Edouard Duchesnay

Atomic Energy and Alternative Energies Commission | CEA · NeuroSpin Research Centre (NeuroSpin)

Decoding states of consciousness from brain activity is a central challenge in neuroscience. Dynamic functional connectivity (dFC) allows the study of short-term temporal changes in functional connectivity (FC) between distributed brain areas. By clustering dFC matrices from resting-state fMRI, we previously described “brain patterns” that underlie...

Functional connectivity (FC) of resting-state fMRI time series can be estimated using methods that differ in their temporal sensitivity (static vs. dynamic) and the number of regions included in the connectivity estimation (derived from a prior atlas). This paper presents a novel framework for identifying and quantifying resting-state networks usin...

Background Treatment resistance is a major challenge in psychiatric disorders. Early detection of potential future resistance would improve prognosis by reducing the delay to appropriate treatment adjustment and recovery. Here, we sought to determine whether neurodevelopmental markers can predict therapeutic response. Methods Healthy controls (N =...

Background and Hypothesis : While age at onset in schizophrenia (SCZ) is usually defined by age at onset of psychosis, the illness actually occurs earlier, with a prodrome often starting in childhood or adolescence. We postulated that SCZ with early-adolescence prodromes (SCZ-eaP) presents with social cognition deficits and sensorimotor impairments...

Introduction Early focal brain injuries lead to long-term disabilities with frequent cognitive impairments, suggesting global dysfunction beyond the lesion. While plasticity of the immature brain promotes better learning, outcome variability across individuals is multifactorial. Males are more vulnerable to early injuries and neurodevelopmental dis...

The cerebellum has been involved in social abilities and autism. Given that the cerebellum is connected to the cortex via the cerebello‐thalamo‐cortical loop, the connectivity between the cerebellum and cortical regions involved in social interactions, that is, the right temporo‐parietal junction (rTPJ) has been studied in individuals with autism,...

Background : Treatment resistance is a major challenge in psychiatric disorders. Early detection of potential future resistance would improve prognosis by reducing the delay to appropriate treatment adjustment and recovery. Here, we sought to determine whether neurodevelopmental markers can predict therapeutic response. Methods : Healthy controls (...

Background The neurobiology of autism remains poorly understood. Brain sulcation is a promising proxy to assess the cortical developmental trajectory in autism spectrum disorders. We aimed to explore this neurodevelopmental marker in children with autism and its association with symptoms in a large multicentric dataset. Methods 841 children with a...

Purpose: The hippocampus is organized in subfields (HSF) involved in learning and memory processes and widely implicated in pathologies at different ages of life, from neonatal hypoxia to temporal lobe epilepsy or Alzheimer's disease. Getting a highly accurate and robust delineation of sub-millimetric regions such as HSF to investigate anatomo-fun...

Post-traumatic stress disorder (PTSD) can affect family members of patients admitted to the intensive care unit (ICU). Easily accessible patient’s and relative’s information may help develop accurate risk stratification tools to direct relatives at higher risk of PTSD toward appropriate management. PTSD was measured 90 days after ICU discharge usin...

Aim: Neuroimaging-based machine-learning predictions of psychosis onset rely on the hypothesis that structural brain anomalies may reflect the underlying pathophysiology. Yet, current predictors remain difficult to interpret in light of brain structure. Here, we combined an advanced interpretable supervised algorithm and a model of neuroanatomical...

Learning biological markers for a specific brain pathology is often impaired by the size of the dataset. With the advent of large open datasets in the general population, new learning strategies have emerged. In particular, deep representation learning consists of training a model via pretext tasks that can be used to solve downstream clinical prob...

Over the last few years, an increasing amount of brain data has been collected. In addition, in recent years there has been easier access to scanners in hospitals and research laboratories, allowing large-scale research on certain neurological diseases and human behaviors to be conducted. The current challenge is that there is large inter-site vari...

Contrastive Analysis VAE (CA-VAEs) is a family of Variational auto-encoders (VAEs) that aims at separating the common factors of variation between a background dataset (BG) (i.e., healthy subjects) and a target dataset (TG) (i.e., patients) from the ones that only exist in the target dataset. To do so, these methods separate the latent space into a...

The hippocampal subfields, pivotal to episodic memory, are distinct both in terms of cyto- and myeloarchitectony. Studying the structure of hippocampal subfields in vivo is crucial to understand volumetric trajectories across the lifespan, from the emergence of episodic memory during early childhood to memory impairments found in older adults. Howe...

Background and hypothesis: The emergence of psychosis in ultra-high-risk subjects (UHR) is influenced by gene-environment interactions that rely on epigenetic mechanisms such as microRNAs. However, whether they can be relevant pathophysiological biomarkers of psychosis' onset remains unknown. Study design: We present a longitudinal study of micr...

