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8 results on '"Eveline A Crone"'

1. Normative Modeling of Brain Morphometry Across the Lifespan using CentileBrain: Algorithm Benchmarking and Model Optimization

Author

Ruiyang Ge, Yuetong Yu, Yi Xuan Qi, Yunan Vera Fan, Shiyu Chen, Chuntong Gao, Shalaila S Haas, Amirhossein Modabbernia, Faye New, Ingrid Agartz, Philip Asherson, Rosa Ayesa-Arriola, Nerisa Banaj, Tobias Banaschewski, Sarah Baumeister, Alessandro Bertolino, Dorret I Boomsma, Stefan Borgwardt, Josiane Bourque, Daniel Brandeis, Alan Breier, Henry Brodaty, Rachel M Brouwer, Randy Buckner, Jan K Buitelaar, Dara M Cannon, Xavier Caseras, Simon Cervenka, Patricia J Conrod, Benedicto Crespo-Facorro, Fabrice Crivello, Eveline A Crone, Liewe de Haan, Greig I de Zubicaray, Annabella Di Giorgio, Susanne Erk, Simon E Fisher, Barbara Franke, Thomas Frodl, David C Glahn, Dominik Grotegerd, Oliver Gruber, Patricia Gruner, Raquel E Gur, Ruben C Gur, Ben J Harrison, Sean N Hatton, Ian Hickie, Fleur M Howells, Hilleke E Hulshoff Pol, Chaim Huyser, Terry L Jernigan, Jiyang Jiang, John A Joska, Rene S Kahn, Andrew J Kalnin, Nicole A Kochan, Sanne Koops, Jonna Kuntsi, Jim Lagopoulos, Luisa Lazaro, Irina S Lebedeva, Christine Lochner, Nicholas G Martin, Bernard Mazoyer, Brenna C McDonald, Colm McDonald, Katie L McMahon, Tomohiro Nakao, Lars Nyberg, Fabrizio Piras, Maria J Portella, Jiang Qiu, Joshua L Roffman, Perminder S Sachdev, Nicole Sanford, Andrew J Saykin, Theodore D Satterthwaite, Sophia I Thomopolous, Carl M Sellgren, Kang Sim, Jordan W Smoller, Jair Soares, Iris E Sommer, Gianfranco Spalletta, Dan J Stein, Christian K Tamnes, Alexander S Tomyshev, Theo GM van Erp, Diana Tordesillas-Gutierrez, Julian N Trollor, Dennis van 't Ent, Odile A van den Heuvel, Neeltje EM van Haren, Daniela Vecchio, Dick J Veltman, Dongtao Wei, Henrik Walter, Yang Wang, Bernd Weber, Margaret J Wright, Wei Wen, Lars T Westlye, Lara M Wierenga, Paul M Thompson, Steven CR Williams, Sarah Medland, Mon-Ju Wu, Kevin Yu, Neda Jahanshad, and Sophia Frangou

Abstract

Background: Normative modeling is a statistical approach to quantify the degree to which a particular individual-level measure deviates from the pattern observed in a normative reference population. When applied to human brain morphometric measures it has the potential to inform about the significance of normative deviations for health and disease. Normative models can be implemented using a variety of algorithms that have not been systematically appraised. Methods: To address this gap, eight algorithms were compared in terms of performance and computational efficiency using brain regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) collated from 87 international MRI datasets. Performance was assessed with the mean absolute error (MAE) and computational efficiency was inferred from central processing unit (CPU) time. The algorithms evaluated were Ordinary Least Squares Regression (OLSR), Bayesian Linear Regression (BLR), Generalized Additive Models for Location, Scale, and Shape (GAMLSS), Parametric Lambda, Mu, Sigma (LMS), Gaussian Process Regression (GPR), Warped Bayesian Linear Regression (WBLG), Hierarchical Bayesian Regression (HBR), and Multivariable Fractional Polynomial Regression (MFPR). Model optimization involved testing nine covariate combinations pertaining to acquisition features, parcellation software versions, and global neuroimaging measures (i.e., total intracranial volume, mean cortical thickness, and mean cortical surface area). Findings: Statistical comparisons across models at PFDR

