2023Activity reportProject-TeamEMPENN

4.1.1 Population imaging

One major objective of neuroimaging researchers and clinicians is to be able to stratify brain imaging data in order to derive new and more specific population models. In practice, this requires to set up large-scale experiments that, due to the lack of resources and capabilities to recruit locally subjects who meet specific inclusion criteria, motivates the need for sharing the load.

However, building and using multi-site large-scale resources pose specific challenges to deal with the huge quantity of data produced and their diversity. Empenn focuses on two challenges in particular:

• Providing computational environments for the computation and use of imaging biomarkers in the targeted brain diseases, a solution to be used by radiologists and neurologists/psychiatrists for the clinical follow-up of a large patient population.
• Modeling analytic variability of image processing pipelines to better understand and predict the behaviour of imaging biomarker detection solutions and improve reproducibility and productivity in clinical neuroimaging research.

4.1.2 Detection and learning

We intend to make significant contributions with major impacts in learning coupling models between functional recordings during neurofeedback procedures. These advances will provide a breakthrough in brain-computer interfaces for rehabilitation protocols. Our aim is to:

• Our research employs data-driven approaches, encompassing machine learning and deep learning, to enhance the detection and segmentation of abnormal patterns in medical images. Our primary focus is on multiple sclerosis (MS) and, more recently, on stroke. The findings from our studies indicate promising outcomes in automated tools for accurate disease activity assessment and lesion segmentation within large MRI databases. Special attention is given to the integration of multimodal information and the utilization of labeled and unlabeled data. As we progress, our aim is to adapt these methods to address a broader range of neurological diseases, including epilepsy, tumors, etc., in both neonate and adult brains. This research contributes to advancing diagnostic tools and methodologies in the field of medical imaging.
• Develop solutions for combining brain state measurements from multimodal sensors or sequences (e.g. fMRI, ASL, EEG, NIRS, etc.) with applications in the spatiotemporal reconstruction of brain activity from MRI-EEG or the combined detection of the endogenous hemodynamic and resting state network of the brain from ASL and NIRS. Over the longer term, the advent of new hybrid brain imaging sensors (e.g. PET-MRI) will require these methods to be extended to a larger spectrum of information combining structural, morphological, metabolic, electrophysiological and cellular/molecular information (e.g. through the use of specific ligands/nanocarriers).

4.1.3 Quantitative imaging

The Empenn research group focuses on the development of several quantitative techniques in magnetic resonance imaging of the brain. These methods allow for characterization of both the function and the structure of the brain with high precision. Arterial spin labelling (ASL) is a contrast agent-free imaging technique which labels arterial blood water as an endogenous tracer for perfusion and can measure resting-state cerebral blood flow. We are interested in estimating multiparametric hemodynamics using ASL, such as combined cerebral blood flow and arterial transit times, and derive statistical descriptors to represent significant differences between groups. In addition to quantitative perfusion parameters, our contributions on tissue compartment imaging aim at delineating neural circuits and characterize their microstructure properties, using both diffusion MRI and relaxometry. In diffusion MRI, arbitrary gradient waveforms were shown to exhibit higher sensitivity to microstructure parameters than standard pulsed gradients. We work on the optimization of sampling protocols in this domain, with the objective to propose sequences compatible with in vivo acquisition. Complementary to diffusion MRI, we develop methods for the reconstruction of myelin-bound, extra-axonal and cerebrospinal fluid water using multi-compartment modelling of the T2-relaxometry signal. We combine these techniques with tractography to identify trajectories of pathologies associated to the evolution of these microstructural parameters along specific fiber bundles in the brain white matter. Finally, we are also focusing on assessing the characteristics (repeatability, reproducibility and sensitivity) of several quantitative metrics variability (e.g. MTR, T1 relaxometry) in the spinal cord of patients with MS.

4.2.1 Behavior

Advances in the field of in vivo imaging offer new opportunities for addressing the management of resistant affective disorders and their consequences (suicide risk and socio-professional impact), and the management of spatial cognition disorders after stroke and their consequences (postural perturbations and the loss of autonomy). Our objective, and the main challenge in this context, is to introduce medical image computing methods to the multidisciplinary field of behavioral disorders (cognitive disorders, particularly spatial and postural control disorders or anterograde memory impairment, mood disorders, notably resistant depression, schizophrenic disorders, pervasive developmental disorders, attention disorders, etc.) in order to gain a better understanding of the pathology and devise innovative therapeutic approaches.

We also expect to become a major player in the future and make important contributions with significant impacts, primarily in drug-resistant depression in young and old populations. In particular, we expect to provide new image-related metrics combining perfusion, metabolism and microstructural information regarding the brain in order to better characterize pathologies, provide prospective evolution values and potentially provide new brain stimulation targets that could be used in neurofeedback rehabilitation protocols or other types of brain stimulation procedures.

We aim to provide new imaging markers of mental diseases, especially in the context of mood disorders. The new biomarkers are derived from the metabolic (ASL and later ASL+PET) point of view as well as from the microstructural point of view (multicompartment diffusion MRI and relaxometry). Similarly, we expect to exhibit imaging biomarker regularities combining metabolic and structural information. Over the longer term, we expect these biomarkers to be the target of neurofeedback rehabilitation procedures. Also, over the longer term, we expect to supplement the MRI markers with molecular markers coming from new PET tracers, especially those associated with serotonin intake, at one time point or during a rehabilitation protocol under hybrid PET-EEG-MRI neurofeedback procedures.

4.2.2 Neuroinflammation

Some of the major ongoing research issues regarding neuroimaging of neuro-inflammatory diseases concern the definition of new biomarkers to track the development of the pathology using high- dimensional data (e.g. nD+t MRI). This includes the use of white matter-specific imaging, such as magnetization transfer MRI, relaxometry and diffusion-weighted imaging (DW-MRI). Our objective is (1) to develop information-processing tools to tag the spatiotemporal evolutions of Multiple Sclerosis patterns at the brain parenchyma and spinal cord levels from their different signatures (inflammatory cells visible with USPIO or Gd contrast agents on MRI, persistent black holes, eloquent regional atrophy and microstructure signatures); and (2) to test these new tools on new imaging cohorts. In this respect, we for instance conduct studies on brain and spinal cord imaging, continuing on from the PHRC multicentric EMISEP project (PI: G. Edan), as it is very likely that lesions in the spine will directly affect the ambulatory ability of the patient (and thereby the clinical scores). In order to extend this experiment to a larger MS population, based on our expertise from the OFSEP cohort, we also plan to improve the MS therapeutic decision process notably through the RHU PRIMUS (PRojection In MUltiple Sclerosis) project (PI: G. Edan). Our goal is to develop and assess a standardized monitoring tool that provides a robust, long-term computerized MRI follow-up that will become the gold standard in clinical practice for therapeutic decisions in MS treatment. As part of this project, Empenn will share its expertise in data management systems (Shanoir and FLI-IAM), automatic processing tools (through the medInria and Anima software repositories) to extract quantitative indices from the images and the assessment of the added-value of promising quantitative sequences.

4.2.3 Recovery

Mental and neurological disorders are the leading cause of years lived with a disability. Treatment-resistant depression affects approximately 2% of the European population. Meanwhile, in the case of brain disorders, almost 1.5 million Europeans (15 million people worldwide) suffer a stroke event each year. Current recovery methods for brain disorders and traumatic brain injuries remain limited, preventing many from achieving full recuperation. We propose to address the issue of brain recovery by introducing new advances from recent breakthroughs in computational medical imaging, data processing and human-machine interfaces, and demonstrate how these new concepts can be used, in particular for the treatment of stroke and major depressive disorders.

We ambition to combine advanced instrumental devices (hybrid EEG, NIRS and MRI platforms), with new hybrid brain computer interface paradigms and new computational models to provide neurofeedback-based therapeutic and neuro-rehabilitation paradigms in some of the major mental and neurological disorders of the developmental and aging brain.

Neurofeedback involves using a brain-computer interface that provides an individual with real-time biofeedback about his or her brain activity in the form of sensory feedback. It enables individuals to learn to better control their brain activity, which can be measured in real time using various non-invasive sensors as described above. Although EEG is currently the only modality used by clinical practitioners in that context, it lacks specificity due to its low spatial resolution. Dynamic research into fMRI-neurofeedback has held promise for treating depression, chronic pain and stroke, since it offers the prospect of real-time imagery of the activity in deep brain structures with high spatial resolution. However, the low temporal resolution and high cost of fMRI-neurofeedback has hampered the development of many applications. We believe that the future belongs to hybrid responses that combine multimodal sensors and intend to demonstrate this in the Empenn project.

7.1.1 Anima

• Keywords:
  Medical imaging, Neuroimaging, Image processing
• Scientific Description:
  Anima is a set of libraries and tools developed by the team as a common repository of research algorithms. As of now, it contains tools for image registration, statistical analysis (group comparison, patient to group comparison), diffusion imaging (model estimation, tractography, etc.), quantitative MRI processing (quantitative relaxation times estimation, MR simulation), image denoising and filtering, and segmentation tools. All of these tools are based on stable libraries (ITK, VTK), making it simple to maintain.
• Functional Description:
  Anima is a set of libraries and tools in command line mode for processing and analysing medical images.
• URL:
  https://­anima.­irisa.­fr
• Contact:
  Julie Coloigner
• Participants:
  Aymeric Stamm, Fang Cao, Florent Leray, Guillaume Pasquier, Laurence Catanese, Olivier Commowick, Renaud Hedouin, René-Paul Debroize

7.1.2 MedINRIA

• Keywords:
  Visualization, DWI, Health, Segmentation, Medical imaging
• Scientific Description:
  MedInria aims at creating an easily extensible platform for the distribution of research algorithms developed at Inria for medical image processing. This project has been funded by the D2T (ADT MedInria-NT) in 2010, renewed in 2012. A fast-track ADT was awarded in 2017 to transition the software core to more recent dependencies and study the possibility of a consortium creation.The Empenn team leads this Inria national project and participates in the development of the common core architecture and features of the software as well as in the development of specific plugins for the team's algorithm.
• Functional Description:
  MedInria is a free software platform dedicated to medical data visualization and processing.
• URL:
  https://­med.­inria.­fr
• Contact:
  Florent Leray
• Participants:
  Maxime Sermesant, Olivier Commowick, Théodore Papadopoulo
• Partners:
  HARVARD Medical School, IHU - LIRYC, NIH

7.1.3 autoMRI

• Keywords:
  FMRI, MRI, ASL, FASL, SPM, Automation
• Scientific Description:
  This software is highly configurable in order to fit a wide range of needs. Pre-processing includes segmentation of anatomical data, as well as co-registration, spatial normalization and atlas building of all data types. The analysis pipelines perform either within-group analysis or between-group or one subject-versus-group comparison, and produce statistical maps of regions with significant differences. These pipelines can be applied to structural data to exhibit patterns of atrophy or lesions, to ASL (both pulsed or pseudo-continuous sequences) data to detect perfusion abnormalities, to functional data - either BOLD or ASL - to outline brain activations related to block or event-related paradigms. New functionalities have been implemented to facilitate the management and processing of data coming from complex projects.
• Functional Description:
  AutoMRI is based on MATLAB and the SPM12 toolbox and provides complete pipelines to pre-process and analyze various types of images (anatomical, functional, perfusion).
• URL:
  https://­team.­inria.­fr/­visages/­software/
• Contact:
  Isabelle Corouge
• Participants:
  Camille Maumet, Elise Bannier, Isabelle Corouge, Pierre Maurel, Quentin Duché, Julie Coloigner

7.1.4 ShanoirUploader

• Name:
  ShanoirUploader (SHAring NeurOImaging Resources Uploader)
• Keywords:
  Webservices, PACS, Medical imaging, Neuroimaging, DICOM, Health, Biology, Java, Shanoir
• Scientific Description:
  ShanoirUploader is a desktop application on base of JavaWebStart (JWS). The application can be downloaded and installed using an internet browser. It interacts with a PACS to query and retrieve the data stored on it. After this ShanoirUploader sends the data to a Shanoir server instance in order to import these data. This application bypasses the situation, that in most of the clinical network infrastructures a server to server connection is complicated to set up between the PACS and a Shanoir server instance.
• Functional Description:
  ShanoirUploader is a Java desktop application that transfers data securely between a PACS and a Shanoir server instance (e.g., within a hospital). It uses either a DICOM query/retrieve connection or a local CD/DVD access to search and access images from a local PACS or the local CD/DVD. After having retrieved the data, the DICOM files are locally anonymized and then uploaded to the Shanoir server. A possible integration of a hash creation application for patient identifiers is provided as well. The primary goals of that application are to enable mass data transfers between different remote server instances and therefore reduce the waiting time of the users, when importing data into Shanoir. Most of the time during import is spent with data transfers.
• URL:
  https://­github.­com/­fli-iam/­shanoir-ng/­wiki/­ShanoirUploader
• Contact:
  Michael Kain
• Participants:
  Christian Barillot, Inès Fakhfakh, Justine Guillaumont, Michael Kain, Yao Chi

7.1.5 Shanoir-NG

• Name:
  Shanoir-NG (SHAring iN vivO Imaging Resources - Next Generation)
• Keyword:
  Medical imaging
• Functional Description:

  Shanoir-NG (SHAring iN vivO Imaging Resources - Next Generation) is an open-source web platform designed to share, archive, search and visualize medical imaging data. It provides an user-friendly secure web access and offers an intuitive workflow to facilitate the collecting and retrieving of imaging data from multiple sources. Quality control can be applied on imported data. Mass data can be downloaded in multiple ways, via the web interface and via a Python script.

