Browsing by Author "Wang, Yang"
Now showing 1 - 10 of 37
Results Per Page
Sort Options
Item Altered Cerebral Blood Flow One Month after Systemic Chemotherapy for Breast Cancer: A Prospective Study Using Pulsed Arterial Spin Labeling MRI Perfusion(Public Library of Science, 2014-05-09) Nudelman, Kelly N. H.; Wang, Yang; McDonald, Brenna C.; Conroy, Susan K.; Smith, Dori J.; West, John D.; O’Neill, Darren P.; Schneider, Bryan P.; Saykin, Andrew J.; Medical and Molecular Genetics, School of MedicineCerebral structural and functional alterations have been reported after chemotherapy for non-CNS cancers, yet the causative mechanism behind these changes remains unclear. This study employed a novel, non-invasive, MRI-based neuroimaging measure to provide the first direct longitudinal measurement of resting cerebral perfusion in breast cancer patients, which was tested for association with changes in cognitive function and gray matter density. Perfusion was measured using pulsed arterial spin labeling MRI in women with breast cancer treated with (N = 27) or without (N = 26) chemotherapy and matched healthy controls (N = 26) after surgery before other treatments (baseline), and one month after chemotherapy completion or yoked intervals. Voxel-based analysis was employed to assess perfusion in gray matter; changes were examined in relation to overall neuropsychological test performance and frontal gray matter density changes measured by structural MRI. Baseline perfusion was not significantly different across groups. Unlike control groups, chemotherapy-treated patients demonstrated significantly increased perfusion post-treatment relative to baseline, which was statistically significant relative to controls in the right precentral gyrus. This perfusion increase was negatively correlated with baseline overall neuropsychological performance, but was not associated with frontal gray matter density reduction. However, decreased frontal gray matter density was associated with decreased perfusion in bilateral frontal and parietal lobes in the chemotherapy-treated group. These findings indicate that chemotherapy is associated with alterations in cerebral perfusion which are both related to and independent of gray matter changes. This pattern of results suggests the involvement of multiple mechanisms of chemotherapy-induced cognitive dysfunction. Additionally, lower baseline cognitive function may be a risk factor for treatment-associated perfusion dysregulation. Future research is needed to clarify these mechanisms, identify individual differences in susceptibility to treatment-associated changes, and further examine perfusion change over time in survivors.Item Altered Default Mode Network Connectivity in Older Adults with Cognitive Complaints and Amnestic Mild Cognitive Impairment(Sage, 2013) Wang, Yang; Risacher, Shannon L.; West, John D.; McDonald, Brenna C.; MaGee, Tamiko R.; Farlow, Martin R.; Gao, Sujuan; O’Neill, Darren P.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineDefault mode network (DMN) disruption has been reported in Alzheimer's disease (AD), yet the specific pattern of altered connectivity over the course of prodromal AD remains to be characterized. The aim of this study was to assess DMN connectivity in older adults with informant-verified cognitive complaints (CC) but normal neuropsychological performance compared to individuals with mild cognitive impairment (MCI) and healthy controls (HC). DMN maps were derived from resting-state fMRI using independent component analysis. Group comparisons of DMN connectivity were performed between older adults with MCI (n = 18), CC (n = 23), and HC (n = 16). Both CC and MCI showed decreased DMN connectivity in the right hippocampus compared to HC, with the CC group showing greater connectivity than MCI. These differences survived atrophy correction and correlated with cognitive performance. DMN connectivity