Published
2023
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2. Mood variability during adolescent development and its relation to sleep and brain development

Author

Yara J. Toenders, Renske van der Cruijsen, Jana Runze, Suzanne van de Groep, Lara Wierenga, and Eveline A. Crone

Abstract

Mood swings, or mood variability, are associated with negative mental health outcomes. Since adolescence is a time when mood disorder onset peaks, mood variability during this time is of significant interest. Understanding biological factors that might be associated with mood variability, such as sleep and structural brain development, could elucidate the mechanisms underlying mood and anxiety disorders. Data from the longitudinal Leiden Self-Concept study (N=171) over 5 yearly timepoints was used to study the association between sleep, brain structure, and mood variability in healthy adolescents aged 11-21 at baseline in this pre-registered study. Sleep was measured both objectively, using actigraphy, as well as subjectively, using a daily diary self-report. Negative mood variability was defined as day-to-day negative mood swings over a period of 5 days after an MRI scan. It was found that negative mood variability peaked in mid-adolescence in females while it linearly increased in males, and average negative mood showed a similar pattern. Sleep duration (subjective and objective) generally decreased throughout adolescence, with a larger decrease in males. Mood variability was not associated with sleep, but average negative mood was associated with lower self-reported energy. In addition, higher thickness in the dorsolateral prefrontal cortex (dlPFC) compared to same-age peers, suggesting a delayed thinning process, was associated with higher negative mood variability in early and mid-adolescence. Together, this study provides an insight into the development of mood variability and its association with brain structure.

Published
2022
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3. Dissociable Cellular and Genetic Mechanisms of Cortical Thinning at Different Life Stages

Author

Amirhossein Modabbernia, Didac Vidal-Pineiro, Ingrid Agartz, Ole A Andreassen, Rosa Ayesa-Arriola, Alessandro Bertolino, Dorret I Boomsma, Josiane Bourque, Alan Breier, Henry Brodaty, Rachel M Brouwer, Jan K Buitelaar, Erick J Canales-Rodríguez, Xavier Caseras, Patricia J Conrod, Benedicto Crespo-Facorro, Fabrice Crivello, Eveline A Crone, Greig I de Zubicaray, Erin W Dickie, Danai Dima, Stefan Frenzel, Simon E Fisher, Barbara Franke, David C Glahn, Hans-Jörgen Grabe, Dominik Grotegerd, Oliver Gruber, Amalia Guerrero-Pedraza, Raquel E Gur, Ruben C Gur, Catharina A Hartman, Pieter J Hoekstra, Hilleke E Hulshoff Pol, Neda Jahanshad, Terry L Jernigan, Jiyang Jiang, Andrew J Kalnin, Nicole A Kochan, Bernard Mazoyer, Brenna C McDonald, Katie L McMahon, Lars Nyberg, Jaap Oosterlaan, Edith Pomarol-Clotet, Joaquim Radua, Perminder S Sachdev, Theodore D Satterthwaite, Raymond Salvador, Salvador Sarro, Andrew J Saykin, Gunter Schumann, Jordan W Smoller, Iris E Sommer, Thomas Espeseth, Sophia I Thomopoulos, Julian N Trollor, Dennis van ‘t Ent, Aristotle Voineskos, Yang Wang, Bernd Weber, Lars T Westlye, Heather C Whalley, Steven CR Williams, Katharina Wittfeld, Margaret J Wright, Paul M Thompson, Thomas Paus, and Sophia Frangou

Abstract

Mechanisms underpinning age-related variations in cortical thickness in the human brain remain poorly understood. We investigated whether inter-regional age-related variations in cortical thinning (in a multicohort neuroimaging dataset from the ENIGMA Lifespan Working Group totalling 14,248 individuals, aged 4-89 years) depended on cell-specific marker gene expression levels. We found differences amidst early-life (60 years) in the patterns of association between inter-regional profiles of cortical thickness and expression profiles of marker genes for CA1 and S1 pyramidal cells, astrocytes, and microglia. Gene ontology and enrichment analyses indicated that each of the three life-stages was associated with different biological processes and cellular components: synaptic modeling in early life, neurotransmission in mid-life, and neurodegeneration in late-life. These findings provide mechanistic insights into age-related cortical thinning during typical development and aging.

