Abstract
Language function in the brain, once thought to be highly localized, is now appreciated as relying on a connected but distributed network. The semantic system is of particular interest in the language domain because of its hypothesized integration of information across multiple cortical regions. Previous work in healthy individuals has focused on group-level functional connectivity (FC) analyses of the semantic system, which may obscure interindividual differences driving variance in performance. These studies also overlook the contributions of white matter networks to semantic function. Here, we identified semantic network nodes at the individual level with a semantic decision fMRI task in 53 typically aging adults, characterized network organization using structural connectivity (SC), and quantified the segregation and integration of the network using FC. Hub regions were identified in left inferior frontal gyrus. The individualized semantic network was composed of three interacting modules: (1) default-mode module characterized by bilateral medial prefrontal and posterior cingulate regions and also including right-hemisphere homotopes of language regions; (2) left frontal module extending dorsally from inferior frontal gyrus to pre-motor area; and (3) left temporoparietal module extending from temporal pole to inferior parietal lobule. FC within Module3 and integration of the entire network related to a semantic verbal fluency task, but not a matched phonological task. These results support and extend the tri-network semantic model (Xu in Front Psychol 8: 1538 1538, 2017) and the controlled semantic cognition model (Chiou in Cortex 103: 100 116, 2018) of semantic function.
Similar content being viewed by others
Data availability
The datasets analyzed during the current study are not presently publicly available as data collection is still ongoing. The data used for this study are available from the corresponding author on reasonable request.
References
Bajada CJ, Trujillo-Barreto NJ, Parker GJM, Cloutman LL, Lambon Ralph MA (2019) A structural connectivity convergence zone in the ventral and anterior temporal lobes: data-driven evidence from structural imaging. Cortex 120:298–307. https://doi.org/10.1016/j.cortex.2019.06.014
Bassett DS, Bullmore ET (2017) Small-world brain networks revisited. Neuroscie Rev J Bring Neurobiol Neurol Psychiat 23(5):499–516. https://doi.org/10.1177/1073858416667720
Binney RJ, Parker GJM, Lambon Ralph MA (2012) Convergent connectivity and graded specialization in the rostral human temporal lobe as revealed by diffusion-weighted imaging probabilistic tractography. J Cogn Neurosci 24(10):1998–2014. https://doi.org/10.1162/jocn_a_00263
Braga RM, DiNicola LM, Becker HC, Buckner RL (2020) Situating the left-lateralized language network in the broader organization of multiple specialized large-scale distributed networks. J Neurophysiol 124(5):1415–1448. https://doi.org/10.1152/jn.00753.2019
Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10(3):186–198. https://doi.org/10.1038/nrn2575
Campbell KL, Tyler LK (2018) Language-related domain-specific and domain-general systems in the human brain. Curr Opin Behav Sci 21:132–137. https://doi.org/10.1016/j.cobeha.2018.04.008
Chan MY, Park DC, Savalia NK, Petersen SE, Wig GS (2014) Decreased segregation of brain systems across the healthy adult lifespan. Proc Natl Acad Sci 111(46):E4997–E5006. https://doi.org/10.1073/pnas.1415122111
Chen Y, Huang L, Chen K, Ding J, Zhang Y, Yang Q, Lv Y, Han Z, Guo Q (2020) White matter basis for the hub-and-spoke semantic representation: evidence from semantic dementia. Brain J Neurol 143(4):1206–1219. https://doi.org/10.1093/brain/awaa057
