Patric Hagmann

• Lausanne University Hospital

Very preterm (VPT) children are prone to a variety of neurodevelopmental impairments, particularly regarding their attention and executive functions (i.e., inhibition, shifting, and working memory). Here, we aimed to investigate whether morphometric and connectivity characteristics from key brain regions associated with attention and executive func...

A critical step before data-sharing of human neuroimaging is removing facial features to protect individuals’ privacy. However, not only does this process redact identifiable information about individuals, but it also removes non-identifiable information. This introduces undesired variability into downstream analysis and interpretation. This regist...

Autism Spectrum Disorder (ASD) is characterized by impairments in social interaction and repetitive behaviors. A key characteristic of ASD is a decreased interest in social interactions, which affects individuals’ ability to engage with their social environment. This study explores the neurobiological basis of these social deficits, focusing on the...

Despite the plethora of AI-based algorithms developed for anomaly detection in radiology, subsequent integration into clinical setting is rarely evaluated. In this work, we assess the applicability and utility of an AI-based model for brain aneurysm detection comparing the performance of two readers with different levels of experience (2 and 13 yea...

Network science has revolutionized our understanding of brain organization by revealing self-organizing patterns underlying its structural and functional connectivity. However, capturing metabolic contrast remains a challenge, leaving a critical gap in connectomics. Using advanced 3D whole-brain proton MR spectroscopic imaging with high spatial res...

Background Cerebral amyloid angiopathy (CAA) has been reported in patients with dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD), with a similar prevalence from pathology studies.1,2 CAA typically affects posterior regions, but amyloid deposits have been observed in the striatum in patients with DLB and with hereditary CAA.1,3 Here, we...

Brain templates aggregate averaged features across subjects in a normalized stereotactic space and are critical to formalize prior knowledge in neuroimaging analyses. The most widespread templates have been developed by the Montreal Neurological Institute (MNI), yielding a number of templates referred to with the umbrella term of “MNI space”. Recen...

A critical requirement before data-sharing of human neuroimaging is removing facial features to protect individuals' privacy. However, not only does this process redact identifiable information about individuals, but it also removes non-identifiable information. This introduces undesired variability into downstream analysis and interpretation. This...

One way to increase the statistical power and generalizability of neuroimaging studies is to collect data at multiple sites or merge multiple cohorts. However, this usually comes with site-related biases due to the heterogeneity of scanners and acquisition parameters, negatively impacting sensitivity. Brain structural connectomes are not an excepti...

In groups of patients suffering from psychosis, redox dysregulation was reported in both peripheral fluids and brain. It has been hypothesized that such dysregulation, including alterations of the glutathione (GSH) cycle could participate in the brain white matter (WM) abnormalities in schizophrenia (SZ) due to the oligodendrocytes’ susceptibility...

Across development, experience has a strong impact on the way we think and adapt. School experience affects academic and social-emotional outcomes, yet whether differences in pedagogical experience modulate underlying brain network development is still unknown. In this study, we compared the brain network dynamics of students with different pedagog...

IntroductionTraditional classification systems based on broad nosological categories do not adequately capture the high heterogeneity of mental illness. One possible solution to this is to move to a multi-dimensional model of mental illness, as has been proposed by the Research Domain Criteria and Hierarchical Taxonomy of Psychopathology frameworks...

While research has unveiled and quantified brain markers of abnormal neurodevelopment, clinicians still work with qualitative metrics for MRI brain investigation. The purpose of the current article is to bridge the knowledge gap between case-control cohort studies and individual patient care. Here, we provide a unique dataset of seventy-three 3-to-...

Connectome spectrum electromagnetic tomography (CSET) combines diffusion MRI‐derived structural connectivity data with well‐established graph signal processing tools to solve the M/EEG inverse problem. Using simulated EEG signals from fMRI responses, and two EEG datasets on visual‐evoked potentials, we provide evidence supporting that (i) CSET capt...

Autism Spectrum Disorder (ASD) is characterized by impairments in social interaction and repetitive behaviors. A key characteristic of ASD is a decreased interest in social interactions, which affects individuals' ability to engage with their social environment. This study explores the neurobiological basis of these social deficits, focusing on the...

Increasing evidence points toward the role of the extracellular matrix, specifically matrix metalloproteinase 9 (MMP-9), in the pathophysiology of psychosis. MMP-9 is a critical regulator of the crosstalk between peripheral and central inflammation, extracellular matrix remodeling, hippocampal development, synaptic pruning, and neuroplasticity. Her...

