Network Neuroscience Theory of Human Intelligence

Trends in Cognitive Sciences

Volumn 22, Issue 1, 2018, Pages 8-20

  Barbey, Aron K ^a,b  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b University of Illinois at Urbana Champaign   (United States)

Author keywords

brain network dynamics; crystallized intelligence; fluid intelligence; general intelligence; intrinsic connectivity networks; small world network

Indexed keywords

DISTRIBUTED COMPUTER SYSTEMS; DYNAMICS; NETWORK ARCHITECTURE; PROBLEM SOLVING; SMALL-WORLD NETWORKS; TOPOLOGY;

BRAIN NETWORKS; COGNITIVE FLEXIBILITY; COMMUNITY STRUCTURES; CRYSTALLIZED INTELLIGENCE; DYNAMIC REORGANIZATION; GENERAL INTELLIGENCE; INDIVIDUAL DIFFERENCES; INFORMATION EXCHANGES;

NEUROLOGY;

BRAIN; COMMUNITY STRUCTURE; CRYSTALLIZATION; HUMAN; HUMAN EXPERIMENT; INFORMATION PROCESSING; INTELLIGENCE; LIQUID; NEUROSCIENCE; PROBLEM SOLVING; BIOLOGICAL MODEL; PHYSIOLOGY; PSYCHOLOGICAL MODEL;

BRAIN; HUMANS; INTELLIGENCE; MODELS, NEUROLOGICAL; MODELS, PSYCHOLOGICAL; NEUROSCIENCES;

EID: 85034584135     PISSN: 13646613     EISSN: 1879307X     Source Type: Journal    
DOI: 10.1016/j.tics.2017.10.001     Document Type: Review

References (105)

