Age‐related mapping of intracortical myelin from late adolescence to middle adulthood using T1‐weighted MRI

Magnetic resonance imaging (MRI) studies in humans have reported that the T1‐weighted signal in the cerebral cortex follows an inverted “U” trajectory over the lifespan. Here, we investigated the T1‐weighted signal trajectory from late adolescence to middle adulthood in humans to characterize the age range when mental illnesses tend to present, and efficacy of treatments are evaluated. We compared linear to quadratic predictors of age on signal in 67 healthy individuals, 17–45 years old. We investigated ¼, ½, and ¾ depths in the cortex representing intracortical myelin (ICM), in the superficial white matter (SWM), and in a reference deep white matter tract. We found that the quadratic fit was superior in all regions of the cortex, while signal in the SWM and deep white matter showed no global dependence on age over this range. The signal trajectory in any region followed a similar shape regardless of cortical depth. The quadratic fit was analyzed in 70 cortical regions to obtain the age of maximum signal intensity. We found that visual, cingulate, and left ventromedial prefrontal cortices peak first around 34 years old, whereas motor and premotor areas peak latest at ∼38 years. Our analysis suggests that ICM trajectories over this range can be modeled well in small cohorts of subjects using quadratic functions, which are amenable to statistical analysis, thus suitable for investigating regional changes in ICM with disease. This study highlights a novel approach to map ICM trajectories using an age range that coincides with the onset of many mental illnesses. Hum Brain Mapp 38:3691–3703, 2017. © 2017 Wiley Periodicals, Inc.

[1]  H. Akaike,et al.  Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .

[2]  B. Brody,et al.  Sequence of Central Nervous System Myelination in Human Infancy. I. An Autopsy Study of Myelination , 1987, Journal of neuropathology and experimental neurology.

[3]  D. Norman,et al.  Normal maturation of the neonatal and infant brain: MR imaging at 1.5 T. , 1988, Radiology.

[4]  E Courchesne,et al.  In vivo myeloarchitectonic analysis of human striate and extrastriate cortex using magnetic resonance imaging. , 1992, Cerebral cortex.

[5]  M. Xi,et al.  Changes in the axonal conduction velocity of pyramidal tract neurons in the aged cat , 1999, Neuroscience.

[6]  R. Turner,et al.  Optimization of 3-D MP-RAGE Sequences for Structural Brain Imaging , 2000, NeuroImage.

[7]  Alan Peters,et al.  Effects of aging on myelinated nerve fibers in monkey primary visual cortex , 2000, The Journal of comparative neurology.

[8]  R. Killiany,et al.  Effects of age on the thickness of myelin sheaths in monkey primary visual cortex , 2001, The Journal of comparative neurology.

[9]  Dzung L. Pham,et al.  Robust fuzzy segmentation of magnetic resonance images , 2001, Proceedings 14th IEEE Symposium on Computer-Based Medical Systems. CBMS 2001.

[10]  G. Bartzokis,et al.  Age-related changes in frontal and temporal lobe volumes in men: a magnetic resonance imaging study. , 2001, Archives of general psychiatry.

[11]  Xiao Han,et al.  CRUISE: Cortical reconstruction using implicit surface evolution , 2004, NeuroImage.

[12]  H. Braak,et al.  Loss of intracortical myelinated fibers: A distinctive age-related alteration in the human striate area , 2004, Acta Neuropathologica.

[13]  G. Bartzokis,et al.  Heterogeneous age-related breakdown of white matter structural integrity: implications for cortical “disconnection” in aging and Alzheimer’s disease , 2004, Neurobiology of Aging.

[14]  George Bartzokis,et al.  Quadratic trajectories of brain myelin content: unifying construct for neuropsychiatric disorders , 2004, Neurobiology of Aging.

[15]  A. Schleicher,et al.  High‐resolution MRI reflects myeloarchitecture and cytoarchitecture of human cerebral cortex , 2005, Human brain mapping.

[16]  Maolin Qiu,et al.  In vivo method for correcting transmit/receive nonuniformities with phased array coils , 2005, Magnetic resonance in medicine.

