Abutalebi, J., Della Rosa, P. A., Gonzaga, A. K., Keim, R., Costa, A., & Perani, D. (2013). The role of the left putamen in multilingual language production. Brain and Language, 125(3), 307–315. https://doi.org/10.1016/j.bandl.2012.03.009.

Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W., Segall, J. M., Silva, R. F., Havlicek, M., Rachakonda, S., Fries, J., Kalyanam, R., Michael, A. M., Caprihan, A., Turner, J. A., Eichele, T., Adelsheim, S., Bryan, A. D., Bustillo, J., Clark, V. P., Feldstein Ewing, S. W., Filbey, F., Ford, C. C., Hutchison, K., Jung, R. E., Kiehl, K. A., Kodituwakku, P., Komesu, Y. M., Mayer, A. R., Pearlson, G. D., Phillips, J. P., Sadek, J. R., Stevens, M., Teuscher, U., Thoma, R. J., & Calhoun, V. D. (2011). A baseline for the multivariate comparison of resting-state networks. Frontiers in Systems Neuroscience, 5, 2. https://doi.org/10.3389/fnsys.2011.00002.

Aminoff, E. M., Kveraga, K., & Bar, M. (2013). The role of the parahippocampal cortex in cognition. Trends in Cognitive Sciences, 17(8), 379–390. https://doi.org/10.1016/j.tics.2013.06.009.

Bar, M., Gronau, N., & Aminoff, E. (2006). The Parahippocampal cortex mediates spatial and nonspatial associations. Cerebral Cortex, 17(7), 1493–1503. https://doi.org/10.1093/cercor/bhl078

Baron-Cohen, S., Knickmeyer, R. C., & Belmonte, M. K. (2005). Sex differences in the brain: Implications for explaining autism. Science, 310(5749), 819–823. https://doi.org/10.1126/science.1115455.

Beaty, R. E., Benedek, M., Silvia, P. J., & Schacter, D. L. (2016). Creative cognition and brain network dynamics. Trends in Cognitive Sciences, 20(2), 87–95. https://doi.org/10.1016/j.tics.2015.10.004.

Beaty, R. E., Kenett, Y. N., Christensen, A. P., Rosenberg, M. D., Benedek, M., Chen, Q., Fink, A., Qiu, J., Kwapil, T. R., Kane, M. J., & Silvia, P. J. (2018). Robust prediction of individual creative ability from brain functional connectivity. Proceedings of the National Academy of Sciences of the United States of America, 115, 1087–1092. https://doi.org/10.1073/pnas.1713532115.

Becker, L., Kutz, D., & Voelcker-Rehage, C. (2016). Exercise-induced changes in basal ganglia volume and their relation to cognitive performance. J Neurol Neuromed, 1(5), 19-24. https://doi.org/10.29245/2572.942X/2016/5.1044.

Bell, E. C., Willson, M. C., Wilman, A. H., Dave, S., & Silverstone, P. H. (2006). Males and females differ in brain activation during cognitive tasks. Neuroimage, 30(2), 529–538. https://doi.org/10.1016/j.neuroimage.2005.09.049.

Bonner, M. F., & Price, A. R. (2013). Where is the anterior temporal lobe and what does it do? The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 33(10), 4213–4215. https://doi.org/10.1523/JNEUROSCI.0041-13.2013.

Burgess, N., Maguire, E. A., Spiers, H. J., & O'Keefe, J. (2001). A temporoparietal and prefrontal network for retrieving the spatial context of lifelike events. Neuroimage, 14(2), 439–453. https://doi.org/10.1006/nimg.2001.0806.

Bzdok, D., Hartwigsen, G., Reid, A., Laird, A. R., Fox, P. T., & Eickhoff, S. B. (2016). Left inferior parietal lobe engagement in social cognition and language. Neuroscience and Biobehavioral Reviews, 68, 319–334. https://doi.org/10.1016/j.neubiorev.2016.02.024.

