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Lerosier B, Simon G, Takerkart S, Auzias G, Dollfus S. Sulcal pits of the superior temporal sulcus in schizophrenia patients with auditory verbal hallucinations. AIMS Neurosci 2024; 11:25-38. [PMID: 38617038 PMCID: PMC11007407 DOI: 10.3934/neuroscience.2024002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 01/16/2024] [Accepted: 01/24/2024] [Indexed: 04/16/2024] Open
Abstract
Auditory verbal hallucinations (AVHs) are among the most common and disabling symptoms of schizophrenia. They involve the superior temporal sulcus (STS), which is associated with language processing; specific STS patterns may reflect vulnerability to auditory hallucinations in schizophrenia. STS sulcal pits are the deepest points of the folds in this region and were investigated here as an anatomical landmark of AVHs. This study included 53 patients diagnosed with schizophrenia and past or present AVHs, as well as 100 healthy control volunteers. All participants underwent a 3-T magnetic resonance imaging T1 brain scan, and sulcal pit differences were compared between the two groups. Compared with controls, patients with AVHs had a significantly different distributions for the number of sulcal pits in the left STS, indicating a less complex morphological pattern. The association of STS sulcal morphology with AVH suggests an early neurodevelopmental process in the pathophysiology of schizophrenia with AVHs.
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Affiliation(s)
| | - Gregory Simon
- Normandie Univ, UNICAEN, ISTS, EA 7466, 14000 Caen, France
| | - Sylvain Takerkart
- Aix Marseille Univ, CNRS, INT, Institut de Neurosciences de la Timone, Marseille, France
| | - Guillaume Auzias
- Aix Marseille Univ, CNRS, INT, Institut de Neurosciences de la Timone, Marseille, France
| | - Sonia Dollfus
- Normandie Univ, UNICAEN, ISTS, EA 7466, 14000 Caen, France
- CHU de Caen, Service de Psychiatrie, 14000 Caen, France
- Normandie Univ, UNICAEN, UFR santé, 14000 Caen, France
- Fédération Hospitalo-Universitaire (FHU-AMP), Normandie Univ, UNICAEN, UFR santé, 14000 Caen, France
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Yadav R, Dupé FX, Takerkart S, Auzias G. Population-wise labeling of sulcal graphs using multi-graph matching. PLoS One 2023; 18:e0293886. [PMID: 37943809 PMCID: PMC10635518 DOI: 10.1371/journal.pone.0293886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 10/23/2023] [Indexed: 11/12/2023] Open
Abstract
Population-wise matching of the cortical folds is necessary to compute statistics, a required step for e.g. identifying biomarkers of neurological or psychiatric disorders. The difficulty arises from the massive inter-individual variations in the morphology and spatial organization of the folds. The task is challenging both methodologically and conceptually. In the widely used registration-based techniques, these variations are considered as noise and the matching of folds is only implicit. Alternative approaches are based on the extraction and explicit identification of the cortical folds. In particular, representing cortical folding patterns as graphs of sulcal basins-termed sulcal graphs-enables to formalize the task as a graph-matching problem. In this paper, we propose to address the problem of sulcal graph matching directly at the population level using multi-graph matching techniques. First, we motivate the relevance of the multi-graph matching framework in this context. We then present a procedure for generating populations of artificial sulcal graphs, which allows us to benchmark several state-of-the-art multi-graph matching methods. Our results on both artificial and real data demonstrate the effectiveness of multi-graph matching techniques in obtaining a population-wise consistent labeling of cortical folds at the sulcal basin level.