Background and Hypothesis: Studies on schizophrenia feature diffusion magnetic resonance imaging (dMRI) to investigate white matter (WM) anomalies. The heterogeneity in the possible interpretations of these metrics highlights the importance of increasing their specificity. Here, we characterize WM pathology in early psychosis (EP) and schizophrenia...

Quality assessment and quality control (QA/QC) checkpoints layered throughout the dataflow are essential to ensure the reliability of neuroimaging analyses. In the case of functional MRI, best practices recommend collecting a ‘positive control’ task with which the different layers of QA/QC can be validated. These are short and simple tasks designed...

Error‐monitoring is a crucial cognitive process that enables us to adapt to the constantly changing environment. The anterior cingulate cortex (ACC) plays a vital role in error‐monitoring, and its prolonged maturation suggests that it can be influenced by experience‐dependent plasticity. To explore this possibility, we collected morphometric magnet...

Background Alterations in brain connectivity occur early during psychosis and underlie the clinical manifestations of the illness as well as patient functioning and outcome. After a first episode of psychosis (FEP), different trajectories are possible and best described by the clinical-staging model that places the patient along a continuum of cond...

Across development, experience has a strong impact on the way we think and adapt. School experience affects academic and social-emotional outcomes, yet the extent to which pedagogy modulates underlying brain network development is still unknown. In this study, we compared brain network dynamics of students with different pedagogical backgrounds. Sp...

Brain oscillations are produced by the coordinated activity of large groups of neurons and different rhythms are thought to reflect different modes of information processing. These modes, in turn, are known to occur at different spatial scales. Nevertheless, how these rhythms support different spatial modes of information processing at the brain sc...

Objective: Structure-function coupling remains largely unknown in brain disorders. We studied this coupling during interictal epileptic discharges (IEDs), using graph signal processing in temporal lobe epilepsy (TLE). Methods: We decomposed IEDs of 17 patients on spatial maps, i.e. network harmonics, extracted from a structural connectome. Harmo...

Aim: Pathological states of recovery after coma as a result of a severe brain injury are marked with changes in structural connectivity of the brain. This study aimed to identify a topological correlation between white matter integrity and the level of functional and cognitive impairment in patients recovering after coma. Methods: Structural con...

Magnetic resonance imaging (MRI) generates a radiofrequency field (B1) to frequency encode the object being imaged. Deviations from the nominal B1 field produce artifactual intensity nonuniformity (INU) across the image, which is problematic, especially for automated analyses that assume a tissue is represented by voxels of similar intensity throug...

MRIQC (Esteban et al. 2017) is a tool to help researchers perform quality control (QC) on their structural and functional MRI data. Not only does MRIQC generate visual reports for reliable, manual assessment but it also automatically extracts a set of image quality metrics (IQMs). However, these IQMs are hard to interpret, and many related question...

The implementation of adequate quality assessment (QA) and quality control (QC) protocols within the magnetic resonance imaging (MRI) research workflow is resource- and time-consuming and even more so is their execution. As a result, QA/QC practices highly vary across laboratories and “MRI schools”, ranging from highly specialized knowledge spots t...

Creating large annotated datasets represents a major bottleneck for the development of deep learning models in radiology. To overcome this, we propose a combined use of weak labels (imprecise, but fast-to-create annotations) and Transfer Learning (TL). Specifically, we explore inductive TL, where source and target domains are identical, but tasks a...

Background and Hypothesis Although the thalamus has a central role in schizophrenia pathophysiology, contributing to sensory, cognitive, and sleep alterations, the nature and dynamics of the alterations occurring within this structure remain largely elusive. Using a multimodal magnetic resonance imaging (MRI) approach, we examined whether anomalies...

The human brain is a complex system that can be efficiently represented as a network of structural connectivity. Many imaging studies would benefit from such network information, which is not always available. In this work, we present a whole-brain multi-scale structural connectome atlas. This tool has been derived from a cohort of 66 healthy subje...

Brain aneurysm detection in Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA) has undergone drastic improvements with the advent of Deep Learning (DL). However, performances of supervised DL models heavily rely on the quantity of labeled samples, which are extremely costly to obtain. Here, we present a DL model for aneurysm detection that ove...

Brain oscillations are produced by the coordinated activity of large groups of neurons and different rhythms are thought to reflect different modes of information processing. These modes, in turn, are known to occur at different spatial scales. Nevertheless, how these rhythms support different modes of information processing at the brain scale is n...