Chiou R, Humphreys GF, Jung J, Lambon Ralph MA (2018) Controlled semantic cognition relies upon dynamic and flexible interactions between the executive ‘semantic control’ and hub-and-spoke ‘semantic representation’ systems. Cortex 103:100–116. https://doi.org/10.1016/j.cortex.2018.02.018
Chiou R, Lambon Ralph MA (2019) Unveiling the dynamic interplay between the hub- and spoke-components of the brain’s semantic system and its impact on human behaviour. Neuroimage 199:114–126. https://doi.org/10.1016/j.neuroimage.2019.05.059
Cox RW (1996) AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res 29(3):162–173. https://doi.org/10.1006/cbmr.1996.0014
Daducci A, Gerhard S, Griffa A, Lemkaddem A, Cammoun L, Gigandet X, Meuli R, Hagmann P, Thiran J-P (2012) The connectome mapper: an open-source processing pipeline to map connectomes with MRI. PLoS ONE 7(12):e48121. https://doi.org/10.1371/journal.pone.0048121
Damoiseaux JS (2017) Effects of aging on functional and structural brain connectivity. Neuroimage 160:32–40. https://doi.org/10.1016/j.neuroimage.2017.01.077
Dickens JV, DeMarco AT, van der Stelt CM, Snider SF, Lacey EH, Medaglia JD, Friedman RB, Turkeltaub PE (2021) Two types of phonological reading impairment in stroke aphasia. Brain Commun 3(3):fcab194. https://doi.org/10.1093/braincomms/fcab194
Fedorenko E (2014) The role of domain-general cognitive control in language comprehension [Hypothesis and Theory]. Front Psychol 5(335). https://doi.org/10.3389/fpsyg.2014.00335
Fedorenko E, Hsieh P-J, Nieto-Castañón A, Whitfield-Gabrieli S, Kanwisher N (2010) New method for fMRI investigations of language: defining ROIs functionally in individual subjects. J Neurophysiol 104(2):1177–1194. https://doi.org/10.1152/jn.00032.2010
Fedorenko E, Kanwisher N (2009) Neuroimaging of language: why hasn’t a clearer picture emerged? Lang Ling Comp 3(4):839–865. https://doi.org/10.1111/j.1749-818X.2009.00143.x
Fedorenko E, Thompson-Schill SL (2014) Reworking the language network. Trends Cogn Sci 18(3):120–126. https://doi.org/10.1016/j.tics.2013.12.006
Fischl B, Van Der Kouwe A, Destrieux C, Halgren E, Ségonne F, Salat DH, Busa E, Seidman LJ, Goldstein J, Kennedy D (2004) Automatically parcellating the human cerebral cortex. Cereb Cortex 14(1):11–22. https://doi.org/10.1093/cercor/bhg087
Friederici AD (2015) White-matter pathways for speech and language processing. Handb Clin Neurol 129:177–186. https://doi.org/10.1016/b978-0-444-62630-1.00010-x
Frost MA, Goebel R (2012) Measuring structural–functional correspondence: spatial variability of specialised brain regions after macro-anatomical alignment. Neuroimage 59(2):1369–1381. https://doi.org/10.1016/j.neuroimage.2011.08.035
Gleichgerrcht E, Kocher M, Nesland T, Rorden C, Fridriksson J, Bonilha L (2015) Preservation of structural brain network hubs is associated with less severe post-stroke aphasia. Restor Neurol Neurosci 34(1):19–28. https://doi.org/10.3233/RNN-150511
Gordon EM, Laumann TO, Adeyemo B, Huckins JF, Kelley WM, Petersen SE (2016) Generation and evaluation of a cortical area parcellation from resting-state correlations. Cereb Cortex 26(1):288–303. https://doi.org/10.1093/cercor/bhu239
Gordon EM, Laumann TO, Adeyemo B, Petersen SE (2017) Individual variability of the system-level organization of the human brain. Cereb Cortex 27(1):386–399. https://doi.org/10.1093/cercor/bhv239
Gough PM, Nobre AC, Devlin JT (2005) Dissociating linguistic processes in the left inferior frontal cortex with transcranial magnetic stimulation. J Neurosci 25(35):8010–8016. https://doi.org/10.1523/JNEUROSCI.2307-05.2005
Griffis JC, Metcalf NV, Corbetta M, Shulman GL (2019) Structural disconnections explain brain network dysfunction after stroke. Cell Rep 28(10):2527-2540.e2529. https://doi.org/10.1016/j.celrep.2019.07.100
Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey CJ, Wedeen VJ, Sporns O (2008) Mapping the structural core of human cerebral cortex. PLoS Biol 6(7):e159. https://doi.org/10.1371/journal.pbio.0060159
