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Publications
Publications (212)
INTRODUCTION
Parkinson’s disease (PD) and Dementia with Lewy bodies (DLB) show heterogeneous brain atrophy patterns and common group-average analyses are limited in capturing individual differences. Neuroanatomical normative modelling overcomes this by comparing individuals to a large reference cohort.
METHODS
We generated z-scores from T1w-MRI sc...
This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6-17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large...
Importance:
To make progress toward precision psychiatry, it is crucial to move beyond case-control studies and instead capture individual variations and interpret them in the context of a normal range of biological systems.
Objective:
To evaluate whether baseline deviations from a normative reference range in subcortical volumes are better pred...
The majority of people worldwide live in cities, yet how urban living affects brain and mental illness is scarcely understood. Urban lives are exposed to a a wide array of environmental factors that may combine and interact to influence mental health. While individual factors of the urban environment have been investigated in isolation, to date no...
Multi-site imaging studies can increase statistical power and improve the reproducibility and generalizability of findings, yet data often need to be harmonized. One alternative to data harmonization in the normative modeling setting is Hierarchical Bayesian Regression (HBR), which overcomes some of the weaknesses of data harmonization. Here, we te...
In this paper, we propose a new framework for understanding and modelling neurobiological extreme atypicalities for individual participants. We combine the strength of normative models, to make predictions for individual patients, with multivariate extreme value statistics, which allows us to model the outer centiles accurately, enabling accurate e...
Combining imaging modalities and metrics that are sensitive to various aspects of brain structure and maturation may help identify individuals that show deviations in relation to same-aged peers, and thus benefit early-risk-assessment for mental disorders. We used one timepoint multimodal brain imaging, cognitive, and questionnaire data from 1280 8...
Alzheimer's disease is clinically heterogeneous, in symptom profiles, progression rates and outcomes. This clinical heterogeneity is linked to underlying neuroanatomical heterogeneity. To explore this, we employed the emerging technique of neuroanatomical normative modelling to index regional patterns of variability in cortical thickness in individ...
While data are the primary fuel for machine learning models, they often suffer from missing values, especially when collected in real-world scenarios. However, many off-the-shelf machine learning models, including artificial neural network models, are unable to handle these missing values directly. Therefore, extra data preprocessing and curation s...
Objective
To uncover transdiagnostic domains of functioning across stress- and neurodevelopmental disorders, and to map these on to the topographic functional organization of cortico-striatal circuitry.
Methods
In a clinical sample (n=186) of subjects with high rates of comorbidity of major depressive disorder, anxiety disorder, attention-deficit/...
Normative modeling is an emerging and innovative framework for mapping individual differences at the level of a single subject or observation in relation to a reference model. It involves charting centiles of variation across a population in terms of mappings between biology and behavior, which can then be used to make statistical inferences at the...
Background:
Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but...
Background
The cerebellum contains more than 50% of the brain neurons and is involved in social cognition. Cerebellar anatomical atypicalities have repeatedly been reported in individuals with autism. However, studies have yielded inconsistent findings, likely because of a lack of statistical power, and did not capture the clinical and neuroanatomi...
Site differences, or systematic differences in feature distributions across multiple data-acquisition sites, are a known source of heterogeneity that may adversely affect large-scale meta- and mega-analyses of independently collected neuroimaging data. They influence nearly all multi-site imaging modalities and biomarkers, and methods to compensate...
BACKGROUND
Sensory atypicalities are particularly common in autism spectrum disorders (ASD). Nevertheless, our knowledge about the divergence of the underlying somatosensory region and its association with ASD phenotype features is limited.
METHODS
We applied a data-driven approach to map the fine-grained variations in functional connectivity of t...
Background
Disruptive behavior disorders (DBD) are heterogeneous at the clinical and the biological level. Therefore, the aims were to dissect the heterogeneous neurodevelopmental deviations of the affective brain circuitry and provide an integration of these differences across modalities.
Methods
We combined two novel approaches. First, normative...
The discrepancy between chronological age and the apparent age of the brain based on neuroimaging data — the brain age delta — has emerged as a reliable marker of brain health. With an increasing wealth of data, approaches to tackle heterogeneity in data acquisition are vital. To this end, we compiled raw structural magnetic resonance images into o...
Objectives
The male preponderance in autism spectrum conditions (ASC) prevalence is among the most pronounced sex ratios across different neurodevelopmental conditions. Here, we aimed to elucidate the relationship between autism and typical sex-differential neuroanatomy, cognition, and related gene expression.
Methods
Using a novel deep learning f...
The substantial individual heterogeneity that characterizes mental illness is often ignored by classical case-control designs that rely on group mean comparisons. Here, we present a comprehensive, multiscale characterization of individual heterogeneity of brain changes in 1294 cases diagnosed with one of six conditions and 1465 matched healthy cont...