Cahill, L., Haier, R. J., White, N. S., Fallon, J., Kilpatrick, L., Lawrence, C., Potkin, S. G., & Alkire, M. T. (2001). Sex-related difference in amygdala activity during emotionally influenced memory storage. Neurobiology of Learning and Memory, 75(1), 1–9. https://doi.org/10.1006/nlme.2000.3999.

Chen, S. H., & Desmond, J. E. (2005). Cerebrocerebellar networks during articulatory rehearsal and verbal working memory tasks. Neuroimage, 24(2), 332–338. https://doi.org/10.1016/j.neuroimage.2004.08.032.

Choi, Y. Y., Shamosh, N. A., Cho, S. H., DeYoung, C. G., Lee, M. J., Lee, J. M., Kim, S. I., Cho, Z. H., Kim, K., Gray, J. R., & Lee, K. H. (2008). Multiple bases of human intelligence revealed by cortical thickness and neural activation. The Journal of Neuroscience, 28(41), 10323–10329. https://doi.org/10.1523/JNEUROSCI.3259-08.2008.

Clements, A. M., Rimrodt, S. L., Abel, J. R., Blankner, J. G., Mostofsky, S. H., Pekar, J. J., Denckla, M. B., & Cutting, L. E. (2006). Sex differences in cerebral laterality of language and visuospatial processing. Brain and Language, 98(2), 150–158. https://doi.org/10.1016/j.bandl.2006.04.007.

Colom, R., Karama, S., Jung, R. E., & Haier, R. J. (2010). Human intelligence and brain networks. Dialogues in Clinical Neuroscience, 12(4), 489–501.

Cui, Y., Liu, B., Zhou, Y., Fan, L., Li, J., Zhang, Y., Wu, H., Hou, B., Wang, C., Zheng, F., Qiu, C., Rao, L. L., Ning, Y., Li, S., & Jiang, T. (2016). Genetic effects on fine-grained human cortical regionalization. Cerebral Cortex, 26(9), 3732–3743. https://doi.org/10.1093/cercor/bhv176.

Dai, X. Y., Ryan, J. J., Paolo, A. M., & Harrington, R. G. (1990). Factor-Analysis of the Mainland Chinese Version of the Wechsler Adult Intelligence Scale (Wais-Rc) in a Brain-Damaged Sample. International Journal of Neuroscience, 55(2–4), 107–111. https://doi.org/10.3109/00207459008985956.

Deary, I. J., Penke, L., & Johnson, W. (2010). The neuroscience of human intelligence differences. Nature Reviews. Neuroscience, 11(3), 201–211. https://doi.org/10.1038/nrn2793.

Dezfouli, A., & Balleine, B. W. (2012). Habits, action sequences and reinforcement learning. The European Journal of Neuroscience, 35(7), 1036–1051. https://doi.org/10.1111/j.1460-9568.2012.08050.x.

Dosenbach, N. U., Nardos, B., Cohen, A. L., Fair, D. A., Power, J. D., Church, J. A., et al. (2010). Prediction of individual brain maturity using fMRI. Science, 329(5997), 1358–1361. https://doi.org/10.1126/science.1194144.

Fah, L. Y. (2009). Logical thinking abilities among form 4 students in the interior division of Sabah, Malaysia. Journal of Science and Mathematics Education in Southeast Asia, 32(2), 161–187.

Fair, D. A., Dosenbach, N. U. F., Church, J. A., Cohen, A. L., Brahmbhatt, S., Miezin, F. M., Barch, D. M., Raichle, M. E., Petersen, S. E., & Schlaggar, B. L. (2007). Development of distinct control networks through segregation and integration. Proceedings of the National Academy of Sciences, 104(33), 13507–13512. https://doi.org/10.1073/pnas.0705843104.

