Process Overlap Theory: A Unified Account of the General Factor of Intelligence

References

• Achard, S., Salvador, R., Whitcher, B., Suckling, J., & Bullmore, E. (2006). A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 26(1), 63–72. doi:10.1523/JNEUROSCI.3874-05.2006
   PubMed Web of Science ®Google Scholar
• Ackerman, P. L. (1988). Determinants of individual differences during skill acquisition: Cognitive abilities and information processing. Journal of Experimental Psychology: General, 117, 288–318. doi:10.1037/0096-3445.117.3.288
   Web of Science ®Google Scholar
• Ackerman, P. L., Beier, M. E., & Boyle, M. O. (2005). Working memory and intelligence: The same or different constructs? Psychological Bulletin, 131, 30–60. doi:10.1037/0033-2909.131.1.30
   PubMed Web of Science ®Google Scholar
• Anderson, B. (2001). g as a consequence of shared genes. Intelligence, 29(5), 367–371. doi:10.1016/S0160-2896(01)00069-1
   Web of Science ®Google Scholar
• Aron, A. R., Robbins, T. W., & Poldrack, R. A. (2004). Inhibition and the right inferior frontal cortex. Trends in Cognitive Sciences, 8(4), 170–177. doi:10.1016/j.tics.2004.02.010
   PubMed Web of Science ®Google Scholar
• Asplund, C. L., Todd, J. J., Snyder, A. P., & Marois, R. (2010). A central role for the lateral prefrontal cortex in goal-directed and stimulus-driven attention. Nature Neuroscience, 13(4), 507–512. doi:10.1038/nn.2509
   PubMed Web of Science ®Google Scholar
• Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. Psychology of Learning and Motivation, 2, 89–105. doi:10.1016/S0079-7421(08)60422-3
   Google Scholar
• Baddeley, A. D. (1996). Exploring the central executive. The Quarterly Journal of Experimental Psychology Section A, 49(1), 5–28. doi:10.1080/713755608
   Web of Science ®Google Scholar
• Baddeley, A. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences, 4(11), 417–423. doi:10.1016/S1364-6613(00)01538-2
   PubMed Web of Science ®Google Scholar
• Baddeley, A. D. (2002). Is working memory still working? European Psychologist, 7(2), 85–97. doi:10.1027/1016-9040.7.2.85
   Web of Science ®Google Scholar
• Baddeley, A. D., & Hitch, G. (1974). Working memory. Psychology of Learning and Motivation, 8, 47–89. doi:10.1016/S0079-7421(08)60452-1
   Google Scholar
• Badre, D., & Wagner, A. D. (2004). Selection, integration, and conflict monitoring; assessing the nature and generality of prefrontal cognitive control mechanisms. Neuron, 41(3), 473–487.
   PubMed Web of Science ®Google Scholar
• Bagozzi, R. P. (2007). On the meaning of formative measurement and how it differs from reflective measurement: Comment on Howell, Breivik, and Wilcox (2007). Psychological Methods, 12(2), 229–237; discussion 238–245. doi:10.1037/1082-989X.12.2.229
   PubMed Web of Science ®Google Scholar
• Barbey, A. K., Colom, R., & Grafman, J. (2013). Dorsolateral prefrontal contributions to human intelligence. Neuropsychologia, 51(7), 1361–1369. doi:10.1016/j.neuropsychologia.2012.05.017
   PubMed Web of Science ®Google Scholar
• Barbey, A. K., Colom, R., Solomon, J., Krueger, F., Forbes, C., & Grafman, J. (2012). An integrative architecture for general intelligence and executive function revealed by lesion mapping. Brain: A Journal of Neurology, 135(Pt. 4), 1154–1164. doi:10.1093/brain/aws021
   PubMed Web of Science ®Google Scholar
• Bartholomew, D. J., Allerhand, M., & Deary, I. J. (2013). Measuring mental capacity: Thomson's Bonds model and Spearman's g-model compared. Intelligence, 41(4), 222–233. doi:10.1016/j.intell.2013.03.007
   Web of Science ®Google Scholar
• Bartholomew, D. J., Deary, I. J., & Lawn, M. (2009). A new lease of life for Thomson's bonds model of intelligence. Psychological Review, 116(3), 567–579. doi:10.1037/a0016262
   PubMed Web of Science ®Google Scholar
• Bassett, D. S., & Bullmore, E. (2006). Small-world brain networks. The Neuroscientist : A Review Journal Bringing Neurobiology, Neurology and Psychiatry, 12(6), 512–523. doi:10.1177/1073858406293182
   PubMed Web of Science ®Google Scholar
• Blair, C. (2006). How similar are fluid cognition and general intelligence? A developmental neuroscience perspective on fluid cognition as an aspect of human cognitive ability. The Behavioral and Brain Sciences, 29(2), 109–125; discussion 125–160. doi:10.1017/S0140525×06009034
   PubMed Web of Science ®Google Scholar
• Borsboom, D., Mellenbergh, G. J., & van Heerden, J. (2003). The theoretical status of latent variables. Psychological Review, 110(2), 203–219.
   PubMed Web of Science ®Google Scholar
• Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108(3), 624–652.
   PubMed Web of Science ®Google Scholar
• Braver, T. S., & Bongiolatti, S. R. (2002). The role of frontopolar cortex in subgoal processing during working memory. NeuroImage, 15(3), 523–536. doi:10.1006/nimg.2001.1019
   PubMed Web of Science ®Google Scholar
• Bressler, S., & Menon, V. (2010). Large-scale brain networks in cognition: Emerging methods and principles. Trends in Cognitive Sciences, 14, 277–290. doi:10.1016/j.tics.2010.04.004
   PubMed Web of Science ®Google Scholar
• Bullmore, E., & Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems. Nature Reviews. Neuroscience, 10(3), 186–198. doi:10.1038/nrn2575
   PubMed Web of Science ®Google Scholar
• Bunting, M. (2006). Proactive interference and item similarity in working memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32(2), 183–196. doi:10.1037/0278-7393.32.2.183
   PubMed Web of Science ®Google Scholar
• Burgess, G. C., Gray, J. R., Conway, A. R. A., & Braver, T. S. (2011). Neural mechanisms of interference control underlie the relationship between fluid intelligence and working memory span. Journal of Experimental Psychology. General, 140(4), 674–692. doi:10.1037/a0024695
   PubMed Web of Science ®Google Scholar
• Carpenter, P. A., Just, M. A., & Shell, P. (1990). What one intelligence test measures: A theoretical account of the processing in the Raven Progressive Matrices Test. Psychological Review, 97(3), 404–431.
   PubMed Web of Science ®Google Scholar
• Carroll, J. B. (1993). Human cognitive abilities: A survey of factor-analytic studies. Cambridge, UK: Cambridge University Press.
   Google Scholar
• Case, R., Kurland, D. M., & Goldberg, J. (1982). Operational efficiency and the growth of short-term memory span. Journal of Experimental Child Psychology, 33(3), 386–404. doi:10.1016/0022-0965(82)90054-6
   Web of Science ®Google Scholar
• Cattell, R. B. (1971). Abilities: Their structure, growth, and action. Boston, MA: Houghton Mifflin.
