Normative brain size variation and brain shape diversity in humans

Shifts in brain regions with brain size Brain size among normal humans varies as much as twofold. Reardon et al. surveyed the cortical and subcortical structure of more than 3000 human brains by noninvasive imaging (see the Perspective by Van Essen). They found that the scaling of different regions across the range of brain sizes is not consistent: Some brain regions are metabolically costly and are favored in larger brains. This shifts the balance between associative and sensorimotor brain systems in a brain size–dependent way. Science, this issue p. 1222; see also p. 1184 A metabolically expensive brain network is preferentially expanded in individuals that have larger brains. Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology.

[1]  C. Papadimitriou,et al.  Introduction to the Theory of Computation , 2018 .

[2]  Israel Steinfeld,et al.  BMC Bioinformatics BioMed Central , 2008 .

[3]  M. Rietschel,et al.  Correlated gene expression supports synchronous activity in brain networks , 2015, Science.

[4]  Andrei G. Vlassenko,et al.  Regional aerobic glycolysis in the human brain , 2010, Proceedings of the National Academy of Sciences.

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

[6]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[7]  Norbert Schuff,et al.  Association of common genetic variants in GPCPD1 with scaling of visual cortical surface area in humans , 2012, Proceedings of the National Academy of Sciences.

[8]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[9]  Alan C. Evans,et al.  A fully automatic and robust brain MRI tissue classification method , 2003, Medical Image Anal..

[10]  R. Berman,et al.  Longitudinal four-dimensional mapping of subcortical anatomy in human development , 2014, Proceedings of the National Academy of Sciences.

[11]  Ichiro Fujita,et al.  Pyramidal cell development: postnatal spinogenesis, dendritic growth, axon growth, and electrophysiology , 2014, Front. Neuroanat..

[12]  Antonio-José Almeida,et al.  NAT , 2019, Springer Reference Medizin.

[13]  M. Mallar Chakravarty,et al.  The creation of a brain atlas for image guided neurosurgery using serial histological data , 2006, NeuroImage.

[14]  David C. Glahn,et al.  The correspondence problem: which brain maps are significantly similar? , 2017, bioRxiv.

[15]  Michael Sipser,et al.  Introduction to the Theory of Computation , 1996, SIGA.

[16]  Christos Davatzikos,et al.  Neuroimaging of the Philadelphia Neurodevelopmental Cohort , 2014, NeuroImage.

[17]  S. Wood Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models , 2011 .

[18]  C. Edelbrock,et al.  Manual for the Child: Behavior Checklist and Revised Child Behavior Profile , 1983 .

[19]  Anders M. Dale,et al.  Genetic Influences on Cortical Regionalization in the Human Brain , 2011, Neuron.

[20]  M. Mallar Chakravarty,et al.  Allometric Analysis Detects Brain Size-Independent Effects of Sex and Sex Chromosome Complement on Human Cerebellar Organization , 2017, The Journal of Neuroscience.

[21]  Alan C. Evans,et al.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.

[22]  Timothy O. Laumann,et al.  Informatics and Data Mining Tools and Strategies for the Human Connectome Project , 2011, Front. Neuroinform..

[23]  R. Gur,et al.  Patterns of coordinated cortical remodeling during adolescence and their associations with functional specialization and evolutionary expansion , 2017, Proceedings of the National Academy of Sciences.

[24]  Efstathios D. Gennatas,et al.  Impact of puberty on the evolution of cerebral perfusion during adolescence , 2014, Proceedings of the National Academy of Sciences.

[25]  Alan C. Evans,et al.  Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification , 2005, NeuroImage.

[26]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[27]  Elizabeth Jefferies,et al.  Situating the default-mode network along a principal gradient of macroscale cortical organization , 2016, Proceedings of the National Academy of Sciences.

[28]  Alan C. Evans,et al.  Positional and surface area asymmetry of the human cerebral cortex , 2009, NeuroImage.

