Abstract
Cortical inhibition is theorized to reflect an underlying property of human brain function, sharpening tuning and shaping connectivity. Although age and sex effects on large-scale resting-state brain connectivity have been well documented, effects on local cortical inhibition have received relatively limited attention. Here, we evaluated age and sex effects on presumed local inhibitory interactions in 6 lateral cortical areas using resting-state functional magnetic resonance imaging (fMRI) data acquired from 1054 young adults who participated in the Human Connectome Project. For each area, all possible pairwise crosscorrelations between prewhitened blood oxygenation level-dependent (BOLD) time series were calculated, and the highest value (CCmax) was retained to determine the mean and percentage of negative and positive CCmax. Here, we focused on the percentage of negative CCmax which we referred to as presumed “percent inhibition”. The results documented regional differences in percent inhibition as well as age and sex effects, such that women’s brains were characterized by significantly higher percent inhibition than men overall and in 4 of the 6 cortical areas, and the percent inhibition increased significantly with age in all 6 areas for women but in only one area for men. The findings from this young adult sample are presumed to reflect ongoing maturational processes involving local network connectivity that may be shaped by sex differences in brain structure, function, and neurochemistry.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
Data are available from the Human Connectome Project (http://www.humanconnectome.org/).
Code availability
Not applicable.
References
Allen EA, Erhardt EB, Damaraju E et al (2011) A base-line for the multivariate comparison of resting-state networks. Front Syst Neurosci 5:2. https://doi.org/10.3389/fnsys.2011.00002
Battaglia-Mayer A, Ferraina S, Mitsuda T, Marconi B, Genovesio A, Onorati P, Lacquaniti F, Caminiti R (2000) Early coding of reaching in the parietooccipital cortex. J Neurophysiol 83(4):2374–2391. https://doi.org/10.1152/jn.2000.83.4.2374
Biswal BB, Yetkin FZ, Haughton VM, Hyde JS (1995) Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 34:537–541. https://doi.org/10.1002/mrm.1910340409
Biswal BB, Mennes M, Zuo XN et al (2010) Toward discovery science of human brain function. Proc Natl Acad Sci USA 107(10):4734–4739. https://doi.org/10.1073/pnas.0911855107
Buckner RL, Krienen FM, Yeo BT (2013) Opportunities and limitations of intrinsic functional connectivity MRI. Nat Neurosci 16(7):832–837. https://doi.org/10.1038/nn.3423
Caminiti R, Genovesio A, Marconi B, Mayer AB, Onorati P, Ferraina S, Mitsuda T, Giannetti S, Squatrito S, Maioli MG, Molinari M (1999) Early coding of reaching: frontal and parietal association connections of parieto-occipital cortex. Eur J Neurosci 11(9):3339–3345. https://doi.org/10.1046/j.1460-9568.1999.00801
Carson RG (2020) Inter-hemispheric inhibition sculpts the output of neural circuits by co-opting the two cerebral hemispheres. J Physiol 598(21):4781–4802. https://doi.org/10.1113/JP279793
Christova P, Georgopoulos AP (2018) Invariant and heritable local cortical organization as revealed by fMRI. J Neurophysiol 120(2):760–764. https://doi.org/10.1152/jn.00137.2018
Christova PS, Lewis SM, Tagaris GA, Uğurbil K, Georgopoulos AP (2008) A voxel-by-voxel parametric fMRI study of motor mental rotation: hemispheric specialization and gender differences in neural processing efficiency. Exp Brain Res 189(1):79–90. https://doi.org/10.1007/s00221-008-1405-x
Christova P, Lewis SM, Jerde TA, Lynch JK, Georgopoulos AP (2011) True associations between resting fMRI time series based on innovations. J Neural Eng 8(4):046025. https://doi.org/10.1088/1741-2560/8/4/046025
Cosgrove KP, Mazure CM, Staley JK (2007) Evolving knowledge of sex differences in brain structure, function, and chemistry. Biol Psychiat 62(8):847–855. https://doi.org/10.1016/j.biopsych.2007.03.001