   Google Scholar
• Chambers, C. D., Bellgrove, M. A., Stokes, M. G., Henderson, T. R., Garavan, H., Robertson, I. H., … Mattingley J. B. (2006). Executive “brake failure” following deactivation of human frontal lobe. Journal of Cognitive Neuroscience, 18(3), 444–455. doi:10.1162/089892906775990606
   PubMed Web of Science ®Google Scholar
• Chein, J. M., Moore, A. B., & Conway, A. R. A. (2011). Domain-general mechanisms of complex working memory span. NeuroImage, 54(1), 550–559. doi:10.1016/j.neuroimage.2010.07.067
   PubMed Web of Science ®Google Scholar
• Choi, Y. Y., Shamosh, N. A., Cho, S. H., DeYoung, C. G., Lee, M. J., Lee, J.-M., … Lee, K. H. (2008). Multiple bases of human intelligence revealed by cortical thickness and neural activation. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 28(41), 10323–10329. doi:10.1523/JNEUROSCI.3259-08.2008
   PubMed Web of Science ®Google Scholar
• Chow, M., & Conway, A. R. A. (2015). The scope and control of attention: Sources of variance in working memory capacity. Memory & Cognition, 43(3), 325–339. doi:10.3758/s13421-014-0496-9
   PubMed Web of Science ®Google Scholar
• Christoff, K., Prabhakaran, V., Dorfman, J., Zhao, Z., Kroger, J. K., Holyoak, K. J., & Gabrieli, J. D. (2001). Rostrolateral prefrontal cortex involvement in relational integration during reasoning. NeuroImage, 14(5), 1136–1149. doi:10.1006/nimg.2001.0922
   PubMed Web of Science ®Google Scholar
• Chuderski, A. (2015). The broad factor of working memory is virtually isomorphic to fluid intelligence tested under time pressure. Personality and Individual Differences, 85, 98–104. doi:10.1016/j.paid.2015.04.046
   Web of Science ®Google Scholar
• Cole, M. W., Pathak, S., & Schneider, W. (2010). Identifying the brain's most globally connected regions. NeuroImage, 49(4), 3132–3148. doi:10.1016/j.neuroimage.2009.11.001
   PubMed Web of Science ®Google Scholar
• Cole, M. W., & Schneider, W. (2007). The cognitive control network: Integrated cortical regions with dissociable functions. NeuroImage, 37(1), 343–360. doi:10.1016/j.neuroimage.2007.03.071
   PubMed Web of Science ®Google Scholar
• Cole, M., & Yarkoni, T. (2012). Global connectivity of prefrontal cortex predicts cognitive control and intelligence. The Journal of Neuroscience, 32(26), 8988–8999. doi:10.1523/JNEUROSCI.0536-12.2012
   Web of Science ®Google Scholar
• Colom, R., Burgaleta, M., Martínez, K., Román, F. J., Álvarez-Linera, J., Quiroga, M. Á., … Privado, J. (2011). Consistency of intelligence in the brain. In International Society for the Study of Individual Differences (ISSID) 2011 meeting.
   Google Scholar
• Colom, R., Burgaleta, M., Román, F. J., Karama, S., Álvarez-linera, J., Abad, F. J., … Haier R. J. (2013). Neuroanatomic overlap between intelligence and cognitive factors: Morphometry methods provide support for the key role of the frontal lobes. Paper presented at International Society for the Study of Individual Differences (ISSID), Barcelona, Spain, July 22–25. doi:10.1016/j.neuroimage.2013.01.032
   Google Scholar
• Colom, R., Haier, R., & Head, K. (2009). Intelligence Gray matter correlates of fluid, crystallized, and spatial intelligence: Testing the P-FIT model. Intelligence, 37(2), 124–135. doi:10.1016/j.intell.2008.07.007
   Web of Science ®Google Scholar
• Colom, R., Jung, R. E., & Haier, R. J. (2006a). Distributed brain sites for the g-factor of intelligence. NeuroImage, 31(3), 1359–65. doi:10.1016/j.neuroimage.2006.01.006
   PubMed Web of Science ®Google Scholar
• Colom, R., Jung, R. E., & Haier, R. J. (2006b). Finding the g-factor in brain structure using the method of correlated vectors. Intelligence, 34(6), 561–570. doi:10.1016/j.intell.2006.03.006
   Web of Science ®Google Scholar
• Conway, A. R. A., Cowan, N., & Bunting, M. F. (2001). The cocktail party phenomenon revisited: The importance of working memory capacity. Psychonomic Bulletin & Review, 8(2), 331–335. doi:10.3758/BF03196169
   PubMed Web of Science ®Google Scholar
• Conway, A. R. A., Cowan, N., Bunting, M. F., Therriault, D. J., & Minkoff, S. R. (2002). A latent variable analysis of working memory capacity, short-term memory capacity, processing speed, and general fluid intelligence. Intelligence, 30(2), 163–183. doi:10.1016/S0160-2896(01)00096-4
   Web of Science ®Google Scholar
• Conway, A. R. A., Kane, M. J., Bunting, M. F., Hambrick, D. Z., Wilhelm, O., & Engle, R. W. (2005). Working memory span tasks: A methodological review and user's guide. Psychonomic Bulletin & Review, 12(5), 769–786. doi:10.3758/BF03196772
   PubMed Web of Science ®Google Scholar
• Conway, A. R. A., Kane, M. J., & Engle, R. W. (1999). Is Spearman's g determined by speed or working memory capacity? Book review of Jensen on Intelligence-g-Factor. PSYCOLOQUY, 10(074).
   Google Scholar
• Conway, A. R. A., Kane, M. J., & Engle, R. W. (2003). Working memory capacity and its relation to general intelligence. Trends in Cognitive Sciences, 7(12), 547–552. doi:10.1016/j.tics.2003.10.005
   PubMed Web of Science ®Google Scholar
• Conway, A. R. A., & Kovacs, K. (2013). Individual differences in intelligence and working memory. Psychology of Learning and Motivation, 58, 233–270. doi:10.1016/B978-0-12-407237-4.00007-4
   Google Scholar
• Conway, A. R. A., Macnamara, B., Getz, S., & Engel de Abreu, P. (2011). Working memory and fluid intelligence: A multi-mechanism view. In R. Sternberg & S. Kaufman (Eds.), Cambridge handbook of intelligence (pp. 394–418). New York, NY: Cambridge University Press.