Background
Autism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioural, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterise heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with...
The striatum receives dense dopaminergic projections making it a key region of the dopaminergic system. Its dysfunction has been implicated in various conditions including Parkinson's disease (PD) and substance use disorder. However, the investigation of dopamine-specific functioning in humans is problematic as current MRI approaches are unable to...
Urbanicity is a growing environmental challenge for mental health. Here, we investigate correlations of urbanicity with brain structure and function, neuropsychology and mental illness symptoms in young people from China and Europe (total n = 3,867). We developed a remote-sensing satellite measure (UrbanSat) to quantify population density at any po...
Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and use normative...
Background
Adolescence hosts a sharp increase in the incidence of mental disorders. The prodromal phases are often characterized by cognitive deficits which predate disease onset by several years. Characterization of cognitive performance in relation to normative trajectories may have value for early risk assessment and monitoring.
Methods
Youth a...
Current neuroimaging acquisition and processing approaches tend to be optimised for quality rather than speed. However, rapid acquisition and processing of neuroimaging data can lead to novel neuroimaging paradigms, such as adaptive acquisition, where rapidly processed data is used to inform subsequent image acquisition steps. Here we first evaluat...
Background
The neurocognitive mechanisms underlying autism spectrum disorder (ASD) remain unclear. Progress has been largely hampered by small sample sizes, variable age ranges and resulting inconsistent findings. There is a pressing need for large definitive studies to delineate the nature and extent of key case/control differences to direct resea...
Normative modelling is becoming more popular in neuroimaging due to its ability to make predictions of deviation from a normal trajectory at the level of individual participants. It allows the user to model the distribution of several neuroimaging modalities, giving an estimation for the mean and centiles of variation. With the increase in the avai...
Background
Alzheimer’s Disease (AD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology. Neuroimaging biomarkers have considerable utility in AD research, however, common statistical designs do not capture neuroanatomical heterogeneity, generally assuming the effects of AD on the brain will be the s...
The discrepancy between chronological age and the apparent age of the brain based on neuroimaging data - the brain age delta - has emerged as a reliable marker of brain health. With an increasing wealth of data, approaches to tackle heterogeneity in data acquisition are vital. To this end, we compiled raw structural magnetic resonance images into o...
Background. Adolescence hosts a sharp increase in the incidence of mental disorders. The prodromal phases are often characterized by cognitive deficits which predate disease onset by several years. Characterization of cognitive performance in relation to normative trajectories may have value for early risk assessment and monitoring. Methods. Youth...
Objective:
Autism spectrum disorder (ASD) is accompanied by highly individualized neuroanatomical deviations that potentially map onto distinct genotypes and clinical phenotypes. This study aimed to link differences in brain anatomy to specific biological pathways to pave the way toward targeted therapeutic interventions.
Methods:
The authors ex...
Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling bra...
Normative modeling is an emerging and innovative framework for mapping individual differences at the level of a single subject or observation in relation to a reference model. It involves charting centiles of variation across a population in terms of mappings between biology and behavior which can then be used to make statistical inferences at the...
Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and use normative...
Normative modeling aims to quantify the degree to which an individual's brain deviates from a reference sample with respect to one or more variables, which can be used as a potential biomarker of a healthy brain and as a tool to study heterogeneity of psychiatric disorders. The application of normative models is hindered by methodological challenge...
A bstract
Clinical neuroimaging data availability has grown substantially in the last decade, providing the potential for studying heterogeneity in clinical cohorts on a previously unprecedented scale. Normative modeling is an emerging statistical tool for dissecting heterogeneity in complex brain disorders. However, its application remains technic...
Dementia is a highly heterogeneous condition, with pronounced individual differences in onset age, clinical presentation, progression rates and neuropathological hallmarks, even within a specific diagnostic group. However, the most common statistical designs used in dementia research studies and clinical trials overlook this heterogeneity, instead...
Normative modelling is becoming more popular in neuroimaging due to its ability to make predictions of deviation from a normal trajectory at the level of individual participants. It allows the user to model the distribution of several neuroimaging modalities, giving an estimation for the mean and centiles of variation. With the increase in the avai...
The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process...
The striatum receives dense dopaminergic projections making it a key region of the dopaminergic system. Its dysfunction has been implicated in various conditions including Parkinson’s disease and substance use disorder. However, the investigation of dopamine-specific functioning in humans is problematic as the striatum is highly interconnected and...
The increasing number of neuroimaging scans in recent years has facilitated the use of complex nonlinear approaches to analyzing such data. More specifically, deep learning, which has been previously hindered by the curse of dimensionality is now feasible. However, it remains challenging to use these techniques develop reliable biomarkers and find...