Connectome Spectrum Electromagnetic Tomography (CSET) combines diffusion MRI-derived structural connectivity data with well-established graph signal processing tools to solve the M/EEG inverse problem. Using simulated EEG signals from fMRI responses, and two EEG datasets on visual-evoked potentials, we provide evidence supporting that (i) CSET capt...

Connectome Mapper 3 (CMP3) is an open-source processing pipeline software, written in Python 3, for multi-scale multi-modal connectome mapping of the human brain. It provides researchers with a unique workflow, implemented in accordance with the Brain Imaging Data Structure (BIDS) App framework, that leverages a number of widely adopted software to...

The dynamic repertoire of functional brain networks is constrained by the underlying topology of structural connections. Despite this intrinsic relationship between structural connectivity (SC) and functional connectivity (FC), integrative and multimodal approaches to combine the two remain limited. Here, we propose a new adaptive filter for estima...

Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool to investigate equivocal neurological patterns during fetal development. However, the number of acquisitions of...

Quality control of functional MRI data is essential as artifacts can have a critical impact on subsequent analysis. Yet, visual assessment of a dataset is tedious and time-consuming. By extending the carpet plot with the voxels located on a closed band (or “crown”) around the brain, we showed that fMRI data quality can be assessed more effectively....

Defacing (i.e. removing facial features) from structural imaging has become a necessary step before data sharing to ensure participants’ anonymity (Schwarz et al. 2021; Fig 1A). This process has proven to have some deleterious effects on the downstream research workflow (de Sitter et al. 2020). Here, we present an exploratory analysis prior to test...

We describe the multimodal neuroimaging dataset VEPCON (OpenNeuro Dataset ds003505). It includes raw data and derivatives of high-density EEG, structural MRI, diffusion weighted images (DWI) and single-trial behavior (accuracy, reaction time). Visual evoked potentials (VEPs) were recorded while participants (n = 20) discriminated briefly presented...

Although shared behavioral and neural mechanisms between working memory (WM) and motor sequence learning (MSL) have been suggested, the additive and interactive effects of training have not been studied. This study aimed at investigating changes in brain functional connectivity (FC) induced by sequential (WM + MSL and MSL + WM) and combined (WM × M...

Epilepsy presurgical investigation may include focal intracortical single-pulse electrical stimulations with depth electrodes, which induce cortico-cortical evoked potentials at distant sites because of white matter connectivity. Cortico-cortical evoked potentials provide a unique window on functional brain networks because they contain sufficient...

Natural Language Processing (NLP) on electronic health records (EHRs) can be used to monitor the evolution of pathologies over time to facilitate diagnosis and improve decision-making. In this study, we designed an NLP pipeline to classify Magnetic Resonance Imaging (MRI) radiology reports of patients with high-grade gliomas. Specifically, we aimed...

Accurate characterization of in utero human brain maturation is critical as it involves complex interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool complementary to the ultrasound gold standard to monitor the development of the fetus, especially in the case of equ...

Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool to investigate equivocal neurological patterns during fetal development. However, the number of acquisitions of...

Signaling in brain networks unfolds over multiple topological scales. Areas may exchange information over local circuits, encompassing direct neighbours and areas with similar functions, or over global circuits, encompassing distant neighbours with dissimilar functions. Here we study how the organization of cortico-cortical networks mediate localiz...

Objective: Epilepsy with myoclonic atonic seizure (EMAS) occurs in young children with previously normal to subnormal development. The outcome ranges from seizure freedom with preserved cognitive abilities to refractory epilepsy with intellectual disability (ID). Routine brain imaging typically shows no abnormalities. We aimed to compare the brain...

The functional organization of neural processes is constrained by the brain's intrinsic structural connectivity, i.e., the connectome. Here, we explore how structural connectivity can improve the representation of brain activity signals and their dynamics. Using a multi-modal imaging dataset (electroencephalography, structural MRI, and diffusion MR...

We present the comparison of two-dimensional (2D) fetal brain biometry on magnetic resonance (MR) images using orthogonal 2D T2-weighted sequences (T2WSs) vs. one 3D super-resolution (SR) reconstructed volume and evaluation of the level of confidence and concordance between an experienced pediatric radiologist (obs1) and a junior radiologist (obs2)...

The human brain consists of specialized areas that flexibly interact to form a multitude of functional networks. Complementary to this notion of modular organization, brain function has been shown to vary along a smooth continuum across the whole cortex. We demonstrate a mathematical framework that accounts for both of these perspectives: harmonic...

The dynamic repertoire of functional brain networks is constrained by the underlying topology of structural connections: the lack of a direct structural link between two brain regions prevents direct functional interactions. Despite the intrinsic relationship between structural (SC) and functional connectivity (FC), integrative and multimodal appro...