[17]  Olga V. Demler,et al.  Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. , 2005, Archives of general psychiatry.

[18]  F. Craik,et al.  Cognition through the lifespan: mechanisms of change , 2006, Trends in Cognitive Sciences.

[19]  John V. Carlis,et al.  Where the brain grows old: Decline in anterior cingulate and medial prefrontal function with normal aging , 2007, NeuroImage.

[20]  Alexander Leemans,et al.  Microstructural maturation of the human brain from childhood to adulthood , 2008, NeuroImage.

[21]  Arthur W. Toga,et al.  Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template , 2008, NeuroImage.

[22]  Nicholas A. Bock,et al.  Visualizing the entire cortical myelination pattern in marmosets with magnetic resonance imaging , 2009, Journal of Neuroscience Methods.

[23]  Steen Moeller,et al.  T 1 weighted brain images at 7 Tesla unbiased for Proton Density, T 2 ⁎ contrast and RF coil receive B 1 sensitivity with simultaneous vessel visualization , 2009, NeuroImage.

[24]  G. Bartzokis,et al.  In vivo evidence of differential impact of typical and atypical antipsychotics on intracortical myelin in adults with schizophrenia , 2009, Schizophrenia Research.

[25]  M. D’Esposito,et al.  Is the rostro-caudal axis of the frontal lobe hierarchical? , 2009, Nature Reviews Neuroscience.

[26]  Anders M. Dale,et al.  Differentiating maturational and aging-related changes of the cerebral cortex by use of thickness and signal intensity , 2010, NeuroImage.

[27]  A. Dale,et al.  Life-span changes of the human brain white matter: diffusion tensor imaging (DTI) and volumetry. , 2010, Cerebral cortex.

[28]  Anders M. Dale,et al.  When does brain aging accelerate? Dangers of quadratic fits in cross-sectional studies , 2010, NeuroImage.

[29]  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.

[30]  Aaron Carass,et al.  Simple paradigm for extra-cerebral tissue removal: Algorithm and analysis , 2011, NeuroImage.

[31]  D. Attwell,et al.  Regulation of Oligodendrocyte Development and Myelination by Glucose and Lactate , 2011, The Journal of Neuroscience.

[32]  Erika P. Raven,et al.  Impact on intracortical myelination trajectory of long acting injection versus oral risperidone in first-episode schizophrenia , 2012, Schizophrenia Research.

[33]  Daniel J. Miller,et al.  Prolonged myelination in human neocortical evolution , 2012, Proceedings of the National Academy of Sciences.

[34]  Jens Frahm,et al.  Glycolytic oligodendrocytes maintain myelin and long-term axonal integrity , 2012, Nature.

[35]  Pierre J. Magistretti,et al.  Oligodendroglia metabolically support axons and contribute to neurodegeneration , 2012, Nature.

[36]  David Attwell,et al.  The Energetics of CNS White Matter , 2012, The Journal of Neuroscience.

[37]  R. Nieuwenhuys The myeloarchitectonic studies on the human cerebral cortex of the Vogt–Vogt school, and their significance for the interpretation of functional neuroimaging data , 2013, Brain Structure and Function.

[38]  R. Turner,et al.  Optimizing T 1-weighted imaging of cortical myelin content at 3 . 0 T , 2012 .

[39]  Jerry L. Prince,et al.  A multiple object geometric deformable model for image segmentation , 2013, Comput. Vis. Image Underst..

[40]  L. Westlye,et al.  Intracortical Myelin Links with Performance Variability across the Human Lifespan: Results from T1- and T2-Weighted MRI Myelin Mapping and Diffusion Tensor Imaging , 2013, The Journal of Neuroscience.

[41]  Rolf Gruetter,et al.  New Developments and Applications of the MP2RAGE Sequence - Focusing the Contrast and High Spatial Resolution R1 Mapping , 2013, PloS one.

[42]  J. Rothstein,et al.  Oligodendroglia: metabolic supporters of axons. , 2013, Trends in cell biology.

[43]  F. Dick,et al.  Mapping the Human Cortical Surface by Combining Quantitative T1 with Retinotopy† , 2012, Cerebral cortex.