appears sensitive to early prodromal neurodegenerative changes associated with AD, notably including pre-MCI individuals with cognitive complaints.Item Associations between regional brain physiology and trait impulsivity, motor inhibition, and impaired control over drinking(Elsevier, 2015-08-30) Weafer, Jessica; Dzemidzic, Mario; Eiler, William J. A. II; Oberlin, Brandon G.; Wang, Yang; Kareken, David A.; Department of Neurology, IU School of MedicineTrait impulsivity and poor inhibitory control are well-established risk factors for alcohol misuse, yet little is known about the associated neurobiological endophenotypes. Here we examined correlations among brain physiology and self-reported trait impulsive behavior, impaired control over drinking, and a behavioral measure of response inhibition. A sample of healthy drinkers (n = 117) completed a pulsed arterial spin labeling (PASL) scan to quantify resting regional cerebral blood flow (rCBF), as well as measures of self-reported impulsivity (Eysenck I7 Impulsivity scale) and impaired control over drinking. A subset of subjects (n = 40) performed a stop signal task during blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging to assess brain regions involved in response inhibition. Eysenck I7 scores were inversely related to blood flow in the right precentral gyrus. Significant BOLD activation during response inhibition occurred in an overlapping right frontal motor/premotor region. Moreover, impaired control over drinking was associated with reduced BOLD response in the same region. These findings suggest that impulsive personality and impaired control over drinking are associated with brain physiology in areas implicated in response inhibition. This is consistent with the idea that difficulty controlling behavior is due in part to impairment in motor restraint systems.Item Brain explorer for connectomic analysis(Springer, 2017-08-23) Li, Huang; Fang, Shiaofen; Contreras, Joey A.; West, John D.; Risacher, Shannon L.; Wang, Yang; Sporns, Olaf; Saykin, Andrew J.; Goñi, Joaquín; Shen, Li; Radiology and Imaging Sciences, School of MedicineVisualization plays a vital role in the analysis of multimodal neuroimaging data. A major challenge in neuroimaging visualization is how to integrate structural, functional, and connectivity data to form a comprehensive visual context for data exploration, quality control, and hypothesis discovery. We develop a new integrated visualization solution for brain imaging data by combining scientific and information visualization techniques within the context of the same anatomical structure. In this paper, new surface texture techniques are developed to map non-spatial attributes onto both 3D brain surfaces and a planar volume map which is generated by the proposed volume rendering technique, spherical volume rendering. Two types of non-spatial information are represented: (1) time series data from resting-state functional MRI measuring brain activation; (2) network properties derived from structural connectivity data for different groups of subjects, which may help guide the detection of differentiation features. Through visual exploration, this integrated solution can help identify brain regions with highly correlated functional activations as well as their activation patterns. Visual detection of differentiation features can also potentially discover image-based phenotypic biomarkers for brain diseases.Item Brain-age prediction: Systematic evaluation of site effects, and sample age range and size(Wiley, 2024) Yu, Yuetong; Cui, Hao-Qi; Haas, Shalaila S.; New, Faye; Sanford, Nicole; Yu, Kevin; Zhan, Denghuang; Yang, Guoyuan; Gao, Jia-Hong; Wei, Dongtao; Qiu, Jiang; Banaj, Nerisa; Boomsma, Dorret I.; Breier, Alan; Brodaty, Henry; Buckner, Randy L.; Buitelaar, Jan K.; Cannon, Dara M.; Caseras, Xavier; Clark, Vincent P.; Conrod, Patricia J.; Crivello, Fabrice; Crone, Eveline