Publications
Reviews:
Mangin, J. F., Rivière, D., Coulon, O., Poupon, C., Cachia, A., Cointepas, Y., ... & Papadopoulos-Orfanos, D. (2004). Coordinate-based versus structural approaches to brain image analysis. Artificial intelligence in Medicine, 30(2), 177-197.
Mangin J-F, Jouvent E, Cachia A (2010) In-vivo measurement of cortical morphology: means and meanings. Curr Opin Neurol 23:359-367.
Mangin J-F, Auzias G, Coulon O, Sun ZY, Rivière D, Régis J (2015a) Sulci as Landmarks. In: Brain Mapping: An Encyclopedic Reference (Arthur W. Toga, ed), pp 45-52: Academic Press: Elsevier.
Mangin J-F, Perrot M, Operto G, Cachia A, Fischer C, Lefèvre J, Rivière D (2015b) Sulcus Identification and Labeling. In: Brain Mapping: An Encyclopedic Reference (Toga AW, ed), pp 365-371: Academic Press: Elsevier
Mangin J-F et al. (2016) Spatial normalization of brain images and beyond. Med Image Anal 33:127-133.
Mangin J-F et al. (2019) "Plis de passage” deserve a role in models of the cortical folding process. Brain topography 32.6 (2019): 1035-1048.
Cachia, A., Borst, G., Jardri, R., Raznahan, A., Murray, G. K., Mangin, J. F., & Plaze, M. (2021). Towards deciphering the fetal foundation of normal cognition and cognitive symptoms from sulcation of the cortex. Frontiers in neuroanatomy, 68.
de Vareilles, H., Rivière, D., Mangin, J. F., & Dubois, J. (2023). Development of cortical folds in the human brain: an attempt to review biological hypotheses, early neuroimaging investigations and functional correlates. Developmental Cognitive Neuroscience, 101249.
Fold-dedicated representations:
Mangin J-F, Frouin V, Bloch I, Régis J, López-Krahe J (1995) From 3D magnetic resonance images to structural representations of the cortex topography using topology preserving deformations. Journal of Mathematical Imaging and Vision 5:297-318.
Mangin J-F, Regis J, Frouin V (1996) Shape bottlenecks and conservative flow systems In: IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, pp 319–328. San Francisco.
Mangin J-F, Coulon O, Frouin V (1998) Robust brain segmentation using histogram scale-space analysis and mathematical morphology. MICCAI’98:1230-1241. Boston.
Mangin J-F (2000) Entropy minimization for automatic correction of intensity nonuniformity. In: IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA’00), pp 162–169. Hilton Head Island.
Mangin et al. (2004) A framework to study the cortical folding patterns. Neuroimage 23 : S129-S138.
Le Troter, A., Auzias, G., & Coulon, O. (2012). Automatic sulcal line extraction on cortical surfaces using geodesic path density maps. NeuroImage, 61(4), 941-949.
Auzias, G., Brun, L., Deruelle, C., & Coulon, O. (2015). Deep sulcal landmarks: algorithmic and conceptual improvements in the definition and extraction of sulcal pits. Neuroimage, 111, 12-25.
Chavas, J., Guillon, L., et al. (2022). Unsupervised Representation Learning of Cingulate Cortical Folding Patterns. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 77-87). Cham: Springer Nature Switzerland.
Sulcus recognition:
Mangin J-F, Régis J, Bloch I, Frouin V, Samson Y, López-Krahe J (1995) A MRF based random graph modelling the human cortical topography. Computer Vision, Virtual Reality and Robotics in Medicine:177-183. Nice
Rivière D, Mangin J-F, Papadopoulos-Orfanos D, Martinez J, Frouin V, Régis J (2002) Automatic recognition of cortical sulci of the human brain using a congregation of neural networks. Med Image Anal 6:77-92.
Perrot M, Rivière D, Mangin J-F (2011) Cortical sulci recognition and spatial normalization. Med Image Anal 15:529-550.