[29]  A. B. Hollingshead Four Factor Index of Social Status [1975] , 1975 .

[30]  Barbara L. Finlay,et al.  Systematic, balancing gradients in neuron density and number across the primate isocortex , 2012, Front. Neuroanat..

[31]  J. Huxley Constant Differential Growth-Ratios and their Significance , 1924, Nature.

[32]  G. Elston Cortex, cognition and the cell: new insights into the pyramidal neuron and prefrontal function. , 2003, Cerebral cortex.

[33]  Mark Jenkinson,et al.  The minimal preprocessing pipelines for the Human Connectome Project , 2013, NeuroImage.

[34]  S. S. Young,et al.  Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment , 1993 .

[35]  D. Collins,et al.  Performing label‐fusion‐based segmentation using multiple automatically generated templates , 2013, Human brain mapping.

[36]  C. Economo,et al.  Die Cytoarchitektonik der Hirnrinde des erwachsenen Menschen , 1925 .

[37]  Peter B. Jones,et al.  373. Adolescence is Associated with Genomically Patterned Consolidation of the Hubs of the Human Brain Connectome , 2016, Biological Psychiatry.

[38]  Matko Bosnjak,et al.  REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms , 2011, PloS one.

[39]  S. Blakemore,et al.  Development of the Cerebral Cortex across Adolescence: A Multisample Study of Inter-Related Longitudinal Changes in Cortical Volume, Surface Area, and Thickness , 2017, The Journal of Neuroscience.

[40]  Mikis D. Stasinopoulos,et al.  Generalized Additive Models: An Introduction with R. by S. N. WOOD , 2007 .

[41]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[42]  Danielle S. Bassett,et al.  Cognitive Network Neuroscience , 2015, Journal of Cognitive Neuroscience.

[43]  Alan C. Evans,et al.  Intellectual ability and cortical development in children and adolescents , 2006, Nature.

[44]  Olaf Sporns,et al.  Network attributes for segregation and integration in the human brain , 2013, Current Opinion in Neurobiology.

[45]  Alan C. Evans,et al.  Brain development during childhood and adolescence: a longitudinal MRI study , 1999, Nature Neuroscience.

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

[47]  Allan R. Jones,et al.  An anatomically comprehensive atlas of the adult human brain transcriptome , 2012, Nature.

[48]  J. Rapoport,et al.  Child Psychiatry Branch of the National Institute of Mental Health Longitudinal Structural Magnetic Resonance Imaging Study of Human Brain Development , 2015, Neuropsychopharmacology.

[49]  R. Gur,et al.  Topologically Dissociable Patterns of Development of the Human Cerebral Cortex , 2015, The Journal of Neuroscience.

[50]  A. Luik,et al.  The Developmental Course of Sleep Disturbances Across Childhood Relates to Brain Morphology at Age 7: The Generation R Study , 2017, Sleep.

[51]  D. Collins,et al.  Automatic 3D Intersubject Registration of MR Volumetric Data in Standardized Talairach Space , 1994, Journal of computer assisted tomography.

[52]  Linda Chang,et al.  Long-term influence of normal variation in neonatal characteristics on human brain development , 2012, Proceedings of the National Academy of Sciences.

[53]  Andre Altmann,et al.  Re-Annotator: Annotation Pipeline for Microarray Probe Sequences , 2015, PloS one.

[54]  Marisa O. Hollinshead,et al.  The organization of the human cerebral cortex estimated by intrinsic functional connectivity. , 2011, Journal of neurophysiology.

[55]  Mikail Rubinov,et al.  Constraints and spandrels of interareal connectomes , 2016, Nature Communications.

[56]  M. A. García-Cabezas,et al.  A role for intermediate radial glia in the tangential expansion of the mammalian cerebral cortex. , 2011, Cerebral cortex.

[57]  P. Hof,et al.  Metabolic costs and evolutionary implications of human brain development , 2014, Proceedings of the National Academy of Sciences.