Published
2022
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4. Longitudinal Network Re-organization Across Learning and Development

Author

Sabine Peters, Eveline A. Crone, Eva H. Telzer, and Ethan M. McCormick

Subjects
Longitudinal study, Modularity (biology), Young adult, Adolescent development, Psychology, Cognitive psychology, Task (project management)
Abstract

While it is well understood that the brain experiences changes across short-term experience/learning and long-term development, it is unclear how these two mechanisms interact to produce developmental outcomes. Here we test an interactive model of learning and development where certain learning-related changes are constrained by developmental changes in the brain against an alternative development-as-practice model where outcomes are determined primarily by the accumulation of experience regardless of age. Participants (8-29 years) participated in a three-wave, accelerated longitudinal study during which they completed a feedback learning task during an fMRI scan. Adopting a novel longitudinal modeling approach, we probed the unique and moderated effects of learning, experience, and development simultaneously on behavioral performance and network modularity during the task. We found nonlinear patterns of development for both behavior and brain, and that greater experience supported increased learning and network modularity relative to naïve subjects. We also found changing brain-behavior relationships across adolescent development, where heightened network modularity predicted improved learning, but only following the transition from adolescence to young adulthood. These results present compelling support for an interactive view of experience and development, where changes in the brain impact behavior in context-specific fashion based on developmental goals.

Published
2020
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5. Cortical Thickness Trajectories across the Lifespan: Data from 17,075 healthy individuals aged 3-90 years