   Google Scholar
• Conway, A. R. A., Tuholski, S. W., Shisler, R. J., & Engle, R. W. (1999). The effect of memory load on negative priming: An individual differences investigation. Memory & Cognition, 27(6), 1042–1050. doi:10.3758/BF03201233
   PubMed Web of Science ®Google Scholar
• Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews. Neuroscience, 3(3), 201–215. doi:10.1038/nrn755
   PubMed Web of Science ®Google Scholar
• Cowan, N., Elliott, E. M., Saults, S. J., Morey, C. C., Mattox, S., Hismjatullina, A., & Conway, A. R. A. (2005). On the capacity of attention: Its estimation and its role in working memory and cognitive aptitudes. Cognitive Psychology, 51, 42–100. doi:10.1016/j.cogpsych.2004.12.001
   PubMed Web of Science ®Google Scholar
• Coyle, T. R. (2001). IQ is related to the worst performance rule in a memory task involving children. Intelligence, 29(2), 117–129. doi:10.1016/S0160-2896(00)00044-1
   Web of Science ®Google Scholar
• Coyle, T. R. (2003a). IQ, the worst performance rule, and Spearman's law: A reanalysis and extension. Intelligence, 31(5), 473–489. doi:10.1016/S0160-2896(02)00175-7
   Web of Science ®Google Scholar
• Coyle, T. R. (2003b). A review of the worst performance rule: Evidence, theory, and alternative hypotheses. Intelligence, 31(6), 567–587. doi:10.1016/S0160-2896(03)00054-0
   Web of Science ®Google Scholar
• Coyle, T. R., & Rindermann, H. (2013). Spearman's Law of Diminishing Returns and national ability. Personality and Individual Differences, 55(4), 406–410. doi:10.1016/j.paid.2013.03.023
   Web of Science ®Google Scholar
• Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning and Verbal Behavior, 19(4), 450–466. doi:10.1016/S0022-5371(80)90312-6
   Google Scholar
• Deary, I. J., Penke, L., & Johnson, W. (2010). The neuroscience of human intelligence differences. Nature Reviews. Neuroscience, 11(3), 201–211. doi:10.1038/nrn2793
   PubMed Web of Science ®Google Scholar
• Derrfuss, J., Brass, M., Neumann, J., & von Cramon, D. Y. (2005). Involvement of the inferior frontal junction in cognitive control: Meta-analyses of switching and Stroop studies. Human Brain Mapping, 25(1), 22–34. doi:10.1002/hbm.20127
   PubMed Web of Science ®Google Scholar
• Detterman, D. K. (1987). Theoretical notions of intelligence and mental fretardation. American Journal of Mental Deficiency, 92, 2–11.
   PubMedGoogle Scholar
• Detterman, D. K. (1994). Theoretical possibilities: The relation of human intelligence to basic cognitive abilities. In D. K. Detterman (Ed.), Current topics in human intelligence volume 4: Theories of intelligence (pp. 85–115). Norwood, NJ: Ablex.
   Google Scholar
• Detterman, D. K. (2000). General intelligence and the definition of phenotypes. In G. R. Bock, J. A. Goode, & K. Webb (Eds.), The nature of intelligence (pp. 136–143). New York, NY: Wiley & Sons.
   Google Scholar
• Detterman, D. K., & Daniel, M. H. (1989). Correlations of mental tests with each other and with cognitive variables are highest for low IQ groups. Intelligence, 13(4), 349–359. doi:10.1016/S0160-2896(89)80007-8
   Web of Science ®Google Scholar
• Dreher, J.-C., & Berman, K. F. (2002). Fractionating the neural substrate of cognitive control processes. Proceedings of the National Academy of Sciences of the United States of America, 99, 14595–14600. doi:10.1073/pnas.222193299
   PubMed Web of Science ®Google Scholar
• Duncan, J. (1995). Attention, intelligence, and the frontal lobes. In M. S. Gazzaniga (Ed.), The cognitive neurosciences (pp. 721–733). Cambridge, MA: MIT Press.
   Google Scholar
• Duncan, J. (2010, February). The multiple-demand (MD) system of the primate brain: Mental programs for intelligent behaviour. Trends in Cognitive Sciences, pp. 172–179. doi:10.1016/j.tics.2010.01.004
   PubMed Web of Science ®Google Scholar
• Duncan, J., Burgess, P., & Emslie, H. (1995). Fluid intelligence after frontal lobe lesions. Neuropsychologia, 33(3), 261–268. doi:10.1016/0028-3932(94)00124-8
   PubMed Web of Science ®Google Scholar
• Duncan, J., Emslie, H., Williams, P., Johnson, R., & Freer, C. (1996). Intelligence and the frontal lobe: The organization of goal-directed behavior. Cognitive Psychology, 30(3), 257–303. doi:10.1006/cogp.1996.0008
   PubMed Web of Science ®Google Scholar
• Duncan, J., & Owen, A. M. (2000). Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends in Neurosciences, 23(10), 475–483. doi:10.1016/S0166-2236(00)01633-7
   PubMed Web of Science ®Google Scholar
• Duncan, J., Parr, A., Woolgar, A., Thompson, R., Bright, P., Cox, S., … Nimmo-Smith, I. (2008). Goal neglect and Spearman's g: Competing parts of a complex task. Journal of Experimental Psychology. General, 137, 131–148. doi:10.1037/0096-3445.137.1.131
   PubMed Web of Science ®Google Scholar
• Duncan, J., Schramm, M., Thompson, R., & Dumontheil, I. (2012). Task rules, working memory, and fluid intelligence. Psychonomic Bulletin & Review, 19(5), 864–870. doi:10.3758/s13423-012-0225-y
   PubMed Web of Science ®Google Scholar
• Duncan, J., Seitz, J., Kolodny, J., Bor, D., Herzog, H., Ahmed, A., … Emslie, H. (2000, July). A neural basis for general intelligence. Science, 289, 457–460.
   PubMed Web of Science ®Google Scholar
• Dutilh, G., Vandekerckhove, J., Forstmann, B. U., Keuleers, E., Brysbaert, M., & Wagenmakers, E.-J. (2012). Testing theories of post-error slowing. Attention, Perception, & Psychophysics, 74, 454–465. doi:10.3758/s13414-011-0243-2
   PubMed Web of Science ®Google Scholar
• Dux, P. E., Ivanoff, J., Asplund, C. L., & Marois, R. (2006). Isolation of a central bottleneck of information processing with time-resolved FMRI. Neuron, 52(6), 1109–1120. doi:10.1016/j.neuron.2006.11.009
   PubMed Web of Science ®Google Scholar
• Edwards, J. R. (2011). The Fallacy of Formative Measurement. Organizational Research Methods, 14(2), 370–388. doi:10.1177/1094428110378369
   Web of Science ®Google Scholar
• Engle, R. W., & Kane, M. J. (2004). Executive attention, working memory capacity, and a two-factor theory of cognitive control. The Psychology of Learning and Motivation, 44, 145–199.
   Web of Science ®Google Scholar
• Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. A. (1999). Working memory, short-term memory, and general fluid intelligence: A latent-variable approach. Journal of Experimental Psychology. General, 128(3), 309–331.
   PubMed Web of Science ®Google Scholar
• Eysenck, H. J. (1987). Thomson's “bonds” or Spearman's “energy”: Sixty years on. Mankind Quarterly, 27, 259–274.
   Google Scholar
• Eysenck, H. J. (1998). Intelligence: A new look. New Brunswick, NJ: Transaction.