[44]  Arthur W. Toga,et al.  Superficial White Matter: Effects of Age, Sex, and Hemisphere , 2013, Brain Connect..

[45]  Robert Turner,et al.  Optimizing T1-weighted imaging of cortical myelin content at 3.0T , 2013, NeuroImage.

[46]  Pierre-Louis Bazin,et al.  Anatomically motivated modeling of cortical laminae , 2014, NeuroImage.

[47]  Christopher W Mount,et al.  Neuronal Activity Promotes Oligodendrogenesis and Adaptive Myelination in the Mammalian Brain , 2014, Science.

[48]  Robert Turner,et al.  Myelin and iron concentration in the human brain: A quantitative study of MRI contrast , 2014, NeuroImage.

[49]  Nikolaus Weiskopf,et al.  Using high-resolution quantitative mapping of R1 as an index of cortical myelination , 2014, NeuroImage.

[50]  Juliane Dinse,et al.  A computational framework for ultra-high resolution cortical segmentation at 7Tesla , 2014, NeuroImage.

[51]  M. Mallar Chakravarty,et al.  Superficial white matter as a novel substrate of age-related cognitive decline , 2015, Neurobiology of Aging.

[52]  Bernhard Preim,et al.  A cytoarchitecture-driven myelin model reveals area-specific signatures in human primary and secondary areas using ultra-high resolution in-vivo brain MRI , 2015, NeuroImage.

[53]  R. Goebel,et al.  High-Resolution Mapping of Myeloarchitecture In Vivo: Localization of Auditory Areas in the Human Brain. , 2015, Cerebral cortex.

[54]  Bruce Fischl,et al.  Gray matter myelination of 1555 human brains using partial volume corrected MRI images , 2015, NeuroImage.

[55]  Kazuhiro Shinosaki,et al.  Use of T1‐weighted/T2‐weighted magnetic resonance ratio images to elucidate changes in the schizophrenic brain , 2015, Brain and behavior.

[56]  Pierre-Louis Bazin,et al.  Multi-contrast multi-scale surface registration for improved alignment of cortical areas , 2015, NeuroImage.

[57]  Christine L. Tardif,et al.  Assessing intracortical myelin in the living human brain using myelinated cortical thickness , 2015, Front. Neurosci..

[58]  K. Walhovd,et al.  Accelerated longitudinal gray/white matter contrast decline in aging in lightly myelinated cortical regions , 2016, Human brain mapping.

[59]  A. Brovelli,et al.  MarsAtlas: A cortical parcellation atlas for functional mapping , 2016, Human brain mapping.

[60]  Evelyn M. R. Lake,et al.  Altered intracortical myelin staining in the dorsolateral prefrontal cortex in severe mental illness , 2017, European Archives of Psychiatry and Clinical Neuroscience.

[61]  Christine L. Tardif,et al.  A subject-specific framework for in vivo myeloarchitectonic analysis using high resolution quantitative MRI , 2016, NeuroImage.

[62]  Natalia Petridou,et al.  Lines of Baillarger in vivo and ex vivo: Myelin contrast across lamina at 7T MRI and histology , 2016, NeuroImage.

[63]  Natalia Petridou,et al.  Myelin contrast across lamina at 7T, ex-vivo and in-vivo dataset , 2016, Data in brief.

[64]  W. Richardson,et al.  Rapid production of new oligodendrocytes is required in the earliest stages of motor skill learning , 2016, Nature Neuroscience.

[65]  Håkon Grydeland,et al.  Intracortical Posterior Cingulate Myelin Content Relates to Error Processing: Results from T1- and T2-Weighted MRI Myelin Mapping and Electrophysiology in Healthy Adults. , 2016, Cerebral cortex.

[66]  Wiepke Cahn,et al.  Accelerated Brain Aging in Schizophrenia: A Longitudinal Pattern Recognition Study. , 2016, The American journal of psychiatry.

[67]  B. Dubois,et al.  Rostro-caudal Architecture of the Frontal Lobes in Humans , 2016, Cerebral cortex.