Fan, L., Li, H., Zhuo, J., Zhang, Y., Wang, J., Chen, L., Yang, Z., Chu, C., Xie, S., Laird, A. R., Fox, P. T., Eickhoff, S. B., Yu, C., & Jiang, T. (2016). The human Brainnetome atlas: A new brain atlas based on connectional architecture. Cerebral Cortex, 26(8), 3508–3526. https://doi.org/10.1093/cercor/bhw157.

Feng, C., Yuan, J., Geng, H., Gu, R., Zhou, H., Wu, X., & Luo, Y. (2018). Individualized prediction of trait narcissism from whole-brain resting-state functional connectivity. Human Brain Mapping, 39, 3701–3712. https://doi.org/10.1002/hbm.24205.

Finn, E. S., Shen, X., Scheinost, D., Rosenberg, M. D., Huang, J., Chun, M. M., Papademetris, X., & Constable, R. T. (2015). Functional connectome fingerprinting: Identifying individuals using patterns of brain connectivity. Nature Neuroscience, 18(11), 1664–1671. https://doi.org/10.1038/nn.4135.

Fischl, B., & Dale, A. M. (2000). Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences, 97(20), 11050–11055. https://doi.org/10.1073/pnas.200033797

Frederikse, M. E., Lu, A., Aylward, E., Barta, P., & Pearlson, G. (1999). Sex differences in the inferior parietal lobule. Cerebral Cortex, 9(8), 896–901. https://doi.org/10.1093/cercor/9.8.896.

Gabrieli, J. D., Ghosh, S. S., & Whitfield-Gabrieli, S. (2015). Prediction as a humanitarian and pragmatic contribution from human cognitive neuroscience. Neuron, 85(1), 11–26. https://doi.org/10.1016/j.neuron.2014.10.047.

Genc, E., Fraenz, C., Schluter, C., Friedrich, P., Hossiep, R., Voelkle, M. C., et al. (2018). Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence. Nature Communications, 9(1), 1905. https://doi.org/10.1038/s41467-01804268-8.

Glascher, J., Rudrauf, D., Colom, R., Paul, L. K., Tranel, D., Damasio, H., & Adolphs, R. (2010). Distributed neural system for general intelligence revealed by lesion mapping. Proceedings of the National Academy of Sciences of the United States of America, 107(10), 4705–4709. https://doi.org/10.1073/pnas.0910397107.

Goh, S., Bansal, R., Xu, D., Hao, X., Liu, J., & Peterson, B. S. (2011). Neuroanatomical correlates of intellectual ability across the life span. Developmental Cognitive Neuroscience, 1(3), 305–312. https://doi.org/10.1016/j.dcn.2011.03.001.

Goriounova, N. A., & Mansvelder, H. D. J. F. i. H. N. (2019). Genes, Cells and Brain Areas of Intelligence, 13. https://doi.org/10.3389/fnhum.2019.00044.

Grazioplene, R. G., S, G. R., Gray, J. R., Rustichini, A., Jung, R. E., & DeYoung, C. G. (2015). Subcortical intelligence: Caudate volume predicts IQ in healthy adults. Human Brain Mapping, 36(4), 1407–1416. https://doi.org/10.1002/hbm.22710.

Greene, A. S., Gao, S., Scheinost, D., & Constable, R. T. (2018). Task-induced brain state manipulation improves prediction of individual traits. Nature Communications, 9(1), 2807. https://doi.org/10.1038/s41467-018-04920-3.

Haier, R. J., Jung, R. E., Yeo, R. A., Head, K., & Alkire, M. T. (2005). The neuroanatomy of general intelligence: Sex matters. Neuroimage, 25(1), 320–327. https://doi.org/10.1016/j.neuroimage.2004.11.019.

Halpern, D. F., Benbow, C. P., Geary, D. C., Gur, R. C., Hyde, J. S., & Gernsbacher, M. A. (2007). The science of sex differences in science and mathematics. Psychological Science in the Public Interest, 8(1), 1–51. https://doi.org/10.1111/j.1529-1006.2007.00032.x.

