Gyri of the human parietal lobe: Volumes, spatial extents, automatic labelling, and probabilistic atlases

Accurately describing the anatomy of individual brains enables interlaboratory communication of functional and developmental studies and is crucial for possible surgical interventions. The human parietal lobe participates in multimodal sensory integration including language processing and also contains the primary somatosensory area. We describe detailed protocols to subdivide the parietal lobe, analyze morphological and volumetric characteristics, and create probabilistic atlases in MNI152 stereotaxic space. The parietal lobe was manually delineated on 3D T1 MR images of 30 healthy subjects and divided into four regions: supramarginal gyrus (SMG), angular gyrus (AG), superior parietal lobe (supPL) and postcentral gyrus (postCG). There was the expected correlation of male gender with larger brain and intracranial volume. We examined a wide range of anatomical features of the gyri and the sulci separating them. At least a rudimentary primary intermediate sulcus of Jensen (PISJ) separating SMG and AG was identified in nearly all (59/60) hemispheres. Presence of additional gyri in SMG and AG was related to sulcal features and volumetric characteristics. The parietal lobe was slightly (2%) larger on the left, driven by leftward asymmetries of the postCG and SMG. Intersubject variability was highest for SMG and AG, and lowest for postCG. Overall the morphological characteristics tended to be symmetrical, and volumes also tended to covary between hemispheres. This may reflect developmental as well as maturation factors. To assess the accuracy with which the labels can be used to segment newly acquired (unlabelled) T1-weighted brain images, we applied multi-atlas label propagation software (MAPER) in a leave-one-out experiment and compared the resulting automatic labels with the manually prepared ones. The results showed strong agreement (mean Jaccard index 0.69, corresponding to a mean Dice index of 0.82, average mean volume error of 0.6%). Stereotaxic probabilistic atlases of each subregion were obtained. They illustrate the physiological brain torque, with structures in the right hemisphere positioned more anteriorly than in the left, and right/left positional differences of up to 10 mm. They also allow an assessment of sulcal variability, e.g. low variability for parietooccipital fissure and cingulate sulcus. Illustrated protocols, individual label sets, probabilistic atlases, and a maximum-probability atlas which takes into account surrounding structures are available for free download under academic licences.

[1]  W. Strik,et al.  Structural and metabolic changes in language areas linked to formal thought disorder. , 2009, The British journal of psychiatry : the journal of mental science.

[2]  Daniel Rueckert,et al.  Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest , 2008, NeuroImage.

[3]  B. Mazoyer,et al.  Heschl’s gyrification pattern is related to speech-listening hemispheric lateralization: FMRI investigation in 281 healthy volunteers , 2014, Brain Structure and Function.

[4]  L. Lemieux,et al.  Statistical neuroanatomy of the human inferior frontal gyrus and probabilistic atlas in a standard stereotaxic space , 2007, Human brain mapping.

[5]  Marinella Cappelletti,et al.  The Role of Right and Left Parietal Lobes in the Conceptual Processing of Numbers , 2009, Journal of Cognitive Neuroscience.

[6]  T. Greitz,et al.  A computerized brain atlas: construction, anatomical content, and some applications. , 1991, Journal of computer assisted tomography.

[7]  John Duncan,et al.  Implementation and application of a brain template for multiple volumes of interest , 2002, Human brain mapping.

[8]  Nadim Joni Shah,et al.  Probabilistic fibre tract analysis of cytoarchitectonically defined human inferior parietal lobule areas reveals similarities to macaques , 2011, NeuroImage.

[9]  J M Stevens,et al.  Magnetic resonance volumetry , 1994, Neurology.

[10]  Katrin Amunts,et al.  The human inferior parietal cortex: Cytoarchitectonic parcellation and interindividual variability , 2006, NeuroImage.

[11]  M. Petrides,et al.  Neuroimaging evidence of the anatomo-functional organization of the human cingulate motor areas. , 2014, Cerebral cortex.

[12]  N. Andreasen,et al.  Gyrification abnormalities in childhood- and adolescent-onset schizophrenia , 2003, Biological Psychiatry.

[13]  J. Gilmore,et al.  Mapping Longitudinal Development of Local Cortical Gyrification in Infants from Birth to 2 Years of Age , 2014, The Journal of Neuroscience.

[14]  James J Levitt,et al.  Reduced left angular gyrus volume in first-episode schizophrenia. , 2005, The American journal of psychiatry.

[15]  H. Duvernoy,et al.  The Human Brain: Surface, Three-Dimensional Sectional Anatomy with MRI, and Blood Supply , 1999 .

[16]  H. Duvernoy The Human Brain , 1999, Springer Vienna.

[17]  Michael C. Stevens,et al.  Cortical Thickness and Folding Deficits in Conduct-Disordered Adolescents , 2012, Biological Psychiatry.

[18]  Daniel Rueckert,et al.  Automatic detection and quantification of hippocampal atrophy on MRI in temporal lobe epilepsy: A proof-of-principle study , 2007, NeuroImage.

[19]  Robert F. Hevner,et al.  Role of Intermediate Progenitor Cells in Cerebral Cortex Development , 2007, Developmental Neuroscience.