  It supports the following formats: DICOM classic/enhanced (MR, CT, PT, NM), BIDS, processed datasets (NIfTI), Bruker, EEG(BrainVision/EDF).

  Shanoir-NG comes along many features such as pseudonymization of data (based on DICOM standard profiles), support for multi-centric clinical studies on subjects. Shanoir-NG offers an ontology-based data organization (OntoNeuroLOG). Among other things, this facilitates the reuse of data and metadata, the integration of processed data and provides traceability trough an evolutionary approach. Shanoir-NG allows researchers, clinicians, PhD students and engineers to undertake quality research projects with an emphasis on remote collaboration. Data user agreements (DUA) can be configured by study to be accepted by each accessing users and access requests can be initated to study administrators.

• Release Contributions:
  Quality control
• URL:
  https://­github.­com/­fli-iam/­shanoir-ng
• Contact:
  Michael Kain
• Participants:
  Michael Kain, Anthony Baire, Julien Louis, Jean-cÔme Douteau, Pierre-henri Dauvergne, Arthur Masson, Youenn Merel

7.1.6 LongiSeg4MS

• Name:
  Longitudinal Segmentation For Multiple Sclerosis
• Keywords:
  3D, Brain MRI, Deep learning, Detection
• Functional Description:
  LongiSeg4MS is an automatic new multiple sclerosis (MS) lesion detection tool based on longitudinal data and using deep learning. The system uses FLAIR, T1 or T2 modalities, or a combination of those. The input is 2, 4 or 6 images (2 FLAIR, 2 FLAIR and 2 T1, etc.), a set of modalities for each time point, and outputs a segmentation map describing the location of new MS lesions.
• URL:
  https://­gitlab.­inria.­fr/­amasson/­longiseg4ms
• Authors:
  Arthur Masson, Brandon Le Bon, Benoit Combes
• Contact:
  Arthur Masson
• Partner:
  OFSEP

7.1.7 Anima medInria plugins

• Keywords:
  IRM, Medical imaging, Diffusion imaging
• Functional Description:
  Plugins for the medInria software based on the open source software Anima developed in the Visages / Empenn team. These plugins are interfaces between anima and medinria allowing to use Anima functionalities within the clinical user interface provided by medInria. The current functionalities included in the plugins are right now: image registration, denoising, quantitative imaging (relaxometry), and model estimation and visualization from diffusion imaging.
• URL:
  https://­github.­com/­medInria/­medInria-visages
• Contact:
  Florent Leray
• Participants:
  Olivier Commowick, Florent Leray, René-Paul Debroize, Guillaume Pasquier

7.2.1 The Neurinfo Platform

Participants: Elise Bannier, Emmanuel Caruyer, Isabelle Corouge, Quentin Duché, Jean-Christophe Ferré, Jean-Yves Gauvrit, Nolwenn Jégou.

Empenn is the founding actor of an experimental research platform which was installed in August 2009 at the University Hospital of Rennes. The University of Rennes 1, Inria, CNRS for the academic side, and the University Hospital of Rennes and the Cancer Institute “Eugene Marquis” for the clinical side, are partners of this neuroinformatics platform called Neurinfo (Neurinfo website). Concerning the Neurinfo Platform, the activity domain is a continuum between methodological and technological research built around specific clinical research projects. On the medical field, the translational research domain mainly concerns medical imaging and more specifically the clinical neurosciences. Among them are multiple sclerosis, epilepsy, neurodegenerative, neurodevelopmental and psychiatric diseases, surgical procedures of brain lesions, neuro-oncology and radiotherapy planning. Beyond these central nervous system applications, the platform is also open to alternative applications. Neurinfo ambitions to support the emergence of research projects based on their level of innovation, their pluri-disciplinarity and their ability to foster collaborations between different actors (public and private research entities, different medical specialties, different scientific profiles). In this context, a research 3T MRI system (Siemens Verio) was acquired in summer 2009 in order to develop the clinical research in the domain of morphological, functional, structural and cellular in-vivo imaging. A new 3T Siemens Prisma MRI scanner was installed at the Neuroinfo platform in February 2018. In 2014, an equipment for simultaneous recording of EEG and MRI images was acquired from Brain Product. In 2015, a mock scanner for experimental set-up was acquired as well as a High Performance Computing environment made of one large computing cluster and a data center that is shared and operated by the Inria center and IRISA (UMR CNRS 6074). The computation cluster (480 cores) and the data center (up to 150 TB) are dedicated to host and process imaging data produced by the Neurinfo platform, but also by other research partners that share their protocols on the Neurinfo neuroinformatics system (currently more than 60 sites). In 2019, an MRI and EEG-compatible fNIRS system was acquired through a co-funding from the INS2I institute of CNRS and FEDER. At the end of 2019, GIS IBISA awarded the Neurinfo platform with a complementary funding that will be dedicated to supplement the current system with additional sensors (from 8x8 optodes to 16x16 optodes). In 2022, the Regional Council of Britanny funding was renewed to provide engineer support for another year to develop and integrate this new imaging system.

The HCP multi-pipeline dataset: an opportunity to investigate analytical variability in fMRI data analysis

Participants: Elodie Germani, Pierre Maurel, Camille Maumet.

Results of functional Magnetic Resonance Imaging (fMRI) studies can be impacted by many sources of variability including differences due to: the sampling of the participants, differences in acquisition protocols and material but also due to different analytical choices in the processing of the fMRI data. While variability across participants or across acquisition instruments have been extensively studied in the neuroimaging literature the root causes of analytical variability remain an open question. Here, we share the HCP multi-pipeline dataset, including the resulting statistic maps for 24 typical fMRI pipelines on 1,080 participants of the HCP-Young Adults dataset. We share both individual and group results - for 1,000 groups of 50 participants - over 5 motor contrasts. We hope that this large dataset covering a wide range of analysis conditions will provide new opportunities to study analytical variability in fMRI. 56. This work was done in collaboration with Prof. Elisa Fromont from the LACODAM team.

8.1.1 Population imaging

Population imaging is fundamental when it comes to evaluate clinical biomarkers. In this section we summarise our contributions over the last year to this theme. We studied how analytical variability can impact fMRI results and proposed recommendations and neuroinformatics models to describe the data. We also maintained our clinical interest regarding several pathologies by exploring brain function and connectivity. Also, technical recommendations regarding multicentric imaging protocols were proposed.

8.1.2 Detection and learning

Expert variability and deep learning performance in spinal cord lesion segmentation for multiple sclerosis patients.

Participants: Ricky Walsh, Cédric Meurée, Anne Kerbrat, Arthur Masson, Burhan Rashid Hussein, Malo Gaubert, Francesca Galassi, Benoît Combès.

Multiple sclerosis (MS) patients often present with lesions in spinal cord magnetic resonance (MR) volumes. However, accurately detecting these lesions is challenging and prone to inter-and intra-rater variability. Deep learning-based methods have the potential to aid clinicians in detecting and segmenting MS lesions, but can also be affected by rater variability. In this work 50, we assessed the inter-and intra-rater variability in manual segmentation of spinal cord lesions, and evaluated raters and a state-of-the-art nnU-Net model against a ground truth (GT) segmentation of a senior expert. Four experts segmented twelve spinal cord MR volumes from six patients twice, at a time distance of two weeks. Considerable inter-and intra-rater variability were observed, with the total number of detected lesions ranging from 28 to 60, depending on the rater. An example of lesion is depicted in Figure 3. Moreover, the segmented volumes of individual lesions varied substantially between raters. All raters and the model achieved high precision when evaluated against the senior expert GT, but sensitivity was notably lower. These results motivate the need for more sensitive automated methods to aid clinicians in lesion detection, and suggest that consideration should be given to inter-rater variability when training and evaluating automated methods.

Illustration of the low contrast of MS spinal cord lesions and of the resulting discrepancy between experts annotations

A study on loss functions and decision thresholds for the segmentation of multiple sclerosis lesions on spinal cord MRI.

Participants: Burhan Rashid Hussein, Cédric Meurée, Malo Gaubert, Arthur Masson, Anne Kerbrat, Benoît Combès, Francesca Galassi.

Multiple sclerosis (MS) patients often present hyper-intense T2-w lesions in the spinal cord. The severe imbalance between background and lesion classes poses a major challenge to Deep Learning segmentation approaches, requiring for ad hoc strategies. Careful selection of the loss function and adjustment of the conventional 0.5-thresholding may help mitigating this issue. In this work 47, 67, we showed the performance advantages of loss functions based on the Tversky Index and the benefits of threshold tuning over more standard settings and the state-of-the-art model for MS lesion segmentation on spinal cord MRI (Figure 4).

Boxplots illustrating the stablility of the F1 score when changing the softmax threshold values for the Tversky-based losses.

8.1.3 Quantitative imaging

Quantitative imaging methods can provide access to imaging metrics which can help characterize tissue integrity or neural activity. These methods can be used to assess tissue impairment, lesion severity and follow disease evolution. We investigated the potential of T1 relaxometry as well as diffusion and functional imaging methods.

8.2.1 Behavior

Connectivity patterns of the core resting-state networks associated with apathy in late-life depression.

Participants: Jean-Charles Roy, Julie Coloigner, Gabriel Robert.

Apathy is associated with reduced antidepressant response and dementia in late-life depression (LLD). However, the functional cerebral basis of apathy is understudied in LLD. In this work 38, we investigated the functional connectivity of 5 resting-state networks (RSN) hypothesized to underlie apathy in LLD. Resting-state functional MRI data were collected from individuals with LLD who did not have dementia as well as healthy older adults between October 2019 and April 2022. Apathy was evaluated using the diagnostic criteria for apathy (DCA), the Apathy Evaluation Scale (AES) and the Apathy Motivation Index (AMI). Subnetworks whose connectivity was significantly associated with each apathy measure were identified via the threshold-free network-based statistics. Regions that were consistently associated with apathy across the measures were reported as robust findings. Our sample included 39 individuals with LLD who did not have dementia and 26 healthy older adults. Compared with healthy controls, individuals with LLD had an altered intraRSN and inter-RNS connectivity in the default mode, the cingulo-opercular and the frontoparietal networks. All 3 apathy measurements showed associations with modified intra-RSN connectivity in these networks, except for the DCA in the cingulo-opercular network 5. The AMI scores showed stronger associations with the cingulo-opercular and frontoparietal networks, whereas the AES had stronger associations with the default mode network and the goal-oriented behaviour network. The study was limited by the small number of participants without apathy according to the DCA, which may have reduced the statistical power of between-group comparisons. Additionally, the reliance on specific apathy measures may have influenced the observed overlap in brain regions. Conclusion: Our findings indicate that apathy in LLD is consistently associated with changes in both intra-RSN and inter-RSN connectivity of brain regions implicated in goal-oriented behaviours. These results corroborate previous findings of altered functional RSN connectivity in severe LLD.

Representation of the brain regions whose functional connectivity are correlated with the apathy measures (AES, AMI and DCA).

8.2.2 Neuro-inflammation

This year, we pursued our investigations regarding the relevance of imaging the spinal cord to target early biomarkers for MS.

8.2.3 Recovery

9.1.1 Siemens

Participants: Elise Bannier, Emmanuel Caruyer, Isabelle Corouge, Jean-Christophe Ferré, Jean-Yves Gauvrit.

A collaboration between Siemens, Empenn and the Neurinfo platform is in place and formalized by a research contract. Thanks to this agreement, the Neurinfo platform has received the object code of MRI sequences under development at Siemens for evaluation in clinical research. In addition, the Neurinfo platform has received the source code of selected MRI sequences. As a result, MRI sequences can be developed on site by our team. For example, an MRI diffusion sequence was modified to load arbitrarly diffusion gradient waveforms for the FastMicroDiff project (led by E. Caruyer).

10.1.1 Visits of national and international scientists

Demian Vera

• Status
  PhD Candidate
• Institution of origin:
  Institution of origin: National University of Central Buenos Aires
• Country:
  Argentina
• Dates:
  Since Oct 2022 until January 2023
• Context of the visit:
  Implementation of a multilayer fNIRS model and experimentation at the Neurinfo platform

Laure Fournier

• Status
  PU-PH
• Institution of origin:
  AP-HP
• Country:
  France
• Dates:
  January 10th
• Context of the visit:
  HDR of Elise Bannier

Michel Dojat

• Status
  Senior Researcher
• Institution of origin:
  GIN, Grenoble
• Country:
  France
• Dates:
  January 10th
• Context of the visit:
  HDR of Elise Bannier

Sophie Achard

• Status
  Senior researcher
• Institution of origin:
  Laboratoire Jean Kuntzmann
• Country:
  France
• Dates:
  November 20-22
• Context of the visit:
  PhD of Jean-Charles Roy

Olivier Coulon

• Status
  Senior researcher
• Institution of origin:
  Institut des Neurosciences de la Timone
• Country:
  France
• Dates:
  December 15
• Context of the visit:
  PhD of Thomas Durantel

10.1.2 Visits to international teams

10.2.1 ANR-20-THIA-0018: programme Contrats doctoraux en intelligence artificielle

Participants: Francesca Galassi, Ricky Walsh, Benoît Combès.

• Funding:
  Co-funding for a PhD thesis in AI - Duration: 2022-2025.
• Summary:
  Co-funding (50% with Univ. Rennes) for a doctoral program in Artificial Intelligence. The PhD concerns the automatic segmentation of MS lesions in spinal cord MRI by means of AI-based solutions.

10.2.2 ANR-20-THIA-0018: programme Contrats doctoraux en intelligence artificielle

Participants: Camille Maumet, Elodie Germani.