   Google Scholar
• Farooqui, A., Mitchell, D., Thompson, R., & Duncan, J. (2012). Hierarchical organization of cognition reflected in distributed frontoparietal activity. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 32(48), 17373–17381. doi:10.1523/JNEUROSCI.0598-12.2012
   PubMed Web of Science ®Google Scholar
• Fedorenko, E., Duncan, J. & Kanwisher, N. (2013). Broad domain generality in focal regions of frontal and parietal cortex. Proceedings of the National Academy of Sciences of the United States of America, 110, 16616–16621. doi:10.1073/pnas.1315235110/-/DCSupplemental.www.pnas.org/cgi/doi/10.1073/pnas.1315235110
   PubMed Web of Science ®Google Scholar
• Flynn, J. R. (1998). Reply to Rushton: A gang of gs overpowers factor analysis. Personality and Individual Differences, 26, 391–393.
   Web of Science ®Google Scholar
• Flynn, J. R. (2007). What Is intelligence?: Beyond the Flynn Effect. Cambridge, UK: Cambridge University Press.
   Google Scholar
• Fukuda, K., Vogel, E., Mayr, U., & Awh, E. (2010). Quantity, not quality: The relationship between fluid intelligence and working memory capacity. Psychonomic Bulletin & Review, 17, 673–679. doi:10.3758/17.5.673
   PubMed Web of Science ®Google Scholar
• Gläscher, 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. doi:10.1073/pnas.0910397107
   PubMed Web of Science ®Google Scholar
• Gold, J. M., Carpenter, C., Randolph, C., Goldberg, T. E., & Weinberger, D. R. (1997). Auditory Working Memory and Wisconsin Card Sorting Test performance in schizophrenia. Archives of General Psychiatry, 54, 159–165. doi:10.1001/archpsyc.1997.01830140071013
   PubMed Web of Science ®Google Scholar
• Gray, J. R., Chabris, C. F., & Braver, T. S. (2003). Neural mechanisms of general fluid intelligence. Nature Neuroscience, 6(3), 316–322. doi:10.1038/nn1014
   PubMed Web of Science ®Google Scholar
• Green, A. E., Fugelsang, J. a, Kraemer, D. J. M., Shamosh, N. A., & Dunbar, K. N. (2006). Frontopolar cortex mediates abstract integration in analogy. Brain Research, 1096(1), 125–137. doi:10.1016/j.brainres.2006.04.024
   PubMed Web of Science ®Google Scholar
• Gustafsson, J.-E. (1984). A unifying model for the structure of intellectual abilities. Intelligence, 8(3), 179–203. doi:10.1016/0160-2896(84)90008-4
   Web of Science ®Google Scholar
• Haier, R. J., Colom, R., Schroeder, D. H., Condon, C. A., Tang, C., Eaves, E., & Head, K. (2009). Intelligence Gray matter and intelligence factors: Is there a neuro-g? Intelligence, 37(2), 136–144. doi:10.1016/j.intell.2008.10.011
   Web of Science ®Google Scholar
• Hampshire, A., Highfield, R. R., Parkin, B. L., & Owen, A. M. (2012). Fractionating human intelligence. Neuron, 76(6), 1225–1237. doi:10.1016/j.neuron.2012.06.022
   PubMed Web of Science ®Google Scholar
• He, Y., & Evans, A. (2010). Graph theoretical modeling of brain connectivity. Current Opinion in Neurology, 23(4), 341–350. doi:10.1097/WCO.0b013e32833aa567
   PubMed Web of Science ®Google Scholar
• Hebb, D. O. (1940). Human behavior after extensive bilateral removal from the frontal lobes. Archives of Neurology And Psychiatry, 44(2), 421. doi:10.1001/archneurpsyc.1940.02280080181011
   Google Scholar
• Heitz, R. P., Redick, T. S., Hambrick, D. Z., Kane, M. J., Conway, A. R. A., & Engle, R. W. (2006). Working memory, executive function, and general fluid intelligence are not the same. Behavioral and Brain Sciences, 29(02), 135–136. doi:10.1017/S0140525×06319036
   Google Scholar
• Henson, R. N. A. (2001). Neural working memory. In J. Andrade (Ed.), Working memory in perspective (pp. 151–173). New York: Psychology Press.
   Google Scholar
• Heuvel, M. P. Van Den, & Pol, H. E. H. (2010). Exploring the brain network: A review on resting-state fMRI functional connectivity. European Neuropsychopharmacology, 20(8), 519–534. doi:10.1016/j.euroneuro.2010.03.008
   PubMed Web of Science ®Google Scholar
• Heuvel, M. van den, & Stam, C. (2009). Efficiency of functional brain networks and intellectual performance. The Journal of Neuroscience, 29, 7619–7624. doi:10.1523/JNEUROSCI.1443-09.2009
   PubMed Web of Science ®Google Scholar
• Horn, J. L. (1989). Cognitive diversity: A framework of learning. In P. L. Ackerman, R. J. Sternberg, & R. Glaser (Eds.), Learning and individual differences (pp. 61–116). New York, NY: W.H. Freeman.
   Google Scholar
• Horn, J. L. (1994). Theory of fluid and crystallized intelligence. In R. Sternberg (Ed.), Encyclopedia of Human Intelligence (pp. 443–451). New York: MacMillan Reference Library.
   Google Scholar
• Howell, R. D., Breivik, E., & Wilcox, J. B. (2007). Reconsidering formative measurement. Psychological Methods, 12(2), 205–218. doi:10.1037/1082-989X.12.2.205
   PubMed Web of Science ®Google Scholar
• Jensen, A. R. (1981). Reaction time and intelligence. In M. Friedman, J. P. Das, & N. O'Connor (Eds.), Intelligence and learning. (pp. 39–50). New York: Plenum.
   Google Scholar
• Jensen, A. R. (1982). Reaction time and psychometric g. In H. J., Eysenck (Ed.), A model for intelligence (pp. 93–132). New York: Springer Verlag.
   Google Scholar
• Jensen, A. R. (1992). The importance of intraindividual variation in reaction time. Personality and Individual Differences, 13(8), 869–881. doi:10.1016/0191-8869(92)90004-9
   Web of Science ®Google Scholar
• Jensen, A. R. (1998). The g factor: The science of mental ability. East (Vol. 17). Westport, CT: Praeger.
   Google Scholar
• Jensen, A. R. (2000). “The g factor” is about variance in mental abilities, not a cognitive theory of mental structure. Reply to Anderson on Jensen on Intelligence-g-Factor. PSYCOLOQUY, 11(041).
   Google Scholar
• Johnson, W., & Bouchard, T. J. (2005). The structure of human intelligence: It is verbal, perceptual, and image rotation (VPR), not fluid and crystallized. Intelligence, 33(4), 393–416. doi:10.1016/j.intell.2004.12.002
   Web of Science ®Google Scholar
• Jonides, J., Reuter-Lorenz, P. A., Smith, E. E., Awh, E., Barnes, L. L., Drain, M., & Al, E. (1996). Verbal and spatial working memory in humans. Psychology of Learning and Motivation, 35, 43–88.
   Web of Science ®Google Scholar
• Juan-Espinosa, M., Cuevas, L., Escorial, S., & García, L. F. (2006). The differentiation hypothesis and the Flynn effect. Psicothema, 18(2), 284–287.