1. Spearman, C., ‘General intelligence’ objectively determined and measured. Am. J. Psychol. 15 (1904), 201–292.
2. Spearman, C., The abilities of man. Science, 68, 1928, 38.
3. Carroll, J.B., Human Cognitive Abilities: A Survey of Factor-Analytic Studies. 1993, Cambridge University Press.
4. McGrew, K.S., Wendling, B.J., Cattell–Horn–Carroll cognitive-achievement relations: what we have learned from the past 20 years of research. Psychol. Sch. 47 (2010), 651–675.
5. Cattell, R.B., Abilities: Their Structure, Growth, and Action. 1971, Houghton Mifflin.
6. Deary, I.J., The stability of intelligence from childhood to old age. Curr. Dir. Psychol. Sci. 23 (2014), 239–245.
7. Sherrington, C.S., Man on His Nature. 1940, The University Press.
8. Bassett, D.S., Sporns, O., Network neuroscience. Nat. Neurosci. 20 (2017), 353–364.
9. Fornito, A., et al. Fundamentals of Brain Network Analysis. 2016, Academic Press.
10. Jensen, A.R., Spearman's g: links between psychometrics and biology. Ann. N. Y. Acad. Sci. 702 (1993), 103–129.
11. Thomson, G.H., A hierarchy without a general factor. Br. J. Psychol. 8 (1916), 271–281.
12. Thomson, G.H., The hierarchy of abilities. Br. J. Psychol. 9 (1919), 337–344.
13. Thomson, G.H., The factorial analysis of human abilities. Human Factor 9 (1935), 180–185.
14. Deary, I.J., et al. A conversation between Charles Spearman, Godfrey Thomson, and Edward L. Thorndike: The International Examinations Inquiry Meetings 1931–1938 (vol 11, pg 122, 2008). Hist. Psychol., 11, 2008 163–163.
15. Bartholomew, D.J., et al. Sir Godfrey Thomson: a statistical pioneer. J. R. Stat. Soc. Ser. A Stat. Soc. 172 (2009), 467–482.
16. van der Maas, H.L., et al. A dynamical model of general intelligence: the positive manifold of intelligence by mutualism. Psychol. Rev. 113 (2006), 842–861.
17. Jensen, A.R., The G Factor: The Science of Mental Ability. 1998, Praeger.
18. Pinker, S., How could a child use verb syntax to learn verb semantics. Lingua 92 (1994), 377–410.
19. Ramón y Cajal, S., et al. Texture of the Nervous System of Man and the Vertebrates. 1999, Springer.
20. Bullmore, E., Sporns, O., The economy of brain network organization. Nat. Rev. Neurosci. 13 (2012), 336–349.
21. Latora, V., Marchiori, M., Efficient behavior of small-world networks. Phys. Rev. Lett., 87, 2001 198701.
22. Barbey, A.K., et al. Network topology and dynamics in traumatic brain injury. Curr. Opin. Behav. Sci. 4 (2015), 92–102.
23. Simon, H., The architecture of complexity. Proc. Am. Philos. Soc. 106 (1962), 467–482.
24. Bassett, D.S., Gazzaniga, M.S., Understanding complexity in the human brain. Trends Cogn. Sci. 15 (2011), 200–209.
25. Deco, G., et al. Rethinking segregation and integration: contributions of whole-brain modelling. Nat. Rev. Neurosci. 16 (2015), 430–439.
26. Bassett, D.S., Bullmore, E., Small-world brain networks. Neuroscientist 12 (2006), 512–523.
27. Bassett, D.S., Bullmore, E.T., Small-world brain networks revisited. Neuroscientist 23 (2017), 499–516.
28. Watts, D.J., Strogatz, S.H., Collective dynamics of ‘small-world’ networks. Nature 393 (1998), 440–442.
29. Sporns, O., et al. Theoretical neuroanatomy: relating anatomical and functional connectivity in graphs and cortical connection matrices. Cereb. Cortex 10 (2000), 127–141.
30. Sporns, O., et al. Connectivity and complexity: the relationship between neuroanatomy and brain dynamics. Neural Netw. 13 (2000), 909–922.
31. Robinson, P.A., et al. Dynamical reconnection and stability constraints on cortical network architecture. Phys. Rev. Lett., 103, 2009 108104.
32. He, Y., et al. Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. Cereb. Cortex 17 (2007), 2407–2419.
33. Eguiluz, V.M., et al. Scale-free brain functional networks. Phys. Rev. Lett., 94, 2005 018102.
34. Achard, S., et al. A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. J. Neurosci. 26 (2006), 63–72.
35. Achard, S., Bullmore, E., Efficiency and cost of economical brain functional networks. PLoS Comput. Biol., 3, 2007, e17.
36. Hagmann, P., et al. Mapping human whole-brain structural networks with diffusion MRI. PLoS One, 2, 2007, e597.
37. van den Heuvel, M.P., et al. Efficiency of functional brain networks and intellectual performance. J. Neurosci. 29 (2009), 7619–7624.
38. Cole, M.W., et al. Global connectivity of prefrontal cortex predicts cognitive control and intelligence. J. Neurosci. 32 (2012), 8988–8999.
39. Stam, C.J., et al. Small-world networks and functional connectivity in Alzheimer's disease. Cereb. Cortex 17 (2007), 92–99.
40. Stam, C.J., Modern network science of neurological disorders. Nat. Rev. Neurosci. 15 (2014), 683–695.
41. Zuo, X.N., et al. Human connectomics across the life span. Trends Cogn. Sci. 21 (2017), 32–45.
42. Bassett, D.S., Bullmore, E.T., Human brain networks in health and disease. Curr. Opin. Neurol. 22 (2009), 340–347.
43. Biswal, B., et al. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 34 (1995), 537–541.
44. Buckner, R.L., et al. Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer's disease. J. Neurosci. 29 (2009), 1860–1873.
45. Bullmore, E., Sporns, O., Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10 (2009), 186–198.