Author

Stefan Ehrlich, Danai Dima, Nhat Trung Doan, Simon E. Fisher, Dominik Grotegerd, Nicholas G. Martin, Tiffany M. Chaim-Avancini, Sophie Maingault, Sean N. Hatton, Derrek P. Hibar, Vincent P. Clark, Anders M. Dale, Iris E. C. Sommer, Ben J. Harrison, Annabella Di Giorgio, Benedicto Crespo-Facorro, Ian H. Gotlib, Andrew J. Kalnin, Andreas Reif, Edith Pomarol-Clotet, Thomas Espeseth, Theodore D. Satterthwaite, Pieter J. Hoekstra, René S. Kahn, Margaret J. Wright, Núria Bargalló, Maria J. Portella, Thomas Frodl, Lianne Schmaal, Chaim Huyser, Sophia I. Thomopoulos, Odille A van den Heuvel, Rachel M. Brouwer, Rachel E. Gur, Stefan Borgwardt, Marise W. J. Machielsen, Kathryn I. Alpert, Dick J. Veltman, Sim Kang, Irina V. Lebedeva, Marcus V. Zanetti, Anne Uhlmann, Christopher R.K. Ching, John D. West, Paul Pauli, Susanne Erk, Xavier Caseras, Kun Yang, Randy L. Buckner, Julian N. Trollor, Katharina Wittfeld, Fabrice Crivello, Theo G.M. van Erp, Luisa Lázaro, Jan Egil Nordvik, Sarah Baumeister, Steven G. Potkin, Calhoun Vd, Ian B. Hickie, Giulio Pergola, Henrik Walter, Katie L. McMahon, Theophilus N. Akudjedu, Patricia J. Conrod, Nic J.A. van der Wee, Won Hee Lee, Dennis van 't Ent, Barbara Franke, Knut Schnell, Josiane Bourque, Matthew D. Sacchet, Perminder S. Sachdev, Esther Walton, Raymond Salvador, Colm McDonald, Gunter Schumann, Paul M. Thompson, Georg C. Ziegler, Erin W. Dickie, Christine Lochner, Andreas Meyer-Lindenberg, Eco J. C. de Geus, Ole A. Andreassen, Joshua L. Roffman, Oliver Grimm, Andrew M. McIntosh, Ryota Kanai, Mauricio H. Serpa, Dennis van den Meer, Jessica A. Turner, Simon Cervenka, Alexander Tomyshev, Lara M. Wierenga, Francisco X. Castellanos, Bernd Kramer, Erlend S. Dørum, Alessandro Bertolino, P. G. P. Rosa, Avram J. Holmes, Klaus-Peter Lesch, Norbert Hosten, Hilleke E. Hulshoff Pol, Jean-Paul Fouche, Neda Jahanshad, Daniel Brandeis, José M. Menchón, Jiyang Jiang, Jan K. Buitelaar, Andrew J. Saykin, Genevieve McPhilemy, Efstathios Papachristou, Hans-Jörgen Grabe, Bernd Weber, Beng-Choon Ho, Pablo Najt, Fleur M. Howells, Yannis Paloyelis, Lieuwe de Haan, Lachlan T. Strike, Dag Alnæs, David Mataix-Cols, Henry Völzke, Daniel H. Wolf, Suzanne C. Swagerman, Paola Fuentes-Claramonte, Marieke Klein, Patricia Gruner, Anthony A. James, Ingrid Agartz, Dara M. Cannon, Jim Lagopoulos, Geraldo F. Busatto, Tomohiro Nakao, Dan J. Stein, Gaelle E Doucet, Erick J. Canales-Rodríguez, Cristopher Davey, Tatyana P Klushnik, Jaap Oosterlaan, Ilya M. Veer, Steven Williams, Bernard Mazoyer, Helena Fatouros-Bergman, Yulyia Yoncheva, Ramona Baur-Streubel, Anouk den Braber, Nynke A. Groenewold, Salvador Sarró, Ignacio