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Affiliation(s)
- Rohit Yadav
- Institut de Neurosciences de la Timone UMR 7289, CNRS, Aix-Marseille Université, Marseille, France
- Institut Marseille Imaging, Aix Marseille Université, Marseille, France
- Laboratoire d’Informatique et Systèmes UMR 7020, CNRS, Aix-Marseille Université, Marseille, France
| | - François-Xavier Dupé
- Laboratoire d’Informatique et Systèmes UMR 7020, CNRS, Aix-Marseille Université, Marseille, France
| | - Sylvain Takerkart
- Institut de Neurosciences de la Timone UMR 7289, CNRS, Aix-Marseille Université, Marseille, France
| | - Guillaume Auzias
- Institut de Neurosciences de la Timone UMR 7289, CNRS, Aix-Marseille Université, Marseille, France
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da Rocha JLD, Kepinska O, Schneider P, Benner J, Degano G, Schneider L, Golestani N. Multivariate Concavity Amplitude Index (MCAI) for characterizing Heschl's gyrus shape. Neuroimage 2023; 272:120052. [PMID: 36965861 DOI: 10.1016/j.neuroimage.2023.120052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 03/21/2023] [Accepted: 03/22/2023] [Indexed: 03/27/2023] Open
Abstract
Heschl's gyrus (HG), which includes primary auditory cortex, is highly variable in its shape (i.e. gyrification patterns), between hemispheres and across individuals. Differences in HG shape have been observed in the context of phonetic learning skill and expertise, and of professional musicianship, among others. Two of the most common configurations of HG include single HG, where a single transverse temporal gyrus is present, and common stem duplications (CSD), where a sulcus intermedius (SI) arises from the lateral aspect of HG. Here we describe a new toolbox, called 'Multivariate Concavity Amplitude Index' (MCAI), which automatically assesses the shape of HG. MCAI works on the output of TASH, our first toolbox which automatically segments HG, and computes continuous indices of concavity, which arise when sulci are present, along the outer perimeter of an inflated representation of HG, in a directional manner. Thus, MCAI provides a multivariate measure of shape, which is reproducible and sensitive to small variations in shape. We applied MCAI to structural magnetic resonance imaging (MRI) data of N=181 participants, including professional and amateur musicians and from non-musicians. Former studies have shown large variations in HG shape in the former groups. We validated MCAI by showing high correlations between the dominant (i.e. highest) lateral concavity values and continuous visual assessments of the degree of lateral gyrification of the first gyrus. As an application of MCAI, we also replicated previous visually obtained findings showing a higher likelihood of bilateral CSDs in musicians. MCAI opens a wide range of applications in evaluating HG shape in the context of individual differences, expertise, disorder and genetics.
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Affiliation(s)
- Josué Luiz Dalboni da Rocha
- Department of Diagnostic Imaging, St Jude Children's Research Hospital, Memphis, USA; Brain and Language Lab, Department of Psychology, Faculty of Psychology and Educational Sciences, University of Geneva, Switzerland.
| | - Olga Kepinska
- Brain and Language Lab, Cognitive Science Hub, University of Vienna, Vienna, Austria; Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Peter Schneider
- Department of Neuroradiology and Department of Neurology, Section of Biomagnetism, University of Heidelberg Hospital, Heidelberg, Germany; Centre for Systematic Musicology, University of Graz, Graz, Austria; Vitols Jazeps Latvian Academy of Music, Riga, Latvia
| | - Jan Benner
- Department of Neuroradiology and Department of Neurology, Section of Biomagnetism, University of Heidelberg Hospital, Heidelberg, Germany
| | - Giulio Degano
- Brain and Language Lab, Department of Psychology, Faculty of Psychology and Educational Sciences, University of Geneva, Switzerland
| | - Letitia Schneider
- Brain and Language Lab, Cognitive Science Hub, University of Vienna, Vienna, Austria
| | - Narly Golestani
- Brain and Language Lab, Department of Psychology, Faculty of Psychology and Educational Sciences, University of Geneva, Switzerland; Brain and Language Lab, Cognitive Science Hub, University of Vienna, Vienna, Austria; Department of Behavioral and Cognitive Biology, Faculty of Life Sciences, University of Vienna, Vienna, Austria; Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria
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Cachia A, Borst G, Jardri R, Raznahan A, Murray GK, Mangin JF, Plaze M. Towards Deciphering the Fetal Foundation of Normal Cognition and Cognitive Symptoms From Sulcation of the Cortex. Front Neuroanat 2021; 15:712862. [PMID: 34650408 PMCID: PMC8505772 DOI: 10.3389/fnana.2021.712862] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 08/31/2021] [Indexed: 01/16/2023] Open
Abstract
Growing evidence supports that prenatal processes play an important role for cognitive ability in normal and clinical conditions. In this context, several neuroimaging studies searched for features in postnatal life that could serve as a proxy for earlier developmental events. A very interesting candidate is the sulcal, or sulco-gyral, patterns, macroscopic features of the cortex anatomy related to the fold topology-e.g., continuous vs. interrupted/broken fold, present vs. absent fold-or their spatial organization. Indeed, as opposed to quantitative features of the cortical sheet (e.g., thickness, surface area or curvature) taking decades to reach the levels measured in adult, the qualitative sulcal patterns are mainly determined before birth and stable across the lifespan. The sulcal patterns therefore offer a window on the fetal constraints on specific brain areas on cognitive abilities and clinical symptoms that manifest later in life. After a global review of the cerebral cortex sulcation, its mechanisms, its ontogenesis along with methodological issues on how to measure the sulcal patterns, we present a selection of studies illustrating that analysis of the sulcal patterns can provide information on prenatal dispositions to cognition (with a focus on cognitive control and academic abilities) and cognitive symptoms (with a focus on schizophrenia and bipolar disorders). Finally, perspectives of sulcal studies are discussed.