Han Z, Ma Y, Gong G, He Y, Caramazza A, Bi Y (2013) White matter structural connectivity underlying semantic processing: evidence from brain damaged patients. Brain 136(10):2952–2965. https://doi.org/10.1093/brain/awt205
Harvey DY, Wei T, Ellmore TM, Hamilton AC, Schnur TT (2013) Neuropsychological evidence for the functional role of the uncinate fasciculus in semantic control. Neuropsychologia 51(5):789–801. https://doi.org/10.1016/j.neuropsychologia.2013.01.028
He Y, Evans A (2010) Graph theoretical modeling of brain connectivity. Curr Opin Neurol 23(4):341–350. https://doi.org/10.1097/WCO.0b013e32833aa567
Jeurissen B, Tournier J-D, Dhollander T, Connelly A, Sijbers J (2014) Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data. Neuroimage 103:411–426. https://doi.org/10.1016/j.neuroimage.2014.07.061
Klaus J, Hartwigsen G (2019) Dissociating semantic and phonological contributions of the left inferior frontal gyrus to language production. Human Brain Map 40(11):3279–3287. https://doi.org/10.1002/hbm.24597
Lancichinetti A, Fortunato S (2012) Consensus clustering in complex networks. Sci Rep 2(1):336. https://doi.org/10.1038/srep00336
Mahowald K, Fedorenko E (2016) Reliable individual-level neural markers of high-level language processing: a necessary precursor for relating neural variability to behavioral and genetic variability. Neuroimage 139:74–93. https://doi.org/10.1016/j.neuroimage.2016.05.073
Maier-Hein KH, Neher PF, Houde JC, Cote MA, Garyfallidis E, Zhong J, Chamberland M, Yeh FC, Lin YC, Ji Q, Reddick WE, Glass JO, Chen DQ, Feng Y, Gao C, Wu Y, Ma J, He R, Li Q et al (2017) The challenge of mapping the human connectome based on diffusion tractography. Nat Commun 8(1):1349. https://doi.org/10.1038/s41467-017-01285-x
Medaglia JD, Lynall M-E, Bassett DS (2015) Cognitive network neuroscience. J Cogn Neurosci 27(8):1471–1491. https://doi.org/10.1162/jocn_a_00810
Meunier D, Lambiotte R, Bullmore ET (2010) Modular and hierarchically modular organization of brain networks. Front Neurosci 4:200. https://doi.org/10.3389/fnins.2010.00200
Milton CK, Dhanaraj V, Young IM, Taylor HM, Nicholas PJ, Briggs RG, Bai MY, Fonseka RD, Hormovas J, Lin YH (2021) Parcellation-based anatomic model of the semantic network. Brain and Behavior 11(4):e02065. https://doi.org/10.1002/brb3.2065
Muldoon SF, Bridgeford EW, Bassett DS (2016) Small-world propensity and weighted brain networks. Sci Rep 6(1):22057. https://doi.org/10.1038/srep22057
Myers RH, Montgomery DC, Anderson-Cook CM (2016) Response surface methodology: process and product optimization using designed experiments. John Wiley and Sons
Nieto-Castañón A, Fedorenko E (2012) Subject-specific functional localizers increase sensitivity and functional resolution of multi-subject analyses. Neuroimage 63(3):1646–1669. https://doi.org/10.1016/j.neuroimage.2012.06.065
Patterson K, and Ralph MAL (2016). The hub-and-spoke hypothesis of semantic memory. In Neurobiology of Language (765–775). Elsevier
Que X, Checconi F, Petrini F, and Gunnels JA (2015, 25–29 May 2015). Scalable community detection with the louvain algorithm. 2015 IEEE international parallel and distributed processing symposium
Raichle ME (2015) The brain’s default mode network. Annu Rev Neurosci 38(1):433–447. https://doi.org/10.1146/annurev-neuro-071013-014030
Ralph MAL, Jefferies E, Patterson K, Rogers TT (2017) The neural and computational bases of semantic cognition. Nat Rev Neurosci 18(1):42–55. https://doi.org/10.1038/nrn.2016.150
Rasero J, Pellicoro M, Angelini L, Cortes JM, Marinazzo D, Stramaglia S (2017) Consensus clustering approach to group brain connectivity matrices. Netw Neurosci 1(3):242–253. https://doi.org/10.1162/NETN_a_00017
