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Uncovering the interplay of structure, function, and dynamics of brain connectivity using MRI

Applicant Esteban Sanz-Dranguet Oscar
Number 185872
Funding scheme Ambizione
Research institution Service Radiologie CHUV
Institution of higher education University of Lausanne - LA
Main discipline Information Technology
Start/End 01.06.2020 - 31.05.2024
Approved amount 907'684.00
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All Disciplines (5)

Discipline
Information Technology
Electrical Engineering
Neurophysiology and Brain Research
Neurology, Psychiatry
Biomedical Engineering

Keywords (6)

functional MRI; connectome; diffusion MRI; thalamus; brain; magnetic resonance imaging

Lay Summary (French)

Lead
Découvrir l'interaction de la structure, de la fonction et de la dynamique de la connectivité cérébrale à l'aide de l'IRM
Lay summary

L'imagerie par résonance magnétique (IRM) est potentiellement le moyen le plus direct mais non invasif de sonder l'architecture et l'activité du cerveau in vivo, avec une résolution spatiale et temporelle suffisante pour dévoiler comment la structure du cerveau définit sa fonction distribuée. Cependant, les limites de l'IRM entravent le lien entre la structure, la fonction et la dynamique. En particulier, les mesures obtenues avec l'IRM sont très indirectes, spatio-temporelles incertaines, et sont confondues par d'autres sources de signal RM. Cette complexité constitue un immense défi informatique qui traverse de multiples modalités d'imagerie, y compris des approches de connectivité structurelle, fonctionnelle et dynamique pour comprendre le cerveau humain. Dans ce projet, nous aborderons la fiabilité du flux de travail de neuroimagerie scientifique en testant l'hypothèse selon laquelle la minimisation des effets de confusion sur le prétraitement de l'IRM fonctionnelle et structurelle permettra une approche de modélisation intégrée qui est fondamentale pour la compréhension du cerveau humain.

Dans l'ensemble, ce projet dotera les chercheurs d'un cadre pour l'extraction de réseaux structurels, fonctionnels et dynamiques fiables et précis qui permettent leur modélisation et leur analyse conjointes avec des méthodes interprétables et reproductibles. Nous publierons publiquement deux ensembles de données très utiles pour l'évaluation des méthodes d'extraction du réseau. Enfin, sur la base de l'amélioration du flux de travail de neuroimagerie, nous déchiffrons le rôle de contrôle des noyaux thalamiques sur la connectivité fonctionnelle dynamique, qui est considérée comme un biomarqueur clé de la progression de la maladie.