In fetal alcohol spectrum disorders (FASD), brain growth deficiency is a hallmark of subjects both with fetal alcohol syndrome (FAS) and with non-syndromic FASD (NS-FASD, i.e., those without specific diagnostic features). However, although the cerebellum was suggested to be more severely undersized than the rest of the brain, it has not yet been gi...

Background The cerebellum contains more than 50% of all neurons in the brain and is involved in a broad range of cognitive functions, including social communication and social cognition. Inconsistent atypicalities in the cerebellum have been reported in individuals with autism compared to controls suggesting the limits of categorical case control c...

Background. The cerebellum contains more than 50% of all neurons in the brain and is involved in a broad range of cognitive functions, including social communication and social cognition. Inconsistent atypicalities in the cerebellum have been reported in individuals with autism compared to controls suggesting the limits of categorical case control...

Building accurate Deep Learning (DL) models for brain age prediction is a very relevant topic in neuroimaging, as it could help better understand neurodegenerative disorders and find new biomarkers. To estimate accurate and generalizable models, large datasets have been collected, which are often multi-site and multi-scanner. This large heterogenei...

Prediction of chronological age from neuroimaging in the healthy population is an important issue because the deviations from normal brain age may highlight abnormal trajectories towards brain disorders. As a first step, ML models have emerged to predict chronological age from brain MRI, as a proxy measure of biological age. However, there is curre...

Data augmentation is a crucial component in unsupervised contrastive learning (CL). It determines how positive samples are defined and, ultimately, the quality of the representation. While efficient augmentations have been found for standard vision datasets, such as ImageNet, it is still an open problem in other applications, such as medical imagin...

Brain anomalies are frequently found in early psychoses. Although they may remain undetected for many years, their interpretation is critical for differential diagnosis. In secondary psychoses, their identification may allow specific management. They may also shed light on various pathophysiological aspects of primary psychoses. Here we reviewed ca...

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...

BACKGROUND Functional magnetic resonance imaging (fMRI) capture aims at detecting auditory-verbal hallucinations (AVHs) from continuously recorded brain activity. Establishing efficient capture methods with low computational cost that easily generalize between patients remains a key objective in precision psychiatry. To address this issue, we devel...

Contrastive Learning has shown impressive results on natural and medical images, without requiring annotated data. However, a particularity of medical images is the availability of meta-data (such as age or sex) that can be exploited for learning representations. Here, we show that the recently proposed contrastive y-Aware InfoNCE loss, that integr...

Background: Brain development is of utmost importance for the emergence of psychiatric disorders, as the most severe of them arise before 25 years old. However, little is known regarding how early transdiagnostic symptoms, in a dimensional framework, are associated with cortical development. Anxiety and irritability are central vulnerability traits...

Traditional supervised learning with deep neural networks requires a tremendous amount of labelled data to converge to a good solution. For 3D medical images, it is often impractical to build a large homogeneous annotated dataset for a specific pathology. Self-supervised methods offer a new way to learn a representation of the images in an unsuperv...

Subtype Discovery consists in finding interpretable and consistent sub-parts of a dataset, which are also relevant to a certain supervised task. From a mathematical point of view, this can be defined as a clustering task driven by supervised learning in order to uncover subgroups in line with the supervised prediction. In this paper, we propose a g...

Subtype Discovery consists in finding interpretable and consistent sub-parts of a dataset, which are also relevant to a certain supervised task. From a mathematical point of view, this can be defined as a clustering task driven by supervised learning in order to uncover subgroups in line with the supervised prediction. In this paper, we propose a g...

Traditional supervised learning with deep neural networks requires a tremendous amount of labelled data to converge to a good solution. For 3D medical images, it is often impractical to build a large homogeneous annotated dataset for a specific pathology. Self-supervised methods offer a new way to learn a representation of the images in an unsuperv...

Deep Learning (DL) and specifically CNN models have become a de facto method for a wide range of vision tasks, outperforming traditional machine learning (ML) methods. Consequently, they drew a lot of attention in the neuroimaging field in particular for phenotype prediction or computer-aided diagnosis. However, most of the current studies often de...

BACKGROUND Functional magnetic resonance imaging (fMRI) capture aims at detecting auditory-verbal hallucinations (AVHs) from continuously recorded brain activity. Establishing efficient capture methods with low computational cost that easily generalize between patients remains a key objective in precision psychiatry. To address this issue, we devel...

To improve the prediction of the individual risk of conversion to psychosis in UHR subjects, by considering all CAARMS’ symptoms at first presentation and using a multivariate machine learning method known as logistic regression with Elastic-net shrinkage. 46 young individuals who sought help from the specialized outpatient unit at Sainte-Anne hosp...