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Affiliation(s)
- Arnaud Cachia
- Université de Paris, LaPsyDÉ, CNRS, Paris, France
- Université de Paris, IPNP, INSERM, Paris, France
| | - Grégoire Borst
- Université de Paris, LaPsyDÉ, CNRS, Paris, France
- Institut Universitaire de France, Paris, France
| | - Renaud Jardri
- Univ Lille, INSERM U-1172, CHU Lille, Lille Neuroscience & Cognition Centre, Plasticity & SubjectivitY (PSY) team, Lille, France
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, United States
| | - Graham K. Murray
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | | | - Marion Plaze
- Université de Paris, IPNP, INSERM, Paris, France
- GHU PARIS Psychiatrie & Neurosciences, site Sainte-Anne, Service Hospitalo-Universitaire, Pôle Hospitalo-Universitaire Paris, Paris, France
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Borne L, Rivière D, Cachia A, Roca P, Mellerio C, Oppenheim C, Mangin JF. Automatic recognition of specific local cortical folding patterns. Neuroimage 2021; 238:118208. [PMID: 34089872 DOI: 10.1016/j.neuroimage.2021.118208] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 04/30/2021] [Accepted: 05/25/2021] [Indexed: 11/15/2022] Open
Abstract
The study of local cortical folding patterns showed links with psychiatric illnesses as well as cognitive functions. Despite the tools now available to visualize cortical folds in 3D, manually classifying local sulcal patterns is a time-consuming and tedious task. In fact, 3D visualization of folds helps experts to identify different sulcal patterns but fold variability is so high that the distinction between these patterns sometimes requires the definition of complex criteria, making manual classification difficult and not reliable. However, the assessment of the impact of these patterns on the functional organization of the cortex could benefit from the study of large databases, especially when studying rare patterns. In this paper, several algorithms for the automatic classification of fold patterns are proposed to allow morphological studies to be extended and confirmed on such large databases. Three methods are proposed, the first based on a Support Vector Machine (SVM) classifier, the second on the Scoring by Non-local Image Patch Estimator (SNIPE) approach and the third based on a 3D Convolution Neural Network (CNN). These methods are generic enough to be applicable to a wide range of folding patterns. They are tested on two types of patterns for which there is currently no method to automatically identify them: the Anterior Cingulate Cortex (ACC) patterns and the Power Button Sign (PBS). The two ACC patterns are almost equally present whereas PBS is a particularly rare pattern in the general population. The three models proposed achieve balanced accuracies of approximately 80% for ACC patterns classification and 60% for PBS classification. The CNN-based model is more interesting for the classification of ACC patterns thanks to its rapid execution. However, SVM and SNIPE-based models are more effective in managing unbalanced problems such as PBS recognition.