• Funding:
  Co-funding for a PhD thesis in AI - Duration: 2021-2024.
• Summary:
  Co-funding (50% with Univ. Rennes) for a doctoral program in Artificial Intelligence. The PhD concerns representation learning for reproducible neuroimaging.

10.2.3 RHU PRIMUS: Transforming the care of patients with Multiple Sclerosis using a multidimensional data-driven clinical decision support system

Participants: Elise Bannier, Benoît Combès, Gilles Edan, Jean-Christophe Ferré, Francesca Galassi, Anne Kerbrat.

• Funding:
  RHU - Duration: 2022-2026 - Budget: 8272kC
• Partners:
  Observatoire Français de la Sclérose en Plaques (OFSEP), France Life Imaging (FLI), Pixyl.
• Summary:
  The overall objective of PRIMUS is to develop and validate a CE-marked data-driven clinical decision support system (CDSS) for multiple sclerosis (MS). The CDSS will support clinical decision-making by providing easily interpretable information on treatment options. MS is a complex disease, with different phenotypes and heterogeneous progression patterns. Over the past two decades, MS practice has been flooded with data and the number of available treatments has considerably increased. Although clinical, biological and imaging information is now being generated on a massive scale, it contributes to clinical decision-making in a rather haphazard, siloed and non-standardised fashion, so that selecting the most appropriate therapeutic option remains hard. PRIMUS contributes to data-driven homogenization of shared decision practices with and for patients with MS. To achieve this goal, the project will develop advanced artificial intelligence solutions, for a patient- and physician-centred CDSS.

10.2.4 EyeSkin-NF : Eye-tracking and skin conductance measures for neurofeedback analysis and validation

Participants: Claire Cury, Elise Bannier, Pierre Maurel, Hachim Bani, Rene-Paul Debroize, Agustina Fragueido.

• Funding:
  Exploratory action Inria - Duration: 2021 - 2024.
• Summary:
  Neurofeedback techniques (NF) or restorative brain computer interfaces (BCI) consist in providing a subject with real-time feedback about its own brain activity, in order to learn self-regulate specific brain regions during NF training. Brain activity can be measured by various techniques such as EEG and/or fMRI. However, analysis of NF sessions is limited due to the difficulty at identifying the origin of failed training. To enhance and monitor participant's motivation in real-time during EEG-fMRI recording, bio-signal can be measured via eye-tracking (ET) or skin conductance (SC) devices. For a precise evaluation of the motivation mental states of interest such as focus, arousal, mind wandering or mental load can be analysed. The main objective of this project is to investigate measures from eye-tracking and skin conductance signals to evaluate in real-time subject’s motivation during NF training.

10.2.5 GRASP: Generalizing Results Across Scientific Pipelines

Participants: Camille Maumet, Boris Clenet, Jeremy Lefort-Besnard.

• Funding:
  Exploratory action Inria - Duration: 2022 - 2024.
• Summary:
  Scientific pipelines are at the heart of modern experimental sciences. But practionners face a highly complex pipeline landscape – different tools, algorithms, parameters – in which different pipelines can lead to contradictory research findings. GRASP will model pipeline-induced variability to derive valid and generalizable results in the field of brain imaging.

10.2.6 ANR-NODAL: Identification de biomarqueurs de maladies neurodégénératives par l'analyse de la connectivité multimodale.

Participants: Julie Coloigner, Carlo Ferritto.

• Funding:
  Appel à projets générique 2022 - Duration: 2022 - 2026.
• Summary:
  The neurodegenerative diseases like Alzheimer’s (AD) and Parkinson’s (PD) disease are the consequences of pathological processes that begin decades before the onset of the typical clinical symptoms. However, current diagnosis comes quite late in the course of the disease, while evidences underline the multiple benefits that would be associated with earlier diagnosis. An outstanding challenge for clinical neurosciences is therefore to provide reliable, non-invasive, affordable and easy-to-track biomarkers able to improve both the early detection and the monitoring of neurodegenerative diseases. Recent advances in non-invasive connectome mapping techniques offer great hope for significant progress in taking up this challenge by investigating cerebral organization. Indeed, it is well acknowledged that AD and PD display a progressive multifactorial disruption of functional and structural cerebral networks, all along the course of the diseases. A recent framework called Graph Signal Processing (GSP) is particular promising to shed new light on the complex interplay between brain function and structure. For the first time, GSP will be extended to the development of more sensitive metric of AD and PD progression, taking into account the cerebral functional-structural coupling, contrary to the classical biomarkers using a single-modality data or clinical assessment. In the PRESCO project, we will develop a new multimodal and multi-stage approach using innovative machine learning methods, adapted for GSP-based features, to provide non-invasive, reliable and easy-to-track candidate biomarkers for each stage of AD and PD diseases. We will apply this approach on two large patients’ cohorts. Then, we will assess the effectiveness of candidate disease-specific biomarkers on a new innovative local multimodal cohorts including patients with and without cognitive impairment, at various stages of AD and PD. At the end of 2023, we began the acquisition of the cohort including the MRI data and neurocognitve assessment. Carlo Ferritto, a PhD student, works on this project from October 2023. This is a collaborative project with Pierre-Yves Jonin, CHU Rennes and Giulia Lioi, researcher, IMT, Brest.

10.2.7 ANR-PASTRAMI: Patient-specific statistics for microstructure-augmented connectomics

Participants: Élise Bannier, Emmanuel Caruyer, Julie Coloigner, Claire Cury, Marie Poirier.

• Funding:
  Appel à projets générique 2023 - Duration: 2023 - 2028.
• Summary:
  The PASTRAMI project proposes to promote the use of diffusion magnetic resonance imaging (MRI) to derive biomarkers of axonal injury along white matter (WM) fascicles as prognostic factors of functional recovery after severe traumatic brain injury (TBI). We propose to develop statistical methods for patient-specific localization of abnormalities in microstructure and/or structural connectivity, along specific WM fascicles and/or on the full connectome. In a clinical study, the objective will be to assess the predictive accuracy of the proposed model evaluated in the 10 days period following TBI to predict unfavourable outcome at 1-year after the first injury in patients admitted in intensive care for severe TBI. This project is a collaboration with the Laboratoire de mathématiques Jean Leray (Nantes), CHU Rennes and the HIA Sainte-Anne (Toulon).

10.2.8 ANR-JCJC-VICUNA: Exploring the variabiIity induced by different configurations in the neuroimaging analytical space

Participants: Camille Maumet.

• Funding:
  Appel à projets générique 2022 - Duration: 2022 - 2026.
• Summary:
  Using the same data to answer the same scientific question, researchers may reach contradictory conclusions depending on the analytical pipeline they choose. For many years this problem has been rampant in experimental sciences and recent studies stemming from many fields have brought scientific evidence of this issue. Overall this phenomenon has reduced confidence in research findings and is effectively an important remaining driver of the reproducibility crisis. Software is central to modern scientific research and with the development of data science and its subfields (such as bioinformatics or neuroinformatics) the different tools and approaches available to study a dataset have multiplied. Those software have been very valuable to practitioners and brought the capacity to process more data in a shorter amount of time. But overall, they also provide a large number of possible analysis paths that can be used in order to address a scientific question. With VICUNA, we will provide a proof-of-concept explorat analytical variability in brain imaging. We will navigate in the pipeline space at large and understand which parts of the space are effectively in-use. We will explore and look into how results vary in 3 large open datasets (NARPS, UK Biobank and HCP). This is a collaborative project with Mathieu Acher, INSA Rennes.

10.2.9 Connectivity of the amygdala in depression

Participants: Emmanuel Caruyer, Julie Coloigner, Claire Cury.

• Funding:
  Fondation de France + INCR – Institut des Neurosciences Cliniques de Rennes - Duration: 2019-2023 - Budget: 250k€
• Summary:
  The onset of depression in teenagers and young adults increases the risk to develop a drug-resistant depression in the adulthood. This project aims at evaluating the role of early changes in the microstructure and connectivity of the amygdala. Using a cohort of drug-resistant patients (N=30), non drug-resistant patients (N=30) and controls (N=30), the aim is to identify imaging biomarkers of the pathology and to compare these with emotional and cognitive phenotypes in this population, searching for early differences in the development of the amygdala connectivity. Inclusions are ongoing. This is a colloborative project with M.-L. Paillère Martinot from Paris-Descartes University, as Principal Investigator.

10.2.10 Knowledge addition through Neuroimaging of Alcohol consumption in healthy young Volunteers, causes or consequences

Participants: Elise Bannier, Quentin Duché, Gabriel Robert.

• Funding:
  Funding: INCR - Duration: 2020-2023 - Budget: 45k€
• Summary:
  Alcohol consumption is responsible for 3 million annual deaths worldwide (5.1 percent of the global burden of disease). It causes disease (liver cirrhosis, cancers, etc.) and other social costs (injuries, road accidents, alcohol dependence, etc.). Excessive alcohol consumption grows through adolescence. This type of behavior has also been shown to have subtle but significant deleterious effects on cognitive function in adolescents. Advances in the field of neuroimaging make it possible to characterize anatomical changes and the evolution of neuropsychological deficits. Besides, focusing on the societal causes of alcohol abuse, a large body of studies show that exposure to alcohol advertising through media bootstraps early consumption initiation, greater desire to drink, increased alcohol use and binge drinking patterns among young people, especially minors. We aim to combine the analysis of the locally acquired IMAJ dataset (PI Karine Gallopel-Morvan, INCA Funding) and data from the european consortium IMAGEN datasets to determine whether there are functional characteristics and external factors that can explain behavior towards alcohol and to extract biomarkers capable of predicting excessive behavior. Relying on the IMAJ dataset, we will analyze whether, depending on warning formats displayed on ads (small and text-only vs. larger, shock-inducing and pictorial), health messages can influence brain activity by decreasing the effect of attractive alcohol content ads on the reward system area and on behavioral responses. Relying on the already effective collaboration of Dr Robert with Prof Schumann, we will explore the longitudinal anatomical and functional data from the IMAGEN cohort to extract biomarkers of alcohol consumption evolution and complement the analysis with the results obtained from the IMAJ dataset.

10.2.11 PHRC EMISEP: Evaluation of early spinal cord injury and late physical disability in Relapsing Remitting Multiple Sclerosis

Participants: Elise Bannier, Emmanuel Caruyer, Benoit Combès, Gilles Edan, Jean-Christophe Ferré, Anne Kerbrat.

• Funding:
  PHRC - Duration: 2016-2023 - Budget: 200k€
• Summary:
  Multiple Sclerosis (MS) is the most frequent acquired neurological disease affecting young adults (1 over 1000 inhabitants in France) and leading to impairment. Early and well adapted treatment is essential for patients presenting aggressive forms of MS. This PHRC (Programme hospitalier de recherche clinique) project focuses on physical impairment and especially on the ability to walk. Several studies, whether epidemiologic or based on brain MRI, have shown that several factors are likely to announce aggressive development of the disease, such as age, number of focal lesions on baseline MRI, clinical activity. However, these factors only partially explain physical impairment progression, preventing their use at the individual level. Spinal cord is often affected in MS, as demonstrated in postmortem or imaging studies. Yet, early radiological depiction of spinal cord lesions is not always correlated with clinical symptoms. Preliminary data, on reduced number of patients, and only investigating the cervical spinal cord, have shown that diffuse spinal cord injury, observed via diffusion or magnetisation transfer imaging, would be correlated with physical impairment as evaluated by the (EDSS) Expanded Disability Status Scale score. Besides, the role of early spinal cord affection (first two years) in the evolution of physical impairment remains unknown. In this project, we propose to address these different issues and perform a longitudinal study on Relapsing Remitting Multiple Sclerosis (RRMS) patients, recruited in the first year of the disease. Our goal is to show that diffuse and focal lesions detected spinal cord MRI in the first two years can be used to predict disease evolution and physical impairment at 5 years. Twelve centers are involved in the study to include 80 patients. To date, all subjects have been included and the last visit of the last patient is scheduled early 2023. The EMISEP data consists of brain and spinal cord structural and quantitative MR images of early MS patients followed over 5 years. Four papers have been published so far on data acquired at baseline on healthy controls and patients. Three papers were co-authored in the context of international collaborations. Additional papers are in preparation.

10.2.12 Estimating the impact of multiple sclerosis lesions in motor and proprioceptive tracts, from the brain to the thoracic spinal cord, on their functions, assessed from clinical tests (MS-TRACTS and MAP-MS)

Participants: Elise Bannier, Benoit Combès, Malo Gaubert, Anne Kerbrat.

• Funding:
  ARSEP, COREC and INCR - Duration: 2020-2023 - Budget: 200k
• Summary:
  Previous studies, whether epidemiologic or based on brain MRI, have shown that several factors were likely to announce aggressive development of the disease, such as age, clinical relapses, number of focal lesions on baseline MRI. However, these factors only partially explain physical disability progression, preventing their use at the individual level. We hypothesize that a fine assessment of damage on specific networks, from the brain to the thoracic cord, offers a relevant biomarker of disability progression in MS. Such damage assessments must take into account both lesion location, assessed on structural brain and cord MR images and lesion severity, assessed using advanced brain and cord imaging through quantitative MRI.We propose to test this hypothesis by combining assessments of lesion location and severity on corticospinal and proprioceptive tracts from the brain to the thoracic cord with clinical and () electrophysiological measurements. The MS-TRACTS study involves two French centers (Rennes,Marseille) and includes a total of 60 relapsing remitting MS patients. The expected outcome is to obtain early biomarkers of physical impairment evolution in RRMS patients, first treated with immunomodulatory treatment. The long-term goal is to provide the clinician with biomarkers able to anticipate therapeutic decisions and support the switch to alternative more aggressive treatment. Inclusions are ongoing. The MAP-MS study involves the same two French centers and will nclude 40 progressive MS patients. The investigation will focus on motor asymetry in these more advanced patients. This study includes two French centers (Rennes, Marseille) and includes a total of 60 patients. The expected outcome is to obtain early biomarkers of physical impairment evolution in RRMS patients, first treated with immunomodulatory treatment. The long-term goal is to provide the clinician with biomarkers able to anticipate therapeutic decisions and support the switch to alternative more aggressive treatment. Inclusions are ongoing.