   PubMed Web of Science ®Google Scholar
• 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. doi:10.1017/S0140525×07001185
   PubMed Web of Science ®Google Scholar
• Kan, K.-J., Kievit, R. A., Dolan, C., & van der Maas, H. L. J. (2011). On the interpretation of the CHC factor Gc. Intelligence, 39(5), 292–302. doi:10.1016/j.intell.2011.05.003
   Web of Science ®Google Scholar
• Kane, H. (2000). A secular decline in Spearman's g: Evidence from the WAIS, WAIS-R and WAIS-III. Personality and Individual Differences, 29, 561–566.
   Web of Science ®Google Scholar
• Kane, H. D., Oakland, T. D., & Brand, C. R. (2006). Differentiation at higher levels of cognitive ability: Evidence from the United States. The Journal of Genetic Psychology, 167(3), 327–341. doi:10.3200/GNTP.167.3.327-341
   PubMed Web of Science ®Google Scholar
• Kane, H., & Oakland, T. D. (2000). Secular declines in Spearman's g: Some evidence from the United States. The Journal of Genetic Psychology, 161(3), 337–345. doi:10.1080/00221320009596716
   PubMed Web of Science ®Google Scholar
• Kane, M., & Engle, R. (2000). Working-memory capacity, proactive interference, and divided attention: Limits on long-term memory retrieval. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26(2), 336–358. doi:10.10371/0278-7393.26.2.336
   PubMed Web of Science ®Google Scholar
• Kane, M. J. (2005). Full frontal fluidity. In O. Wilhelm & R. Engle (Eds.), Handbook of understanding and measuring intelligence (pp. 141–165). Thousand Oaks, CA: Sage.
   Google Scholar
• Kane, M. J., Bleckley, M. K., Conway, A. R. A., & Engle, R. W. (2001). A controlled-attention view of working-memory capacity. Journal of Experimental Psychology: General, 130(2), 169–183. doi:10.1037/0096-3445.130.2.169
   PubMed Web of Science ®Google Scholar
• Kane, M. J., Conway, A. R. A., Miura, T. K., & Colflesh, G. J. H. (2007). Working memory, attention control, and the N-back task: A question of construct validity. Journal of Experimental Psychology. Learning, Memory, and Cognition, 33(3), 615–622. doi:10.1037/0278-7393.33.3.615
   PubMed Web of Science ®Google Scholar
• Kane, M. J., Conway, A. R. A., Hambrick, D. Z., & Engle, R. W. (2007). Variation in working memory as variation in executive attention and control. In A. R. A. Conway, C. Jarrold, M. J. Kane, A. Miyake & J. N. Towse (Eds.),Variation in working memory. New York: Oxford University Press.
   Google Scholar
• Kane, M. J., & Engle, R. W. (2002). The role of prefrontal cortex in working-memory capacity, executive attention, and general fluid intelligence: An individual-differences perspective. Psychonomic Bulletin & Review, 9(4), 637–671.
   PubMed Web of Science ®Google Scholar
• Kane, M. J., & Engle, R. W. (2003). Working-memory capacity and the control of attention: The contributions of goal neglect, response competition, and task set to Stroop interference. Journal of Experimental Psychology: General, 132(1), 47–70. doi:10.1037/0096-3445.132.1.47
   PubMed Web of Science ®Google Scholar
• Kane, M. J., Hambrick, D. Z., & Conway, A. R. A. (2005). Working memory capacity and fluid intelligence are strongly related constructs: Comment on Ackerman, Beier, and Boyle (2005). Psychological Bulletin, 131, 66–71; author reply 72–75. doi:10.1037/0033-2909.131.1.66
   PubMed Web of Science ®Google Scholar
• Kane, M. J., Hambrick, D. Z., Tuholski, S. W., Wilhelm, O., Payne, T. W., & Engle, R. W. (2004). The generality of working memory capacity: A latent-variable approach to verbal and visuospatial memory span and reasoning. Journal of Experimental Psychology. General, 133(2), 189–217. doi:10.1037/0096-3445.133.2.189
   PubMed Web of Science ®Google Scholar
• Kaufman, S. B., DeYoung, C. G., Gray, J. R., Brown, J., & Mackintosh, N. (2009). Associative learning predicts intelligence above and beyond working memory and processing speed. Intelligence, 37(4), 374–382. doi:10.1016/j.intell.2009.03.004
   Web of Science ®Google Scholar
• Kievit, R. A., Davis, S. W., Mitchell, D. J., Taylor, J. R., Duncan, J., & Henson, R. N. A. (2014). Distinct aspects of frontal lobe structure mediate age-related differences in fluid intelligence and multitasking. Nature Communications, 5, 56–58. doi:10.1038/ncomms6658
   Web of Science ®Google Scholar
• Kievit, R. A., Rooijen, H. van, Wicherts, J. M., Waldorp, L. J., Kan, K.-J., Scholte, H. S., & Borsboom, D. (2012). Intelligence and the brain: A model-based approach. Cognitive Neuroscience, 3(2), 89–97. doi:10.1080/17588928.2011.628383
   PubMed Web of Science ®Google Scholar
• Kievit, R. A., Scholte, H. S., Waldorp, L. J. & Borsboom, D. (2016). Inter- and intra-individual differences in fluid reasoning show distinct cortical responses. bioRxiv, preprint. doi:10.1101/039412
   Google Scholar
• Koechlin, E., & Hyafil, A. (2007). Anterior Prefrontal Function and the Limits of Human Decision-Making. Science, 318(5850), 594–598.
   PubMed Web of Science ®Google Scholar
• Kovacs, K. (2009). A component process account of the general factor of intelligence. Unpublished PhD thesis. University of Cambridge.
   Google Scholar
• Kovacs, K., Plaisted, K. C., & Mackintosh, N. J. (2006). Difficulties differentiating dissociations. Behavioral and Brain Sciences, 29(02), 138–139. doi:10.1017/S0140525×06349035
   Google Scholar
• Kovacs, K., Rozsa, S., Ko, N., Meszaros, A., Mlinko, R., Kuncz, E., Nagyne Rez, I., Lanyine Engelmayer, A. (2016). Forward and backward digit span measure different cognitive abilities. Manuscript submitted for publication.