Direct link to Lay Summary Last update: 28.04.2020

Responsible applicant and co-applicants

Employees

Publications

Publication
Age-Specific Adult Rat Brain MRI Templates and Tissue Probability Maps
MacNicol Eilidh, Wright Paul, Kim Eugene, Brusini Irene, Esteban Oscar, Simmons Camilla, Turkheimer Federico E., Cash Diana (2022), Age-Specific Adult Rat Brain MRI Templates and Tissue Probability Maps, in Frontiers in Neuroinformatics, 15, 669049.
Searching for Imaging Biomarkers of Psychotic Dysconnectivity
Rodrigue Amanda L., Mastrovito Dana, Esteban Oscar, Durnez Joke, Koenis Marinka M.G., Janssen Ronald, Alexander-Bloch Aaron, Knowles Emma M., Mathias Samuel R., Mollon Josephine, Pearlson Godfrey D., Frangou Sophia, Blangero John, Poldrack Russell A., Glahn David C. (2021), Searching for Imaging Biomarkers of Psychotic Dysconnectivity, in Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 6(12), 1135-1144.
The OpenNeuro resource for sharing of neuroscience data
Markiewicz Christopher J, Gorgolewski Krzysztof J, Feingold Franklin, Blair Ross, Halchenko Yaroslav O, Miller Eric, Hardcastle Nell, Wexler Joe, Esteban Oscar, Goncavles Mathias, Jwa Anita, Poldrack Russell (2021), The OpenNeuro resource for sharing of neuroscience data, in eLife, 10, 71774.
NiTransforms: A Python tool to read, represent, manipulate, and apply dimensional spatial transforms
Goncalves Mathias, Markiewicz Christopher, Moia Stefano, Ghosh Satrajit, Poldrack Russell, Esteban Oscar (2021), NiTransforms: A Python tool to read, represent, manipulate, and apply dimensional spatial transforms, in Journal of Open Source Software, 6(65), 3459-3459.
Centering inclusivity in the design of online conferences—An OHBM–Open Science perspective
Levitis Elizabeth, van Praag Cassandra D Gould, Gau Rémi, Heunis Stephan, DuPre Elizabeth, Kiar Gregory, Bottenhorn Katherine L, Glatard Tristan, Nikolaidis Aki, Whitaker Kirstie Jane, Mancini Matteo, Niso Guiomar, Afyouni Soroosh, Alonso-Ortiz Eva, Appelhoff Stefan, Arnatkeviciute Aurina, Atay Selim Melvin, Auer Tibor, Baracchini Giulia, Bayer Johanna M M, Beauvais Michael J S, Bijsterbosch Janine D, Bilgin Isil P, Bollmann Saskia, et al. (2021), Centering inclusivity in the design of online conferences—An OHBM–Open Science perspective, in GigaScience, 10(8), giab051.
Brainhack: Developing a culture of open, inclusive, community-driven neuroscience
Gau Rémi, Noble Stephanie, Heuer Katja, Bottenhorn Katherine L., Bilgin Isil P., Yang Yu-Fang, Huntenburg Julia M., Bayer Johanna M.M., Bethlehem Richard A.I., Rhoads Shawn A., Vogelbacher Christoph, Borghesani Valentina, Levitis Elizabeth, Wang Hao-Ting, Van Den Bossche Sofie, Kobeleva Xenia, Legarreta Jon Haitz, Guay Samuel, Atay Selim Melvin, Varoquaux Gael P., Huijser Dorien C., Sandström Malin S., Herholz Peer, Nastase Samuel A., et al. (2021), Brainhack: Developing a culture of open, inclusive, community-driven neuroscience, in Neuron, 109(11), 1769-1775.
Atlas-Based Brain Extraction Is Robust Across RAT MRI Studies
MacNicol E., Ciric R., Kim E., Censo D. Di, Cash D., Poldrack R. A., Esteban O. (2021), Atlas-Based Brain Extraction Is Robust Across RAT MRI Studies, in 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), Nice, FranceIEEE Xplore, France.
BIDS Statistical Models - An implementation-independent representation of General Linear Models
MarkiewiczChristopher J., BlairRoss W., BottenhornKatherine, ChenGang, De la VegaAlejandro, DuPreElizabeth, EstebanOscar, GhoshSatrajit S., LeeJohn, MaumetCamille, NarayanManjari, NicholsThomas, NielsonDylan, OmbaoHernando, PoldrackRussell A., PolineJean-Baptiste, WagnerAdina, YarkoniTal (2021), BIDS Statistical Models - An implementation-independent representation of General Linear Models, in 2021 OHBM ANNUAL MEETING, Organization for Human Brain Mapping (OHBM), Online Event.
NiBabies: A robust preprocessing workflow tailored for neonate and infant MRI
GoncalvesMathias, MarkiewiczChristopher, StynerMartin, MooreLucille, SniderKathy, EarlEric, SmyserChristopher, ZolleiLilla, PoldrackRussell A., EstebanOscar, FeczkoEric, FairDamien (2021), NiBabies: A robust preprocessing workflow tailored for neonate and infant MRI, in 2021 OHBM ANNUAL MEETING, 27th Organization for Human Brain Mapping (OHBM), Online Event.
Putting pipeline implementation-related variation into perspective for functional connectomics
MilhamMichael, AiLei, LiXinhui, GiavasisSteve, JinHecheng, FrancoAlexandre, VogelsteinJoshua, CraddockCameron, XuTing, EstebanOscar, PoldrackRussell A., SatterthwaiteTheodore (2021), Putting pipeline implementation-related variation into perspective for functional connectomics, in 2021 OHBM ANNUAL MEETING, 27th Organization for Human Brain Mapping (OHBM), Online Event.
The Bermuda Triangle of d- and f-MRI sailors - software for susceptibility distortions (SDCFlows)
Esteban Oscar, Adebimpe Azeez, Markiewicz Christopher, Goncalves Mathias, Blair Ross W., Cieslak Matthew, Naveau Mikaël, Sitek Kevin, Sneve Markus, Provins Céline, MacNicol Eilidh, Satterthwaite Theodore, Poldrack Russell A. (2021), The Bermuda Triangle of d- and f-MRI sailors - software for susceptibility distortions (SDCFlows), in 2021 OHBM ANNUAL MEETING, 27th Organization for Human Brain Mapping (OHBM), Online Event.
Analysis of task-based functional MRI data preprocessed with fMRIPrep
Esteban Oscar, Ciric Rastko, Finc Karolina, Blair Ross W., Markiewicz Christopher J., Moodie Craig A., Kent James D., Goncalves Mathias, DuPre Elizabeth, Gomez Daniel E. P., Ye Zhifang, Salo Taylor, Valabregue Romain, Amlien Inge K., Liem Franziskus, Jacoby Nir, Stojić Hrvoje, Cieslak Matthew, Urchs Sebastian, Halchenko Yaroslav O., Ghosh Satrajit S., De La Vega Alejandro, Yarkoni Tal, Wright Jessey, et al. (2020), Analysis of task-based functional MRI data preprocessed with fMRIPrep, in Nature Protocols, 15(7), 2186-2202.
Software Tool to Read, Represent, Manipulate, and Apply N-Dimensional Spatial Transforms
Esteban O., Goncalves M., Markiewicz C. J., Ghosh S. S., Poldrack R. A. (2020), Software Tool to Read, Represent, Manipulate, and Apply N-Dimensional Spatial Transforms, in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, USAIEEE Xplore, USA.
NiPreps: enabling the division of labor in neuroimaging beyond fMRIPrep
EstebanOscar, et al. (2020), NiPreps: enabling the division of labor in neuroimaging beyond fMRIPrep, in 26th Annual Meeting of the Organization for Human Brain Mapping, Organization for Human Brain Mapping (OHBM), Online Event.
Pydra - a flexible and lightweight dataflow engine for scientific analyses
JareckaDorota, GoncalvesMathias, MarkiewiczChristopher, EstebanOscar, LoNicole, KaczmarzykJakub (2020), Pydra - a flexible and lightweight dataflow engine for scientific analyses, in Proc. of the 19th Python In Science Conf. (SCIPY 2020), SCIPY, Online Event.
ASLPrep: A Generalizable Platform for Processing of Arterial Spin Labeled MRI and Quantification of Regional Brain Perfusion
AdebimpeAzeez, BertoleroMaxwell, DoluiSudipto, CieslakMatthew, MurthaKristin, BallerErica B., BoeveBradley, BoxerAdam, ButlerEllyn R., CookPhil, ColcombeStan, CovitzSydney, DavatzikosChristos, DavilaDiego G, ElliottMark A., FloundersMatthew W., FrancoAlexandre R., GurRaquel E., GurRuben C., JaberBasma, McMillianCorey, ALLFTD Consortium, MilhamMichael, MutsaertsHenk JMM, OatheDesmond J., OlmChristopher A., PhillipsJeffrey S., TackettWill, RoalfDavid R., RosenHoward, TaperaTinashe M., TisdallM. Dylan, EstebanOscar, PoldrackRussell A., DetreJohn A., SatterthwaiteTheodore D., ASLPrep: A Generalizable Platform for Processing of Arterial Spin Labeled MRI and Quantification of Regional Brain Perfusion, in Nature Methods, n/a.