Identifying brain processes involved in the risk and development of mental disorders is a major aim. We recently reported substantial interindividual heterogeneity in brain structural aberrations among patients with schizophrenia and bipolar disorder. Estimating the normative range of voxel-based morphometry (VBM) data among healthy individuals usi...
Current neuroimaging acquisition and processing approaches tend to be optimised for quality rather than speed. However, rapid acquisition and processing of neuroimaging data can lead to novel neuroimaging paradigms, such as adaptive acquisition, where rapidly processed data is used to inform subsequent image acquisition steps. Here we first evaluat...
A bstract
The potential of normative modeling to make individualized predictions from neuroimaging data has enabled inferences that go beyond the case-control approach. However, site effects are often confounded with variables of interest in a complex manner and can bias estimates of normative models, which has impeded the application of normative...
Complex social interplay is a defining property of the human species. In social neuroscience, many experiments have sought to first define and then locate 'perspective taking', 'empathy', and other psychological concepts to specific brain circuits. Seldom, bottom-up studies were conducted to first identify explanatory patterns of brain variation, w...
Autism is a complex neurodevelopmental condition with substantial phenotypic, biological, and etiologic heterogeneity. It remains a challenge to identify biomarkers to stratify autism into replicable cognitive or biological subtypes. Here, we aim to introduce a novel methodological framework for parsing neuroanatomical subtypes within a large cohor...
Clinical neuroimaging has recently witnessed explosive growth in data availability which brings studying heterogeneity in clinical cohorts to the spotlight. Normative modeling is an emerging statistical tool for achieving this objective. However, its application remains technically challenging due to difficulties in properly dealing with nuisance v...
Machine learning predictive models are being used in neuroimaging to predict information about the task or stimuli or to identify potentially clinically useful biomarkers. However, the predictions can be driven by confounding variables unrelated to the signal of interest, such as scanner effect or head motion, limiting the clinical usefulness and i...
The complexity of social interactions is a defining property of the human species. Many social neuroscience experiments have sought to map "perspective taking", "empathy", and other canonical psychological constructs to distinguishable brain circuits. This predominant research paradigm was seldom complemented by bottom-up studies of the unknown sou...
Objective
Preterm birth carries a significant risk for atypical development. While studies comparing group means have identified a number of early brain correlates of prematurity, they may ‘average out’ effects significant in a single individual. To understand better the cerebral consequences of prematurity, we created normative ‘growth curves’ cha...
Background
Autism Spectrum Disorder (‘autism’) is a highly heterogeneous neurodevelopmental condition with few effective treatments for core and associated features. To make progress we need to both identify and validate neural markers that help to parse heterogeneity to tailor therapies to specific neurobiological profiles. Atypical hemispheric la...
Clinical neuroimaging has recently witnessed explosive growth in data availability which brings studying heterogeneity in clinical cohorts to the spotlight. Normative modeling is an emerging statistical tool for achieving this objective. However, its application remains technically challenging due to difficulties in properly dealing with nuisance v...
Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling bra...
The expanding behavioral repertoire of the developing brain during childhood and adolescence is shaped by complex brain–environment interactions and flavored by unique life experiences. The transition into young adulthood offers opportunities for adaptation and growth but also increased susceptibility to environmental perturbations, such as the cha...
Identifying brain processes involved in the risk and development of mental disorders is a major aim. We recently reported substantial inter-individual heterogeneity in brain structural aberrations among patients with schizophrenia and bipolar disorder. Estimating the normative range of voxel-based morphometry (VBM) data among healthy individuals us...
Preterm-born children are at increased risk of lifelong neurodevelopmental difficulties. Group-wise analyses of magnetic resonance imaging show many differences between preterm- and term-born infants but do not reliably predict neurocognitive prognosis for individual infants. This might be due to the unrecognized heterogeneity of cerebral injury wi...
Background
Autism Spectrum Disorder (henceforth ‘autism’) is a highly heterogeneous neurodevelopmental condition with few effective treatments for core and associated features. To make progress we need to both identify and validate neural markers that help to parse heterogeneity to tailor therapies to specific neurobiological profiles. Atypical hem...
The meaning of a sentence can be understood, whether presented in written or spoken form. Therefore it is highly probable that brain processes supporting language comprehension are at least partly independent of sensory modality. To identify where and when in the brain language processing is independent of sensory modality, we directly compared neu...
Network connectivity fingerprints are among today's best choices to obtain a faithful sampling of an individual's brain and cognition. Widely available MRI scanners can provide rich information tapping into network recruitment and reconfiguration that now scales to hundreds and thousands of humans. Here, we contemplate the advantages of analysing s...
Patients with major depressive disorder (MDD) show heterogeneous treatment response and highly variable clinical trajectories: while some patients experience swift recovery, others show relapsing-remitting or chronic courses. Predicting individual clinical trajectories at an early stage is a key challenge for psychiatry and might facilitate individ...
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 t...