   Google Scholar
• Kranzler, J. H. (1992). A test of Larson and Alderton's (1990) worst performance rule of reaction time variability. Personality and Individual Differences, 13(3), 255–261. doi:10.1016/0191-8869(92)90099-B
   Web of Science ®Google Scholar
• Kranzler, J. H., & Jensen, A. R. (1991). The nature of psychometric g: Unitary process or a number of independent processes? Intelligence, 15(4), 397–422. doi:10.1016/0160-2896(91)90003-V
   Web of Science ®Google Scholar
• Kranzler, J. H., & Jensen, A. R. (1993). Psychometric g is still not unitary after eliminating supposed “impurities”: Further comment on Carroll. Intelligence, 17(1), 11–14. doi:10.1016/0160-2896(93)90033-2
   Web of Science ®Google Scholar
• Krijnen, W. P. (2004). Positive loadings and factor correlations from positive covariance matrices. Psychometrika, 69(4), 655–660. doi:10.1007/BF02289861
   Web of Science ®Google Scholar
• Kyllonen, P. C., & Christal, R. E. (1990). Reasoning ability is (little more than) working-memory capacity?! Intelligence, 14, 389–433. doi:10.1016/S0160-2896(05)80012-1
   Web of Science ®Google Scholar
• Larson, G. E., & Alderton, D. L. (1990). Reaction time variability and intelligence: A “worst performance” analysis of individual differences. Intelligence, 14(3), 309–325. doi:10.1016/0160-2896(90)90021-K
   Web of Science ®Google Scholar
• Lehto, J. (1996). Are executive function tests dependent on working memory capacity? The Quarterly Journal of Experimental Psychology A, 49, 29–50. doi:10.1080/027249896392793
   Web of Science ®Google Scholar
• Lehto, J. E., Juujärvi, P., Kooistra, L., & Pulkkinen, L. (2003). Dimensions of executive functioning: Evidence from children. British Journal of Developmental Psychology, 21(1), 59–80. doi:10.1348/026151003321164627
   Web of Science ®Google Scholar
• Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390, 279–281. doi:10.1038/36846
   PubMed Web of Science ®Google Scholar
• Luo, Q., Perry, C., Peng, D., Jin, Z., Xu, D., Ding, G., & Xu, S. (2003). The neural substrate of analogical reasoning: An fMRI study. Brain Research. Cognitive Brain Research, 17(3), 527–534.
   PubMedGoogle Scholar
• Lynn, R., & Cooper, C. (1993). A secular decline in Spearman's g in France. Learning and Individual Differences, 5(1), 43–48.
   Web of Science ®Google Scholar
• Lynn, R., & Cooper, C. (1994). A secular decline in the strength of Spearman'sg in Japan. Current Psychology, 13(1), 3–9.
   Web of Science ®Google Scholar
• MacDonald, A. W. (2000). Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science, 288(5472), 1835–1838. doi:10.1126/science.288.5472.1835
   PubMed Web of Science ®Google Scholar
• Mackintosh, N., & Bennett, E. (2002). IT, IQ and perceptual speed. Personality and Individual Differences, 32(4), 685–693. doi:10.1016/S0191-8869(01)00069-1
   Web of Science ®Google Scholar
• Mackintosh, N. J. (1998). IQ and human intelligence (first edition). Oxford, UK: Oxford University Press.
   Google Scholar
• Mackintosh, N. J. (2008). Sex differences and IQ. Journal of Biosocial Science, 28(04), 558–571. doi:10.1017/S0021932000022586
   Google Scholar
• Mackintosh, N. J. (2011a). History of theories and measurement of intelligence. In R. Sternberg & S. Kaufman (Eds.), Cambridge handbook of intelligence (pp. 3–19). New York, NY: Cambridge University Press.
   Google Scholar
• Mackintosh, N. J. (2011b). IQ and human intelligence. Oxford, UK: Oxford University Press.
   Google Scholar
• Major, J. T., Johnson, W., & Bouchard, T. J. (2011). The dependability of the general factor of intelligence: Why small, single-factor models do not adequately represent g. Intelligence, 39(5), 418–433. doi:10.1016/j.intell.2011.07.002
   Web of Science ®Google Scholar
• Marois, R., & Ivanoff, J. (2005). Capacity limits of information processing in the brain. Trends in Cognitive Sciences, 9(6), 296–305. doi:10.1016/j.tics.2005.04.010
   PubMed Web of Science ®Google Scholar
• Matzke, D., Dolan, C. V., & Molenaar, D. (2010). The issue of power in the identification of “g” with lower-order factors. Intelligence, 38(3), 336–344. doi:10.1016/j.intell.2010.02.001
   Web of Science ®Google Scholar
• Maxwell, A. E. (1972). Factor analysis: Thomson's sampling theory recalled. British Journal of Mathematical and Statistical Psychology, 25(1), 1–21. doi:10.1111/j.2044-8317.1972.tb00474.x
   PubMed Web of Science ®Google Scholar
• McCabe, D. P., Roediger, H. L., McDaniel, M. A., Balota, D. A., & Hambrick, D. Z. (2010). The relationship between working memory capacity and executive functioning: Evidence for a common executive attention construct. Neuropsychology, 24(2), 222–243. doi:10.1037/a0017619
   PubMed Web of Science ®Google Scholar
• McFarland, D. J. (2012). A single g factor is not necessary to simulate positive correlations between cognitive tests. Journal of Clinical and Experimental Neuropsychology, 34(4), 378–384. doi:10.1080/13803395.2011.645018
   PubMed Web of Science ®Google Scholar
• McGrew, K. S. (2009). CHC theory and the human cognitive abilities project: Standing on the shoulders of the giants of psychometric intelligence research. Intelligence, 37(1), 1–10. doi:10.1016/j.intell.2008.08.004
   Web of Science ®Google Scholar
• Miele, F. (2002). Intelligence, race, and genetics. Conversations with Arthur R. Jensen. Boulder, CO: Westview Press.
   Google Scholar
• Miller, B. T., & D'Esposito, M. (2005). Searching for “the top” in top-down control. Neuron, 48(4), 535–538. doi:10.1016/j.neuron.2005.11.002
   PubMed Web of Science ®Google Scholar
• Miller, E. K. (2000). The prefrontal cortex and cognitive control. Nature Reviews. Neuroscience, 1(1), 59–65. doi:10.1038/35036228
   PubMed Web of Science ®Google Scholar
• Miller, E. K., & Cohen, J. D. (2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167–202. doi:10.1146/annurev.neuro.24.1.167
   PubMed Web of Science ®Google Scholar
• Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The unity and diversity of executive functions and their contributions to complex “Frontal Lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49–100. doi:10.1006/cogp.1999.0734
   PubMed Web of Science ®Google Scholar
• Miyake, A., Friedman, N. P., Rettinger, D. A., Shah, P., & Hegarty, M. (2001). How are visuospatial working memory, executive functioning, and spatial abilities related? A latent-variable analysis. Journal of Experimental Psychology: General, 130, 621–640. doi:10.1037/0096-3445.130.4.621
   Web of Science ®Google Scholar
• Molenaar, D., Dolan, C. V., Wicherts, J. M., & van der Maas, H. L. J. (2010). Modeling differentiation of cognitive abilities within the higher-order factor model using moderated factor analysis. Intelligence, 38(6), 611–624. doi:10.1016/j.intell.2010.09.002
   Web of Science ®Google Scholar
• Molenaar, P. C. M., & Campbell, C. G. (2009). The New Person-Specific Paradigm in Psychology. Current Directions in Psychological Science, 18(2), 112–117. doi:10.1111/j.1467-8721.2009.01619.x
   Web of Science ®Google Scholar
• Mueller, S., Wang, D., Fox, M. D., Yeo, B. T. T., Sepulcre, J., Sabuncu, M. R., … Liu, H. (2013). Individual variability in functional connectivity architecture of the human brain. Neuron, 77(3), 586–595. doi:10.1016/j.neuron.2012.12.028
   PubMed Web of Science ®Google Scholar
• Mukunda, K. V., & Hall, V. C. (1992). Does performance on memory for order correlate with performance on standardized measures of ability? A meta-analysis. Intelligence, 16(1), 81–97. doi:10.1016/0160-2896(92)90026-N
   Web of Science ®Google Scholar
• Must, O., Must, A., & Raudik, V. (2003). The secular rise in IQs: In Estonia, the Flynn effect is not a Jensen effect. Intelligence, 31(5), 461–471. doi:10.1016/S0160-2896(03)00013-8
   Web of Science ®Google Scholar
• Négyessy, L., Bányai, M., Nepusz, T., & Bazsó, F. (2012). What makes the prefrontal cortex so appealing in the era of brain imaging? A network analytical perspective. Acta Biologica Hungarica, 63, 38–53. doi:10.1556/ABiol.63.2012.Suppl.1.5
   PubMed Web of Science ®Google Scholar
• Niendam, T., Laird, A., & Ray, K. (2012). Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions. Cognitive, Affective, & Behavioral Neuroscience, 12(2), 241–268. doi:10.3758/s13415-011-0083-5.Meta-analytic
   PubMed Web of Science ®Google Scholar
• Oberauer, K. (2004). The measurement of working memory capacity. In O. Wilhelm & R. W. Engle (Eds.), Handbook of understanding and measuring intelligence (pp. 393–408). London, UK: Sage.