Estimating the impact of multiple sclerosis lesions in motor and proprioceptive tracts, from the brain to the thoracic spinal cord, on their functions, assessed from clinical tests (MS-TRACTS and MAP-MS): An example of Magnetization Transfer Ratio (MTR) mapping of the whole spinal cord acquired from the MS-TRACTS imaging protocol.

10.2.13 France Life Imaging (FLI)

Participants: Michael Kain, Camille Maumet, Jean-Christophe Ferré.

• Funding:
  Funding: FLI - Duration: 2012-2023 - Total budget: 2000k€ (phase 1) + 1200k€ (phase 2) + 800k€ (phase 3)
• Summary:
  France Life Imaging (FLI) is a large-scale research infrastructure project to establish a coordinated and harmonized network of biomedical imaging in France. This project was selected by the call “Investissements d’Avenir - Infrastructure en Biologie et Santé”. One node of this project is the node Information Analysis and Management (IAM), a transversal node built by a consortium of teams that contribute to the construction of a network for data storage and information processing. Instead of building yet other dedicated facilities, the IAM node use already existing data storage and information processing facilities (LaTIM Brest; CREATIS Lyon; CIC-IT Nancy; Empenn U1228 Inria Rennes; CATI CEA Saclay; ICube Strasbourg) that increase their capacities for the FLI infrastructure. Inter-connections and access to services are achieved through a dedicated software platform that is developed based on the expertise gained through successful existing developments. The IAM node has several goals. It is building a versatile facility for data management that inter-connects the data production sites and data processing for which state-of-the-art solutions, hardware and software, are available to infrastructure users. Modular solutions are preferred to accommodate the large variety of modalities acquisitions, scientific problems, data size, and to be adapted for future challenges. Second, it offers the latest development that are made available to image processing research teams. The team Empenn fulfills multiple roles in this nation-wide project. Michael Kain is the technical manager, Camille Maumet is part of the steering committee. Apart from the team members, software solutions like MedInria and Shanoir are part of the software platform.

10.2.14 OFSEP: French Multiple Sclerosis Observatory

Participants: Elise Bannier, Gilles Edan, Jean-Christophe Ferré, Francesca Galassi, Arthur Masson, Benoît Combès, Anne Kerbrat.

• Funding:
  ANR-PIA - Duration: since 2017 - Budget: 175k€
• Summary:
  The French Observatory of Multiple Sclerosis (OFSEP) is one of ten projects selected in January 2011 in response to the call for proposal in the "Investissements d’Avenir - Cohorts 2010" program aunched by the French Government. It allows support from the National Agency for Research (ANR) of approximately 10 million € for 10 years. It is coordinated by the Department of Neurology at the Neurological Hospital Pierre Wertheimer in Lyon (Professor Christian Confavreux), and it is supported by the EDMUS Foundation against multiple sclerosis, the University Claude Bernard Lyon 1 and the Hospices Civils de Lyon. OFSEP is based on a network of neurologists and radiologists distributed throughout the French territory and linked to 61 centers. OFSEP national cohort includes more than 50,000 people with Multiple Sclerosis, approximately half of the patients residing in France. The generalization of longitudinal monitoring and systematic association of clinical data and neuroimaging data is one of the objectives of OFSEP in order to improve the quality, efficiency and safety of care and promote clinical, basic and translational research in MS. For the concern of data management, the Shanoir platform of Inria has been retained to manage the imaging data of the National OFSEP cohort in multiple sclerosis. One long term objective of the OFSEP project is to identify prognostic factors of the evolution of Multiple Sclerosis. The HD Cohort is an enhanced cohort specifically designed for this purpose in which some patients are followed-up on a yearly basis. Additional clinical, quality of life and other patient-reported data is also collected. This study aims at developing personalized predictive tools to improve patient care management, and help in making decision to start, maintain or adapt medical care. Collected data will be processed to extract valuable information enabling to determine specific biomarkers of the evolution of the disease. Multiple Sclerosis brain lesions are of particular interest, hence the need for a careful comparison of lesion segmentation methods. A litterature review enabled to gather most promising cross-sectionnal methods, designed to identify and localize lesions with precise measurement of the lesion load at one particular point in time ; and longitudinal methods which gives more insight on the evolution of those lesions over the different time points. Those later methods are particularly interesting for clinicians for whom the type of lesion evolution is of foremost importance. A cross-sectionnal method and a longitudinal method were trained and evaluated to select the ones which will be used to analyze the entire HD Cohort dataset. Moreover, an experimental and a statistical design to compare the accuracy, sensitivity and specificity of the active/inactive classification of MS patients based on brain MRI as assessed using the analysis of brain was proposed. These designs will allow to assess the interest of re-analyzing the MRI data to improve the quality of the standardized reports used in most epidemiologic studies from the OFSEP cohorts. The collaboration has recently been extended until end of 2025 with a particular focus on spinal cord imaging and slowly evolving lesions.

10.2.15 QSM-SPICO: Quantitative Susceptibility Mapping for Spinal Cord

Participants: Elise Bannier, Benjamin Streichenberger, Anne Kerbrat, Benoit Combès.

• Funding:
  FLI-RE4 - 20k€
• Summary:
  Quantitative Susceptibility Mapping (QSM) is a promissing quantative imaging technique for the characterization of lesions in Multiple Sclerosis (MS). QSM provides a novel type of contrast linked to the tissue magnetic susceptibility. The latter is sensitive to iron accumulation and myelin content, which are both important metrics when studying MS lesions. As part as a research expertise transfer sponsored by France Life Imaging, in collaboratin with Mathieu Santin, at ICM/CENIR and Ludovic de Rochefort and Stéphane Roche from the Ventio Startup in Marseille, we are exploring the possibility to perform QSM in the spinal cord. This is challenging because of size of the cord and the presence of fat in the spine. To tackle this challenge, we use the IDEAL algorithm - iterative decomposition of water and fat with echo asymmetry and least-squares estimation. The aim is be able to characterize spinal MS lesions using QSM. The first results are encouraging.

10.2.16 PEPR ShareFAIR

Participants: Camille Maumet, Elise Bannier.

• Funding:
  PEPR Santé numérique.
• Summary:

  Access to a wide variety of complementary, multi-scale and massive data collections offers unprecedented opportunities for healthcare research. A large number of analyses can be performed on these datasets, for scientific advances and discoveries to emerge. The national 'Digital Health'Acceleration Strategy ambitions to boost digital health innovation which includes designing innovative health data analysis approaches.

  Importantly, such data analyses are complex, they rely on various computational tools that have to be parametrized and chained together. There is now compelling evidence that many scientific discoveries will not stand the test of time: increasing the reproducibility of computed results is of paramount importance, especially in the healthcare domain.

  Sharing of health data is often hampered by personal data protection requirements and comes up against technical constraints (security, volume). These constraints can however be limited when the protocols and the workflows implementing analyses are sufficiently reusable to reproduce analyses in situ.

  Additionally, when designed to be reusable, protocols and their implementations - workflows - provide the provenance traces of the analyzed data, describing how data results have been obtained and thus increasing scientists’ confidence in the results produced.

  This calls for innovative solutions for the annotation of biomedical and clinical datasets and extraction of provenance. Protocols and their implementation as workflows using and generating datasets should be elevated to first-class objects and the inherent dual relationship between datasets and protocols/workflows should be better exploited.

  Challenges thus include standardization and annotation for datasets and protocols, extracting protocols and workflows from text and other datasets, and synthesizing them into interoperable, yet shareable protocols.

  The originality of ShareFAIR lies in tackling both the reliability of datasets and analysis protocols and in harnessing the dual relationship between datasets and protocols. Specifically, ShareFAIR will provide:

  (i) standards to uniformly represent datasets, ontologies/common vocabularies to annotate datasets and protocols/workflows, and provenance to trace the origin of datasets,

  (ii) an interoperable framework for the design, annotation and reuse of reliable and shareable protocols,

  (iii) approaches to extract protocols from textual data to enrich the set of protocols and workflows and better document the provenance of datasets, and approaches to learn protocols from biomedical and clinical datasets.

  This project is led by Sarah Boulakia-Cohen from Univ Paris Saclay.

10.3.1 PEPERONI : Portable and Personalized Neurofeedback for Stroke Rehabilitation

Participants: Elise Bannier, Isabelle Bonan, Julie Coloigner, Isabelle Corouge, Claire Cury, Pierre Maurel, Camille Muller, Caroline Pinte.

• Funding:
  Labex CominLabs : from Sept. 2022 to end of 2024 - Budget: 290k€
• Summary:
  Neurofeedback (NF) consists in presenting a person with a stimulus directly related to his or her ongoing brain activity. NF can be used to teach subjects how to regulate their own brain functions by providing real-time sensory feedback of the brain “in action”. Recent studies showed that NF is promising for the treatment of various neuronal pathologies. Electroencephalography (EEG), which has historically been the preferred modality for NF, suffers from a lack of specificity, preventing the transfer of this treatment to clinical use. On the other hand functional Magnetic Resonance Imaging (fMRI) has a good specificity, but it is a cumbersome and expensive modality, making it difficult to develop personalized protocols. In this project, we aim to develop a methodological and experimental framework opening the door to a more portable and personalized NF, for easier and effective clinical use, with a focus on post-stroke motor rehabilitation. We propose to organize the project in four work packages, grouped in two axes. The following figure summarizes the organization of the project.

10.3.2 Région Bretagne: SAD

Participants: Burhan Rashid Hussein, Francesca Galassi, Benoit Combès.

• Funding:
  SAD 2022 - 2024 : RHU PRIMUS - Duration: 48 months (start: December 2022) - Budget: 75k€
• Summary:
  Complementary funding for a post-doctoral position (Burhan Rashid Hussein) within the RHU PRIMUS project.

10.3.3 Région Bretagne: ARED

Participants: Nolwenn Jégou, Anne Kerbrat, Benoit Combès.

• Funding:
  ARED 2023 - 2026 : RHU PRIMUS - Duration: 36 months (start: December 2023)
• Summary:
  Complementary funding for a PhD position (Nolwenn Jégou) within the RHU PRIMUS project.

10.3.4 Région Bretagne: ARED

Participants: Elodie Germani, Camille Maumet.

• Funding:
  ARED 2022 - 2024 : ARED MAPPIS - Duration: 36 months
• Summary:
  Complementary funding for a PhD position (Elodie Germani).

10.3.5 Région Bretagne: ARED

Participants: Sebastien Dam, Julie Coloigner, Pierre Maurel.

• Funding:
  ARED 2022 - 2024 : ARED CONGRATS - Duration: 36 months
• Summary:
  Complementary funding for a PhD position (Sébastien Dam).

11.1.1 Scientific events: organisation

11.1.2 Scientific events: selection

11.1.3 Journal

11.1.4 Invited talks

• Agustina Fragueiro, “Pilot study: eye-tracking and skin conductance to monitor task engagement during bimodal neurofeedback” in the special session “Bimodal functional neuroimaging data fusion: methods and applications”, 20th IEEE-International Symposium on Biomedical Imaging (ISBI), Cartagena de Indias, Colombia, April 2023
• Caroline Pinte, "EMPENN projects presentation & Improving portability of bi-modal neurofeedback", Advanced Telecommunications Research Institute International (ATR) Kyoto Japan, September 2023.
• Agustina Fragueiro, “Shift in hippocampal medial position and increased fissure volumes in individuals affected by Developmental Topographical Disorientation”, 8th Scientific Meeting of the Federation of European Societies of Neuropsychology (FESN) and 2nd Panhellenic Conference on Neuropsychology, Thessaloniki, Greece, September 2023
• Francesca Galassi, "Deep Learning in Medical Imaging: What's Needed for Training Data?", Biogenouest days 2023, Oct 2023, Rennes (Campus Villejean), France 82.
• Fanny Dégeilh "Imaging the uniqueness of young child's brain". AI in Pervasive Well-Being and Healthy Ageing Workshop, University of Glasgow, Glasgow, Scotland, June 2023.
• Jérémy Lefort-Besnard, "Data sharing in Europe: reviewing current practices". Conférence GliMR Imaging 2.0 à Porto, Portugal. Mai 2023.
• Jérémy Lefort-Besnard, "The next generation of tools for meta-analysis". Panéliste pour la table ronde de la conférence Cogbases à l'Institut Pasteur, Paris. Octobre 2023.
• Emmanuel Caruyer, "Towards feature-specific diffusion acquisitions?". Microstructure by the Lake, EPFL, Lausanne, Switzerland, September 2023.
• Elise Bannier, Anne Hespel, Camille Maumet "Information, consentement au traitement des données et au recours à l'IA", Journée Les données et l'intelligence artificielle en santé, Rennes, Juin 2023.73.
• Elise Bannier, Claire Cury and Julie Coloigner, "fMRI & EEG bimodal neurofeedback for brain rehabilitation : methodological and clinical aspects", Genève, Switzerland, September 2023.
• Elise Bannier, Anne Hespel, "Partage des données de neuroimagerie : considérations règlementaires, techniques et enjeux de science ouverte", Journée ARDoISE, Atelier rennais de la Donnée, Rennes, Décembre 2023.
• Julie Coloigner, "Marqueurs IRM de l'inflammation : Nouvelles approches et applications en neuropsychiatrie", Journées Neurosciences Psychiatrie Neurologie, Rennes, Juin 2023.
• Camille Maumet "Reproductibilité en neuroimagerie état des lieux", Journées Recherche reproductible: état des lieux, Mars 2023, Paris, France.
• Camille Maumet "BIDS-Prov: Recording neuroimaging provenance", Brain Imaging Data Structure (BIDS) derivatives meeting, Jun 2023, Copenhagen, Denmark.
• Camille Maumet "Open science practices for keeping inventions alive after project ends", ESMRMB 2023 - 39th Annual Scientific Meeting on European Society for Magnetic Resonance in Medicine and Biology, Oct 2023, Basel (CH), Switzerland. 2023. 75.
• Camille Maumet "Towards reproducible neuroimaging across different analysis pipelines" CogBases 2023, Oct 2023, Paris, France. 2023
• Camille Maumet "Towards reusable derived data in neuroimaging", MRI Together, Dec 2023, Online.