Psychosis, characterized by hallucinations and delusions, is a common feature of psychiatric disease, especially schizophrenia. One prominent theory posits that psychosis is driven by abnormal sensorimotor predictions leading to the misattribution of self-related events. This misattribution has been linked to passivity experiences (PE), such as los...

We describe the multimodal neuroimaging dataset VEPCON (OpenNeuro Dataset ds003505). It includes raw data and derivatives of high-density EEG, structural MRI, diffusion weighted images (DWI) and single-trial behavior (accuracy, reaction time). Visual evoked potentials (VEPs) were recorded while participants (n=20) discriminated briefly presented fa...

Autism Spectrum Disorders are accompanied by atypical brain activity and impairments in brain connectivity. In particular, dynamic functional connectivity approaches highlighted aberrant brain fluctuations at rest in individuals with autism compared to a group composed of typically developed individuals, matched in age and gender. However, the char...

Supervised segmentation algorithms yield state-of-the-art results for automated anomaly detection. However, these models require voxel-wise labels which are time-consuming to draw for medical experts. An interesting alternative to voxel-wise annotations is the use of weak labels: these can be coarse or oversized annotations that are less precise, b...

The functional organization of neural processes is constrained by the brain's intrinsic structural connectivity. Here, we explore the potential of exploiting this structure in order to improve the signal representation properties of brain activity and its dynamics. Using a multi-modal imaging dataset (electroencephalography, structural MRI and diff...

An accurate evaluation and detection of awareness after a severe brain injury is crucial to a patient’s diagnosis, therapy, and end-of-life decisions. Misdiagnosis is frequent as behavior-based assessments often overlook subtle signs of consciousness. This study aimed to identify brain MRI characteristics of patients with residual consciousness aft...

Natural Language Processing (NLP) on electronic health records (EHRs) can be used to monitor the evolution of pathologies over time to facilitate diagnosis and improve decision-making. In this study, we designed an NLP pipeline to classify Magnetic Resonance Imaging (MRI) radiology reports of patients with high-grade gliomas. Specifically, we aimed...

A commonly adopted approach to carry out detection tasks in medical imaging is to rely on an initial segmentation. However, this approach strongly depends on voxel-wise annotations which are repetitive and time-consuming to draw for medical experts. An interesting alternative to voxel-wise masks are so-called “weak” labels: these can either be coar...

Most biological brains, as well as artificial neural networks, are capable of performing multiple tasks [1]. The mechanisms through which simultaneous tasks are performed by the same set of units are not yet entirely clear. Such systems can be modular or mixed selective through some variables such as sensory stimulus [2,3]. Based on simple tasks st...

The development of error monitoring is central to learning and academic achievement. However, few studies exist on the neural correlates of children’s error monitoring, and no studies have examined its susceptibility to educational influences. Pedagogical methods differ on how they teach children to learn from errors. Here, 32 students (aged 8–12 y...

A commonly adopted approach to carry out detection tasks in medical imaging is to rely on an initial segmentation. However, this approach strongly depends on voxel-wise annotations which are repetitive and time-consuming to draw for medical experts. An interesting alternative to voxel-wise masks are so-called "weak" labels: these can either be coar...

PurposeWe aimed at assessing the potential of automated MR morphometry to assess individual basal ganglia and thalamus volumetric changes at the chronic phase after cortical stroke.Methods Ninety-six patients (mean age: 65 ± 18 years, male 55) with cortical stroke at the chronic phase were retrospectively included. Patients were scanned at 1.5 T or...

The wiring of the brain is organized around a putative unimodal-transmodal hierarchy. Here we investigate how this intrinsic hierarchical organization of the brain shapes the transmission of information among regions. The hierarchical positioning of individual regions was quantified by applying diffusion map embedding to resting-state functional MR...

Signaling events in brain networks unfold over multiple topological scales. Areas may exchange information over local circuits, primarily encompassing direct neighbours and areas with similar functions. Alternatively, areas may exchange information over global circuits, encompassing more distant neighbours with increasingly dissimilar functions. In...

Relaxometry studies in preterm and at-term newborns have provided insight into brain microstructure, thus opening new avenues for studying normal brain development and supporting diagnosis in equivocal neurological situations. However, such quantitative techniques require long acquisition times and therefore cannot be straightforwardly translated t...

Significance The architecture of the human brain underlies human behavior and is extremely complex with multiple scales interacting with one another. However, research efforts are typically focused on a single spatial scale. We explored the spatial multiscale organization of the human brain by using two high-quality datasets with connectomes at fiv...