La moitié des maladies psychiatriques se manifeste avant l’âge de 14 ans, et les trois quarts avant 24 ans, suggérant que l’enfance, l’adolescence, et le début de l’âge adulte sont des fenêtres de grande fragilité aux troubles mentaux. La schizophrénie survient ainsi à l’adolescence tardive chez des individus à risque, repérables cliniquement, et d...

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal app...

MRI‐derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta‐Analysis (ENIGMA) Bipolar Disorder...

Background Lithium (Li) is a first line treatment for bipolar disorders (BD). In order to study its cerebral distribution and association with plasmatic concentrations, we used ⁷Li MRI at 7T in euthymic patients with BD treated with Li carbonate for at least 2 years. Methods 3D ⁷Li MRI (n=21) were acquired using an ultra-short echo-time sequence u...

Objectives: The existence of anatomo-functional brain abnormalities in Bipolar Disorder (BD) is now well established by magnetic resonance imaging (MRI) studies. To create diagnostic and prognostic tools, as well as identifying biologically valid subtypes of BD, research has recently turned towards the use of machine learning (ML) techniques. We a...

Huntington's disease (HD) is an inherited, autosomal dominant disorder that is characteristically thought of as a degenerative disorder. Despite cellular and molecular grounds suggesting HD could also impact normal development, there has been scarce systems-level data obtained from in vivo human studies supporting this hypothesis. Sulcus-specific m...

Background Lithium (Li) is the gold standard treatment for bipolar disorder (BD). However, its mechanisms of action remain unknown but include neurotrophic effects. We here investigated the influence of Li on cortical and local grey matter (GM) volumes in a large international sample of patients with BD and healthy controls (HC). Methods We analyz...

Although bipolar disorder (BD) is a relatively frequent, severe and disabling disease, we still lack reliable diagnostic tools. The existence of anatomo-functional brain abnormalities in BD is now well established by MRI studies [1]. Machine learning allows individual level analysis and could potentially lead to diagnostic applications [2]. This is...

Background: Lithium is recommended as a first line treatment for bipolar disorders. However, only 30% of patients show an optimal outcome and variability in lithium response and tolerability is poorly understood. It remains difficult for clinicians to reliably predict which patients will benefit without recourse to a lengthy treatment trial. Great...

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities th...

Objective: The cerebellum is involved in cognitive processing and emotion control. Cerebellar alterations could explain symptoms of schizophrenia spectrum disorder (SZ) and bipolar disorder (BD). In addition, literature suggests that lithium might influence cerebellar anatomy. Our aim was to study cerebellar anatomy in SZ and BD, and investigate t...

Autism spectrum disorder (ASD) is a developmental disorder underdiagnosed in adults. To date, no consistent evidence of alterations in brain structure has been reported in adults with ASD and few studies were conducted at that age. We analyzed structural magnetic resonance imaging data from 167 high functioning adults with ASD and 195 controls. We...

Robust spatial alignment of post mortem data and in vivo MRI acquisitions from different ages, especially from the early developmental stages, into standard spaces is still a bottleneck hampering easy comparison with the mainstream neuroimaging results. In this paper, we test a landmark-based spatial normalization strategy as a framework for the se...

Les hallucinations fascinent depuis les débuts de l’humanité, mais ce n’est que depuis quelques décennies seulement que leur exploration par les outils des neurosciences a été possible et a permis de mieux comprendre les bases neurales de ces expériences. Cette présentation est l’occasion de reprendre l’état de l’art en matière d’imagerie cérébrale...

L’adolescence est une période de vulnérabilité qui peut s’exprimer sous forme de Symptômes Psychotiques Atténués (SPA) et/ou de Comportements Suicidaires (CS). Les objectifs sont de déceler la nature, l’intensité et la fréquence des SPA dans une population d’adolescents reçus en urgence puis d’établir quels SPA sont subjectivement pourvoyeurs de CS...

A very active field of research in Bioinformatics is to integrate structure in Machine Learning methods. Methods recently developed claim that they allow simultaneously to link the computed model to the graphical structure of the data set and to select a handful of important features in the analysis. However, there is still no way to simulate data...

Objective: Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizophrenia. Previous machine learning applications suggest that individual classification is feasible and reliable and, however, is focused on the predictive performance of the clinical status in cross‐sectional designs, which has limited biological persp...

Objective: In CADASIL (Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy), white matter hyperintensities (WMH) are considered to result from hypoperfusion. We hypothesized that in fact the burden of WMH results from the combination of several regional populations of WMH with different mechanisms and clinical...

As an effective but poorly understood treatment for the prevalent bipolar disorder, studies focused on investigating the cerebral distribution of lithium are of important clinical interest. Here, we report our preliminary results obtained from 5 euthymic bipolar patients using 7Li MRI at 7T. Using a 3D SSFP sequence with ultra-short TE and Twisted...