   Google Scholar
• Oberauer, K., Schulze, R., Wilhelm, O., & Süss, H.-M. (2005). Working memory and intelligence—Their correlation and their relation: Comment on Ackerman, Beier, and Boyle (2005). Psychological Bulletin, 131, 61–65; author reply 72–75. doi:10.1037/0033-2909.131.1.61
   PubMed Web of Science ®Google Scholar
• Oberauer, K., Süß, H.-M., Wilhelm, O., & Wittman, W. W. (2003). The multiple faces of working memory: Storage, processing, supervision, and coordination. Intelligence, 60, 167–193. doi:10.1016/S0160-2896(02)00115-0
   Web of Science ®Google Scholar
• Parkin, A. (1998). The central executive does not exist. Journal of the International Neuropsychological Society, 4, 518–22. doi:10.1017/s1355617798005128
   PubMed Web of Science ®Google Scholar
• Penke, L., Maniega, S. M., Bastin, M. E., Valdés Hernández M. C., Murray, C., Royle, N. A., … Deary, I. J. (2012). Brain white matter tract integrity as a neural foundation for general intelligence. Molecular Psychiatry, 17(10), 1026–1030. doi:10.1038/mp.2012.66
   PubMed Web of Science ®Google Scholar
• Pollack, I., Johnson, L. B., & Knaff, P. R. (1959). Running memory span. Journal of Experimental Psychology, 57, 137–146. doi:10.1037/h0046137
   PubMedGoogle Scholar
• Prabhakaran, V., Smith, J. A, Desmond, J. E., Glover, G. H., & Gabrieli, J. D. (1997). Neural substrates of fluid reasoning: An fMRI study of neocortical activation during performance of the Raven's Progressive Matrices Test. Cognitive Psychology, 33(1), 43–63. doi:10.1006/cogp.1997.0659
   PubMed Web of Science ®Google Scholar
• Rabaglia, C., Marcus, G., & Lane, S. (2011). What can individual differences tell us about the specialization of function? Cognitive Neuropsychology, 28, 37–41.
   Web of Science ®Google Scholar
• Rabbitt, P. M. A. (1997). Introduction: Methodologies and models in the study of executive function. In P. M. A. Rabbitt (Ed.), Methodology of frontal and executive function (pp. 1–38). East Sussex, UK: Psychology Press.
   Google Scholar
• Reckase, M. D. (2009). Multidimensional item response theory. New York, NY: Springer-Verlag.
   Google Scholar
• Robbins, T. W. (1996). Dissociating executive functions of the prefrontal cortex. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 351, 1463–1470; discussion 1470–1471. doi:10.1098/rstb.1996.013
   PubMed Web of Science ®Google Scholar
• Román, F. J., Abad, F. J., Escorial, S., Burgaleta, M., Martínez, K., Alvarez-Linera, J., … Colom, R. (2014). Reversed hierarchy in the brain for general and specific cognitive abilities: A morphometric analysis. Human Brain Mapping, 35, 3805–3818. doi:10.1002/hbm.22438
   Web of Science ®Google Scholar
• Rushton, J. (1999). Secular gains in IQ not related to the g factor and inbreeding depression Ð unlike Black-White differences: A reply to Flynn. Personality and Individual Differences, 26, 381–389.
   Web of Science ®Google Scholar
• Salthouse, T. A., Atkinson, T. M., & Berish, D. E. (2003). Executive functioning as a potential mediator of age-related cognitive decline in normal adults. Journal of Experimental Psychology. General, 132(4), 566–594. doi:10.1037/0096-3445.132.4.566
   PubMed Web of Science ®Google Scholar
• Santarnecchi, E., & Galli, G. (2014). Efficiency of weak brain connections support general cognitive functioning. Human Brain, 35, 4566–4582. doi:10.1002/hbm.22495
   Google Scholar
• Shipstead, Z., Redick, T. S., Hicks, K. L., & Engle, R. W. (2012). The scope and control of attention as separate aspects of working memory. Memory, 20, 608–662. doi:10.1080/09658211.2012.691519
   PubMed Web of Science ®Google Scholar
• Sohn, M. H., Ursu, S., Anderson, J. R., Stenger, V. A., & Carter, C. S. (2000). The role of prefrontal cortex and posterior parietal cortex in task switching. Proceedings of the National Academy of Sciences of the United States of America, 97(24), 13448–13453. doi:10.1073/pnas.240460497
   PubMed Web of Science ®Google Scholar
• Song, M., Zhou, Y., Li, J., Liu, Y., Tian, L., Yu, C., & Jiang, T. (2008). Brain spontaneous functional connectivity and intelligence. Neuroimage, 41, 1168–1176. doi:10.1016/j.neuroimage.2008.02.036
   PubMed Web of Science ®Google Scholar
• Spearman, C. (1904). “General intelligence,” Objectively determined and measured. The American Journal of Psychology, 15(2), 201–292. doi:10.2307/1412107
   Google Scholar
• Spearman, C. (1927). The abilities of Man: Their nature and measurement. New York: Macmillan.
   Google Scholar
• Sporns, O. (2002). Network analysis, complexity, and brain function. Complexity, 8(1), 56–60.