Martínez-Zalacaín, Sanne Koops, M. Aghajani, Lei Wang, Sarah E. Medland, C.A. Hartman, Aurora Bonvino, Pascual Sánchez-Juan, Andreas Heinz, Tobias Banaschewski, Amirhossein Modabbernia, Jilly Naaijen, Yang Wang, Sophia Frangou, Henry Brodaty, Henk Temmingh, Greig I. de Zubicaray, Nancy C. Andreasen, Carles Soriano-Mas, Neeltje E.M. van Haren, Brenna C. McDonald, Ruben C. Gur, Micael Andersson, Dorret I. Boomsma, Dirk J. Heslenfeld, Erik G. Jönsson, Oliver Gruber, Víctor Ortiz-García de la Foz, Anton Albajes-Eizagirre, David C. Glahn, Alan Breier, Heather C. Whalley, Jordan W. Smoller, Joaquim Radua, Christian K. Tamnes, Eveline A. Crone, Philip Asherson, John A. Joska, Wei Wen, Jonna Kuntsi, Lars Nyberg, Thomas H. Wassink, Diana Tordesillas-Gutiérrez, Martine Hoogman, Lars T. Westlye, Annette Conzelmann, Sarah Hohmann, and Laura Koenders

Subjects
0303 health sciences, medicine.medical_specialty, Fractional polynomial, Cognition, Audiology, Biology, Regression, Pooling data, 03 medical and health sciences, 0302 clinical medicine, Neuroimaging genetics, Healthy individuals, medicine, General pattern, Analysis of variance, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Delineating age-related cortical trajectories in healthy individuals is critical given the association of cortical thickness with cognition and behaviour. Previous research has shown that deriving robust estimates of age-related brain morphometric changes requires large-scale studies. In response, we conducted a large-scale analysis of cortical thickness in 17,075 individuals aged 3-90 years by pooling data through the Lifespan Working group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium. We used fractional polynomial (FP) regression to characterize age-related trajectories in cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma (LMS) method. Inter-individual variability was estimated using meta-analysis and one-way analysis of variance. Overall, cortical thickness peaked in childhood and had a steep decrease during the first 2-3 decades of life; thereafter, it showed a gradual monotonic decrease which was steeper in men than in women particularly in middle-life. Notable exceptions to this general pattern were entorhinal, temporopolar and anterior cingulate cortices. Inter-individual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results reconcile uncertainties about age-related trajectories of cortical thickness; the centile values provide estimates of normative variance in cortical thickness, and may assist in detecting abnormal deviations in cortical thickness, and associated behavioural, cognitive and clinical outcomes.