Datasets

The TemplateFlow Archive

Author Esteban, Oscar; et al.,
Publication date 10.01.2021
Persistent Identifier (PID) RRID:SCR_021876
Repository TemplateFlow
Abstract
Reference anatomies of the brain and corresponding atlases play a central role in experimental neuroimaging workflows and are the foundation for reporting standardized results. The choice of such references -i.e., templates- and atlases is one relevant source of methodological variability across studies, which has recently been brought to attention as an important challenge to reproducibility in neuroscience. TemplateFlow is a publicly available framework for human and nonhuman brain models. The framework combines an open database with software for access, management, and vetting, allowing scientists to distribute their resources under FAIR -findable, accessible, interoperable, reusable- principles. TemplateFlow supports a multifaceted insight into brains across species, and enables multiverse analyses testing whether results generalize across standard references, scales, and in the long term, species, thereby contributing to increasing the reliability of neuroimaging results.Please visit www.templateflow.org for a more comprehensive description of this project. News and some discussions take place at the Nipy discourse platform [https://nipy.discourse.group/c/nipreps/9].## VisionThe rationale behind TemplateFlow and how we envision it as a fundamental instrument to neuroimaging studies is presented in our preprint: Ciric R. et al., 2021. doi:10.1101/2021.02.10.430678

Collaboration

Group / person Country
Types of collaboration
Medical Image Analysis Laboratory (CHUV) Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Exchange of personnel
- Industry/business/other use-inspired collaboration
Poldracklab (Stanford University) United States of America (North America)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
- Research Infrastructure
- Exchange of personnel
- Industry/business/other use-inspired collaboration