11.1.5 Leadership within the scientific community

• Elise Bannier is elected member of the Board of the French Society for MRI Physics (SFRMBM, )
• Elise Bannier is founding member of the Board of the REMI francophone Network (https://remi.network/) for multicentric mutual aid in MRI Clinical research - until December 2023.
• Camille Maumet is member (elected) of the steering committee of the Brain Imaging Data Structure (BIDS)
• Camille Maumet is member (by selection) of the national committee on Open Science, Working group "open software" led by Roberto Di Cosmo and François Pellegrini.

11.1.6 Research administration

• Anne Kerbrat, Francesca Galassi, and Benoit Combès are part of the Scientific Committee of the RHU Primus project.

11.2.1 Teaching

• ESIR, École Supérieure d'Ingénieur de Rennes:
  • Pierre Maurel is co-head of the Master program "imagerie numérique" (two last year of the Engineering School)
  • Pierre Maurel, "General image processing" (30h).
  • Pierre Maurel, "Algorithmique et complexité" (30h).
  • Pierre Maurel, "Imagerie médicale" (30h).
  • Francesca Galassi is co-head of the Master program "Systemes d'Information" (two last year of the Engineering School)
  • Francesca Galassi, "Apprentissage Automatique" (Plenary: 12h, TP: 24h).
  • Francesca Galassi, "Algoritmique des graphes" (Plenary: 12h, TD: 6h, TP: 6h).
  • Francesca Galassi, "Base de données" (Plenary: 8h).
  • Francesca Galassi, "Imagerie médicale" (TP: 15h).
  • Ricky Walsh, "Apprentissage Automatique" (TP: 24h).
  • Julie Coloigner, "Analyse avancé de Signaux et images" (35h).
  • Julie Coloigner, "Mathématiques appliqués" (25h).
  • Claire Cury, "Traitement avancé des images" (Plenary : 12h).
  • Cédric Meurée, "Algorithmique et complexité" (TD: 14h)
  • Caroline Pinte, "Mathématiques appliquées au traitement d'images" (TP: 18h)
  • Caroline Pinte, "Projets d'imagerie médicale" (TP: 12h)
  • Caroline Pinte, "Neurofeedback (NF) et Brain Computer Interface (BCI) : Une Introduction" (Plenary: 3h)
  • Sébastien Dam, "Algorithmique et complexité" (TP: 28h).
  • Sébastien Dam, "Algoritmique des graphes" (TD: 6h, TP: 12h).
  • Carla Joud, ESIR 1, Maths-S5/S4, Rennes Engineering school (TD: 10h, TP:10h)
  • Jérémy Lefort-Besnard, "Algorithmique et complexité" (Master ESIR, TD:14h et TP:14h)
• Master SIBM, M2, University of Angers-Brest-Rennes:
  • Jean-Christophe Ferré is head of the master.
  • Benoît Combès is co-head of the UE “Modélisation et Apprentissage Automatique pour le Traitement des Images Médicales”.
  • Camille Maumet is co-head of the UE “Gestion de données massives et complexes”.
  • Emmanuel Caruyer, "Méthodes d'analyse d'IRM de diffusion" (Plenary: 3h).
  • Julie Coloigner, "Méthode d'analyse de la connectivité cérébrale" (Plenary: 3h).
  • Benoit Combès, "Méthodes de segmentation pour l'imagerie médicale" (Plenary: 3h).
  • Benoit Combès, “Méthodes de recalage linéaire et non-linéaires des images médicales” (Plenary: 6h).
  • Benoit Combès, “Applications des méthodes de traitement des images médicales” (Plenary: 3h).
  • Benoit Combès, “Eléments de statistiques pour l’induction scientifique” (Plenary: 4.5h).
  • Benoit Combès, Camille Maumet, “Soutenance de présentations critiques d'articles scientifiques” (TD: 3h).
  • Isabelle Corouge, "IRM de perfusion par Arterial Spin Labeling (ASL)" (Plenary: 3h).
  • Elise Bannier, "Imagerie fonctionnelle cérébrale" (Plenary: 1h).
  • Quentin Duché, "Traitement des données d'IRM fonctionnelle" (Plenary: 1h).
  • Elise Bannier, “Utilisation et réutilisation des données d'imagerie” (Plenary: 1h).
  • Elodie Germani, "Workflows de traitement d'images" (Plenary: 3h)
• ENS Rennes/Univ. Rennes:
  • Emmanuel Caruyer, "Méthodes numériques pour le traitement d'images", L3 SIF (Plenary: 20h).
  • Francesca Galassi, "Traitement d'Images", M2 Informatique (Plenary: 10h, TP: 10h).
• Master EIT Data Science, M2, Univ. Rennes:
  • Francesca Galassi, "Deep Learning" (Plenary: 12h, TP: 12h).
  • Ricky Walsh, "Machine Learning II" (TP: 12h).
  • Ricky Walsh, "Case Study" (TD: 12h).
• Master Informatique, ISTIC, Univ. Rennes:
  • Julie Coloigner, "Computer Vision" (Plenary: 10h)parcours Science informatique (SIF), M2.
  • Elodie Germani, "Option Machine Learning" (TP: 10h), specialités IL (Ingenierie Logiciel).
• Licence 1 ISTN, ISTIC, Université de Rennes 1:
  • Elodie Germani, "Principes des Systèmes Informatiques" (TP: 24h)
  • Elodie Germani, "Projet professionnel et communication" (TP: 8h)
• Licence BECV (Biologie, Environnement, Chimie du Vivant), University of Rennes 1: Elodie Germani, "Mathématiques pour la biologie" (TD: 27h).
• Bachelor for speech therapy, L3, University of Rennes: Elise Bannier, "Imagerie fonctionnelle cérébrale du langage" (Plenary: 2h).
• Diplome Universitaire MERC (Manipulateur en Recherche Clinique), University of Montpellier: Elise Bannier, "Spécificités de la recherche clinique en imagerie" (Plenary: 7h).
• Master Physique Médicale, M2, University of Rennes:
  • Elise Bannier, "Imagerie par Résonance Magnétique " (TD: 4h).
• L2, IFMEM, MR Technologists, University Hospital of Rennes:
  • Elise Bannier, "Imagerie par Résonance Magnétique " (Plenary: 10h).
• Master Neuropsychologie, M2, University of Savoie: Pierre-Yves Jonin, "Limites méthodologiques du bilan neuropsychologique à visée diagnostique" (Plenary: 3h30).
• Master Psychologie et neuropsychologie de l’enfant et de l’adulte : langage, cognition et apprentissage, M2, University of Poitiers: Pierre-Yves Jonin, "Méthodologie de l'étude de cas" (Plenary: 3h).
• Master Biologie et Santé, M1, University of Bretagne Occidentale: Pierre-Yves Jonin, "Explorations neuropsychologiques des maladies neurologiques et psychiatriques" (Plenary: 4h).
• Master Psychologie Clinique, Psychopathologie et Psychologie de la Santé, M2, University of Rennes 2:
  • Pierre-Yves Jonin, "Neuropsychologie clinique des pathologies neurodégénératives" (Plenary: 4h).
  • Pierre-Yves Jonin, "Méthodologie de l'étude de cas" (Plenary: 4h).
• Licence Psychologie, L3, University of Rennes 2:
  • Pierre-Yves Jonin, "Les syndromes neuropsychologiques" (TD: 16h).
  • Pierre-Yves Jonin, "Approche neuropsychologique du handicap" (TD: 4h).
• Master Neurosciences Cliniques, M2, University of Rennes 1:
  • Pierre-Yves Jonin, "Neurosciences cognitives et cliniques de la mémoire humaine" (Plenary: 3h).
• STAPS, DEUST Métiers de la forme, Université de Rennes 2 :
  • Camille Muller, "Neurosciences" (TD: 12h).

11.2.2 Supervision

M2 Internship

• M2 SIBM, Univ. Rennes : Alice Dufey, "Quantification of motor tract lesions load and severity and consequences on motor function in patients with relapsing-remitting multiple sclerosis", supervised by Anne Kerbrat and Malo Gaubert.
• M2 Physique, Univ. Rennes : Gaëlle Baudron, "EMISEP : Evaluation de l’impact du changement de machine IRM sur la qualité des images acquises", supervised by Benoit Combès, Malo Gaubert and Anne Kerbrat.
• M2 SIBM, Univ. Rennes : Vivien Caron, "Spinal cord microstructural damage measured in recently diagnosed Relapsing Remitting MS patients: prognostic value at 5-year", supervised by Anne Kerbrat and Benoit Combès.
• M2 IMaGHE Sciences du vivant, EPHE-PSL: Mathilde Liffran "Etude du lien entre l'atteinte structurelle des voies motrices en IRM et l'asymétrie clinique chez les patients atteints de sclérose en plaques progressive", supervised by Anne Kerbrat, Malo Gaubert and Benoit Combès.
• M1, ESIR: Louis-Gabriel Capliez, "Intégration d'un prototype de segmentation de lésions de sclérose en plaques dans la moëlle épinière - Implémentation d'une batterie de tests unitaires, d'intégration et de fonctionnement", supervised by Burhan Rashid Hussein and Cédric Meurée.
• M1, ENS/Univ. Rennes: Lounes Meddhai, "Segmentation of chronique stroke lesions", supervised by Stephanie Leplaideur, Elise Bannier and Francesca Galassi.
• L3, Univ. Rennes: Emma Redor, "Identifying and comparing multiple brain image segmentation algorithms in young children", supervised by Fanny Dégeilh
• M2 Univ. Rennes: Mathys Bizière, "Association between pediatric mild traumatic brain injury and brain structure development in a large population-based study" supervised by Fanny Dégeilh and Claire Cury
• M1, ENS: Emma Redor, "Analyse de la variabilité logicielle dans l'harmonisation inter-scanner des imageries pédiatriques en IRM", supervised by Camille Maumet and Fanny Dégeilh
• M. Sc. Artificial Intelligence and Data Science, M2, University of Düsseldorf: Maiwenn Fleig, "Image-to-image transition between pipelines for functional MRI statistic maps", supervised by Elodie Germani and Elisa Fromont.
• Master Informatique, M1, ENS Rennes: Thibault Chanus, "Image-to-image transition between fMRI pipelines statistic maps using diffusion models", supervised by Elodie Germani and Elisa Fromont.
• Valentin Septiers, ESIR 3, "Évaluation de tâches d'IRM fonctionnelle d'activation pour cartographier les fonctions primaires avant une opération" supervised by Elise Bannier, Quentin Duché, Pierre-Yves Jonin and Nicolas Lassalle.
• Benjamin Prigent, M2 Physique, "Spatio-temporal exploration of fMRI and fNIRS signals" supervised by Elise Bannier, Nicolas Coquery and Yann Serrand.