Borne L, Rivière D, Mancip M, Mangin J-F (2020). Automatic labeling of cortical sulci using patch-or CNN-based segmentation techniques combined with bottom-up geometric constraints. Med Image Anal, 62, 101651.
Borne L et al. (2021). Automatic recognition of specific local cortical folding patterns. NeuroImage, 118208.
Looking for models:
Cachia A et al. (2003) A primal sketch of the cortex mean curvature: a morphogenesis based approach to study the variability of the folding patterns. IEEE transactions on medical imaging 22(6) 754-765.
Cachia A et al. (2003). A generic framework for the parcellation of the cortical surface into gyri using geodesic Voronoı diagrams. Medical image analysis, 7(4), 403-416.
Ochiai T et al. (2004). Sulcal pattern and morphology of the superior temporal sulcus. Neuroimage, 22(2), 706-719.
Régis J et al. (2005) "Sulcal root" generic model: a hypothesis to overcome the variability of the human cortex folding patterns. Neurologia Medico-Chirurgica 45:1-17.
Sun ZY et al. (2007). Automatic inference of sulcus patterns using 3D moment invariants. In MICCAI (pp. 515-522). Springer, Berlin, Heidelberg.
Lefèvre J et al. (2009). Identification of growth seeds in the neonate brain through surfacic Helmholtz decomposition. In IPMI (pp. 252-263). Springer, Berlin, Heidelberg.
Sun ZY et al. (2009). Constructing a dictionary of human brain folding patterns. In MICCAI (pp. 117-124). Springer, Berlin, Heidelberg.
Clouchoux, C., Rivière, D., Mangin, J. F., Operto, G., Régis, J., & Coulon, O. (2010). Model-driven parameterization of the cortical surface for localization and inter-subject matching. Neuroimage, 50(2), 552-566.
Im K et al. (2010). Spatial distribution of deep sulcal landmarks and hemispherical asymmetry on the cortical surface. Cerebral cortex, 20(3), 602-611.
Lefèvre J, Mangin J-F (2010). A reaction-diffusion model of human brain development. PLoS Comput Biol, 6(4), e1000749.
Auzias, G., Colliot, O., Glaunes, J. A., Perrot, M., Mangin, J. F., Trouve, A., & Baillet, S. (2011). Diffeomorphic brain registration under exhaustive sulcal constraints. DISCO. IEEE transactions on medical imaging, 30(6), 1214-1227.
Auzias, G., Lefevre, J., Le Troter, A., Fischer, C., Perrot, M., Régis, J., & Coulon, O. (2013). Model-driven harmonic parameterization of the cortical surface: HIP-HOP. IEEE transactions on medical imaging, 32(5), 873-887.
Sun Z Y et al. (2016). Linking morphological and functional variability in hand movement and silent reading. Brain Structure and Function, 221(7), 3361-3371.
Auzias, G., Coulon, O., & Brovelli, A. (2016). MarsAtlas: A cortical parcellation atlas for functional mapping. Human brain mapping, 37(4), 1573-1592.
Lebenberg, J., Labit, M., Auzias, G., Mohlberg, H., Fischer, C., Rivière, D., ... & Mangin, J. F. (2018). A framework based on sulcal constraints to align preterm, infant and adult human brain images acquired in vivo and post mortem. Brain Structure and Function, 223(9), 4153-4168.
Sulcus morphometry:
Mangin J-F et al. (2004) Object-based morphometry of the cerebral cortex. IEEE Transactions on Medical Imaging, 23:968-982.
Mangin, J-F., et al. (2004) Brain morphometry using 3D moment invariants. Medical Image Analysis 8.3 (2004): 187-196.
Kochunov P et al. (2005) Age‐related morphology trends of cortical sulci. Human brain mapping 26.3:210-220.
Duchesnay E et al. (2007). Classification based on cortical folding patterns. IEEE Transactions on Medical Imaging, 26(4), 553-565.
Cykowski, M. D., Coulon, O., Kochunov, P. V., Amunts, K., Lancaster, J. L., Laird, A. R., ... & Fox, P. T. (2008). The central sulcus: an observer-independent characterization of sulcal landmarks and depth asymmetry. Cerebral cortex, 18(9), 1999-2009.