Hartwigsen, G., Golombek, T., & Obleser, J. (2015). Repetitive transcranial magnetic stimulation over left angular gyrus modulates the predictability gain in degraded speech comprehension. Cortex, 68, 100–110. https://doi.org/10.1016/j.cortex.2014.08.027.

Hill, A. C., Laird, A. R., & Robinson, J. L. (2014). Gender differences in working memory networks: A BrainMap meta-analysis. Biological Psychology, 102, 18–29. https://doi.org/10.1016/j.biopsycho.2014.06.008.

Hsu, W. T., Rosenberg, M. D., Scheinost, D., Constable, R. T., & Chun, M. M. (2018). Resting-state functional connectivity predicts neuroticism and extraversion in novel individuals. Social Cognitive and Affective Neuroscience, 13(2), 224–232. https://doi.org/10.1093/scan/nsy002.

Huttenlocher, P. R. (1990). Morphometric study of human cerebral cortex development. Neuropsychologia, 28(6), 517–527. https://doi.org/10.1016/0028-3932(90)90031-I.

Ingalhalikar, M., Smith, A., Parker, D., Satterthwaite, T. D., Elliott, M. A., Ruparel, K., Hakonarson, H., Gur, R. E., Gur, R. C., & Verma, R. (2014). Sex differences in the structural connectome of the human brain. Proceedings of the National Academy of Sciences of the United States of America, 111(2), 823–828. https://doi.org/10.1073/pnas.1316909110.

Irwing, P., & Lynn, R. (2006). Intelligence: Is there a sex difference in IQ scores? Nature, 442(7098), E1–E1; discussion E2. https://doi.org/10.1038/nature04966.

Jangraw, D. C., Gonzalez-Castillo, J., Handwerker, D. A., Ghane, M., Rosenberg, M. D., Panwar, P., & Bandettini, P. A. (2018). A functional connectivity-based neuromarker of sustained attention generalizes to predict recall in a reading task. Neuroimage, 166, 99–109. https://doi.org/10.1016/j.neuroimage.2017.10.019.

Janzen, G., Wagensveld, B., & van Turennout, M. (2007). Neural representation of navigational relevance is rapidly induced and long lasting. Cerebral Cortex, 17(4), 975–981. https://doi.org/10.1093/cercor/bhl008.

Jensen, A. R. (1998). The g factor: The science of mental ability. https://doi.org/10.1007/BF02685991.

Jiang, R. T., Qi, S. L., Du, Y. H., Yan, W. Z., Calhoun, V. D., Jiang, T. Z., et al. (2017). Predicting Individualized Intelligence Quotient Scores Using Brainnetome-Atlas Based Functional Connectivity. 2017 Ieee 27th International Workshop on Machine Learning for Signal Processing. https://doi.org/10.1109/MLSP.2017.8168150.

Jiang, R., Calhoun, V. D., Zuo, N., Lin, D., Li, J., Fan, L., Qi, S., Sun, H., Fu, Z., Song, M., Jiang, T., & Sui, J. (2018). Connectome-based individualized prediction of temperament trait scores. Neuroimage, 183, 366–374. https://doi.org/10.1016/j.neuroimage.2018.08.038.

Jin, L., Bing, L., Chuansheng, C., Yue, C., Liqing, S., Yun, Z., et al. (2015). RAB2A Polymorphism impacts prefrontal morphology, functional connectivity, and working memory. 36(11), 4372–4382. https://doi.org/10.1002/hbm.22924.

Jung, R. E., & Haier, R. J. (2007). The Parieto-frontal integration theory (P-FIT) of intelligence: Converging neuroimaging evidence. The Behavioral and Brain Sciences, 30(2), 135–154; discussion 154-187. https://doi.org/10.1017/S0140525X07001185.

Jung, R. E., Mead, B. S., Carrasco, J., & Flores, R. A. (2013). The structure of creative cognition in the human brain. Frontiers in Human Neuroscience, 7, 330. https://doi.org/10.3389/fnhum.2013.00330.

