Sex and Age Effects of Functional Connectivity in Early Adulthood

Abstract Functional connectivity (FC) in resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to find coactivating regions in the human brain. Despite its widespread use, the effects of sex and age on resting FC are not well characterized, especially during early adulthood. Here we apply regression and graph theoretical analyses to explore the effects of sex and age on FC between the 116 AAL atlas parcellations (a total of 6670 FC measures). rs-fMRI data of 494 healthy subjects (203 males and 291 females; age range: 22–36 years) from the Human Connectome Project were analyzed. We report the following findings. (1) Males exhibited greater FC than females in 1352 FC measures (1025 survived Bonferroni correction; \documentclass{aastex}\usepackage{amsbsy}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{bm}\usepackage{mathrsfs}\usepackage{pifont}\usepackage{stmaryrd}\usepackage{textcomp}\usepackage{portland, xspace}\usepackage{amsmath, amsxtra}\pagestyle{empty}\DeclareMathSizes{10}{9}{7}{6}\begin{document} $$p < 7.49{ \rm{E}} - 6$$ \end{document}). In 641 FC measures, females exhibited greater FC than males but none survived Bonferroni correction. Significant FC differences were mainly present in frontal, parietal, and temporal lobes. Although the average FC values for males and females were significantly different, FC values of males and females exhibited large overlap. (2) Age effects were present only in 29 FC measures and all significant age effects showed higher FC in younger subjects. Age and sex differences of FC remained significant after controlling for cognitive measures. (3) Although sex \documentclass{aastex}\usepackage{amsbsy}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{bm}\usepackage{mathrsfs}\usepackage{pifont}\usepackage{stmaryrd}\usepackage{textcomp}\usepackage{portland, xspace}\usepackage{amsmath, amsxtra}\pagestyle{empty}\DeclareMathSizes{10}{9}{7}{6}\begin{document} $$\times$$ \end{document} age interaction did not survive multiple comparison correction, FC in females exhibited a faster cross-sectional decline with age. (4) Male brains were more locally clustered in all lobes but the cerebellum; female brains had a higher clustering coefficient at the whole-brain level. Our results indicate that although both male and female brains show small-world network characteristics, male brains were more segregated and female brains were more integrated. Findings of this study further our understanding of FC in early adulthood and provide evidence to support that age and sex should be controlled for in FC studies of young adults.

[1]  S. Rombouts,et al.  Consistent resting-state networks across healthy subjects , 2006, Proceedings of the National Academy of Sciences.

[2]  Massimo Filippi,et al.  The organization of intrinsic brain activity differs between genders: A resting‐state fMRI study in a large cohort of young healthy subjects , 2013, Human brain mapping.

[3]  G. Busatto,et al.  Resting-state functional connectivity in normal brain aging , 2013, Neuroscience & Biobehavioral Reviews.

[4]  Stephen M Smith,et al.  Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.

[5]  Bryon A. Mueller,et al.  Altered resting state complexity in schizophrenia , 2012, NeuroImage.

[6]  V Latora,et al.  Efficient behavior of small-world networks. , 2001, Physical review letters.

[7]  B. Biswal,et al.  Network homogeneity reveals decreased integrity of default-mode network in ADHD , 2008, Journal of Neuroscience Methods.

[8]  Ralph-Axel Müller,et al.  Underconnected, but how? A survey of functional connectivity MRI studies in autism spectrum disorders. , 2011, Cerebral cortex.

[9]  Alex R. Smith,et al.  Sex differences in the structural connectome of the human brain , 2013, Proceedings of the National Academy of Sciences.

[10]  Yu-Feng Zang,et al.  Resting-state fMRI studies in epilepsy , 2012, Neuroscience Bulletin.

[11]  C. Grady The cognitive neuroscience of ageing , 2012, Nature Reviews Neuroscience.

[12]  Dustin Scheinost,et al.  The (in)stability of functional brain network measures across thresholds , 2015, NeuroImage.

[13]  Rachael D. Seidler,et al.  Frontiers in Systems Neuroscience Systems Neuroscience , 2022 .

[14]  R. Poldrack Region of interest analysis for fMRI. , 2007, Social cognitive and affective neuroscience.