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
BrainHack Donostia 2021 Individual talk Building the NiPreps community 17.11.2021 online, Spain Esteban Sanz-Dranguet Oscar;
27th Organization for Human Brain Mapping (OHBM) Poster The Bermuda Triangle of d- and f-MRI sailors - software for susceptibility distortions (SDCFlows) 21.06.2021 Online, Switzerland Esteban Sanz-Dranguet Oscar; Provins Céline;
OHBM 2021 Open Science Room Talk given at a conference Panel “The future of open tools/technologies” (Moderator role) 21.06.2021 online, Switzerland Esteban Sanz-Dranguet Oscar;
ISBI 2021 Tutorial Talk given at a conference Implementing a head-motion correction algorithm for diffusion MRI 19.04.2021 online, France Provins Céline; Esteban Sanz-Dranguet Oscar;
BrainHack Donostia 2020 Individual talk NiPreps 25.11.2020 online, Spain Esteban Sanz-Dranguet Oscar;
Open and Reproducible Neuroimaging Workshop ᐧ University of Oldenburg (Germany) Individual talk Community-built and standardized workflows - The NiPreps experience 20.10.2020 online, Germany Esteban Sanz-Dranguet Oscar;
NeuroHackademy 2020 Individual talk NiPreps 24.07.2020 online, United States of America Esteban Sanz-Dranguet Oscar;
Think Open Rovereto Workshop Individual talk Building next-generation preprocessing pipelines 13.07.2020 online, Italy Esteban Sanz-Dranguet Oscar;
OHBM 2020 Open Science Room Individual talk Emergent Session on “Open Workflows” (Speaker) 24.06.2020 online, United States of America Esteban Sanz-Dranguet Oscar;


Self-organised

Title Date Place
fMRIPrep / NiPreps roundup meetings (bi-monthly) 12.05.2021 online, Switzerland

Use-inspired outputs

Software

Name Year
dMRIPrep (experimental development) 2021
fMRIPrep 21.x series 2021
MRIQC 21.x series 2021
SDCFlows 2.x series 2021
TemplateFlow Python Client 2021


Associated projects

Number Title Start Funding scheme
157040 Advanced high-field MR imaging and quantitative image analysis for segmentation of the thalamic nuclei 01.04.2015 Project funding (Div. I-III)
156874 Quantitative characterization of the connectome in the progression of psychosis 01.05.2015 Project funding (Div. I-III)

Abstract

Unveiling how the brain's structure defines its distributed function and modulates the dynamics of processing holds the promise of triggering a revolution in neuroscience and applications to mental health and neurodegenerative diseases. Magnetic resonance imaging (MRI) has proven a valuable, non-invasive way of probing both the architecture and activity of the brain in-vivo, with sufficient spatial and temporal resolution to understand many aspects of its function. However, limitations in MRI impede the link between structure, function, and dynamics. In particular, the measurements obtained with MRI are highly indirect, spatio-temporally uncertain, and are confounded by other sources of MR signal. This complexity provides an immense informatics challenge that crosses multiple imaging modalities, including structural, functional and dynamic connectivity approaches to understanding the human brain.In this project, we will address the reliability of the scientific neuroimaging workflow by testing the hypothesis that minimizing the confounding effects on preprocessing of functional and structural MRI will enable an integrated modeling approach that is fundamental to the understanding of the human brain. Using a dense sampling approach on a single healthy participant (an approach that has been dubbed "precision neuroimaging"), optimal acquisition and processing for each modality will be determined across four scanner models. The wealth of repeated data in this dataset will allow us to define a set of "gold" standards necessary in the validation of workflows to extract functional and structural networks. We will comprehensively evaluate the multiplicity of processing alternatives to select those that achieve the highest sensitivity and specificity. We hypothesize that such improvements in sensitivity and specificity of functional and structural networks generalize across scanners and subjects, allowing the univocal identification (or "fingerprinting") of networks. We will test whether gains in reliability of connectomes are reproduced when applied on data from ten new subjects (5M / 5F), whose data will be acquired using the optimized protocols from the previous step and the precision neuroimaging approach. Our approach will focus specifically on the thalamus, which mediates the dynamical activity propagation through the cortex, and thus is thought to regulate the trajectories of connectivity when the brain switches between task-oriented and internal functional networks. Additional evidence suggests that the Thalamus may be a relevant descriptor of disease and have associated the disruption in thalamo-cortical connectivity with Schizophrenia and Bipolar Disorder. To attain the necessary topological resolution of regions anatomically connected to the Thalamus, we will use very-high resolution dMRI by limiting the field of view to our region of interest. Preprocessed data will be then integrated into a common framework for the analysis and modelling of brain functional dynamics. In particular, we will test the hypothesis that integrative thalamic nuclei control the dynamics of functional networks that aperiodically oscillate between integrated and segregated topological states. Overall, this project will equip researchers with a framework for the extraction of reliable and precise structural, functional and dynamic networks that permit their joint modeling and analysis with interpretable and reproducible methods. The project will publicly release two highly valuable datasets necessary in the improvement of the workflow for structural and functional network extraction. Finally, with the support of the improved neuroimaging workflow, we will decipher the control role of the integrative thalamic nuclei over dynamic functional connectivity, which is thought to be a key biomarker of disease progression in Schizophrenia and Bipolar Disorder.
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