Kenett, Y. N., Medaglia, J. D., Beaty, R. E., Chen, Q., Betzel, R. F., Thompson-Schill, S. L., & Qiu, J. (2018). Driving the brain towards creativity and intelligence: A network control theory analysis. Neuropsychologia, 118, 79–90. https://doi.org/10.1016/j.neuropsychologia.2018.01.001.

Kimura, D. (1996). Sex, sexual orientation and sex hormones influence human cognitive function. Current Opinion in Neurobiology, 6(2), 259-263. https://doi.org/10.1016/S0959-4388(96)80081-X.

Langeslag, S. J., Schmidt, M., Ghassabian, A., Jaddoe, V. W., Hofman, A., van der Lugt, A., et al. (2013). Functional connectivity between parietal and frontal brain regions and intelligence in young children: The generation R study. Human Brain Mapping, 34(12), 3299–3307. https://doi.org/10.1002/hbm.22143.

Levy, I., Hasson, U., Avidan, G., Hendler, T., & Malach, R. (2001). Center-periphery organization of human object areas. Nature Neuroscience, 4(5), 533–539. https://doi.org/10.1038/87490.

Liu, B., Li, J., Zhang, X., Tao, Y., Cui, Y., Jiang, T., et al. (2016). Polygenic risk for schizophrenia influences cortical Gyrification in 2 independent general populations. Schizophrenia Bulletin, 43(3), 673–680. https://doi.org/10.1093/schbul/sbw051.

Liu, Z., Zhang, J., Xie, X., Rolls, E. T., Sun, J., Zhang, K., Jiao, Z., Chen, Q., Zhang, J., Qiu, J., & Feng, J. (2018). Neural and genetic determinants of creativity. Neuroimage, 174, 164–176. https://doi.org/10.1016/j.neuroimage.2018.02.067.

Manto, M., Bower, J. M., Conforto, A. B., Delgado-Garcia, J. M., da Guarda, S. N., Gerwig, M., et al. (2012). Consensus paper: Roles of the cerebellum in motor control--the diversity of ideas on cerebellar involvement in movement. Cerebellum, 11(2), 457–487. https://doi.org/10.1007/s12311-011-0331-9.

Mariën, P., Ackermann, H., Adamaszek, M., Barwood, C. H. S., Beaton, A., Desmond, J., de Witte, E., Fawcett, A. J., Hertrich, I., Küper, M., Leggio, M., Marvel, C., Molinari, M., Murdoch, B. E., Nicolson, R. I., Schmahmann, J. D., Stoodley, C. J., Thürling, M., Timmann, D., Wouters, E., & Ziegler, W. (2014). Consensus paper: Language and the cerebellum: An ongoing enigma. Cerebellum (London, England), 13(3), 386–410. https://doi.org/10.1007/s12311-013-0540-5.

Meng, X., Jiang, R., Lin, D., Bustillo, J., Jones, T., Chen, J., Yu, Q., du, Y., Zhang, Y., Jiang, T., Sui, J., & Calhoun, V. D. (2017). Predicting individualized clinical measures by a generalized prediction framework and multimodal fusion of MRI data. Neuroimage, 145(Pt B), 218–229. https://doi.org/10.1016/j.neuroimage.2016.05.026.

Murdoch, B. E. (2010). The cerebellum and language: Historical perspective and review. Cortex, 46(7), 858–868. https://doi.org/10.1016/j.cortex.2009.07.018.

Narr, K. L., Toga, A. W., Szeszko, P., Thompson, P. M., Woods, R. P., Robinson, D., Sevy, S., Wang, Y. P., Schrock, K., & Bilder, R. M. (2005). Cortical thinning in cingulate and occipital cortices in first episode schizophrenia. Biological Psychiatry, 58(1), 32–40. https://doi.org/10.1016/j.biopsych.2005.03.043.