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Affiliation(s)
- Léonie Borne
- Université Paris-Saclay, CEA, CNRS, Baobab, Neurospin, Gif-sur-Yvette, France; University of Newcastle, HMRI, Systems Neuroscience Group, NSW, Australia.
| | - Denis Rivière
- Université Paris-Saclay, CEA, CNRS, Baobab, Neurospin, Gif-sur-Yvette, France
| | - Arnaud Cachia
- Université de Paris, LaPsyDÉ, CNRS, Paris, France; Université de Paris, Institut de Psychiatrie et Neurosciences de Paris (IPNP), INSERM, UMR S1266, Paris, France
| | - Pauline Roca
- Université de Paris, Institut de Psychiatrie et Neurosciences de Paris (IPNP), INSERM, UMR S1266, Paris, France; Groupe Hospitalier Universitaire Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Imaging Department, Paris, France; Pixyl, Research and Development Laboratory, Grenoble, France
| | - Charles Mellerio
- Université de Paris, Institut de Psychiatrie et Neurosciences de Paris (IPNP), INSERM, UMR S1266, Paris, France; Groupe Hospitalier Universitaire Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Imaging Department, Paris, France; Centre d'imagerie du Nord, Saint Denis, France
| | - Catherine Oppenheim
- Université de Paris, Institut de Psychiatrie et Neurosciences de Paris (IPNP), INSERM, UMR S1266, Paris, France; Groupe Hospitalier Universitaire Paris Psychiatrie et Neurosciences, Sainte-Anne Hospital, Imaging Department, Paris, France
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Li X, Wang W, Wang P, Hao C, Li Z. Atypical sulcal pattern in boys with attention-deficit/hyperactivity disorder. Hum Brain Mapp 2021; 42:4362-4371. [PMID: 34057775 PMCID: PMC8356996 DOI: 10.1002/hbm.25552] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 05/22/2021] [Accepted: 05/24/2021] [Indexed: 12/21/2022] Open
Abstract
Neurodevelopmental disorders, such as attention‐deficit/hyperactivity disorder (ADHD), are often accompanied by disrupted cortical folding. We applied a quantitative sulcal pattern analysis technique using graph structures to study the atypical cortical folding at the lobar level in ADHD brains in this study. A total of 183 ADHD patients and 167 typical developmental controls matched according to age and gender were enrolled. We first constructed sulcal graphs at the brain lobar level and then investigated their similarity to the typical sulcal patterns. The within‐group variability and interhemispheric similarity in sulcal patterns were also compared between the ADHD and TDC groups. The results showed that, compared with controls, the left frontal, right parietal, and temporal lobes displayed altered similarities to the typical sulcal patterns in patients with ADHD. Moreover, the sulcal patterns in ADHD seem to be more heterogeneous than those in controls. The results also identified the disruption of the typical asymmetric sulcal patterns in the frontal lobe between the ADHD and control groups. Taken together, our results revealed the atypical sulcal pattern in boys with ADHD and provide new insights into the neuroanatomical mechanisms of ADHD.
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Affiliation(s)
- Xinwei Li
- Chongqing Post-doctoral Research Station of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China.,Chongqing Engineering Laboratory of Digital Medical Equipment and Systems, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Wei Wang
- Chongqing Engineering Laboratory of Digital Medical Equipment and Systems, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Panyu Wang
- College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Chenru Hao
- Department of Medical Physics, Hebei Medical University, Shijiazhuang, Hebei, China
| | - Zhangyong Li
- Chongqing Post-doctoral Research Station of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China.,Chongqing Engineering Laboratory of Digital Medical Equipment and Systems, Chongqing University of Posts and Telecommunications, Chongqing, China
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Kaltenmark I, Deruelle C, Brun L, Lefèvre J, Coulon O, Auzias G. Group-level cortical surface parcellation with sulcal pits labeling. Med Image Anal 2020; 66:101749. [PMID: 32877840 DOI: 10.1016/j.media.2020.101749] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Revised: 04/09/2020] [Accepted: 06/03/2020] [Indexed: 11/16/2022]
Abstract
Sulcal pits are the points of maximal depth within the folds of the cortical surface. These shape descriptors give a unique opportunity to access to a rich, fine-scale representation of the geometry and the developmental milestones of the cortical surface. However, using sulcal pits analysis at group level requires new numerical tools to establish inter-subject correspondences. Here, we address this issue by taking advantage of the geometrical information carried by sulcal basins that are the local patches of surfaces surrounding each sulcal pit. Our framework consists in two phases. First, we present a new method to generate a population-specific atlas of this sulcal basins organi- zation as a fold-level parcellation of the cortical surface. Then, we address the labeling of individual sulcal pits and corresponding basins with respect to this atlas. To assess their validity, we applied these methodological advances on two different populations of healthy subjects. The first database of 137 adults allowed us to compare our method to the state-of-the-art and the second database of 209 children, aged between 0 and 18 years, illustrates the adaptability and relevance of our method in the context of pediatric data showing strong variations in cortical volume and folding.
