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.