A.; Dannlowski, Udo; Davey, Christopher G.; de Haan, Lieuwe; de Zubicaray, Greig I.; Di Giorgio, Annabella; Fisch, Lukas; Fisher, Simon E.; Franke, Barbara; Glahn, David C.; Grotegerd, Dominik; Gruber, Oliver; Gur, Raquel E.; Gur, Ruben C.; Hahn, Tim; Harrison, Ben J.; Hatton, Sean; Hickie, Ian B.; Hulshoff Pol, Hilleke E.; Jamieson, Alec J.; Jernigan, Terry L.; Jiang, Jiyang; Kalnin, Andrew J.; Kang, Sim; Kochan, Nicole A.; Kraus, Anna; Lagopoulos, Jim; Lazaro, Luisa; McDonald, Brenna C.; McDonald, Colm; McMahon, Katie L.; Mwangi, Benson; Piras, Fabrizio; Rodriguez-Cruces, Raul; Royer, Jessica; Sachdev, Perminder S.; Satterthwaite, Theodore D.; Saykin, Andrew J.; Schumann, Gunter; Sevaggi, Pierluigi; Smoller, Jordan W.; Soares, Jair C.; Spalletta, Gianfranco; Tamnes, Christian K.; Trollor, Julian N.; Van't Ent, Dennis; Vecchio, Daniela; Walter, Henrik; Wang, Yang; Weber, Bernd; Wen, Wei; Wierenga, Lara M.; Williams, Steven C. R.; Wu, Mon-Ju; Zunta-Soares, Giovana B.; Bernhardt, Boris; Thompson, Paul; Frangou, Sophia; Ge, Ruiyang; ENIGMA-Lifespan Working Group; Psychiatry, School of MedicineStructural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.Item Cerebral blood flow in acute concussion: preliminary ASL findings from the NCAA-DoD CARE consortium(Springer, 2019-10-01) Wang, Yang; Nencka, Andrew S.; Meier, Timothy B.; Guskiewicz, Kevin; Mihalik, Jason P.; Alison Brooks, M.; Saykin, Andrew J.; Koch, Kevin M.; Wu, Yu-Chien; Nelson, Lindsay D.; McAllister, Thomas W.; Broglio, Steven P.; McCrea, Michael A.; Radiology and Imaging Sciences, School of MedicineSport-related concussion (SRC) has become a major health problem, affecting millions of athletes each year. Despite the increasing occurrence and prevalence of SRC, its underlying mechanism and recovery course have yet to be fully elucidated. The National Collegiate Athletic Association–Department of Defense Grand Alliance: Concussion Assessment, Research and Education (CARE) Consortium is a large-scale, multisite study of the natural history of concussion across multiple sports. The Advanced Research Core (ARC) of CARE is focused on the advanced biomarker assessment of a reduced subject cohort. This paper reports findings from two ARC sites to evaluate cerebral blood flow (CBF) changes in acute SRC, as measured using advanced arterial spin labeling (ASL) magnetic resonance imaging (MRI). We compared relative CBF maps assessed in 24 concussed contact sport athletes obtained at 24–48 h after injury to those of a control group of 24 matched contact sport players. Significantly less CBF was detected in several brain regions in concussed athletes, while clinical assessments also indicated clinical symptom and performance impairments in SRC patients. Correlations were found between decreased CBF in acute SRC and clinical assessments, including Balance Error Scoring System total score and Immediate Post-Concussion Assessment and Cognitive Test memory composite and impulse control composite scores, as well as days from injury to asymptomatic. Although using different ASL MRI sequences, our preliminary results from two sites are consistent with previous reports and suggest that advanced ASL MRI methods might be useful for detecting acute neurobiological changes in acute SRC.Item Cerebral Perfusion and Gray Matter Changes Associated With Chemotherapy-Induced Peripheral Neuropathy(American Society of Clinical Oncology, 2016-03-01) Nudelman, Kelly N.H.; McDonald, Brenna C.; Wang, Yang; Smith, Dori J.; West, John D.; O'Neill, Darren P.; Zanville, Noah R.; Champion, Victoria L.; Schneider, Bryan P.; Saykin, Andrew J.; IU School of NursingPURPOSE: To investigate the longitudinal relationship between chemotherapy-induced peripheral neuropathy (CIPN) symptoms (sx) and brain perfusion changes in patients with breast cancer. Interaction of CIPN-sx perfusion effects with known chemotherapy-associated