Narr, K. L., Woods, R. P., Thompson, P. M., Szeszko, P., Robinson, D., Dimtcheva, T., Gurbani, M., Toga, A. W., & Bilder, R. M. (2007). Relationships between IQ and regional cortical gray matter thickness in healthy adults. Cerebral Cortex, 17(9), 2163–2171. https://doi.org/10.1093/cercor/bhl125.

Nejad, A. B., Jiang, J., Zhisheng, K., Salleh, S. R., Manning, V., Graham, S., et al. (2009). IQ-related fMRI differences during cognitive set shifting. Cerebral Cortex, 20(3), 641–649. https://doi.org/10.1093/cercor/bhp130.

Pezoulas, V. C., Zervakis, M., Michelogiannis, S., & Klados, M. A. (2017). Resting-state functional connectivity and network analysis of cerebellum with respect to crystallized IQ and gender. Frontiers in Human Neuroscience, 11, 189. https://doi.org/10.3389/fnhum.2017.00189.

Power, J. D., Cohen, A. L., Nelson, S. M., Wig, G. S., Barnes, K. A., Church, J. A., Vogel, A. C., Laumann, T. O., Miezin, F. M., Schlaggar, B. L., & Petersen, S. E. (2011). Functional network organization of the human brain. Neuron, 72(4), 665–678. https://doi.org/10.1016/j.neuron.2011.09.006.

Qi, S., Yang, X., Zhao, L., Calhoun, V. D., Perrone-Bizzozero, N., Liu, S., Jiang, R., Jiang, T., Sui, J., & Ma, X. (2018). MicroRNA132 associated multimodal neuroimaging patterns in unmedicated major depressive disorder. Brain, 141, 916–926. https://doi.org/10.1093/brain/awx366.

Rashid, B., Damaraju, E., Pearlson, G. D., & Calhoun, V. D. (2014). Dynamic connectivity states estimated from resting fMRI identify differences among schizophrenia, bipolar disorder, and healthy control subjects. Frontiers in Human Neuroscience, 8, 897. https://doi.org/10.3389/fnhum.2014.00897.

Rosenberg, M. D., Finn, E. S., Scheinost, D., Papademetris, X., Shen, X., Constable, R. T., & Chun, M. M. (2016). A neuromarker of sustained attention from whole-brain functional connectivity. Nature Neuroscience, 19(1), 165–171. https://doi.org/10.1038/nn.4179.

Ryman, S. G., Yeo, R. A., Witkiewitz, K., Vakhtin, A. A., van den Heuvel, M., de Reus, M., Flores, R. A., Wertz, C. R., & Jung, R. E. (2016). Fronto-parietal gray matter and white matter efficiency differentially predict intelligence in males and females. Human Brain Mapping, 37(11), 4006–4016. https://doi.org/10.1002/hbm.23291.

Schmithorst, V. J., & Holland, S. K. (2006). Functional MRI evidence for disparate developmental processes underlying intelligence in boys and girls. Neuroimage, 31(3), 1366–1379. https://doi.org/10.1016/j.neuroimage.2006.01.010.

Schmithorst, V. J., & Holland, S. K. (2007). Sex differences in the development of neuroanatomical functional connectivity underlying intelligence found using Bayesian connectivity analysis. Neuroimage, 35(1), 406–419. https://doi.org/10.1016/j.neuroimage.2006.11.046.

Schnack, H. G., van Haren, N. E., Brouwer, R. M., Evans, A., Durston, S., Boomsma, D. I., et al. (2015). Changes in thickness and surface area of the human cortex and their relationship with intelligence. Cerebral Cortex, 25(6), 1608–1617. https://doi.org/10.1093/cercor/bht357.

Shen, X., Finn, E. S., Scheinost, D., Rosenberg, M. D., Chun, M. M., Papademetris, X., & Constable, R. T. (2017). Using connectome-based predictive modeling to predict individual behavior from brain connectivity. [protocol]. Nature Protocols, 12(3), 506–518. https://doi.org/10.1038/nprot.2016.178.