PhD

• PhD: Ambre Godet, "Intervention par neurofeedback-fNIRS contre l’hyperphagie émotionnelle : caractérisation cérébrale et comportementale", Univ. Rennes, from Oct 2020 to Novembre 2023, David Val-Laillet, Nicolas Coquery, Elise Bannier - Defended in November 2023.
• PhD: Jean-Charles Roy, "Apathy in Late Life Depression: New Biomarkers Using Actimetry and Magnetic Resonance Imaging (ACTIDEP)", Univ. Rennes / INCR, from Oct 2020 to December 2023, Julie Coloigner and Gabriel Robert - Defended in November 2023.
• PhD; Thomas Durantel, "Anatomy and microstructure informed tractography for connectivity evaluation in neurological pathologies", Univ. Rennes, from Nov 2020 to December 2023, Olivier Commowick and Julie Coloigner - Defended in December 2023.
• PhD in progress; Ricky Walsh, "Accurate and robust automated segmentation of multiple sclerosis lesions in spinal cord MRI", Univ. Rennes, from Nov 2022 to December 2025, Francesca Galassi, Benoit Combès and Anne Kerbrat.
• PhD in progress; Nolwenn Jégou, "Apports de nouveaux biomarqueurs de démyélinisation issus de l’IRM quantitative pour le suivi des patients ayant une sclérose en plaques", Inria, from Decembre 2023 to Janvier 2027, Anne Kerbrat, Elise Bannier and Benoit Combès
• PhD in progress; Alix Lamouroux, "Connectivity and Neurofeedback", at IMT Atlantique Brest, from Oct. 2022, co-supervised by Julie Coloigner and Pierre Maurel, with Giulia Lioi (Brain team, IMT Atlantique) and Nicolas Farrugia (Brain team, IMT Atlantique).
• PhD in progress: Carla Joud, "Analyse conjointe de données multimodales en épilepsie", Univ. Rennes, from Nov 2022, Julie Coloigner.
• PhD in progress: Sébastien Dam, "Structural Brain Connectivity and Treatment Response in Mood Depressive Disorder", Inria, from Oct 2022, Julie Coloigner and Pierre Maurel.
• PhD in progress: Caroline Pinte, “Methodology for enhanced and adapted Neurofeedback training”, Univ. Rennes, from Oct 2021, Claire Cury and Pierre Maurel.
• PhD in progress: Lisa Hemforth, "Methodology for automatic scoring of Incomplete Hippocampal Inversion", Sorbonne University, from Oct. 2021, Claire Cury, Baptiste Couvy-Duchesne and Olivier Colliot.
• PhD in progress: Carlo Ferritto "Modeling brain structural and functional connectivity in neurodegenerative diseases", IRISA, CNRS, from Oct 2023, Julie Coloigner.
• PhD in progress: Constance Bocquillon, "Optimizing diffusion MRI acquisition for quantitative connectivity mapping", Univ Rennes, from Oct. 2022, Emmanuel Caruyer and Isabelle Corouge.
• PhD in progress: Marie Poirier, "Robust, patient-specific statistics for the evaluation of brain pathologies using diffusion MRI", Univ. Rennes, from Dec. 2022, Emmanuel Caruyer and Aymeric Stamm (IR CNRS, Laboratoire de Mathématiques Jean Leray, Nantes).
• PhD in progress; Maud Guillen, "Etude longitudinale de la neuroplasticité cérébrale pour la récupération motrice du membre supérieur post-AVC", CHU/Univ. Rennes from December 2023 to Janvier 2027, Isabelle Bonan, Pierre Maurel, Elise Bannier
• PhD in progress: Elodie Germani, “Mapping the fMRI pipeline-space towards more robust pipelines”, Univ. Rennes, from Oct 2021, Camille Maumet and Elisa Fromont (Lacodam).

11.2.3 Juries

• Fanny Dégeilh: Member - Jury d'Examen général de synthèse (doctorat) : Polytechnique Montréal (Canada)
• Francesca Galassi: Member of Selection Committee (COS) for the position of Associate Professor (Maître de conférence, section 61) Toulouse NeuroImaging Center, Université de Toulouse.
• Emmanuel Caruyer: Reviewer of the PhD thesis of Zheyi Yang, Institut polytechnique de Paris/Inria Saclay.
• Elise Bannier: Reviewer of the PhD Thesis of Giulia Rocco, Université de Nice.
• Elise Bannier: Examiner of the PhD Thesis of Emile Kadalie, Université de Bordeaux.
• Francesca Galassi: Member of Selection Committee (COS) for the position of Associate Professor (Maître de conférence, section 61) Toulouse NeuroImaging Center, Université de Toulouse.
• Emmanuel Caruyer: reviewer of the PhD thesis of Zheyi Yang, Institut polytechnique de Paris/Inria Saclay.
• Pierre Maurel : President of the doctoral defence Jury of Jean-Baptiste de Saint-Aubert, Institut de la Vision, Sorbonne University.
• Pierre Maurel : President of the doctoral defense jury of Thomas Durantel, IRISA, Rennes University.

11.3.1 Internal or external Inria responsibilities

• Claire Cury, mediation Officer of the Inria Rennes Scientific mediation team.
• Camille Maumet is a co-organizer of the local version of the program "L codent L créent", an outreach program to send PhD students to teach Python to middle school students in 8 sessions of 45 minutes. It was initiated in Lille, with Anne-Cécile Orgerie and Tassadit Bouadi. The program is currently supported by: Fondation Blaise Pascal, ED MathSTIC, Inria and Fondation Rennes 1.

11.3.2 Education

• Claire Cury, setting-up a general audience writing workshop for 2nd year PhD students.

11.3.3 Interventions

• Elodie Germani, participating in the LCLC (Elles Codent Elles Créent) program for middle schoolers at Collège Le Landry, Rennes, 8 * 45min of workshops between January and March 2023.
• Elodie Germani, intervention as part of the training on scientific mediation, in the TISSAGE project (TrIptyque Science Société pour AGir Ensemble), May 2023.
• Jérémy Lefort-Besnard, organisateur d’un atelier de conception, câblage et programmation d’un robot avec Arduino