[15]  Tianzi Jiang,et al.  Age-related decrease in functional connectivity of the right fronto-insular cortex with the central executive and default-mode networks in adults from young to middle age , 2013, Neuroscience Letters.

[16]  Jorge Sepulcre,et al.  Evidence from intrinsic activity that asymmetry of the human brain is controlled by multiple factors , 2009, Proceedings of the National Academy of Sciences.

[17]  C. Hamilton,et al.  Cognition and sex differences , 2008 .

[18]  Emily L. Dennis,et al.  Functional Brain Connectivity Using fMRI in Aging and Alzheimer’s Disease , 2014, Neuropsychology Review.

[19]  Ludovica Griffanti,et al.  Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers , 2014, NeuroImage.

[20]  Moriah E. Thomason,et al.  Age-related increases in long-range connectivity in fetal functional neural connectivity networks in utero , 2014, Developmental Cognitive Neuroscience.

[21]  Rainer Goebel,et al.  Independent component model of the default-mode brain function: combining individual-level and population-level analyses in resting-state fMRI. , 2008, Magnetic resonance imaging.

[22]  Adam Gazzaley,et al.  An expectation-based memory deficit in aging , 2011, Neuropsychologia.

[23]  David J. Madden,et al.  Functional brain connectivity and cognition: effects of adult age and task demands , 2013, Neurobiology of Aging.

[24]  Yong He,et al.  Hemisphere- and gender-related differences in small-world brain networks: A resting-state functional MRI study , 2011, NeuroImage.

[25]  K. Sneppen,et al.  Specificity and Stability in Topology of Protein Networks , 2002, Science.

[26]  Roberto Cabeza,et al.  Adult Age Differences in Functional Connectivity during Executive Control Nih Public Access Materials and Methods Cue-related Activation Functional Connectivity of Switch-related Activation on Cue-only Trials , 2022 .

[27]  Olaf Sporns,et al.  Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.

[28]  M. Greicius,et al.  Decoding subject-driven cognitive states with whole-brain connectivity patterns. , 2012, Cerebral cortex.

[29]  Yong He,et al.  Sex- and brain size-related small-world structural cortical networks in young adults: a DTI tractography study. , 2011, Cerebral cortex.

[30]  Margarete Delazer,et al.  Sex differences in cognitive functions , 2003 .

[31]  Y. Stern,et al.  Age-Related Changes in Task Related Functional Network Connectivity , 2012, PloS one.

[32]  B. Biswal,et al.  Functional connectivity in the motor cortex of resting human brain using echo‐planar mri , 1995, Magnetic resonance in medicine.

[33]  P. Golland,et al.  Whole brain resting state functional connectivity abnormalities in schizophrenia , 2012, Schizophrenia Research.

[34]  Steen Moeller,et al.  ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging , 2014, NeuroImage.

[35]  Bernard J. Ransil,et al.  Associations of handedness with hair color and learning disabilities , 1987, Neuropsychologia.

[36]  Yong He,et al.  Aging-related changes in the default mode network and its anti-correlated networks: A resting-state fMRI study , 2011, Neuroscience Letters.

[37]  Abraham Z. Snyder,et al.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.

[38]  M. Hallett,et al.  The influence of normal human ageing on automatic movements , 2005, The Journal of physiology.

[39]  Vince D. Calhoun,et al.  A method for functional network connectivity among spatially independent resting-state components in schizophrenia , 2008, NeuroImage.

[40]  Serge A. R. B. Rombouts,et al.  The Effects of Sustained Cognitive Task Performance on Subsequent Resting State Functional Connectivity in Healthy Young and Middle-Aged Male Schoolteachers , 2012, Brain Connect..

[41]  N. Tzourio-Mazoyer,et al.  Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain , 2002, NeuroImage.

[42]  Timothy O. Laumann,et al.  Methods to detect, characterize, and remove motion artifact in resting state fMRI , 2014, NeuroImage.

[43]  C. Grady,et al.  Age differences in the intrinsic functional connectivity of default network subsystems , 2013, Front. Aging Neurosci..

[44]  C. Grady,et al.  Age differences in the frontoparietal cognitive control network: Implications for distractibility , 2012, Neuropsychologia.

[45]  Richard Coppola,et al.  Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks , 2013, Front. Comput. Neurosci..

[46]  K. Davis,et al.  Cognitive and default‐mode resting state networks: Do male and female brains “rest” differently? , 2010, Human brain mapping.