gray matter density decrease was also assessed to elucidate the relationship between CIPN and previously reported cancer treatment-related brain structural changes. METHODS: Patients with breast cancer treated with (n = 24) or without (n = 23) chemotherapy underwent clinical examination and brain magnetic resonance imaging at the following three time points: before treatment (baseline), 1 month after treatment completion, and 1 year after the 1-month assessment. CIPN-sx were evaluated with the self-reported Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity four-item sensory-specific scale. Perfusion and gray matter density were assessed using voxel-based pulsed arterial spin labeling and morphometric analyses and tested for association with CIPN-sx in the patients who received chemotherapy. RESULTS: Patients who received chemotherapy reported significantly increased CIPN-sx from baseline to 1 month, with partial recovery by 1 year (P < .001). CIPN-sx increase from baseline to 1 month was significantly greater for patients who received chemotherapy compared with those who did not (P = .001). At 1 month, neuroimaging showed that for the group that received chemotherapy, CIPN-sx were positively associated with cerebral perfusion in the right superior frontal gyrus and cingulate gyrus, regions associated with pain processing (P < .001). Longitudinal magnetic resonance imaging analysis in the group receiving chemotherapy indicated that CIPN-sx and associated perfusion changes from baseline to 1 month were also positively correlated with gray matter density change (P < .005). CONCLUSION: Peripheral neuropathy symptoms after systemic chemotherapy for breast cancer are associated with changes in cerebral perfusion and gray matter. The specific mechanisms warrant further investigation given the potential diagnostic and therapeutic implications.Item Characterizing neurodegeneration in the human connectome: a network science study of hereditary diffuse leukoencephalopathy with spheroids(Office of the Vice Chancellor for Research, 2015-04-17) Contreras, Joey; Rishacher, Shannon L.; West, John D.; Wu, Yu-Chien; Wang, Yang; Murrell, Jill R.; Dzemidzic, Mario; Farlow, Martin R.; Unverzagt, Frederik; Ghetti, Bernardino; Matthews, Brandy R.; Quaid, Kimberly A.; Sporns, Olaf; Saykin, Andrew J.; Goñi, JoaquínAbstract The effect of white matter neurodegeneration on the human connectome and its functional implications is an important topic with clinical applicability of advanced brain network analysis. The aim of this study was to evaluate integration and segregation changes in structural connectivity (SC) that arise as consequence of white matter lesions in hereditary diffuse leukoencephalopathy with spheroids (HDLS). Also, we assessed the relationship between HDLS induced structural changes and changes in restingstate functional connectivity (rsFC). HDLS is a rare autosomal dominant neurodegenerative disorder caused by mutations in the CSF1R gene. HDLS is characterized by severe white matter damage leading to prominent subcortical lesions detectable by structural MRI. Spheroids, an important feature of HDLS, are axonal swellings indicating damage. HDLS causes progressive motor and cognitive decline. The clinical symptoms of HDLS are often mistaken for other diseases such as Alzheimer’s disease, frontotemporal dementia, atypical Parkinsonism or multiple sclerosis. Our study is focused on the follow-up of two siblings, one being a healthy control (HC) and the other one being an HDLS patient. In this study, deterministic fiber-tractography of diffusion MRI with multi-tensor modeling was used in order to obtain reliable and reproducible SC matrices. Integration changes were measured by means of SC shortest-paths (including distance and number of edges), whereas segregation and community organization were measured by means of a multiplex modularity analysis on the SC