International journals

• 12 articleF.-D.François-Daniel Ardellier, S.Seyyid Baloglu, M.Magdalena Sokolska, V.Vincent Noblet, F.François Lersy, O.Olivier Collange, J.-C.Jean-Christophe Ferré, A.Adel Maamar, B.Béatrice Carsin-Nicol, J.Julie Helms, M.Maleka Schenck, A.Antoine Khalil, A.Augustin Gaudemer, S.Sophie Caillard, J.Julien Pottecher, N.Nicolas Lefèbvre, P.-E.Pierre-Emmanuel Zorn, M.Muriel Matthieu, J. C.Jean Christophe Brisset, C.Clotilde Boulay, V.Véronique Mutschler, Y.Yves Hansmann, P.-M.Paul-Michel Mertes, F.Francis Schneider, S.Samira Fafi-Kremer, M.Mickael Ohana, F.Ferhat Meziani, N.Nicolas Meyer, T.Tarek Yousry, M.Mathieu Anheim, F.François Cotton, H. R.Hans Rolf Jäger, S.Stéphane Kremer, F.Fabrice Bonneville, G.Gilles Adam, G.Guillaume Martin-Blondel, J.Jérémie Pariente, T.Thomas Geeraerts, H.Hélène Oesterlé, F.Federico Bolognini, J.Julien Messie, G.Ghazi Hmeydia, J.Joseph Benzakoun, C.Catherine Oppenheim, J.-M.Jean-Marc Constans, S.Serge Metanbou, A.Adrien Heintz, B.Blanche Bapst, I.Imen Megdiche, L.Lavinia Jager, P.Patrick Nesser, Y. T.Yannick Talla Mba, T.Thomas Tourdias, J.Juliette Coutureau, C.Céline Hemmert, P.Philippe Feuerstein, N.Nathan Sebag, S.Sophie Carre, M.Manel Alleg, C.Claire Lecocq, E.Emmanuel Schmitt, R.René Anxionnat, F.François Zhu, G.Géraud Forestier, A.Aymeric Rouchaud, P.-O.Pierre-Olivier Comby, F.Frederic Ricolfi, P.Pierre Thouant, S.Sylvie Grand, A.Alexandre Krainik, I.Isaure de Beaurepaire, G.Grégoire Bornet, A.Audrey Lacalm, P.Patrick Miailhes, J.Julie Pique, C.Claire Boutet, X.Xavier Fabre, B.Béatrice Claise, S.Sonia Mirafzal, L.Laure Calvet, H.Hubert Desal, J.Jérome Berge, G.Grégoire Boulouis, A.Apolline Kazemi, N.Nadya Pyatigorskaya, A.Augustin Lecler, S.Suzana Saleme, M.Myriam Edjlali-Goujon, B.Basile Kerleroux, J.-C.Jean-Christophe Brisset and S.Samir Chenaf. Cerebral perfusion using ASL in patients with COVID-19 and neurological manifestations: A retrospective multicenter observational study.Journal de Neuroradiologie / Journal of NeuroradiologyJanuary 2023HALDOI
• 13 articleJ.-M.Jean-Marie Batail, I.Isabelle Corouge, B.Benoit Combès, C.Camille Conan, M.Muriel Guillery-Sollier, M.Marc Vérin, P.Paul Sauleau, F.Florence Le Jeune, J.-Y.Jean-Yves Gauvrit, J.-Y.Jen-Yves Gauvrit, G.Gabriel Robert, C.Christian Barillot, J.-C.Jean-Christophe Ferré and D.Dominique Drapier. Apathy in depression: An arterial spin labeling perfusion MRI study.Journal of Psychiatric Research157January 2023, 7-16HALDOIback to text
• 14 articleM.Miriam Beauchamp, F.Fanny Dégeilh and S.Sean Rose. Improving outcome after paediatric concussion: challenges and possibilities.The Lancet Child & Adolescent Health710October 2023, 728-740HALDOIback to text
• 15 articleJ.Jeremy Beaumont, J.Jurgen Fripp, P.Parnesh Raniga, O.Oscar Acosta, J.-C.Jean-Christophe Ferré, K.Katie Mcmahon, J.Julie Trinder, T.Tobias Kober and G.Giulio Gambarota. Multi T1-weighted contrast imaging and T1 mapping with compressed sensing FLAWS at 3 T.Magnetic Resonance Materials in Physics, Biology and Medicine2023, 1-44HALDOI
• 16 articleA.Anamaria Bogdan, R.Roxane Fabre, T.Thomas Desmidt, J.Jérôme Golebiowski, J.Jérémie Topin, I.Ingrid Bethus, O.Olivier Hanon, C.Claire Boutoleau-Bretonniere, N.Nathalie Wagemann, C.Cédric Annweiler, P.-J.Pierre-Jean Ousset, O.Olivier Godefroy, I.Isabelle Rouch, M.Marc Paccalin, M.Maryana Sukhorukova, A.Audrey Gabelle, G.Gabriel Robert and R.Renaud David. Different Trajectories of Apathy and Depression Among Subjective Cognitive Impairment Individuals with or without Conversion to Dementia: Results from the Memento Cohort in France.Journal of Alzheimer's Disease952September 2023, 415-426HALDOI
• 17 articleE.Elena Bonke, A.Amanda Clauwaert, S.Stefan Hillmann, U.Uta Tacke, C.Caroline Seer, E.Eukyung Yhang, Y.Yorghos Tripodis, S.Stian Sandmo, T. L.Tim L.T. Wiegand, D.David Kaufmann, E.Elisabeth Kaufmann, S.Sutton Richmond, M.Malo Gaubert, J.Johanna Seitz-Holland, A.Alexander Leemans, S.Stephan Swinnen, R.Roald Bahr, O.Ofer Pasternak, F.Florian Heinen, I.Inga Koerte, M.Michaela Bonfert and J.Jolien Gooijers. Neurological soft signs are associated with reduced medial-lateral postural control in adolescent athletes.Journal of the Neurological Sciences445February 2023, 120516HALDOI
• 18 articleM.Marine Cacioppo, H.Helene Menard, C.Camille Olivari-Philiponnet, E.Estelle Le Pabic, C.Charlène Brochard, B.Benoît Peyronnet, P.Philippe Violas, L.Laurent Riffaud and I.Isabelle Bonan. Prevalence and risk factors for scoliosis in adults with closed and open spina bifida: A large, cross-sectional study.Annals of Physical and Rehabilitation Medicine6622023, 101685HALDOI
• 19 articleM.Mélanie Cogné, A.Arthur Delayre, P.Pauline Coignard, J.-L.Jean-Luc Le Guiet, P.-A.Pierre-Alain Joseph, I.Isabelle Bonan, E.Eric Sorita, C.Claire Le Gall and P.Philippe Azouvi. Combined visual and auditory cues do not improve virtual spatial navigation after traumatic brain injury.Annals of Physical and Rehabilitation Medicine668November 2023, 101758HALDOI
• 20 articleO.Olivier Commowick, B.Benoît Combès, F.Frédéric Cervenansky and M.Michel Dojat. Editorial: Automatic methods for multiple sclerosis new lesions detection and segmentation.Frontiers in Neuroscience172023, 1176625HALDOI
• 21 articleF.Fanny Dégeilh, J.Jessica Lacombe-Barrios, C.Carola Tuerk, C.Catherine Lebel, V.Véronique Daneault, R.Ramy El-Jalbout, J.Jocelyn Gravel, S.Sylvain Deschênes, J.Josée Dubois, C.Chantale Lapierre, I.Isabelle Gagnon, M.Mathieu Dehaes, T. M.Thuy Mai Luu and M.Miriam Beauchamp. Behavioral-play familiarization for non-sedated magnetic resonance imaging in young children with mild traumatic brain injury.Pediatric RadiologyFebruary 2023, 1-31HALDOIback to text
• 22 articleF.Fanny Dégeilh, É.Élizabel Leblanc, V.Véronique Daneault, M.Miriam Beauchamp and A.Annie Bernier. Longitudinal associations between mother-child attachment security in toddlerhood and white matter microstructure in late childhood: a preliminary investigation.Attachment and Human Development2023, 291-310HALDOI
• 23 articleF.Fanny Dégeilh, T.Tilmann von Soest, L.Lia Ferschmann, J.Joanne Beer, M.Malo Gaubert, I.Inga Koerte and C.Christian Tamnes. Social problems and brain structure development following childhood mild traumatic brain injury.Cortex162May 2023, 26-37HALDOIback to text
• 24 articleG.Gilles Edan and E.Emmanuelle Le Page. Escalation Versus Induction/High-Efficacy Treatment Strategies for Relapsing Multiple Sclerosis: Which is Best for Patients?Drugs83152023, 1351-1363HALDOI
• 25 articleN.N Erhart, E.E Bannier, I.I Corouge, I.I Abaakil and J.-C.J-C Ferré. 15 minutes pour comprendre la spectroscopie du proche infrarouge (NIRS) en imagerie cérébrale fonctionnelle.Journal d'imagerie diagnostique et interventionnelleFebruary 2023, 1-12HALDOIback to text
• 26 articleA.Agustina Fragueiro, C.Claire Cury, F.Federica Santacroce, F.Ford Burles, G.Giuseppe Iaria and G.Giorgia Committeri. Medial positioning of the hippocampus and hippocampal fissure volume in Developmental Topographical Disorientation.Hippocampus2024HALDOIback to text
• 27 articleM.Malo Gaubert, A.Andrea Dell’orco, C.Catharina Lange, A.Antoine Garnier-Crussard, I.Isabella Zimmermann, M.Martin Dyrba, M.Marco Duering, G.Gabriel Ziegler, O.Oliver Peters, L.Lukas Preis, J.Josef Priller, E. J.Eike Jakob Spruth, A.Anja Schneider, K.Klaus Fliessbach, J.Jens Wiltfang, B.Björn Schott, F.Franziska Maier, W.Wenzel Glanz, K.Katharina Buerger, D.Daniel Janowitz, R.Robert Perneczky, B.-S.Boris-Stephan Rauchmann, S.Stefan Teipel, I.Ingo Kilimann, C.Christoph Laske, M.Matthias Munk, A.Annika Spottke, N.Nina Roy, L.Laura Dobisch, M.Michael Ewers, P.Peter Dechent, J. D.John Dylan Haynes, K.Klaus Scheffler, E.Emrah Düzel, F.Frank Jessen and M.Miranka Wirth. Performance evaluation of automated white matter hyperintensity segmentation algorithms in a multicenter cohort on cognitive impairment and dementia.Frontiers in Psychiatry13January 2023, 1-14HALDOI
• 28 articleE.Elodie Germani, E.Elisa Fromont and C.Camille Maumet. On the benefits of self-taught learning for brain decoding.GigaScience12May 2023, 1-17HALDOIback to text
• 29 articleG.Gabriel Girard, J.Jonathan Rafael-Patiño, R.Raphaël Truffet, D. B.Dogu Baran Aydogan, N.Nagesh Adluru, V. A.Veena A Nair, V.Vivek Prabhakaran, B. B.Barbara B Bendlin, A. L.Andrew L Alexander, S.Sara Bosticardo, I.Ilaria Gabusi, M.Mario Ocampo-Pineda, M.Matteo Battocchio, Z.Zuzana Piskorova, P.Pietro Bontempi, S.Simona Schiavi, A.Alessandro Daducci, A.Aleksandra Stafiej, D.Dominika Ciupek, F.Fabian Bogusz, T.Tomasz Pieciak, M.Matteo Frigo, S.Sara Sedlar, S.Samuel Deslauriers-Gauthier, I.Ivana Kojčić, M.Mauro Zucchelli, H.Hiba Laghrissi, Y.Yang Ji, R.Rachid Deriche, K. G.Kurt G Schilling, B. A.Bennett A Landman, A.Alberto Cacciola, G. A.Gianpaolo Antonio Basile, S.Salvatore Bertino, N.Nancy Newlin, P.Praitayini Kanakaraj, F.Francois Rheault, P.Patryk Filipiak, T. M.Timothy M Shepherd, Y.-C.Ying-Chia Lin, D. G.Dimitris G Placantonakis, F. E.Fernando E Boada, S. H.Steven H Baete, E.Erick Hernández-Gutiérrez, A.Alonso Ramírez-Manzanares, R.Ricardo Coronado-Leija, P.Pablo Stack-Sánchez, L.Luis Concha, M.Maxime Descoteaux, C.Caio Seguin, A.Andrew Zalesky, K.Kenji Marshall, E. J.Erick J Canales-Rodríguez, Y.Ye Wu, S.Sahar Ahmad, P.-T.Pew-Thian Yap, A.Antoine Théberge, F.Florence Gagnon, F.Frédéric Massi, E.Elda Fischi-Gomez, R.Rémy Gardier, J. L.Juan Luis Villarreal Haro, M.Marco Pizzolato, E.Emmanuel Caruyer and J.-P.Jean-Philippe Thiran. Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge.NeuroImage277June 2023, 1-11HALDOIback to text
• 30 articleA.Ambre Godet, Y.Yann Serrand, A.Alexandra Fortier, B.Brieuc Leger, E.Elise Bannier, D.David Val-Laillet and N.Nicolas Coquery. Subjective feeling of control during fNIRS-based neurofeedback targeting the DL-PFC is related to neural activation determined with short-channel correction.PLoS ONE1882023, 0290005HALDOIback to text
• 31 articleE. Y.Elie Yutong Guo, É.Élizabel Leblanc, F.Fanny Dégeilh, M.Miriam Beauchamp and A.Annie Bernier. Prospective associations between maternal mind-mindedness, child theory of mind, and brain morphology in school-aged children.Social Neuroscience2023, 1-44HALDOI
• 32 articleA.Aya Kabbara, N.Nina Forde, C.Camille Maumet and M.Mahmoud Hassan. Successful reproduction of a large EEG study across software packages.Neuroimage: Reports322023, 100169HALDOIback to text
• 33 articleS.Simon Lamy, D.David Veillard, H.Helene Doyen, A.Anne Kerbrat, L.Laure Michel, E.Emilie Chretien, A.Ahmad Ousmen, G.Giles Edan and E.Emmanuelle Le Page. Switching from natalizumab administration at the day hospital to administration at home. A 1 year prospective study of patient experience and quality of life in 30 consecutive patients with multiple sclerosis (TYSAD-35).Multiple Sclerosis and Related Disorders732023, 104657HALDOI
• 34 articleV.Valeria Manera, C.Claudia Partos, O.Olivier Beauchet, M.Michel Benoit, B.Benjamin Dupetit, J.Julia Elbaum, R.Roxane Fabre, M.Morgane Gindt, A.Auriane Gros, R.Rachid Guerchouche, S.Stefan Klöppel, A.Alexandra König, A.Annick Martin, A.Aurélie Mouton, M.-P.Marie-Pierre Pancrazi, A.Antonios Politis, G.Gabriel Robert, G.Guillaume Sacco, S.Sabrina Sacconi, K.Kim Sawchuk, F.Fabio Solari, L.Lucille Thiebot, P. D.Pietro Davide Trimarchi, R.Radia Zeghari and P.Philippe Robert. Teleconsultations for mental health: Recommendations from a Delphi panel.Internet Interventions34December 2023, 100660-100660HALDOI
• 35 articleK.Kevin de Matos, C.Claire Cury, L.Lydia Chougar, L. T.Lachlan T Strike, T.Thibault Rolland, M.Maximilien Riche, L.Lisa Hemforth, A.Alexandre Martin, T.Tobias Banaschewski, A. L.Arun L W Bokde, S.Sylvane Desrivières, H.Herta Flor, A.Antoine Grigis, H.Hugh Garavan, P.Penny Gowland, A.Andreas Heinz, R.Rüdiger Brühl, J.-L.Jean-Luc Martinot, M.-L.Marie-Laure Paillère Martinot, E.Eric Artiges, F.Frauke Nees, J. H.Juliane H Fröhner, H.Herve Lemaitre, D.Dimitri Papadopoulos Orfanos, T.Tomáš Paus, L.Luise Poustka, S.Sarah Hohmann, S.Sabina Millenet, J. H.Juliane H Fröhner, M. N.Michael N Smolka, N.Nilakshi Vaidya, H.Henrik Walter, R.Robert Whelan, G.Gunter Schumann, V.Vincent Frouin, M.Meritxell Bach Cuadra, O.Olivier Colliot and B.Baptiste Couvy-Duchesne. Temporo-basal sulcal connections: a manual annotation protocol and an investigation of sexual dimorphism and heritability.Brain Structure and Function2286June 2023, 1459-1478HALDOIback to text
• 36 articleA.Abdallah Namoun, M.Mohammad Ali Humayun, O.Oussama Benrhouma, B. R.Burhan Rashid Hussein, A.Ali Tufail, A.Abdullah Alshanqiti and W.Waqas Nawaz. Service Selection Using an Ensemble Meta-Learning Classifier for Students with Disabilities.Multimodal Technologies and Interaction752023, 1-18HALDOI
• 37 articleT.Thibaud Orcel, H. T.H. T. Chau, B.Bruno Turlin, J.Julien Chaigneau, E.Elise Bannier, P.Philippe Otal, E.Eric Frampas, A.Arnaud Leguen, A.Anne Boulic, H.Hervé Saint-Jalmes, C.Christophe Aubé, J.Jérôme Boursier, E.Edouard Bardou-Jacquet and Y.Yves Gandon. Evaluation of proton density fat fraction (PDFF) obtained from a vendor-neutral MRI sequence and MRQuantif software.European Radiology2023, -HALDOI
• 38 articleJ.-C.Jean-Charles Roy, T.Thomas Desmidt, S.Sébastien Dam, I.Iris Mirea-Grivel, L.Louise Weyl, E.Elise Bannier, L.Laurent Barantin, D.Dominique Drapier, J.-M.Jean-Marie Batail, R.Renaud David, J.Julie Coloigner and G. H.Gabriel H Robert. Connectivity patterns of the core resting-state networks associated with apathy in late-life depression.Journal of Psychiatry and Neuroscience486November 2023, E404 - E413HALDOIback to text
• 39 articleH.Haykel Snoussi, J.Julien Cohen-Adad, B.Benoît Combès, É.Élise Bannier, S.Slimane Tounekti, A.Anne Kerbrat, C.Christian Barillot and E.Emmanuel Caruyer. Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord.Brain and Behavior1311September 2023, e3159HALDOI
• 40 articleW.Whitney Stee, A.Antoine Legouhy, M.Michele Guerreri, T.Thomas Villemonteix, H.Hui Zhang and P.Philippe Peigneux. Microstructural dynamics of motor learning and sleep-dependent consolidation: A diffusion imaging study.iScience2612December 2023, 108426HALDOI
• 41 articleC.Chau Vu, A.Adam Bush, M.Matthew Borzage, S.Soyoung Choi, J.Julie Coloigner, S.Shayan Farzad, Y.Yaqiong Chai, T.Thomas Coates and J.John Wood. Brain BOLD and NIRS response to hyperoxic challenge in sickle cell disease and chronic anemias.Magnetic Resonance Imaging100July 2023, 26-35HALDOIback to text

International peer-reviewed conferences

• 42 inproceedingsF.Fanny Dégeilh, T.Tilmann von Soest, C.Claire Cury, L.Lia Ferschmann and C. K.Christian K Tamnes. Pre-post change in mental health and brain structure in pediatric mild traumatic brain injury.IBIA 2023 - 14th Biennial World Congress on Brain Injury378Dublin, IrelandJuly 2023, 758-1040HALDOI
• 43 inproceedingsA.Agustina Fragueiro, G.Giorgia Committeri and C.Claire Cury. Incomplete Hippocampal Inversion and Hippocampal Subfield Volumes: Implementation and inter-reliability of automatic segmentation.ISBI 2023 - 20th IEEE International Symposium on Biomedical ImagingCarthagène des Indes, ColombiaIEEE2023, 1-5HALDOIback to text
• 44 inproceedingsM.Malo Gaubert, B.Benoit Combès, E.Elise Bannier, A.Arthur Masson, V.Vivien Caron, G.Gaëlle Baudron, J.-C.Jean-Christophe Ferré, E.Emmanuelle Le Page, L.Laure Michel, B.Bruno Stankoff, G.Gilles Edan, B.Benedetta Bodini and A.Anne Kerbrat. Myelin dynamics in the spinal cord predict cord atrophy and disability progression at 5-years in early relapsing-remitting MS.ECTRIMS 2023 - 39th Congress of the European Committee for Treatment and Research in Multiple SclerosisMilano, Italy2023, 1-2HALback to text
• 45 inproceedingsM.Malo Gaubert, B.Benoit Combès, J.-C.Jean-Christophe Ferré, A.Alice Dufey, R.Raphaël Chouteau, A.Anne Kerbrat, E.Elise Bannier and V.Virginie Callot. Simultaneous brain and cervical spinal cord MP2RAGE for T1 measurement: robustness and sensitivity for tissue modification assessment in multiple sclerosis in a multicenter context.ESMRBM 2023 - 40th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and BiologyBâle, Switzerland2023, 1-5HALback to text
• 46 inproceedingsL. J.Lisa J Hemforth, C.Claire Cury, V.Vincent Frouin, S.Sylvane Desrivières, A.Antoine Grigis, H.Hugh Garavan, R.Rüdiger Brühl, J.-L.Jean-Luc Martinot, M.-L.Marie-Laure Paillère Martinot, E.Eric Artiges, L.Luise Poustka, S.Sarah Hohmann, S.Sabina Millenet, N.Nilakshi Vaidya, H.Henrik Walter, R.Robert Whelan, G.Gunter Schumann, B.Baptiste Couvy-Duchesne and O.Olivier Colliot. Interpretable automatic detection of incomplete hippocampal inversions using anatomical criteria.SPIE Medical Imaging 2023San Diego (California), United StatesFebruary 2023, 1-7HALback to text
• 47 inproceedingsB. R.Burhan Rashid Hussein, C.Cédric Meurée, M.Malo Gaubert, A.Arthur Masson, A.Anne Kerbrat, B.Benoît Combès and F.Francesca Galassi. A study on loss functions and decision thresholds for the segmentation of multiple sclerosis lesions on spinal cord MRI.2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)20th IEEE International Symposium on Biomedical Imaging (ISBI 2023)Cartagena (Colombia), ColombiaApril 2023HALback to text
• 48 inproceedingsP.-Y.Pierre-Yves Jonin, A.Audrey Lavenu, M.Mélissa Brossais and A.Audrey Noël. Familiar faces recognition across the lifespan: Subjective memorability enhances encoding beyond prior knowledge.2023 - 3rd edition of the international conference "Cognitive neuroscience of memory: Recollection, familiarity and novelty detection170Liège, Belgium2023, 106043HALDOI
• 49 inproceedingsN.Nicolas Vianne, M.M. Abbas, J.-C.Jean-Charles Roy, G.Gabriel Robert and R.Régine Le Bouquin Jeannès. A Promising Approach to Detect Signs of Apathy from a Single Tri-axial Accelerometer.ICABME - 2023 Seventh International Conference on Advances in Biomedical EngineeringBeirut, LebanonOctober 2023HALDOI
• 50 inproceedingsR.Ricky Walsh, C.Cédric Meurée, A.Anne Kerbrat, A.Arthur Masson, B. R.Burhan Rashid Hussein, M.Malo Gaubert, F.Francesca Galassi and B.Benoit Combés. Expert Variability and Deep Learning Performance in Spinal Cord Lesion Segmentation for Multiple Sclerosis Patients.2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS)CBMS 2023 - 36th IEEE International Symposium on Computer-Based Medical Systems (CBMS)L'Aquila, ItalyIEEE; IEEEJune 2023, 1-8HALDOIback to text