Reber J, Hwang K, Bowren M, Bruss J, Mukherjee P, Tranel D, and Boes AD (2021). Cognitive impairment after focal brain lesions is better predicted by damage to structural than functional network hubs. Proceedings of the National Academy of Sciences, 118(19). e2018784118 https://doi.org/10.1073/pnas.2018784118
Rossetti HC, Lacritz LH, Cullum CM, Weiner MF (2011) Normative data for the Montreal cognitive assessment (MoCA) in a population-based sample. Neurology 77(13):1272. https://doi.org/10.1212/WNL.0b013e318230208a
Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52(3):1059–1069. https://doi.org/10.1016/j.neuroimage.2009.10.003
Rubinov M, Sporns O (2011) Weight-conserving characterization of complex functional brain networks. Neuroimage 56(4):2068–2079. https://doi.org/10.1016/j.neuroimage.2011.03.069
Shao Z, Janse E, Visser K, Meyer AS (2014) What do verbal fluency tasks measure? Predictors of verbal fluency performance in older adults [Original Research]. Front Psychol 5(772):772. https://doi.org/10.3389/fpsyg.2014.00772
Siegel JS, Ramsey LE, Snyder AZ, Metcalf NV, Chacko RV, Weinberger K, Baldassarre A, Hacker CD, Shulman GL, Corbetta M (2016) Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke. Proc Natl Acad Sci 113(30):E4367–E4376. https://doi.org/10.1073/pnas.1521083113(ProceedingsoftheNationalAcademyofSciences)
Smith RE, Tournier J-D, Calamante F, Connelly A (2012) Anatomically-constrained tractography: improved diffusion MRI streamlines tractography through effective use of anatomical information. Neuroimage 62(3):1924–1938. https://doi.org/10.1016/j.neuroimage.2012.06.005
Smith RE, Tournier J-D, Calamante F, Connelly A (2015) SIFT2: Enabling dense quantitative assessment of brain white matter connectivity using streamlines tractography. Neuroimage 119:338–351. https://doi.org/10.1016/j.neuroimage.2015.06.092
Sporns, O. (2013). Structure and function of complex brain networks. Dial Clin Neurosci 15(3), 247–262. https://doi.org/10.31887/DCNS.2013.15.3/osporns
Sporns O, Betzel RF (2016) Modular brain networks. Annu Rev Psychol 67:613–640. https://doi.org/10.1146/annurev-psych-122414-033634
Sporns O, Honey CJ, Kötter R (2007) Identification and classification of hubs in brain networks. PLoS ONE 2(10):e1049. https://doi.org/10.1371/journal.pone.0001049
Sundqvist M, Routier A, Dubois B, Colliot O, Teichmann M (2020) The white matter module-hub network of semantics revealed by semantic dementia. J Cogn Neurosci 32(7):1330–1347. https://doi.org/10.1162/jocn_a_01549
Tournier J-D, Smith R, Raffelt D, Tabbara R, Dhollander T, Pietsch M, Christiaens D, Jeurissen B, Yeh C-H, Connelly A (2019) MRtrix3: a fast, flexible and open software framework for medical image processing and visualisation. Neuroimage 202:116137. https://doi.org/10.1016/j.neuroimage.2019.116137
Turkeltaub PE (2019) A taxonomy of brain–behavior relationships after stroke. J Speech Lang Hear Res 62(11):3907–3922. https://doi.org/10.1044/2019_JSLHR-L-RSNP-19-0032
van den Heuvel MP, Sporns O (2013a) An anatomical substrate for integration among functional networks in human cortex. J Neurosci 33(36):14489–14500
van den Heuvel MP, Sporns O (2013b) Network hubs in the human brain. Trends Cogn Sci 17(12):683–696. https://doi.org/10.1016/j.tics.2013b.09.012
van Wijk BCM, Stam CJ, Daffertshofer A (2010) Comparing brain networks of different size and connectivity density using graph theory. PLoS ONE 5(10):e13701. https://doi.org/10.1371/journal.pone.0013701
Vandenberghe R, Wang Y, Nelissen N, Vandenbulcke M, Dhollander T, Sunaert S, Dupont P (2013) The associative-semantic network for words and pictures: effective connectivity and graph analysis. Brain Lang 127(2):264–272. https://doi.org/10.1016/j.bandl.2012.09.005
Vanderwal T, Eilbott J, Finn ES, Craddock RC, Turnbull A, Castellanos FX (2017) Individual differences in functional connectivity during naturalistic viewing conditions. Neuroimage 157:521–530. https://doi.org/10.1016/j.neuroimage.2017.06.027