Published
2020
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6. Subcortical Volume Trajectories across the Lifespan: Data from 18,605 healthy individuals aged 3-90 years

Author

Lara M. Wierenga, Iris E. C. Sommer, Edith Pomarol-Clotet, Erick J. Canales-Rodríguez, van Erp Tg, Lars T. Westlye, van Haren Ne, Francisco X. Castellanos, P. G. P. Rosa, Kang S, van der Wee Nj, Joaquim Radua, Jim Lagopoulos, José M. Menchón, Helena Fatouros-Bergman, Jan K. Buitelaar, Bernd Weber, Annette Conzelmann, Núria Bargalló, S. E. Medland, Maria J. Portella, Patricia J. Conrod, Amanda Worker, Klaus-Peter Lesch, Jonna Kuntsi, S.G. Potkin, R. Salvador, Knut Schnell, Stefan Borgwardt, Katharina Wittfeld, Kathryn I. Alpert, Dick J. Veltman, de Geus Ej, Ole A. Andreassen, Sophia Frangou, Di Giorgio A, Avram J. Holmes, Rachel M. Brouwer, Thomas Frodl, Lachlan T. Strike, Anton Albajes-Eizagirre, Giulio Pergola, van den Heuvel Oa, Perminder S. Sachdev, Esther Walton, Josiane Bourque, Dag Alnæs, David C. Glahn, Ramona Baur-Streubel, Laura Koenders, Christian K. Tamnes, Alan Breier, Jordan W. Smoller, Yulyia Yoncheva, Marise W. J. Machielsen, Sarah Hohmann, Magnus Andersson, Paola Fuentes-Claramonte, David Mataix-Cols, Salvador Sarró, Stefan Ehrlich, John A. Joska, Marieke Klein, Mauricio H. Serpa, den Braber A, Henry Völzke, Jilly Naaijen, de Haan L, Thomas H. Wassink, Daniel H. Wolf, Thomas Espeseth, Yang Wang, Henrik Walter, Wei Wen, Calhoun, Dan J. Stein, Simon E. Fisher, Eveline A. Crone, Ingrid Agartz, Susanne Erk, Oliver Grimm, Andrew M. McIntosh, Dominik Grotegerd, Henry Brodaty, Katie L. McMahon, Jaap Oosterlaan, Danai Dima, Aurora Bonvino, Anders M. Dale, Alexander Tomyshev, Ignacio Martínez-Zalacaín, Anthony A. James, Andrew J. Kalnin, Barbara Franke, Theophilus N. Akudjedu, Andreas Reif, Pieter J. Hoekstra, Nordvik Je, Lars Nyberg, Bernard Mazoyer, Paul M. Thompson, Andrew J. Saykin, Genevieve McPhilemy, Nhat Trung Doan, Geraldo F. Busatto, Colm McDonald, van ’t Ent D, Sophia I. Thomopoulos, Derrek P. Hibar, Neda Jahanshad, Norbert Hosten, Ryota Kanai, Ruben C. Gur, D.I. Boomsma, Lianne Schmaal, Jean-Paul Fouche, Anne Uhlmann, Jessica A. Turner, Fabrice Crivello, P. Asherson, de la Foz Vo, Heather C. Whalley, C.A. Hartman, Ching Cr, Dirk J. Heslenfeld, Jiyang Jiang, Pascual Sánchez-Juan, Andreas Heinz, Simon Cervenka, Irina V. Lebedeva, Nancy C. Andreasen, Erik G. Jönsson, Oliver Gruber, Ben J. Harrison, Tiffany M. Chaim-Avancini, Sophie Maingault, Efstathios Papachristou, Beng-Choon Ho, Marcus V. Zanetti, Doucet Ge, Nynke A. Groenewold, Sacchet, Andreas Meyer-Lindenberg, Bernhard K. Krämer, M. Aghajani, Diana Tordesillas-Gutiérrez, Martine Hoogman, Lu Wang, Pablo Najt, van den Meer D, Christopher G. Davey, Theodore D. Satterthwaite, René S. Kahn, Margaret J. Wright, N. G. Martin, G. Schumann, Tobias Banaschewski, Amirhossein Modabbernia, Benedicto Crespo-Facorro, Ian B. Hickie, Alessandro Bertolino, Sanne Koops, Sean N. Hatton, Georg C. Ziegler, Carles Soriano-Mas, Kun Yang, Brenna C. McDonald, Sarah Baumeister, Scr Williams, Julian N. Trollor, Paul Pauli, Joshua L. Roffman, Xavier Caseras, Won Hee Lee, Henk Temmingh, Rachel E. Gur, Randy L. Buckner, Vincent P. Clark, Daniel Brandeis, Ian H. Gotlib, Hulshoff Pol He, Hans-Jörgen Grabe, Fleur M. Howells, Christine Lochner, Yannis Paloyelis, Erlend S. Dørum, Suzanne C. Swagerman, Patricia Gruner, Dara M. Cannon, Tomohiro Nakao, Tatyana P Klushnik, Ilya M. Veer, de Zubicaray Gi, Chaim Huyser, John D. West, Luisa Lázaro, and Erin W. Dickie