[47]  R. Bluhm,et al.  Default mode network connectivity: effects of age, sex, and analytic approach , 2008, Neuroreport.

[48]  Rui Li,et al.  Multimodal intervention in older adults improves resting-state functional connectivity between the medial prefrontal cortex and medial temporal lobe† , 2014, Front. Aging Neurosci..

[49]  Vince D. Calhoun,et al.  Classification of schizophrenia patients based on resting-state functional network connectivity , 2013, Front. Neurosci..

[50]  Menglong Li,et al.  Age-related changes in functional connectivity between young adulthood and late adulthood , 2015 .

[51]  K. Gurney,et al.  Network ‘Small-World-Ness’: A Quantitative Method for Determining Canonical Network Equivalence , 2008, PloS one.

[52]  Christian Windischberger,et al.  Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.

[53]  R. Buckner Memory and Executive Function in Aging and AD Multiple Factors that Cause Decline and Reserve Factors that Compensate , 2004, Neuron.

[54]  A. Fleisher,et al.  Alterations of Directional Connectivity among Resting-State Networks in Alzheimer Disease , 2013, American Journal of Neuroradiology.

[55]  Mario Dzemidzic,et al.  Resting state corticolimbic connectivity abnormalities in unmedicated bipolar disorder and unipolar depression , 2009, Psychiatry Research: Neuroimaging.

[56]  Lutz Jäncke,et al.  Associations between age, motor function, and resting state sensorimotor network connectivity in healthy older adults , 2015, NeuroImage.

[57]  S. Rombouts,et al.  Reduced resting-state brain activity in the "default network" in normal aging. , 2008, Cerebral cortex.

[58]  S. Kitazawa,et al.  Sex differences in lateralization revealed in the posterior language areas. , 2000, Cerebral cortex.

[59]  Martijn P. van den Heuvel,et al.  The parcellation-based connectome: Limitations and extensions , 2013, NeuroImage.

[60]  Yong He,et al.  Graph-based network analysis of resting-state functional MRI. , 2010 .

[61]  E. Bullmore,et al.  Neurophysiological architecture of functional magnetic resonance images of human brain. , 2005, Cerebral cortex.

[62]  Alan C. Evans,et al.  Growing Together and Growing Apart: Regional and Sex Differences in the Lifespan Developmental Trajectories of Functional Homotopy , 2010, The Journal of Neuroscience.

[63]  M. Brammer,et al.  Linear age‐correlated functional development of right inferior fronto‐striato‐cerebellar networks during response inhibition and anterior cingulate during error‐related processes , 2007, Human brain mapping.

[64]  R Cameron Craddock,et al.  A whole brain fMRI atlas generated via spatially constrained spectral clustering , 2012, Human brain mapping.

[65]  Peter Fransson,et al.  Assessing the Influence of Different ROI Selection Strategies on Functional Connectivity Analyses of fMRI Data Acquired During Steady-State Conditions , 2011, PloS one.

[66]  Rex E. Jung,et al.  A Baseline for the Multivariate Comparison of Resting-State Networks , 2011, Front. Syst. Neurosci..

[67]  L. A. Flashman,et al.  Sex differences in semantic language processing: A functional MRI study , 2003, Brain and Language.

[68]  Susanne M. Jaeggi,et al.  Disrupted cortico-cerebellar connectivity in older adults , 2013, NeuroImage.

[69]  B. Biswal,et al.  The resting brain: unconstrained yet reliable. , 2009, Cerebral cortex.

[70]  Angela D. Friederici,et al.  The development of the intrinsic functional connectivity of default network subsystems from age 3 to 5 , 2015, Brain Imaging and Behavior.

[71]  Reisa A. Sperling,et al.  Functional Connectivity in Multiple Cortical Networks Is Associated with Performance Across Cognitive Domains in Older Adults , 2015, Brain Connect..

[72]  Danielle S Bassett,et al.  Brain graphs: graphical models of the human brain connectome. , 2011, Annual review of clinical psychology.

[73]  Justin L. Vincent,et al.  Disruption of Large-Scale Brain Systems in Advanced Aging , 2007, Neuron.

[74]  Simon B. Eickhoff,et al.  An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data , 2013, NeuroImage.