de Lacy N, McCauley E, Kutz JN, Calhoun VD (2019) Sex-related differences in intrinsic brain dynamism and their neurocognitive correlates. Neuroimage 202:116116. https://doi.org/10.1016/j.neuroimage.2019.116116
Deco G, Ponce-Alvarez A, Hagmann P, Romani GL, Mantini D, Corbetta M (2014) How local excitation–inhibition ratio impacts the whole brain dynamics. J Neurosci 34(23):7886–7898. https://doi.org/10.1523/JNEUROSCI.5068-13.2014
Desikan RS, Ségonne F, Fischl B et al (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31:968–980. https://doi.org/10.1016/j.neuroimage.2006.01.021
Epperson C, Haga K, Mason G et al (2002) Cortical-aminobutyric acid levels across the menstrual cycle in healthy women and those with premenstrual dysphoric disorder. Arch Gen Psychiat 59:851–858. https://doi.org/10.1001/archpsyc.59.9.851
Fair DA, Cohen AL, Power JD et al (2009) Functional brain networks develop from a “local to distributed” organization. PLoS Comput Biol 5:e1000381. https://doi.org/10.1371/journal.pcbi.1000381
Filippi M, Valsasina P, Misci P, Falini A, Comi G, Rocca MA (2013) The organization of intrinsic brain activity differs between genders: a resting-state fMRI study in a large cohort of young healthy subjects. Hum Brain Mapp 34:1330–1343. https://doi.org/10.1002/hbm.21514
Fisher RA (1958) Statistical methods for research workers. Hafner, New York
Fox MD, Raichle M (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 8:700–711. https://doi.org/10.1038/nrn2201
Friston KJ, Frith CD, Liddle PF, Frackowiak RSJ (1993) Functional connectivity: the principal component analysis of large (PET) data sets. J Cereb Blood Flow Metab 3:5–14. https://doi.org/10.1038/jcbfm.1993.4
Geerligs L, Renken RJ, Saliasi E, Maurits NM, Lorist MM (2015) A brain-wide study of age-related changes in functional connectivity. Cereb Cortex 25(7):1987–1999. https://doi.org/10.1093/cercor/bhu012
Georgopoulos AP (2014) Cell directional spread determines accuracy, precision, and length of the neuronal population vector. Exp Brain Res 232(7):2391–2405. https://doi.org/10.1007/s00221-014-3936-7
Georgopoulos AP, Carpenter AF (2015) Coding of movements in the motor cortex. Curr Opin Neurobiol 33:34–39. https://doi.org/10.1016/j.conb.2015.01.012
Georgopoulos AP, Stefanis CN (2007) Local shaping of function in the motor cortex: motor contrast, directional tuning. Brain Res Rev 55:383–389
Georgopoulos AP, Stefanis C (2010) The motor cortical circuit. In: Shepherd G, Grillner S (eds) Brain microcircuits. Oxford University Press, New York, pp 39–45
Glasser MF, Sotiropoulos SN, Wilson JA et al (2013) The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage 80:105–124. https://doi.org/10.1016/j.neuroimage.2013.04.127
Greenhouse I, Noah S, Maddock RJ, Ivry RB (2016) Individual differences in GABA content are reliable but are not uniform across the human cortex. Neuroimage 139:1–7. https://doi.org/10.1016/j.neuroimage.2016.06.007
Greicius MD, Krasnow B, Reiss AL, Menon V (2003) Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. PNAS 100(1):253–258. https://doi.org/10.1073/pnas.0135058100
Isaacson JS, Scanziani M (2011) How inhibition shapes cortical activity. Neuron 72(2):231–243. https://doi.org/10.1016/j.neuron.2011.09.027
Johnson PB, Ferraina S, Bianchi L, Caminiti R (1996) Cortical networks for visual reaching: physiological and anatomical organization of frontal and parietal lobe arm regions. Cereb Cortex 6(2):102–119. https://doi.org/10.1093/cercor/6.2.102
Lee S-H, Kwan AC, Zhang S et al (2012) Activation of specific interneurons improves V1 feature selectivity and visual perception. Nature 488(7411):379–383. https://doi.org/10.1038/nature11312
Li YT, Ma WP, Pan CJ, Zhang LI, Tao HW (2012a) Broadening of cortical inhibition mediates developmental sharpening of orientation selectivity. J Neurosci 32:3981–3991. https://doi.org/10.1523/JNEUROSCI.5514-11.2012
Li YT, Ma WP, Li LY, Ibrahim LA, Wang SZ, Tao HW (2012b) Broadening of inhibitory tuning underlies contrast-dependent sharpening of orientation selectivity in mouse visual cortex. J Neurosci 32:16466–16477. https://doi.org/10.1523/JNEUROSCI.3221-12.2012
