptive measure to withstand exposure to prolonged environmental change. Little is known about whether such changes may occur independently of external cues, such as photoperiod or temperature, or how they may impact the central nervous system (CNS). We compared membrane properties of central neurons isolated from the retina of goldfish (Carassius auratus), an organism well-adapted to extreme environmental change, during the summer and winter months. Goldfish were maintained in a facility under constant environmental conditions throughout the year. Analysis of whole-retina phospholipid composition using mass spectrometry-based lipidomics revealed a two-fold increase in phosphatidylethanolamine species during the winter, suggesting an increase in cell membrane fluidity. Atomic force microscopy was used to produce localized, nanoscale-force deformation of neuronal membranes. Measurement of Youngs modulus indicated increased membrane stiffness (or decreased elasticity) in neurons isolated during the winter. Voltage-clamp electrophysiology was used to assess physiological changes in neurons between seasons. Winter neurons displayed a hyperpolarized reversal potential (Vrev) and a significantly lower input resistance (Rin) compared to summer neurons. This was indicative of a decrease in membrane excitability during the winter. Subsequent measurement of intracellular Ca2+ activity using Fura-2 microspectrofluorometry confirmed a reduction in action potential activity, including duration and action potential profile, in neurons isolated during the winter. These studies demonstrate chemical and biophysical changes that occur in central neurons of goldfish throughout the year without exposure to seasonal cues, and suggest a novel mechanism of seasonal regulation of CNS activity. SUMMARY STATEMENTCentral neurons isolated from the retina of goldfish held under constant environmental conditions undergo seasonal changes in membrane structure and excitability.

neuroscience↗

bioRxiv2021

Evaluating mono and combination therapy of meropenem and amikacin against Pseudomonas aeruginosa bacteremia in the Hollow-Fiber Infection Model

Debate continues as to the role of combination antibiotic therapy for the management of Pseudomonas aeruginosa infections. We studied extent of bacterial killing and resistance emergence of meropenem and amikacin as monotherapy and as a combination therapy against susceptible and resistant P. aeruginosa isolates from bacteremic patients using the dynamic in vitro hollow-fiber infection model. Three P. aeruginosa isolates (meropenem MICs 0.125, 0.25 & 64 mg/L) were used simulating bacteremia with an initial inoculum ~1x105 CFU/mL and the expected pharmacokinetics of meropenem and amikacin in critically ill patients. For isolates susceptible to amikacin and meropenem (isolates 1 and 2), the rate of bacterial killing was increased with the combination regimen when compared with monotherapy of either antibiotic. Both the combination and meropenem monotherapy were able to sustain bacterial killing throughout the seven-day treatment course, whereas regrowth of bacteria occurred with amikacin monotherapy after 12 hours. For the meropenem-resistant P. aeruginosa isolate (isolate 3), only the combination regimen demonstrated bacterial killing. Given that tailored antibiotic regimens can maximize potential synergy against some isolates, future studies should explore the benefit of combination therapy against resistant P. aeruginosa.

pharmacology and toxicology↗

bioRxiv2021

Automated detection of artefacts in neonatal EEG with residual neural networks

Background and ObjectiveTo develop a computational algorithm that detects and identifies different artefact types in neonatal electroencephalography (EEG) signals. MethodsAs part of a larger algorithm, we trained a Residual Deep Neural Network on expert human annotations of EEG recordings from 79 term infants recorded in a neonatal intensive care unit (112 h of 18-channel recording). The network was trained using 10 fold cross validation in Matlab. Artefact types included: device interference, EMG, movement, electrode pop, and non-cortical biological rhythms. Performance was assessed by prediction statistics and further validated on a separate independent dataset of 13 term infants (143 h of 3-channel recording). EEG pre-processing steps, and other post-processing steps such as averaging probability over a temporal window, were also included in the algorithm. ResultsThe Residual Deep Neural Network showed high accuracy (95%) when distinguishing periods of clean, artefact-free EEG from any kind of artefact, with a median accuracy for individual patient of 91% (IQR: 81%-96%). The accuracy in identifying the five different types of artefacts ranged from 57%-92%, with electrode pop being the hardest to detect and EMG being the easiest. This reflected the proportion of artefact available in the training dataset. Misclassification as clean was low for each artefact type, ranging from 1%-11%. The detection accuracy was lower on the validation set (87%). We used the algorithm to show that EEG channels located near the vertex were the least susceptible to artefact. ConclusionArtefacts can be accurately and reliably identified in the neonatal EEG using a deep learning algorithm. Artefact detection algorithms can provide continuous bedside quality assessment and support EEG review by clinicians or analysis algorithms. HighlightsO_LIWe applied a Residual Deep Neural Network as part of an artefact detection algorithm in neonatal electroencephalograms. C_LIO_LIThe algorithm shows high accuracy in identifying artefactual data in general and for specific artefact types. C_LIO_LIEEG channels near the top of the head are less prone to artefact. C_LI

neuroscience↗

bioRxiv2020

Stochastic synchronization of dynamics on the human connectome

Synchronization is a collective mechanism by which oscillatory networks achieve their functions. Factors driving synchronization include the networks topological and dynamical properties. However, how these factors drive the emergence of synchronization in the presence of potentially disruptive external inputs like stochastic perturbations is not well understood, particularly for real-world systems such as the human brain. Here, we aim to systematically address this problem using a large-scale model of the human brain network (i.e., the human connectome). The results show that the model can produce complex synchronization patterns transitioning between incoherent and coherent states. When nodes in the network are coupled at some critical strength, a counterintuitive phenomenon emerges where the addition of noise increases the synchronization of global and local dynamics, with structural hub nodes benefiting the most. This stochastic synchronization effect is found to be driven by the intrinsic hierarchy of neural timescales of the brain and the heterogeneous complex topology of the connectome. Moreover, the effect coincides with clustering of node phases and node frequencies and strengthening of the functional connectivity of some of the connectomes subnetworks. Overall, the work provides broad theoretical insights into the emergence and mechanisms of stochastic synchronization, highlighting its putative contribution in achieving network integration underpinning brain function.

neuroscience↗

bioRxiv2019

Automated cot-side tracking of functional brain age in preterm infants with routine EEG monitoring

ObjectiveA major challenge in the care of preterm infants is the early identification of compromised neurological development. While several measures are routinely used to track anatomical growth, there is a striking lack of reliable and objective tools for tracking maturation of early brain function; a cornerstone of lifelong neurological health. We present a cot-side method for measuring the functional maturity of the newborn brain based on routinely-available neurological monitoring with electroencephalography (EEG). MethodsWe used a dataset of 177 EEG recordings from 65 preterm infants to train a multivariable prediction of functional brain age (FBA) from EEG. The FBA was validated on an independent set of 99 EEG recordings from 42 preterm infants. The difference between FBA and postmenstrual age (PMA) was evaluated as a predictor for neurodevelopmental outcome. ResultsThe FBA correlated strongly with the PMA of an infant, with a median prediction error of less than 1 week. Moreover, individual babies follow well-defined individual trajectories. The accuracy of the FBA applied to the validation set was statistically equivalent to the training set accuracy. In a subgroup of infants with repeated EEG recordings, a persistently negative predicted age difference was associated with poor neurodevelopmental outcome. InterpretationThe FBA enables the tracking of functional neurodevelopment in preterm infants. This establishes proof of principle for growth charts for brain function, a new tool to assist clinical management and identify infants who will benefit most from early intervention.

neuroscience↗