Subjects
0303 health sciences, Putamen, Thalamus, Brain morphometry, Hippocampus, Nucleus accumbens, Biology, 03 medical and health sciences, Lateral ventricles, 0302 clinical medicine, nervous system, Brain size, Basal ganglia, Neuroscience, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalised on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine the age-related morphometric trajectories of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum early in life; the volume of the basal ganglia showed a gradual monotonic decline thereafter while the volumes of the thalamus, amygdala and the hippocampus remained largely stable (with some degree of decline in thalamus) until the sixth decade of life followed by a steep decline thereafter. The lateral ventricles showed a trajectory of continuous enlargement throughout the lifespan. Significant age-related increase in inter-individual variability was found for the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to derive risk predictions for the early identification of diverse clinical phenotypes.

Published
2020
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7. 10Kin1day: A bottom-up neuroimaging initiative

Author

Christiaan H. Vinkers, Franziskus Liem, Ronny Redlich, Veronica A. Witte, Veronica O’Keane, Axel Krug, Michael V. Lombardo, Susan Mérillat, Laurena Holleran, Fredica Agosta, Irina S. Lebedeva, Ignacio Martínez-Zalacaín, Carlos López-Jaramillo, Bob Oranje, Martijn P. van den Heuvel, Wiepke Cahn, Eric Y.H. Chen, Bruno Dietsche, Simon J.G. Lewis, Frauke Beyer, Vladimir S. Kostic, Martin Reuter, Arno Villringer, Linda Booij, Paul E. Rasser, Andreas Jansen, Jonathan Repple, Colm McDonald, Sebastiaan Wf Neggers, Massimo Filippi, Lea Waller, Genevieve McPhilemy, Soraya Seedat, Benedicto Crespo-Facorro, Julie M. Hall, Pedro Morgado, Kees P.J. Braun, Krzysztof Narkiewicz, David Mothersill, Dominik Grotegerd, Patrycja Naumczyk, Christian Montag, Leila Nabulsi, Thomas Frodl, Gary Donohoe, Stefan Du Plessis, Eveline A. Crone, Víctor Ortiz-García de la Foz, Robin Emsley, Manon J. N. L. Benders, Martin Gorges, Krzysztof Jodzio, Rosemary Holt, Pablo Najt, Devon Shook, Vasiliy G. Kaleda, Ulrich Schall, Marcus V. Zanetti, Sarah Durston, Daniel S. Margulies, Tilo Kircher, Carles Soriano-Mas, Amber N. V. Ruigrok, Stephen M. Lawrie, Lianne H. Scholtens, Henrik Walter, Edyta Szurowska, Andrew M. McIntosh, Tiffany M. Chaim-Avancini, Tristram A. Lett, Christian Vollmar, Edwin Ho Ming Lee, Stavros Skouras, Martijn G.J.C. Koevoets, Diana Tordesillas-Gutierrez, Neeltje E.M. van Haren, Udo Dannlowski, Jiska S. Peper, Sandra S. M. Chan, Paulo Marques, Silvia Basaia, Rui Zhang, Jan Kassubek, Z Julian A Pineda, Beata Graff, Joanna Goc, Helene J. Hopman, Heather C. Whalley, Hans-Peter Müller, Dariusz Gąsecki, Mauricio H. Serpa, Theo G.M. van Erp, Nuno Sousa, Pedro G.P. Rosa, Geraldo Busatto Filho, Clara Alloza, Sebastian Markett, Judith M.C. van Leeuwen, Shahrzad Kharabian Masouleh, José M. Menchón, Alexander S Tomyshev, Simon Baron-Cohen, Siemon C. de Lange, Lutz Jäncke, Sofie L. Valk, Leonard H. van den Berg, Marta Witkowska, Leonardo Tozzi, Pedro Moreira, Sonja M C de Zwarte, Ana M. Díaz-Zuluaga, Hannelore K. van der Burgh, Susanne Meinert, Agnieszka Sabisz, and Dara M. Cannon

Subjects
Cognitive science, 0303 health sciences, 03 medical and health sciences, 0302 clinical medicine, Neuroimaging, Computer science, Event (relativity), Connectome, Top-down and bottom-up design, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.

Published
2019
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8. Developmental maturation of the precuneus as a functional core of the default-mode network

Author

Sabine Peters, Eveline A. Crone, Scott A. Huettel, Anna C. K. van Duijvenvoorde, Rosa Li, Amanda V. Utevsky, and Barbara R. Braams

Subjects
Rest (physics), 0303 health sciences, Elementary cognitive task, medicine.diagnostic_test, Artificial neural network, Developmental maturation, Precuneus, Task (project management), 03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, medicine, Functional magnetic resonance imaging, Psychology, 030217 neurology & neurosurgery, Default mode network, 030304 developmental biology, Cognitive psychology
Abstract

Efforts to map the functional architecture of the developing human brain have shown that connectivity between and within functional neural networks changes from childhood to adulthood. While prior work has established that the adult precuneus distinctively modifies its connectivity during task versus rest states (Utevsky, Smith, & Huettel, 2014), it remains unknown how these connectivity patterns emerge over development. Here, we use functional magnetic resonance imaging (fMRI) data collected at two longitudinal timepoints from over 250 participants between the ages of 8 and 26 engaging in two cognitive tasks and a resting-state scan. By applying independent component analysis (ICA) to both task and rest data, we identified three canonical networks of interest – the rest-based default mode network (DMN) and the task-based left and right frontoparietal networks (LFPN, RFPN) – which we explored for developmental changes using dual-regression analyses. We found systematic state-dependent functional connectivity in the precuneus, such that engaging in a task (compared to rest) resulted in greater precuneus-LFPN and precuneus-RFPN connectivity, whereas being at rest (compared to task) resulted in greater precuneus-DMN connectivity. These cross-sectional results replicated across both tasks and at both developmental timepoints. Finally, we used longitudinal mixed models to show that the degree to which precuneus distinguishes between task and rest states increases with age, due to age-related increasing segregation between precuneus and LFPN at rest. Our results highlight the distinct role of the precuneus in tracking processing state, in a manner that is both present throughout and strengthened across development.

Published
2018
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