Lissemore JI, Bhandari A, Mulsant BH et al (2018) Reduced GABAergic cortical inhibition in aging and depression. Neuropsychopharmacol 43(11):2277–2284. https://doi.org/10.1038/s41386-018-0093-x
Logothetis NK (2002) The neural basis of the blood-oxygen-level-dependent functional magnetic resonance imaging signal. Philos Trans R Soc Lond B Biol Sci 357(1424):1003–1037. https://doi.org/10.1098/rstb.2002.1114
Lopez-Larson MP, Anderson JS, Ferguson MA, Yurgelun-Todd D (2011) Local brain connectivity and associations with gender and age. Dev Cogn Neurosci 1(2):187–197. https://doi.org/10.1016/j.dcn.2010.10.001
Luders E, Narr KL, Thompson PM et al (2004) Gender differences in cortical complexity. Nat Neurosci 7(8):799–800. https://doi.org/10.1038/nn1277
Mahan M, Georgopoulos A (2013) Motor directional tuning across brain areas: directional resonance and the role of inhibition for directional accuracy. Front Neural Circuits 7:92. https://doi.org/10.3389/fncir.2013.00092
Marsh R, Gerber AJ, Peterson BS (2008) Neuroimaging studies of normal brain development and their relevance for understanding childhood neuropsychiatric disorders. J Amer Acad Child Psy 47(11):1233–1251. https://doi.org/10.1097/CHI.0b013e318185e703
McEwen BS, Milner TA (2017) Understanding the broad influence of sex hormones and sex differences in the brain. J Neurosci Res 95(1–2):24–39. https://doi.org/10.1002/jnr.23809
Merchant H, Georgopoulos AP (2018) Inhibitory mechanisms in the motor cortical circuit (MCC). In: Shepherd GM, Grillner S (eds) Handbook of brain microcircuits. Oxford/Academic Press, NY
Merchant H, Naselaris T, Georgopoulos AP (2008) Dynamic sculpting of directional tuning in the primate motor cortex during three-dimensional reaching. J Neurosci 28:9164–9172
Merchant H, Crowe DA, Fortes AF, Georgopoulos AP (2014) Cognitive modulation of local and callosal neural interactions in decision making. Front Neurosci 8:245. https://doi.org/10.3389/fnins.2014.00245
O’Gorman RL, Michels L, Edden RA, Murdoch JB, Martin E (2011) In vivo detection of GABA and glutamate with MEGA-PRESS: reproducibility and gender effects. J Magn Res Imag 33(5):1262–1267. https://doi.org/10.1002/jmri.22520
Oldfield RC (1971) The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia 9(1):97–113. https://doi.org/10.1016/0028-3932(71)90067-4
Perkel DH, Gerstein GL, Moore GP (1967) Neuronal spike trains and stochastic point processes II Simultaneous spike trains. Biophys J 7:419–440. https://doi.org/10.1016/S0006-3495(67)86597-4
Raichle ME (2015) The restless brain: how intrinsic activity organizes brain function. Phil Trans R Soc B 370:20140172. https://doi.org/10.1098/rstb.2014.0172
Sanacora G, Mason GF, Rothman DL et al (1999) Reduced cortical γ-aminobutyric acid levels in depressed patients determined by proton magnetic resonance spectroscopy. Arch Gen Psychiat 56(11):1043–1047. https://doi.org/10.1001/archpsyc.56.11.1043
Satterthwaite TD, Wolf DH, Roalf DR et al (2015) Linked sex differences in cognition and functional connectivity in youth. Cereb Cortex 25(9):2383–2394. https://doi.org/10.1093/cercor/bhu036
Schachter SC, Ransil BJ, Geschwind N (1987) Associations of handedness with hair color and learning disabilities. Neuropsychologia 25(1, Part 2):269–276. https://doi.org/10.1016/0028-3932(87)90137-0
Scheinost D, Finn ES, Tokoglu F et al (2015) Sex differences in normal age trajectories of functional brain networks. Hum Brain Mapp 36(4):1524–1535. https://doi.org/10.1002/hbm.22720
Sepulcre J, Liu H, Talukdar T, Martincorena I, Yeo BT, Buckner RL (2010) The organization of local and distant functional connectivity in the human brain. PLoS Comput Biol 6(6):e1000808. https://doi.org/10.1371/journal.pcbi.1000808
Smith SM, Fox PT, Miller KL et al (2009) Correspondence of the brain’s functional architecture during activation and rest. Proc Natl Acad Sci USA 106:13040–13045. https://doi.org/10.1073/pnas.0905267106
Stefanis C, Jasper H (1964) Recurrent collateral inhibition in pyramidal tract neurons. J Neurophysiol 27:855–877