[20]  C. Price The anatomy of language: a review of 100 fMRI studies published in 2009 , 2010, Annals of the New York Academy of Sciences.

[21]  Linda G. Shapiro,et al.  Parcellation of human inferior parietal lobule based on diffusion MRI , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[22]  K. Huffman,et al.  The Developing, Aging Neocortex: How Genetics and Epigenetics Influence Early Developmental Patterning and Age-Related Change , 2012, Front. Gene..

[23]  Meritxell Bach Cuadra,et al.  How to measure cortical folding from MR images: a step-by-step tutorial to compute local gyrification index. , 2012, Journal of visualized experiments : JoVE.

[24]  H. Kennedy,et al.  Comparative aspects of cerebral cortical development , 2006, The European journal of neuroscience.

[25]  D. Shattuck,et al.  The human cerebral cortex on MRI: value of the coronal plane , 2005, Surgical and Radiologic Anatomy.

[26]  Jennifer L. Whitwell,et al.  Accurate automatic estimation of total intracranial volume: A nuisance variable with less nuisance , 2015, NeuroImage.

[27]  Daniel Rueckert,et al.  Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy , 2009, NeuroImage.

[28]  Joseph T. Devlin,et al.  Supramarginal gyrus involvement in visual word recognition , 2009, Cortex.

[29]  Jean-Francois Mangin,et al.  Sulcal pattern and morphology of the superior temporal sulcus , 2004, NeuroImage.

[30]  Peter H. Sudmant,et al.  Diversity of Human Copy Number Variation and Multicopy Genes , 2010, Science.

[31]  Alan C. Evans,et al.  Anatomical-Functional Correlation Using an Adjustable MRI-Based Region of Interest Atlas with Positron Emission Tomography , 1988, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[32]  Daniel Rueckert,et al.  Automatic Whole Brain MRI Segmentation of the Developing Neonatal Brain , 2014, IEEE Transactions on Medical Imaging.

[33]  Alexander Hammers,et al.  Three‐dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe , 2003, Human brain mapping.

[34]  T. Greitz,et al.  Adjustable computerized stereotaxic brain atlas for transmission and emission tomography. , 1983, AJNR. American journal of neuroradiology.

[35]  François Chollet,et al.  Writing, calculating, and finger recognition in the region of the angular gyrus: a cortical stimulation study of Gerstmann syndrome. , 2003, Journal of neurosurgery.

[36]  Robert Turner,et al.  Connectivity architecture and subdivision of the human inferior parietal cortex revealed by diffusion MRI. , 2014, Cerebral cortex.

[37]  Alexander Hammers,et al.  Automatic segmentation of the brain and intracranial cerebrospinal fluid in T1‐weighted volume MRI scans of the head, and its application to serial cerebral and intracranial volumetry , 2003, Magnetic resonance in medicine.

[38]  Stephen Lawrie,et al.  Pre-frontal lobe gyrification index in schizophrenia, mental retardation and comorbid groups: An automated study , 2007, NeuroImage.

[39]  Manuel Carreiras,et al.  Where syntax meets math: Right intraparietal sulcus activation in response to grammatical number agreement violations , 2010, NeuroImage.

[40]  Anders M. Dale,et al.  Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature , 2010, NeuroImage.

[41]  小野 道夫,et al.  Atlas of the Cerebral Sulci , 1990 .

[42]  Jesse S. Jin,et al.  Cortical Gyrification and Sulcal Spans in Early Stage Alzheimer's Disease , 2012, PloS one.

[43]  V Menon,et al.  Functional heterogeneity of inferior parietal cortex during mathematical cognition assessed with cytoarchitectonic probability maps. , 2009, Cerebral cortex.

[44]  Arthur W. Toga,et al.  Construction of a 3D probabilistic atlas of human cortical structures , 2008, NeuroImage.

[45]  P. Liddle,et al.  Dissociable morphometric differences of the inferior parietal lobule in schizophrenia , 2012, European Archives of Psychiatry and Clinical Neuroscience.

[46]  Bernard Mazoyer,et al.  Disentangling the brain networks supporting affective speech comprehension , 2012, NeuroImage.

[47]  R. Bajcsy,et al.  Elastically Deforming 3D Atlas to Match Anatomical Brain Images , 1993, Journal of computer assisted tomography.

[48]  F. Fazio,et al.  Matching a Computerized Brain Atlas to Multimodal Medical Images , 1997, NeuroImage.

[49]  L. Fañanás,et al.  A cross-sectional and longitudinal structural magnetic resonance imaging study of the post-central gyrus in first-episode schizophrenia patients , 2015, Psychiatry Research: Neuroimaging.

[50]  Nicolas Cherbuin,et al.  Cortical gyrification and its relationships with cortical volume, cortical thickness, and cognitive performance in healthy mid-life adults , 2015, Behavioural Brain Research.

[51]  R. Haier,et al.  Neuroanatomy of creativity , 2009, Human brain mapping.