matrices. Additionally, rsFC was modeled using state of the art preprocessing methods including motion regressors and scrubbing. This allowed us to characterize functional changes associated to the disease. Major integration disruption involved superior frontal (L,R), caudal middle frontal (R), precentral (L,R), inferior parietal (R), insula (R) and paracentral (L) regions. Major segregation changes were characterized by the disruption of a large bilateral module that was observed in the HC that includes the frontal pole (L,R), medial orbitofrontal (L,R), rostral middle frontal (L), superior frontal (L,R), precentral (L,R), paracentral (L,R), rostral anterior cingulate (L,R), caudal anterior cingulate (L,R), posterior cingulate (L,R), postcentral (L), precuneus (L,R), lateral orbitofrontal (R) and parsorbitalis (R). The combination of tractography and network analysis permitted the detection and characterization of profound cortical to cortical changes in integration and segregation associated with HDLS white matter lesions and its relationship with rsFC. Our preliminary findings suggest that advanced network analytic approaches show promising sensitivity to known white matter pathology and progression. Further Indiana Alzheimer Disease Center Symposium. March 6, 2015. research is needed to address the specificity of network profiles for differentiation among white matter pathologies and diseases.Item Cholinergic Enhancement of Brain Activation in Mild Cognitive Impairment during Episodic Memory Encoding(Frontiers Media, 2013-09-17) Risacher, Shannon L.; Wang, Yang; Wishart, Heather A.; Rabin, Laura A.; Flashman, Laura A.; McDonald, Brenna C.; West, John D.; Santulli, Robert B.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineObjective: To determine the physiological impact of treatment with donepezil (Aricept) on neural circuitry supporting episodic memory encoding in patients with amnestic mild cognitive impairment (MCI) using functional magnetic resonance imaging (fMRI). Methods: Eighteen patients with MCI and 20 age-matched healthy controls (HC) were scanned twice while performing an event-related verbal episodic encoding task. MCI participants were scanned before treatment and after approximately 3 months on donepezil; HC were untreated but rescanned at the same interval. Voxel-level analyses assessed treatment effects on activation profiles in MCI patients relative to retest changes in non-treated HC. Changes in task-related connectivity in medial temporal circuitry were also evaluated, as were associations between brain activation, task-related functional connectivity, task performance, and clinical measures of cognition. Results: At baseline, the MCI group showed reduced activation during encoding relative to HC in the right medial temporal lobe (MTL; hippocampal/parahippocampal) and additional regions, as well as attenuated task-related deactivation, relative to rest, in a medial parietal lobe cluster. After treatment, the MCI group showed normalized MTL activation and improved parietal deactivation. These changes were associated with cognitive performance. After treatment, the MCI group also demonstrated increased task-related functional connectivity from the right MTL cluster seed region to a network of other sites including the basal nucleus/caudate and bilateral frontal lobes. Increased functional connectivity was associated with improved task performance. Conclusion: Pharmacologic enhancement of cholinergic function in amnestic MCI is associated with changes in brain activation and functional connectivity during episodic memory processing which are in turn related to increased cognitive performance. fMRI is a promising biomarker for assessing treatment related changes in brain function.Item Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years(Wiley, 2022-01) Frangou, Sophia; Modabbernia, Amirhossein; Williams, Steven