Tomasi D, Volkow ND (2012a) Aging and functional brain networks. Mol Psychiatry 17(471):549–558. https://doi.org/10.1038/mp.2011.81
Tomasi D, Volkow ND (2012b) Gender differences in brain functional connectivity density. Hum Brain Mapp 33:849–860. https://doi.org/10.1002/hbm.21252
Uğurbil K, Xu J, Auerbach EJ, Moeller S et al (2013) Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project. Neuroimage 80:80–104. https://doi.org/10.1016/j.neuroimage.2013.05.012
Van Essen DC, Smith SM, Barch DM, Behrens TEJ, Yacoub E, Ugurbil K (2013) The WU-Minn human Connectome Project: an overview. Neuroimage 80:62–79. https://doi.org/10.1016/j.neuroimage.2013.05.041
Van Den Heuvel MP, Pol HE, Pol HE (2010) Exploring the brain network: a review on resting-state fMRI functional connectivity. Eur Neuropsychopharm 20(8):519–534. https://doi.org/10.1016/j.euroneuro.2010.03.008
Weissman-Fogel I, Moayedi M, Taylor KS, Pope G, Davis KD (2010) Cognitive and default-mode resting state networks: do male and female brains “rest” differently? Hum Brain Mapp 31:1713–1726. https://doi.org/10.1002/hbm.20968
Wu T, Zang Y, Wang L, Long X, Li K, Chan P (2007) Normal aging decreases regional homogeneity of the motor areas in the resting state. Neurosci Lett 423(3):189–193. https://doi.org/10.1016/j.neulet.2007.06.057
Zang YF, Jiang TZ, Lu YL, He Y, Tian LX (2004) Regional homogeneity approach to fMRI data analysis. Neuroimage 22:394–400. https://doi.org/10.1016/j.neuroimage.2003.12.030
Zhang D, Snyder AZ, Fox MD, Sansbury MW, Shimony JS, Raichle ME (2008) Intrinsic functional relations between human cerebral cortex and thalamus. J Neurophysiol 100:1740–1748. https://doi.org/10.1152/jn.90463.2008
Zhang C, Dougherty CC, Baum SA, White T, Michael AM (2018) Functional connectivity predicts gender: evidence for gender differences in resting brain connectivity. Hum Brain Mapp 39(4):1765–1776. https://doi.org/10.1002/hbm.23950
Zheng P (2009) Neuroactive steroid regulation of neurotransmitter release in the CNS: action, mechanism and possible significance. Prog Neurobiol 89:134–152. https://doi.org/10.1016/j.pneurobio.2009.07.001
Acknowledgements
Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 National Institutes of Health (NIH) institutes and centers that support the NIH Blueprint for Neuroscience Research and by the McDonnell Center for Systems Neuroscience at Washington University.
Funding
Partial funding for this study was provided by the University of Minnesota (the Anita Kunin Chair in Women's Healthy Brain Aging, the Brain and Genomics Fund, the McKnight Presidential Chair of Cognitive Neuroscience, and the American Legion Brain Sciences Chair) and the U.S. Department of Veterans Affairs. The sponsors had no role in the current study design, analysis, or interpretation, or in the writing of this paper. The contents do not represent the views of the U.S. Department of Veterans Affairs or the United States Government.
Author information
Authors and Affiliations
Contributions
APG conceived research; PC and APG designed research and analyzed data; LMJ, APG, and PK wrote the paper and approved final version of manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflicts of interest.
Ethics approval
The Institutional Review Board of Washington University in St. Louis approved the HCP research protocol. The present analyses were approved by the Minneapolis VAHCS Research and Development Committee.
Consent to participate
All participants in the present study gave informed written consent to participate in this study.
Consent for publication
All participants in the present study gave consent for the publication of the result of this study.
Additional information
Communicated by Francesco Lacquaniti.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Christova, P., James, L.M. & Georgopoulos, A.P. Effects of sex and age on presumed inhibitory interactions in 6 areas of the human cerebral cortex as revealed by the fMRI Human Connectome Project. Exp Brain Res 240, 969–979 (2022). https://doi.org/10.1007/s00221-021-06298-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00221-021-06298-z