Song, M., Zhou, Y., Li, J., Liu, Y., Tian, L., Yu, C., & Jiang, T. (2008). Brain spontaneous functional connectivity and intelligence. Neuroimage, 41(3), 1168–1176. https://doi.org/10.1016/j.neuroimage.2008.02.036.

Stoodley, C. J., & Schmahmann, J. D. (2009). Functional topography in the human cerebellum: A meta-analysis of neuroimaging studies. Neuroimage, 44(2), 489–501. https://doi.org/10.1016/j.neuroimage.2008.08.039.

Sui, J., Adali, T., Yu, Q., Chen, J., & Calhoun, V. D. (2012). A review of multivariate methods for multimodal fusion of brain imaging data. Journal of Neuroscience Methods, 204(1), 68–81. https://doi.org/10.1016/j.jneumeth.2011.10.031.

Sui, J., Pearlson, G. D., Du, Y., Yu, Q., Jones, T. R., Chen, J., et al. (2015). In search of multimodal neuroimaging biomarkers of cognitive deficits in schizophrenia. Biological Psychiatry, 78(11), 794–804. https://doi.org/10.1016/j.biopsych.2015.02.017.

Sui, J., Qi, S., van Erp, T. G. M., Bustillo, J., Jiang, R., Lin, D., Turner, J. A., Damaraju, E., Mayer, A. R., Cui, Y., Fu, Z., du, Y., Chen, J., Potkin, S. G., Preda, A., Mathalon, D. H., Ford, J. M., Voyvodic, J., Mueller, B. A., Belger, A., McEwen, S. C., O’Leary, D. S., McMahon, A., Jiang, T., & Calhoun, V. D. (2018). Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion. Nature Communications, 9(1), 3028. https://doi.org/10.1038/s41467-018-05432-w.

Tomasi, D., & Volkow, N. D. (2012). Laterality patterns of brain functional connectivity: Gender effects. Cerebral Cortex, 22(6), 1455–1462. https://doi.org/10.1093/cercor/bhr230.

Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002). Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage, 15(1), 273–289. https://doi.org/10.1006/nimg.2001.0978.

Vakhtin, A. A., Ryman, S. G., Flores, R. A., & Jung, R. E. (2014). Functional brain networks contributing to the Parieto-frontal integration theory of intelligence. Neuroimage, 103, 349–354. https://doi.org/10.1016/j.neuroimage.2014.09.055.

van den Heuvel, M. P., & Sporns, O. (2011). Rich-club organization of the human connectome. The Journal of Neuroscience, 31(44), 15775–15786. https://doi.org/10.1523/JNEUROSCI.3539-11.2011.

Wechsler, D. (1981). WAIS-R manual: Wechsler adult intelligence scale-revised: Psychological Corporation.

Yan, C., Gong, G., Wang, J., Wang, D., Liu, D., Zhu, C., Chen, Z. J., Evans, A., Zang, Y., & He, Y. (2011). Sex- and brain size-related small-world structural cortical networks in young adults: A DTI tractography study. Cerebral Cortex, 21(2), 449–458. https://doi.org/10.1093/cercor/bhq111.

Yip, S. W., Scheinost, D., Potenza, M. N., & Carroll, K. M. (2019). Connectome-based prediction of cocaine abstinence. American Journal of Psychiatry, 176(2), 156–164. https://doi.org/10.1176/appi.ajp.2018.17101147.

Zhang, X., Yu, J.-T., Li, J., Wang, C., Tan, L., Liu, B., & Jiang, T. (2015). Bridging integrator 1 (BIN1) genotype effects on working memory, hippocampal volume, and functional connectivity in young healthy individuals. Neuropsychopharmacology, 40(7), 1794-1803. https://doi.org/10.1038/npp.2015.30 .