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Affiliation(s)
- Irène Kaltenmark
- Institut de Neurosciences de la Timone UMR 7289, Aix-Marseille Université, CNRS Faculté de Médecine, 27 boulevard Faculté Jean Moulin, 13005 Marseille, France.
| | - Christine Deruelle
- Institut de Neurosciences de la Timone UMR 7289, Aix-Marseille Université, CNRS Faculté de Médecine, 27 boulevard Faculté Jean Moulin, 13005 Marseille, France
| | - Lucile Brun
- Institut de Neurosciences de la Timone UMR 7289, Aix-Marseille Université, CNRS Faculté de Médecine, 27 boulevard Faculté Jean Moulin, 13005 Marseille, France
| | - Julien Lefèvre
- Institut de Neurosciences de la Timone UMR 7289, Aix-Marseille Université, CNRS Faculté de Médecine, 27 boulevard Faculté Jean Moulin, 13005 Marseille, France
| | - Olivier Coulon
- Institut de Neurosciences de la Timone UMR 7289, Aix-Marseille Université, CNRS Faculté de Médecine, 27 boulevard Faculté Jean Moulin, 13005 Marseille, France
| | - Guillaume Auzias
- Institut de Neurosciences de la Timone UMR 7289, Aix-Marseille Université, CNRS Faculté de Médecine, 27 boulevard Faculté Jean Moulin, 13005 Marseille, France
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Duan D, Xia S, Rekik I, Meng Y, Wu Z, Wang L, Lin W, Gilmore JH, Shen D, Li G. Exploring folding patterns of infant cerebral cortex based on multi-view curvature features: Methods and applications. Neuroimage 2019; 185:575-592. [PMID: 30130646 PMCID: PMC6289765 DOI: 10.1016/j.neuroimage.2018.08.041] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 08/15/2018] [Accepted: 08/17/2018] [Indexed: 12/30/2022] Open
Abstract
The highly convoluted cortical folding of the human brain is intriguingly complex and variable across individuals. Exploring the underlying representative patterns of cortical folding is of great importance for many neuroimaging studies. At term birth, all major cortical folds are established and are minimally affected by the complicated postnatal environments; hence, neonates are the ideal candidates for exploring early postnatal cortical folding patterns, which yet remain largely unexplored. In this paper, we propose a novel method for exploring the representative regional folding patterns of infant brains. Specifically, first, multi-view curvature features are constructed to comprehensively characterize the complex characteristics of cortical folding. Second, for each view of curvature features, a similarity matrix is computed to measure the similarity of cortical folding in a specific region between any pair of subjects. Next, a similarity network fusion method is adopted to nonlinearly and adaptively fuse all the similarity matrices into a single one for retaining both shared and complementary similarity information of the multiple characteristics of cortical folding. Finally, based on the fused similarity matrix and a hierarchical affinity propagation clustering approach, all subjects are automatically grouped into several clusters to obtain the representative folding patterns. To show the applications, we have applied the proposed method to a large-scale dataset with 595 normal neonates and discovered representative folding patterns in several cortical regions, i.e., the superior temporal gyrus (STG), inferior frontal gyrus (IFG), precuneus, and cingulate cortex. Meanwhile, we have revealed sex difference in STG, IFG, and cingulate cortex, as well as hemispheric asymmetries in STG and cingulate cortex in terms of cortical folding patterns. Moreover, we have also validated the proposed method on a public adult dataset, i.e., the Human Connectome Project (HCP), and revealed that certain major cortical folding patterns of adults are largely established at term birth.
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Affiliation(s)
- Dingna Duan
- Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, China; Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA
| | - Shunren Xia
- Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, China
| | - Islem Rekik
- BASIRA Lab, CVIP, Computing, School of Science and Engineering, University of Dundee, UK
| | - Yu Meng
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA
| | - Zhengwang Wu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA
| | - Li Wang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA
| | - Weili Lin
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, USA
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA; Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea.
| | - Gang Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA.