[52]  M. Seghier,et al.  Functional Subdivisions in the Left Angular Gyrus Where the Semantic System Meets and Diverges from the Default Network , 2010, The Journal of Neuroscience.

[53]  D. V. van Essen,et al.  Mapping Human Cortical Areas In Vivo Based on Myelin Content as Revealed by T1- and T2-Weighted MRI , 2011, The Journal of Neuroscience.

[54]  Alan C. Evans,et al.  MRI-PET Correlation in Three Dimensions Using a Volume-of-Interest (VOI) Atlas , 1991, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[55]  Stephen M. Smith,et al.  Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.

[56]  Karl J. Friston,et al.  Incorporating Prior Knowledge into Image Registration , 1997, NeuroImage.

[57]  Vincent A Magnotta,et al.  Cerebral cortex: a topographic segmentation method using magnetic resonance imaging , 2000, Psychiatry Research: Neuroimaging.

[58]  Henry Kennedy,et al.  Cortical High-Density Counterstream Architectures , 2013, Science.

[59]  Joseph V. Hajnal,et al.  A robust method to estimate the intracranial volume across MRI field strengths (1.5T and 3T) , 2010, NeuroImage.

[60]  Marc G. Lucas,et al.  Dissociated Neural Processing for Decisions in Managers and Non-Managers , 2012, PloS one.

[61]  K. Amunts,et al.  The human inferior parietal lobule in stereotaxic space , 2008, Brain Structure and Function.

[62]  I. Dan,et al.  Sound to Language: Different Cortical Processing for First and Second Languages in Elementary School Children as Revealed by a Large-Scale Study Using fNIRS , 2011, Cerebral cortex.

[63]  Daniel Rueckert,et al.  Automatic morphometry in Alzheimer's disease and mild cognitive impairment☆☆☆ , 2011, NeuroImage.

[64]  Matthew F. Glasser,et al.  Trends and Properties of Human Cerebral Cortex: Correlations with Cortical Myelin Content Introduction and Review , 2022 .

[65]  Henry Kennedy,et al.  Self-organization and interareal networks in the primate cortex. , 2012, Progress in brain research.

[66]  B. Horwitz,et al.  Functional connectivity of the angular gyrus in normal reading and dyslexia. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[67]  Yasuhiro Kawasaki,et al.  Parietal lobe volume deficits in schizophrenia spectrum disorders , 2007, Schizophrenia Research.

[68]  Richard J. S. Wise,et al.  The Contribution of the Parietal Lobes to Speaking and Writing , 2009, Cerebral cortex.

[69]  John W. Harwell,et al.  Similar patterns of cortical expansion during human development and evolution , 2010, Proceedings of the National Academy of Sciences.

[70]  L. Brown,et al.  Regional brain activity during early-stage intense romantic love predicted relationship outcomes after 40 months: An fMRI assessment , 2012, Neuroscience Letters.

[71]  Juha Silvanto,et al.  The role of the angular gyrus in the modulation of visuospatial attention by the mental number line , 2009, NeuroImage.

[72]  R. Bajcsy,et al.  Evaluation of Elastic Matching System for Anatomic (CT, MR) and Functional (PET) Cerebral Images , 1989, Journal of computer assisted tomography.

[73]  A. Evans,et al.  Development of Cortical Surface Area and Gyrification in Attention-Deficit/Hyperactivity Disorder , 2012, Biological Psychiatry.

[74]  G. Bruyn Atlas of the Cerebral Sulci, M. Ono, S. Kubik, Chad D. Abernathey (Eds.). Georg Thieme Verlag, Stuttgart, New York (1990), 232, DM 298 , 1990 .

[75]  T Greitz,et al.  Journal of Cerebral Blood Flow and Metabolism Accuracy and Precision of the Computerized Brain Atlas Programme for Localization and Quantification in Positron Emission Tomography , 2022 .

[76]  Daniel Rueckert,et al.  Automatic anatomical brain MRI segmentation combining label propagation and decision fusion , 2006, NeuroImage.

[77]  E. Torrey,et al.  Schizophrenia and the inferior parietal lobule , 2007, Schizophrenia Research.

[78]  Daniel Rueckert,et al.  Improving intersubject image registration using tissue-class information benefits robustness and accuracy of multi-atlas based anatomical segmentation , 2010, NeuroImage.

[79]  D. V. van Essen,et al.  Structural and Functional Analyses of Human Cerebral Cortex Using a Surface-Based Atlas , 1997, The Journal of Neuroscience.

[80]  Alexander Hammers,et al.  Macroanatomy and 3D probabilistic atlas of the human insula , 2017, NeuroImage.

[81]  Karl J. Friston,et al.  Unified segmentation , 2005, NeuroImage.

[82]  Alexander Hammers,et al.  Volumes, spatial extents and a probabilistic atlas of the human basal ganglia and thalamus , 2007, NeuroImage.

[83]  S. Huettel,et al.  A Distinct Role of the Temporal-Parietal Junction in Predicting Socially Guided Decisions , 2012, Science.

[84]  R. Bajcsy,et al.  A computerized system for the elastic matching of deformed radiographic images to idealized atlas images. , 1983, Journal of computer assisted tomography.