Recently, EEG recording techniques and source analysis have improved, making it feasible to tap into fast network dynamics. Yet, analyzing whole-cortex EEG signals in source space is not standard, partly because EEG suffers from volume conduction: Functional connectivity (FC) reflecting genuine functional relationships is impossible to disentangle...

Relaxometry studies in preterm and at-term newborns have provided insight into brain microstructure, thus opening new avenues for studying normal brain development and supporting diagnosis in equivocal neurological situations. However, such quantitative techniques require long acquisition times and therefore cannot be straightforwardly translated t...

The structural complexity of the thalamus, due to its mixed composition of gray and white matter, make it challenging to disjoint and quantify each tissue contribution to the thalamic anatomy. This work promotes the use of partial‐volume‐based over probabilistic‐based tissue segmentation approaches to better capture thalamic gray matter differences...

Objective Epilepsy diagnosis can be difficult in the absence of interictal epileptic discharges (IED) on scalp EEG. We used high-density EEG to measure connectivity in large‐scale functional networks of patients with focal epilepsy (Temporal and Extratemporal Lobe Epilepsy, TLE and ETLE) and tested for network alterations during resting wakefulness...

We present an approach for tracking fast spatiotemporal cortical dynamics in which we combine white matter connectivity data with source-projected electroencephalographic (EEG) data. We employ the mathematical framework of graph signal processing in order to derive the Fourier modes of the brain structural connectivity graph, or “network harmonics”...

A brief session of rightward prismatic adaptation (R-PA) has been shown to alleviate neglect symptoms in patients with right hemispheric damage, very likely by switching hemispheric dominance of the ventral attentional network (VAN) from the right to the left and by changing task-related activity within the dorsal attentional network (DAN). We have...

We present an approach for tracking fast spatiotemporal cortical dynamics in which we combine white matter connectivity data with source-projected electroencephalographic (EEG) data. We employ the mathematical framework of graph signal processing; in order to derive the Fourier modes of the brain structural connectivity graph, or "network harmonics...

Schizophrenia, as a psychiatric disorder, has recognized brain alterations both at the structural and at the functional magnetic resonance imaging level. The developing field of connectomics has attracted much attention as it allows researchers to take advantage of powerful tools of network analysis in order to study structural and functional conne...

Background In general, MR spectroscopy (MRS) studies report alterations of both glutamatergic indices and NAA not only in first episode psychosis and established schizophrenia but also in high risk populations, suggesting that altered excitatory neurotransmission and loss of neuronal integrity are early pathophysiological processes. However, interp...

Background The ability to recognize whether sensory consequences have been self-generated or externally produced is an important element of motor control and self-monitoring. Deficits in self-monitoring have been proposed to cause abnormal bodily experiences and psychotic symptoms such as hallucinations. A recent study designed a robotic system tha...

Background Very preterm (VPT) infants are at risk for neurodevelopmental impairments and early clinical findings such as transient tone anomalies (TTA) might represent potential predictive indicators. Aims The aims of this study were to assess 1) the prevalence of TTA at 6 months corrected age in a population of VPT infants, 2) the association wit...

The wiring of the brain is organized around a putative unimodal-transmodal hierarchy. Here we investigate how this intrinsic hierarchical organization of the brain shapes the transmission of information among regions. The hierarchical positioning of individual regions was quantified by applying diffusion map embedding to resting state functional MR...

Dysfunction of sensorimotor predictive processing is thought to underlie abnormalities in self-monitoring producing passivity symptoms in psychosis. Experimentally induced sensorimotor conflict can produce a failure in bodily self-monitoring (presence hallucination [PH]), yet it is unclear how this is related to auditory self-monitoring and psychos...

Late human development is characterized by the maturation of high-level functional processes, which rely on reshaping of white matter connections, as well as synaptic density. However, the relationship between the whole-brain dynamics and the underlying white matter networks in neurodevelopment is largely unknown. In this study, we focused on how t...

Through performance monitoring individuals detect and learn from unexpected outcomes, indexed by post‐error slowing and post‐error improvement in accuracy. Although performance monitoring is essential for academic learning and improves across childhood, its susceptibility to educational influences has not been studied. Here we compared performance...

Studies have shown scholastic, creative, and social benefits of Montessori education, benefits that were hypothesized to result from better executive functioning on the part of those so educated. As these previous studies have not reported consistent outcomes supporting this idea, we therefore evaluated scholastic development in a cross-sectional s...