   Google Scholar
• Sporns, O., Honey, C., & Kötter, R. (2007). Identification and classification of hubs in brain networks. PloS One, 10. doi:10.1371/Citation
   Google Scholar
• Spreng, R. N., Sepulcre, J., Turner, G. R., Stevens, W. D., & Schacter, D. L. (2013). Intrinsic architecture underlying the relations among the default, dorsal attention, and frontoparietal control networks of the human brain. Journal of Cognitive Neuroscience, 25(1), 74–86. doi:10.1162/jocn_a_00281
   PubMed Web of Science ®Google Scholar
• St Clair-Thompson, H. L., & Gathercole, S. E. (2006). Executive functions and achievements in school: Shifting, updating, inhibition, and working memory. Quarterly Journal of Experimental Psychology, 59(4), 745–759. doi:10.1080/17470210500162854
   PubMed Web of Science ®Google Scholar
• Stuss, D. T., & Alexander, M. P. (2000). Executive functions and the frontal lobes: A conceptual view. Psychological Research, 63(3–4), 289–298.
   PubMed Web of Science ®Google Scholar
• Süß, H. M., Oberauer, K., Wittmann, W. W., Wilhelm, O., & Schulze, R. (2002). Working-memory capacity explains reasoning ability—And a little bit more. Intelligence, 30, 261–288. doi:10.1016/S0160-2896(01)00100-3
   Web of Science ®Google Scholar
• Thomson, G. H. (1916). A hierarchy without a general factor. British Journal of Psychology, 1904-1920, 8, 271–281. doi:10.1111/j.2044-8295.1916.tb00133.x
   Google Scholar
• Thurstone, L. L. (1938). Primary mental abilities. Chicago, IL: University of Chicago Press.
   Google Scholar
• Toga, A., Clark, K., & Thompson, P. (2012). Mapping the human connectome. Neurosurgery, 71(1), 1–5.
   PubMed Web of Science ®Google Scholar
• Tombu, M. N., Asplund, C. L., Dux, P. E., Godwin, D., Martin, J. W., & Marois, R. (2011). A unified attentional bottleneck in the human brain. Proceedings of the National Academy of Sciences of the United States of America, 108(33), 13426–13431. doi:10.1073/pnas.1103583108
   PubMed Web of Science ®Google Scholar
• Turner, M. L., & Engle, R. W. (1989). Is working memory capacity task dependent? Journal of Memory and Language, 28(2), 127–154. doi:10.1016/0749-596X(89)90040-5
   Web of Science ®Google Scholar
• Unsworth, N., & Engle, R. W. (2006). Simple and complex memory spans and their relation to fluid abilities: Evidence from list-length effects. Journal of Memory and Language, 54, 68–80. doi:10.1016/j.jml.2005.06.003
   Web of Science ®Google Scholar
• Unsworth, N., & Engle, R. W. (2007). The nature of individual differences in working memory capacity: Active maintenance in primary memory and controlled search from secondary memory. Psychological Review, 114(1), 104–132. doi:10.1037/0033-295X.114.1.104
   PubMed Web of Science ®Google Scholar
• van der Maas, H. L. J., Dolan, C. V., Grasman, R. P. P. P., Wicherts, J. M., Huizenga, H. M., & Raijmakers, M. E. J. (2006). A dynamical model of general intelligence: The positive manifold of intelligence by mutualism. Psychological Review, 113(4), 842–861. doi:10.1037/0033-295X.113.4.842
   PubMed Web of Science ®Google Scholar
• van der Maas, H. L. J., Kan, K.-J., & Borsboom, D. (2014). intelligence is what the intelligence test measures. Seriously. Journal of Intelligence, 2(1), 12–15. doi:10.3390/jintelligence2010012
   Google Scholar
• Vicari, S., Bellucci, S., & Carlesimo, G. A. (2007). Visual and spatial working memory dissociation: Evidence from Williams syndrome. Developmental Medicine & Child Neurology, 45(4), 269–273. doi:10.1111/j.1469-8749.2003.tb00342.x
   Google Scholar
• Vincent, J. L., Kahn, I., Snyder, A. Z., Raichle, M. E., & Buckner, R. L. (2008). Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. Journal of Neurophysiology, 100(6), 3328–3342. doi:10.1152/jn.90355.2008
   PubMed Web of Science ®Google Scholar
• Voelkle, M. C., Brose, A., Schmiedek, F., & Lindenberger, U. (2014). Toward a unified framework for the study of between-person and within-person structures: Building a bridge between two research paradigms. Multivariate Behavioral Research, 49(3), 193–213. doi:10.1080/00273171.2014.889593
   PubMed Web of Science ®Google Scholar
• Volle, E., Gilbert, S. J., Benoit, R. G., & Burgess, P. W. (2010). Specialization of the rostral prefrontal cortex for distinct analogy processes. Cerebral Cortex (New York, N.Y. : 1991), 20(11), 2647–2659. doi:10.1093/cercor/bhq012
   PubMed Web of Science ®Google Scholar
• Wager, T. O. R. D., & Smith, E. E. (2003). Neuroimaging studies of working memory: A meta-analysis. Cognitive, Affective, & Behavioral Neuroscience, 3(4), 255–274.
   PubMed Web of Science ®Google Scholar
• Waltz, J. A., Knowlton, B. J., Holyoak, K. J., Boone, K. B., Mishkin, F. S., de Menezes Santos, M., … Miller, B. L. (1999). A System for Relational Reasoning in Human Prefrontal Cortex. Psychological Science, 10(2), 119–125. doi:10.1111/1467-9280.00118
   Web of Science ®Google Scholar
• Wang, P. P., & Bellugi, U. (1994). Evidence from two genetic syndromes for a dissociation between verbal and visual-spatial short-term memory. Journal of Clinical and Experimental Neuropsychology, 16(2), 317–322. doi:10.1080/01688639408402641
   PubMed Web of Science ®Google Scholar
• Weinstein, S., & Teuber, H.-L. (1957). Effects of penetrating brain injury on intelligence test scores. Science, 125, 1036–1037. doi:10.1126/science.125.3256.1036
   PubMed Web of Science ®Google Scholar
• Wendelken, C., Nakhabenko, D., Donohue, S. E., Carter, C. S., & Bunge, S. A. (2008). “Brain is to thought as stomach is to ??”: Investigating the role of rostrolateral prefrontal cortex in relational reasoning. Journal of Cognitive Neuroscience, 20(4), 682–693. doi:10.1162/jocn.2008.20055
   PubMed Web of Science ®Google Scholar
• Wharton, C. M., Grafman, J., Flitman, S. S., Hansen, E. K., Brauner, J., Marks, A., & Honda, M. (2000). Toward neuroanatomical models of analogy: A positron emission tomography study of analogical mapping. Cognitive Psychology, 40(3), 173–197. doi:10.1006/cogp.1999.0726
   PubMed Web of Science ®Google Scholar
• Wiley, J., & Jarosz, A. (2011). New rule use drives the relation between working memory capacity and Raven's Advanced Progressive Matrices. Journal of Experimental Psychology. Learning, Memory, and Cognition, 37(1), 256–263. doi:10.1037/a0021613
   PubMed Web of Science ®Google Scholar
• Woolgar, A., Parr, A., Cusack, R., Thompson, R., Nimmo-Smith, I., Torralva, T., … Duncan, J. (2010). Fluid intelligence loss linked to restricted regions of damage within frontal and parietal cortex. Proceedings of the National Academy of Sciences of the United States of America, 107(33), 14899–14902. doi:10.1073/pnas.1007928107
   PubMed Web of Science ®Google Scholar