Germanaud D et al. (2012). Larger is twistier: spectral analysis of gyrification (SPANGY) applied to adult brain size polymorphism. Neuroimage, 63(3), 1257-1272.
Sun ZY et al. (2012) The effect of handedness on the shape of the central sulcus. Neuroimage 60:332-339.
Cachia A et al. (2014). The shape of the ACC contributes to cognitive control efficiency in preschoolers. Journal of cognitive neuroscience, 26(1), 96-106.
Leroy F et al. (2015) New human-specific brain landmark: the depth asymmetry of superior temporal sulcus. Proc Natl Acad Sci U S A 112:1208-1213.
Takerkart, S., Auzias, G., Brun, L., & Coulon, O. (2017). Structural graph-based morphometry: A multiscale searchlight framework based on sulcal pits. Medical image analysis, 35, 32-45.
Cachia A. et al. (2018). How interindividual differences in brain anatomy shape reading accuracy. Brain Structure and Function, 223(2), 701-712.
Le Guen Y et al. (2019) eQTL of KCNK2 regionally influences the brain sulcal widening: evidence from 15,597 UK Biobank participants with neuroimaging data. Brain Struct Funct 224:847-857.
Folding developmental dynamics:
Dubois J et al. (2008). Mapping the early cortical folding process in the preterm newborn brain. Cerebral cortex, 18(6), 1444-1454.
Kochunov, P., Castro, C., Davis, D., Dudley, D., Brewer, J., Zhang, Y., ... & Schatten, G. (2010). Mapping primary gyrogenesis during fetal development in primate brains: high-resolution in utero structural MRI study of fetal brain development in pregnant baboons. Frontiers in neuroscience, 4, 20.
Germanaud D et al. (2014). Simplified gyral pattern in severe developmental microcephalies? New insights from allometric modeling for spatial and spectral analysis of gyrification. NeuroImage, 102, 317-331.
Lefèvre J et al. (2016). Are developmental trajectories of cortical folding comparable between cross-sectional datasets of fetuses and preterm newborns?. Cerebral cortex, 26(7), 3023-3035.
Dubois J et al. (2019). The dynamics of cortical folding waves and prematurity-related deviations revealed by spatial and spectral analysis of gyrification. Neuroimage, 185, 934-946.
de Vareilles et al. (2022). Shape variability of the central sulcus in the developing brain: a longitudinal descriptive and predictive study in preterm infants. NeuroImage, 251, 118837.
de Vareilles et al. (2023). Exploring the emergence of morphological asymmetries around the brain’s Sylvian fissure: A longitudinal study of shape variability in preterm infants. Cerebral Cortex, 33(11), 6667-6680.
Folding and genetics:
Kochunov, P., Glahn, D. C., Fox, P. T., Lancaster, J. L., Saleem, K., Shelledy, W., ... & Rogers, J. (2010). Genetics of primary cerebral gyrification: Heritability of length, depth and area of primary sulci in an extended pedigree of Papio baboons. Neuroimage, 53(3), 1126-1134.
McKay, D. R., Kochunov, P., Cykowski, M. D., Kent, J. W., Laird, A. R., Lancaster, J. L., ... & Fox, P. T. (2013). Sulcal depth-position profile is a genetically mediated neuroscientific trait: description and characterization in the central sulcus. Journal of Neuroscience, 33(39), 15618-15625.
Fish AM et al. (2017). Influences of brain size, sex, and sex chromosome complement on the architecture of human cortical folding. Cerebral Cortex, 27(12), 5557-5567.
Le Guen Y et al. (2018). Genetic influence on the sulcal pits: on the origin of the first cortical folds. Cerebral Cortex, 28(6), 1922-1933.
Le Guen Y et al. (2018). The chaotic morphology of the left superior temporal sulcus is genetically constrained. Neuroimage, 174, 297-307.