Conferences without proceedings

• 51 inproceedingsJ.Jeremy Lefort-Besnard, T. E.Thomas E Nichols and C.Camille Maumet. Systematic review and evaluation of meta-analysis methods for same data meta-analyses.Cogbases-2023 - Workshop on open science methods for analyzing brain imaging dataParis, France2023, 1-1HALback to text

Reports & preprints

• 52 miscT.Thomas Durantel, G.Gabriel Girard, E.Emmanuel Caruyer, O.Olivier Commowick and J.Julie Coloigner. A Riemannian framework for incorporating white matter bundle priors in ODF-based tractography algorithms..October 2023HALback to text
• 53 miscM.Mathis Fleury, P.Patrícia Figueiredo, A.Athanasios Vourvopoulos and A.Anatole Lécuyer. Two is better ? Combining EEG and fMRI for BCI and Neurofeedback : A systematic review.March 2023HALback to text
• 54 miscA.Agustina Fragueiro, G.Giorgia Committeri and C.Claire Cury. Incomplete hippocampal inversion and hippocampal subfield volumes: Implementation and inter-reliability of automatic segmentation.April 2023HALback to text
• 55 miscE.Elodie Germani, E.Elisa Fromont and C.Camille Maumet. Uncovering communities of pipelines in the task-fMRI analytical space.December 2023HALback to text
• 56 miscE.Elodie Germani, E.Elisa Fromont, P.Pierre Maurel and C.Camille Maumet. The HCP multi-pipeline dataset: an opportunity to investigate analytical variability in fMRI data analysis.December 2023HALback to text
• 57 miscP.Patrick Héas, C.Cédric Herzet and B.Benoit Combès. Non-Linear Reduced Modeling by Generalized Kernel-Based Dynamic Mode Decomposition.December 2023HAL
• 58 miscJ.Jeremy Lefort-Besnard, T. E.Thomas E. Nichols and C.Camille Maumet. Systematic review and evaluation of meta-analysis methods for same data meta-analyses in a multiverse setting.March 2024HAL
• 59 miscR. A.Russell A. Poldrack, C. J.Christopher J. Markiewicz, S.Stefan Appelhoff, Y. K.Yoni K. Ashar, T.Tibor Auer, S.Sylvain Baillet, S.Shashank Bansal, L.Leandro Beltrachini, C. G.Christian G. Benar, G.Giacomo Bertazzoli, S.Suyash Bhogawar, R. W.Ross W. Blair, M.Marta Bortoletto, M.Mathieu Boudreau, T. L.Teon L. Brooks, V. D.Vince D. Calhoun, F. M.Filippo Maria Castelli, P.Patricia Clement, A. L.Alexander L Cohen, J.Julien Cohen-Adad, S.Sasha d'Ambrosio, G.Gilles de Hollander, M.María de la Iglesia-Vayá, A.Alejandro de la Vega, A.Arnaud Delorme, O.Orrin Devinsky, D.Dejan Draschkow, E. P.Eugene Paul Duff, E.Elizabeth Dupre, E.Eric Earl, O.Oscar Esteban, F. W.Franklin W. Feingold, G.Guillaume Flandin, A.Anthony Galassi, G.Giuseppe Gallitto, M.Melanie Ganz, R.Rémi Gau, J.James Gholam, S. S.Satrajit S. Ghosh, A.Alessio Giacomel, A. G.Ashley G Gillman, P.Padraig Gleeson, S.Samuel Guay, T.Tal Yarkoni, K. J.Krzysztof J. Gorgolewski, A.Alexandre Gramfort, G.Giacomo Guidali, Y. O.Yaroslav O. Halchenko, D. A.Daniel A. Handwerker, N.Nell Hardcastle, P.Peer Herholz, D.Dora Hermes, C. J.Christopher J. Honey, R. B.Robert B. Innis, H.-I.Horea-Ioan Ioanas, A.Andrew Jahn, A.Agah Karakuzu, D. B.David B. Keator, G.Gregory Kiar, B.Balint Kincses, A. R.Angela R. Laird, J. C.Jonathan C. Lau, A.Alberto Lazari, J. H.Jon Haitz Legarreta, A.Adam Li, X.Xiangrui Li, B. C.Bradley C. Love, H.Hanzhang Lu, G.Giacomo Mazzamuto, S.Sajjad Torabian, B.Bradley Voytek, J.Julius Welzel, M.Martin Wilson, C.Camille Maumet, S. L.Steven L. Meisler, M.Mark Mikkelsen, H.Henk Mutsaerts, T. E.Thomas E. Nichols, A.Aki Nikolaidis, G.Gustav Nilsonne, G.Guiomar Niso, M.Martin Norgaard, T. W.Thomas W Okell, R.Robert Oostenveld, E.Eduard Ort, P. J.Patrick J. Park, M.Mateusz Pawlik, C. R.Cyril R. Pernet, F.Franco Pestilli, J.Jan Petr, C.Christophe Phillips, J.-B.Jean-Baptiste Poline, L.Luca Pollonini, P. R.Pradeep Reddy Raamana, P.Petra Ritter, G.Gaia Rizzo, K. A.Kay A. Robbins, A. P.Alexander P. Rockhill, C.Christine Rogers, A.Ariel Rokem, C.Chris Rorden, J. M.Jose Manuel Saborit-Torres, A. M.Alexandre M Routier, R. E.Robert E. Smith, T.Tamas Spisak, J.Julia Sprenger, N. C.Nicole C. Swann, M.Martin Szinte, S.Sylvain Takerkart, B.Bertrand Thirion, A. G.Adam G. Thomas, T.Taylor Salo, M.Michael Schirner and G.Gaël Varoquaux. The Past, Present, and Future of the Brain Imaging Data Structure (BIDS).September 2023HAL

Other scientific publications

• 60 inproceedingsC.Constance Bocquillon, M.Marc Lapert, E.Elise Bannier, I.Isabelle Corouge and E.Emmanuel Caruyer. Étude de l’effet du bruit sur l'estimation de l'anisotropie microscopique en IRM de diffusion.SFRMBM 2023 - Sixième congrès de la Société Française de Résonance Magnétique en Biologie et MédecineParis, FranceMarch 2023HALback to text
• 61 inproceedingsA.Agustina Fragueiro, G.Giorgia Committeri and C.Claire Cury. Incomplete Hippocampal Inversion and hippocampal subfield volumes: Implementation and inter-reliability of automatic segmentation.ISBI 2023 - IEEE International Symposium on Biomedical ImagingCarthagène des Indes, ColombiaIEEE2023, 1HAL
• 62 inproceedingsA.Agustina Fragueiro, R.-P.Renè-Paul Debroize, A.Antoine Coutrot, E.Elise Bannier and C.Claire Cury. Pilot Study: eye-tracking and skin conductance to monitor task engagement during bimodal neurofeedback.ISBI 2023Carthagène des Indes, ColombiaApril 2023HALback to text
• 63 miscA.Agustina Fragueiro, F.F. Santacroce, F.Ford Burles, C.Claire Cury, G.Giuseppe Laria and G.Giorgia Committeri. Shift in hippocampal medial position and increased fissure volumes in individuals affected by Developmental Topographical Disorientation.Thessaloniki, GreeceSeptember 2023, 1-1HALback to text
• 64 inproceedingsM.Malo Gaubert, E.Elise Bannier, R.Raphaël Chouteau, V.Virginie Callot, J.-C.Jean-Christophe Ferré, G.Guillaume Hamon, A.Anne Kerbrat and B.Benoit Combès. Transfert d'aimantation (MTR) de l'ensemble de la moelle épinière chez des patients atteints de sclérose en plaques.SFRMBM 2023 - 6ème Congrès de la Société Française de Résonance Magnétique en Biologie et MédecineParis, FranceMarch 2023HAL
• 65 inproceedingsE.Elodie Germani, E.Elisa Fromont and C.Camille Maumet. Exploring variability patterns in the task-fMRI analytical space.OHBM 2023 - 29th Annual Meeting of the Organization for Human Brain MappingMontreal, CanadaJuly 2023HAL
• 66 inproceedingsE.Elodie Germani, E.Elisa Fromont and C.Camille Maumet. Representation learning for more reproducible fMRI data analyses.IABM 2023 - Colloque Français d'Intelligence Artificielle en Imagerie BiomédicalParis, FranceMarch 2023, 1HALback to text
• 67 inproceedingsB. R.Burhan Rashid Hussein, C.Cédric Meurée, M.Malo Gaubert, A.Arthur Masson, A.Anne Kerbrat, B.Benoît Combès and F.Francesca Galassi. A study on loss functions and decision thresholds for the segmentation of multiple sclerosis lesions on spinal cord MRI.IABM 2023 - Colloque Français d'Intelligence Artificielle en Imagerie BiomédicaleParis, FranceMarch 2023HALback to text
• 68 inproceedingsN.Nolwenn Jégou, E.Elise Bannier, N.Nora Erhart, H. H.Hector H Garcia, E.Emmanuel Caruyer and I.Isabelle Corouge. Reproductibilité d'une tâche motrice en NIRS et comparaison à l'IRMf BOLD sur des sujets adultes sains.SFRMBM 2023 - 6ème Congrès Scientifique de la Société Française de Résonance Magnétique en Biologie et MédecineParis, FranceMarch 2023, 1-1HALback to text
• 69 miscJ.Jeremy Lefort-Besnard, C.Camille Maumet, B.Boris Clenet and E.Elodie Germani. Presentation of the project 'Narps Open Pipeline'.Paris, France2023HALback to text
• 70 inproceedingsA.Arthur Masson, B.Benoit Combès, R.Romain Casey, F.François Cotton, A.Alice Dufey, D.David‐axel Laplaud, E.Eric Thouvenot, E.Emmanuelle Leray, J.Jonathan Epstein, F.Francis Guillemin, S.Sandra Vukusic and A.Anne Kerbrat. Can we accurately assess disease activity using automated methods in large real-life MRI databases?: Insights from the OFSEP HD database..MSMilan2023Milano (Italy), Italy2023HALback to text
• 71 miscC.Camille Maumet. BIDS-Prov: Recording neuroimaging provenance.Copenhagen, DenmarkJune 2023HAL
• 72 misc C.Camille Maumet. Different analysis pipelines, different results... How to deal with analytical variability? Cartagena (Colombia), Colombia April 2023 HAL
• 73 miscC.Camille Maumet. Intervenante dans la table ronde "Information, consentement au traitement des données et au recours à l'IA".Rennes, FranceJune 2023, 1-1HALback to text
• 74 miscC.Camille Maumet. Introduction to the special session "10 years of reproducibility in biomedical research: how can we achieve generalizability and fairness?".Cartagenas de Indias, ColombiaApril 2023, 1-12HAL
• 75 miscC.Camille Maumet. Open science practices for keeping inventions alive after project ends.Basel (CH), SwitzerlandOctober 2023HALback to text
• 76 miscC.Camille Maumet. Reproducible neuroimaging: a review on past and emerging questions.Paris, FranceMarch 2023, 1-27HAL
• 77 miscC.Camille Maumet. Towards reproducible neuroimaging across different analysis pipelines.Paris, France2023HAL
• 78 miscC.Camille Maumet. Towards reusable derived data in neuroimaging.Online, Germany2023, 1-53HAL
• 79 inproceedingsC.Caroline Pinte, C.Claire Cury and P.Pierre Maurel. Améliorer la portabilité du neurofeedback bimodal : prédire par apprentissage automatique les scores NF-IRMf à partir des signaux EEG.IABM 2023 - Colloque Français d'Intelligence Artificielle en Imagerie BiomédicaleParis, France2023HALback to text
• 80 inproceedingsC.Caroline Pinte, C.Claire Cury and P.Pierre Maurel. Improving portability of bimodal neurofeedback: predicting NF-fMRI scores from EEG signals.OHBM 2023 - Organization for Human Brain MappingMontréal, CanadaJuly 2023, 1-1HALback to text
• 81 miscA. S.Adina Svenja Wagner, C.Camille Maumet, M.Melanie Ganz and C.Cassandra Gould van Praag. 10 years of reproducibility in biomedical research: how can we achieve generalizability and fairness?Cartagena de Indias, ColombiaApril 2023, 3HAL

Scientific popularization

• 82 misc F.Francesca Galassi. Deep Learning in Medical Imaging:What's Needed for Training Data? Rennes (Campus Villejean), France October 2023 HAL back to text