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Im K, Grant PE. Sulcal pits and patterns in developing human brains. Neuroimage 2018; 185:881-890. [PMID: 29601953 DOI: 10.1016/j.neuroimage.2018.03.057] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 03/15/2018] [Accepted: 03/24/2018] [Indexed: 12/15/2022] Open
Abstract
Spatial distribution and specific geometric and topological patterning of early sulcal folds have been hypothesized to be under stronger genetic control and are more associated with optimal organization of cortical functional areas and their white matter connections, compared to later developing sulci. Several previous studies of sulcal pit (putative first sulcal fold) distribution and sulcal pattern analyses using graph structures have provided evidence of the importance of sulcal pits and patterns as remarkable anatomical features closely related to human brain function, suggesting additional insights concerning the anatomical and functional development of the human brain. Recently, early sulcal folding patterns have been observed in healthy fetuses and fetuses with brain abnormalities such as polymicrogyria and agenesis of corpus callosum. Graph-based quantitative sulcal pattern analysis has shown high sensitivity in detecting emerging subtle abnormalities in cerebral cortical growth in early fetal stages that are difficult to detect via qualitative visual assessment or using traditional cortical measures such as gyrification index and curvature. It has proven effective for characterizing genetically influenced early cortical folding development. Future studies will be aimed at better understanding a comprehensive map of spatio-temporal dynamics of fetal cortical folding in a large longitudinal cohort in order to examine individual clinical fetal MRIs and predict postnatal neurodevelopmental outcomes from early fetal life.
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Affiliation(s)
- Kiho Im
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA 02215, USA; Division of Newborn Medicine, Boston Children's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA.
| | - P Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA 02215, USA; Division of Newborn Medicine, Boston Children's Hospital, Boston, MA 02115, USA; Department of Radiology, Boston Children's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA
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Klein A, Ghosh SS, Bao FS, Giard J, Häme Y, Stavsky E, Lee N, Rossa B, Reuter M, Chaibub Neto E, Keshavan A. Mindboggling morphometry of human brains. PLoS Comput Biol 2017; 13:e1005350. [PMID: 28231282 PMCID: PMC5322885 DOI: 10.1371/journal.pcbi.1005350] [Citation(s) in RCA: 314] [Impact Index Per Article: 44.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2016] [Accepted: 01/08/2017] [Indexed: 01/01/2023] Open
Abstract
Mindboggle (http://mindboggle.info) is an open source brain morphometry platform that takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data containing label, feature, and shape information for further analysis. In this article, we document the software and demonstrate its use in studies of shape variation in healthy and diseased humans. The number of different shape measures and the size of the populations make this the largest and most detailed shape analysis of human brains ever conducted. Brain image morphometry shows great potential for providing much-needed biological markers for diagnosing, tracking, and predicting progression of mental health disorders. Very few software algorithms provide more than measures of volume and cortical thickness, while more subtle shape measures may provide more sensitive and specific biomarkers. Mindboggle computes a variety of (primarily surface-based) shapes: area, volume, thickness, curvature, depth, Laplace-Beltrami spectra, Zernike moments, etc. We evaluate Mindboggle's algorithms using the largest set of manually labeled, publicly available brain images in the world and compare them against state-of-the-art algorithms where they exist. All data, code, and results of these evaluations are publicly available.
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Affiliation(s)
- Arno Klein
- Child Mind Institute, New York, New York, United States of America
| | - Satrajit S. Ghosh
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- Department of Otolaryngology, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Forrest S. Bao
- Department of Electrical and Computer Engineering, University of Akron, Akron, Ohio, United States of America
| | | | - Yrjö Häme
- Columbia University, New York, New York, United States of America
| | - Eliezer Stavsky
- Columbia University, New York, New York, United States of America
| | - Noah Lee
- Columbia University, New York, New York, United States of America
| | - Brian Rossa
- TankThink Labs, Boston, Massachusetts, United States of America
| | - Martin Reuter
- Harvard Medical School, Cambridge, Massachusetts, United States of America
| | | | - Anisha Keshavan
- University of California San Francisco, San Francisco, California, United States of America
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