Le Guen Y et al. (2020). Enhancer locus in ch14q23. 1 modulates brain asymmetric temporal regions involved in language processing. Cerebral Cortex, 30(10), 5322-5332.
Pizzagalli F et al. (2020). The reliability and heritability of cortical folds and their genetic correlations across hemispheres. Communications biology, 3(1), 1-12.
Cross-species comparisons:
Hopkins, W. D., Coulon, O., & Mangin, J. F. (2010). Observer-independent characterization of sulcal landmarks and depth asymmetry in the central sulcus of the chimpanzee brain. Neuroscience, 171(2), 544-551.
Hopkins, W. D., Meguerditchian, A., Coulon, O., Bogart, S., Mangin, J. F., Sherwood, C. C., ... & Vauclair, J. (2014). Evolution of the central sulcus morphology in primates. Brain, behavior and evolution, 84(1), 19-30
Hopkins, W. D., Meguerditchian, A., Coulon, O., Misiura, M., Pope, S., Mareno, M. C., & Schapiro, S. J. (2017). Motor skill for tool-use is associated with asymmetries in Broca’s area and the motor hand area of the precentral gyrus in chimpanzees (Pan troglodytes). Behavioural Brain Research, 318, 71-81.
Margiotoudi, K., Marie, D., Claidière, N., Coulon, O., Roth, M., Nazarian, B., ... & Meguerditchian, A. (2019). Handedness in monkeys reflects hemispheric specialization within the central sulcus. An in vivo MRI study in right-and left-handed olive baboons. Cortex, 118, 203-211.
Balzeau, A., & Mangin, J. F. (2021). What Are the Synergies between Paleoanthropology and Brain Imaging?. Symmetry, 13(10), 1974.
Hopkins, W. D. et al. (2023). Genetic determinants of individual variation in the superior temporal sulcus of chimpanzees (Pan troglodytes). Cerebral Cortex, 33(5), 1925-1940.
Clinical applications:
Molko N et al. (2003). Functional and structural alterations of the intraparietal sulcus in a developmental dyscalculia of genetic origin. Neuron, 40(4), 847-858.
Cachia A et al. (2008). Cortical folding abnormalities in schizophrenia patients with resistant auditory hallucinations. Neuroimage, 39(3), 927-935.
Jouvent E et al. (2008). Cortical changes in cerebral small vessel diseases: a 3D MRI study of cortical morphology in CADASIL. Brain, 131(8), 2201-2208.
Dubois J et al. (2008). Primary cortical folding in the human newborn: an early marker of later functional development. Brain, 131(8), 2028-2041.
Régis J et al. (2011). Subclinical abnormal gyration pattern, a potential anatomic marker of epileptogenic zone in patients with magnetic resonance imaging–negative frontal lobe epilepsy. Neurosurgery, 69(1), 80-94.
Jouvent E et al. (2012). Longitudinal changes of cortical morphology in CADASIL. Neurobiology of aging, 33(5), 1002-e29.
Hamelin L et al.(2015). Sulcal morphology as a new imaging marker for the diagnosis of early onset Alzheimer's disease. Neurobiology of aging, 36(11), 2932-2939.
Jouvent E et al. (2016). Shape of the central sulcus and disability after subcortical stroke: a motor reserve hypothesis. Stroke, 47(4), 1023-1029.
Kersbergen KJ et al. (2016). Relation between clinical risk factors, early cortical changes, and neurodevelopmental outcome in preterm infants. Neuroimage, 142, 301-310.
Hotier S et al. (2017). Social cognition in autism is associated with the neurodevelopment of the posterior superior temporal sulcus. Acta Psychiatrica Scandinavica, 136(5), 517-525.
Sarrazin S et al. (2018). Neurodevelopmental subtypes of bipolar disorder are related to cortical folding patterns: An international multicenter study. Bipolar disorders, 20(8), 721-732.
Mangin J-F et al. (2020). Neocortical morphometry in Huntington's disease: Indication of the coexistence of abnormal neurodevelopmental and neurodegenerative processes. NeuroImage: Clinical, 26, 102211.