C.R.; Papachristou, Efstathios; Doucet, Gaelle E.; Agartz, Ingrid; Aghajani, Moji; Akudjedu, Theophilus N.; Albajes-Eizagirre, Anton; Alnæs, Dag; Alpert, Kathryn I.; Andersson, Micael; Andreasen, Nancy C.; Andreassen, Ole A.; Asherson, Philip; Banaschewski, Tobias; Bargallo, Nuria; Baumeister, Sarah; Baur-Streubel, Ramona; Bertolino, Alessandro; Bonvino, Aurora; Boomsma, Dorret I.; Borgwardt, Stefan; Bourque, Josiane; Brandeis, Daniel; Breier, Alan; Brodaty, Henry; Brouwer, Rachel M.; Buitelaar, Jan K.; Busatto, Geraldo F.; Buckner, Randy L.; Calhoun, Vincent; Canales-Rodríguez, Erick J.; Cannon, Dara M.; Caseras, Xavier; Castellanos, Francisco X.; Cervenka, Simon; Chaim-Avancini, Tiffany M.; Ching, Christopher R.K.; Chubar, Victoria; Clark, Vincent P.; Conrod, Patricia; Conzelmann, Annette; Crespo-Facorro, Benedicto; Crivello, Fabrice; Crone, Eveline A.; Dale, Anders M.; Dannlowski, Udo; Davey, Christopher; de Geus, Eco J.C.; de Haan, Lieuwe; de Zubicaray, Greig I.; den Braber, Anouk; Dickie, Erin W.; Di Giorgio, Annabella; Doan, Nhat Trung; Dørum, Erlend S.; Ehrlich, Stefan; Erk, Susanne; Espeseth, Thomas; Fatouros-Bergman, Helena; Fisher, Simon E.; Fouche, Jean-Paul; Franke, Barbara; Frodl, Thomas; Fuentes-Claramonte, Paola; Glahn, David C.; Gotlib, Ian H.; Grabe, Hans-Jörgen; Grimm, Oliver; Groenewold, Nynke A.; Grotegerd, Dominik; Gruber, Oliver; Gruner, Patricia; Gur, Rachel E.; Gur, Ruben C.; Hahn, Tim; Harrison, Ben J.; Hartman, Catharine A.; Hatton, Sean N.; Heinz, Andreas; Heslenfeld, Dirk J.; Hibar, Derrek P.; Hickie, Ian B.; Ho, Beng-Choon; Hoekstra, Pieter J.; Hohmann, Sarah; Holmes, Avram J.; Hoogman, Martine; Hosten, Norbert; Howells, Fleur M.; Hulshoff Pol, Hilleke E.; Huyser, Chaim; Jahanshad, Neda; James, Anthony; Jernigan, Terry L.; Jiang, Jiyang; Jönsson, Erik G.; Joska, John A.; Kahn, Rene; Kalnin, Andrew; Kanai, Ryota; Klein, Marieke; Klyushnik, Tatyana P.; Koenders, Laura; Koops, Sanne; Krämer, Bernd; Kuntsi, Jonna; Lagopoulos, Jim; Lázaro, Luisa; Lebedeva, Irina; Lee, Won Hee; Lesch, Klaus-Peter; Lochner, Christine; Machielsen, Marise W.J.; Maingault, Sophie; Martin, Nicholas G.; Martínez-Zalacaín, Ignacio; Mataix-Cols, David; Mazoyer, Bernard; McDonald, Colm; McDonald, Brenna C.; McIntosh, Andrew M.; McMahon, Katie L.; McPhilemy, Genevieve; Meinert, Susanne; Menchón, José M.; Medland, Sarah E.; Meyer-Lindenberg, Andreas; Naaijen, Jilly; Najt, Pablo; Nakao, Tomohiro; Nordvik, Jan E.; Nyberg, Lars; Oosterlaan, Jaap; Ortiz-García de la Foz, Víctor; Paloyelis, Yannis; Pauli, Paul; Pergola, Giulio; Pomarol-Clotet, Edith; Portella, Maria J.; Potkin, Steven G.; Radua, Joaquim; Reif, Andreas; Rinker, Daniel A.; Roffman, Joshua L.; Rosa, Pedro G.P.; Sacchet, Matthew D.; Sachdev, Perminder S.; Salvador, Raymond; Sánchez-Juan, Pascual; Sarró, Salvador; Satterthwaite, Theodore D.; Saykin, Andrew J.; Serpa, Mauricio H.; Schmaal, Lianne; Schnell, Knut; Schumann, Gunter; Sim, Kang; Smoller, Jordan W.; Sommer, Iris; Soriano-Mas, Carles; Stein, Dan J.; Strike, Lachlan T.; Swagerman, Suzanne C.; Tamnes, Christian K.; Temmingh, Henk S.; Thomopoulos, Sophia I.; Tomyshev, Alexander S.; Tordesillas-Gutiérrez, Diana; Trollor, Julian N.; Turner, Jessica A.; Uhlmann, Anne; van den Heuvel, Odile A.; van den Meer, Dennis; van der Wee, Nic J.A.; van Haren, Neeltje E.M.; van't Ent, Dennis; van Erp, Theo G.M.; Veer, Ilya M.; Veltman, Dick J.; Voineskos, Aristotle; Völzke, Henry; Walter, Henrik; Walton, Esther; Wang, Lei; Wang, Yang; Wassink, Thomas H.; Weber, Bernd; Wen, Wei; West, John D.; Westlye, Lars T.; Whalley, Heather; Wierenga, Lara M.; Wittfeld, Katharina; Wolf, Daniel H.; Worker, Amanda; Wright, Margaret J.; Yang, Kun; Yoncheva, Yulyia; Zanetti, Marcus V.; Ziegler, Georg C.; Karolinska Schizophrenia Project (KaSP); Thompson, Paul M.; Dima, Danai; Radiology and Imaging Sciences, School of MedicineDelineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.