Vanderwal T, Kelly C, Eilbott J, Mayes LC, Castellanos FX (2015) Inscapes: a movie paradigm to improve compliance in functional magnetic resonance imaging. Neuroimage 122:222–232. https://doi.org/10.1016/j.neuroimage.2015.07.069
Whitney C, Kirk M, O’Sullivan J, Lambon Ralph MA, Jefferies E (2010) The neural organization of semantic control: TMS evidence for a distributed network in left inferior frontal and posterior middle temporal Gyrus. Cereb Cortex 21(5):1066–1075. https://doi.org/10.1093/cercor/bhq180
Wilson SM, Yen M, Eriksson DK (2018) An adaptive semantic matching paradigm for reliable and valid language mapping in individuals with aphasia. Hum Brain Mapp 39(8):3285–3307. https://doi.org/10.1002/hbm.24077
Worsley KJ, Liao CH, Aston J, Petre V, Duncan G, Morales F, Evans A (2002) A general statistical analysis for fMRI data. Neuroimage 15(1):1–15. https://doi.org/10.1006/nimg.2001.0933
Xia M, Wang J, He Y (2013) BrainNet Viewer: a network visualization tool for human brain connectomics. PLoS ONE 8(7):e68910. https://doi.org/10.1371/journal.pone.0068910
Xing S, Lacey EH, Skipper-Kallal LM, Zeng J, Turkeltaub PE (2017) White matter correlates of auditory comprehension outcomes in chronic post-stroke aphasia. Front Neurol 8:54. https://doi.org/10.3389/fneur.2017.00054
Xu Y, He Y, Bi Y (2017) A tri-network model of human semantic processing [review]. Front Psychol 8(1538):1538. https://doi.org/10.3389/fpsyg.2017.01538
Xu Y, Lin Q, Han Z, He Y, Bi Y (2016) Intrinsic functional network architecture of human semantic processing: modules and hubs. Neuroimage 132:542–555. https://doi.org/10.1016/j.neuroimage.2016.03.004
Yeo BTT, Krienen FM, Sepulcre J, Sabuncu MR, Lashkari D, Hollinshead M, Roffman JL, Smoller JW, Zöllei L, Polimeni JR, Fischl B, Liu H, Buckner RL (2011) The organization of the human cerebral cortex estimated by intrinsic functional connectivity. J Neurophysiol 106(3):1125–1165. https://doi.org/10.1152/jn.00338.2011
Yu M, Wu Z, Luan M, Wang X, Song Y, Liu J (2018) Neural correlates of semantic and phonological processing revealed by functional connectivity patterns in the language network. Neuropsychologia 121:47–57. https://doi.org/10.1016/j.neuropsychologia.2018.10.027
Zhao Y, Song L, Ding J, Lin N, Wang Q, Du X, Sun R, Han Z (2017) Left anterior temporal lobe and bilateral anterior cingulate cortex are semantic hub regions: evidence from behavior-nodal degree mapping in brain-damaged patients. J Neurosci 37(1):141–151. https://doi.org/10.1523/jneurosci.1946-16.2016
Funding
This work was supported by NIH/NIDCD R01DC014960 to PET and K99DC018828 to AD.
Author information
Authors and Affiliations
Contributions
The conception and design of this study was developed by authors WTK, AD, and PET. Data collection was performed by authors SP and CV. Author WTK was responsible for material preparation, data analysis, and original manuscript writing. All authors contributed to revision and finalization of the manuscript and have approved the final version.
Corresponding author
Ethics declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose.
Ethics approval
This study was performed in line with the principles of the Declaration of Helsinki, and all study procedures were approved by the Georgetown Institutional Review Board.
Consent to participate
Written informed consent was obtained from all participants included in this study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Ketchabaw, W.T., DeMarco, A.T., Paul, S. et al. The organization of individually mapped structural and functional semantic networks in aging adults. Brain Struct Funct 227, 2513–2527 (2022). https://doi.org/10.1007/s00429-022-02544-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00429-022-02544-4