46. Power, J.D., et al. Functional network organization of the human brain. Neuron 72 (2011), 665–678.
47. Sporns, O., et al. Organization, development and function of complex brain networks. Trends Cogn. Sci. 8 (2004), 418–425.
48. van den Heuvel, M.P., et al. Functionally linked resting-state networks reflect the underlying structural connectivity architecture of the human brain. Hum. Brain Mapp. 30 (2009), 3127–3141.
49. Power, J.D., Petersen, S.E., Control-related systems in the human brain. Curr. Opin. Neurobiol. 23 (2013), 223–228.
50. Smith, S.M., et al. Resting-state fMRI in the Human Connectome Project. Neuroimage 80 (2013), 144–168.
51. Park, H.J., Friston, K., Structural and functional brain networks: from connections to cognition. Science, 342, 2013 1238411.
52. Byrge, L., et al. Developmental process emerges from extended brain-body-behavior networks. Trends Cogn. Sci. 18 (2014), 395–403.
53. Shine, J.M., et al. The dynamics of functional brain networks: integrated network states during cognitive task performance. Neuron 92 (2016), 544–554.
54. Meunier, D., et al. Modular and hierarchically modular organization of brain networks. Front. Neurosci., 4, 2010, 200.
55. Betzel, R.F., Bassett, D.S., Multi-scale brain networks. Neuroimage, 2016, 10.1016/j.neuroimage.2016.11.006 Published online November 11, 2016.
56. Power, J.D., et al. Evidence for hubs in human functional brain networks. Neuron 79 (2013), 798–813.
57. van den Heuvel, M.P., Sporns, O., Network hubs in the human brain. Trends Cogn. Sci. 17 (2013), 683–696.
58. Guimera, R., Nunes Amaral, L.A., Functional cartography of complex metabolic networks. Nature 433 (2005), 895–900.
59. Bertolero, M.A., et al. The modular and integrative functional architecture of the human brain. Proc. Natl. Acad. Sci. U. S. A. 112 (2015), E6798–E6807.
60. van den Heuvel, M.P., Sporns, O., Rich-club organization of the human connectome. J. Neurosci. 31 (2011), 15775–15786.
61. Gu, S., et al. Controllability of structural brain networks. Nat. Commun., 6, 2015, 8414.
62. Bassett, D.S., et al. Dynamic reconfiguration of human brain networks during learning. Proc. Natl. Acad. Sci. U. S. A. 108 (2011), 7641–7646.
63. Buchel, C., et al. The predictive value of changes in effective connectivity for human learning. Science 283 (1999), 1538–1541.
64. Pascual-Leone, A., et al. The plastic human brain cortex. Annu. Rev. Neurosci. 28 (2005), 377–401.
65. Betzel, R.F., et al. Optimally controlling the human connectome: the role of network topology. Sci. Rep., 6, 2016, 30770.
66. Christoff, K., et al. Mind-wandering as spontaneous thought: a dynamic framework. Nat. Rev. Neurosci. 17 (2016), 718–731.
67. Kucyi, A., Just a thought: how mind-wandering is represented in dynamic brain connectivity. Neuroimage, 2017, 10.1016/j.neuroimage.2017.07.001 Published online July 3, 2017.
68. Wirth, M., et al. Semantic memory involvement in the default mode network: a functional neuroimaging study using independent component analysis. Neuroimage 54 (2011), 3057–3066.
69. St Jacques, P.L., et al. Dynamic neural networks supporting memory retrieval. Neuroimage 57 (2011), 608–616.
70. Schneidman, E., et al. Weak pairwise correlations imply strongly correlated network states in a neural population. Nature 440 (2006), 1007–1012.
71. Granovetter, M.S., The strength of weak ties. Am. J. Sociol. 78 (1973), 1360–1380.
72. Gallos, L.K., et al. A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks. Proc. Natl. Acad. Sci. U. S. A. 109 (2012), 2825–2830.
73. Dosenbach, N.U., et al. A dual-networks architecture of top-down control. Trends Cogn. Sci. 12 (2008), 99–105.
74. Santarnecchi, E., et al. Efficiency of weak brain connections support general cognitive functioning. Hum. Brain Mapp. 35 (2014), 4566–4582.
75. Barbey, A.K., et al. An integrative architecture for general intelligence and executive function revealed by lesion mapping. Brain 135 (2012), 1154–1164.
76. Glascher, J., et al. Distributed neural system for general intelligence revealed by lesion mapping. Proc. Natl. Acad. Sci. U. S. A. 107 (2010), 4705–4709.
77. Jung, R.E., Haier, R.J., The parieto-frontal integration theory (P-FIT) of intelligence: converging neuroimaging evidence. Behav. Brain Sci. 30 (2007), 135–154.
78. Barbey, A.K., et al. Architecture of fluid intelligence and working memory revealed by lesion mapping. Brain Struct. Funct. 219 (2014), 485–494.
79. Barbey, A.K., et al. Architecture of cognitive flexibility revealed by lesion mapping. Neuroimage 82 (2013), 547–554.
80. Duncan, J., et al. Complexity and compositionality in fluid intelligence. Proc. Natl. Acad. Sci. U. S. A. 114 (2017), 5295–5299.
81. Duncan, J., et al. A neural basis for general intelligence. Science 289 (2000), 457–460.
82. Duncan, J., The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour. Trends Cogn. Sci. 14 (2010), 172–179.
83. Kovacs, K., Conway, A.R.A., Process overlap theory: a unified account of the general factor of intelligence. Psychol. Inq. 27 (2016), 151–177.
84. Beggs, J.M., The criticality hypothesis: how local cortical networks might optimize information processing. Philos. Trans. A Math. Phys. Eng. Sci. 366 (2008), 329–343.
85. Petermann, T., et al. Spontaneous cortical activity in awake monkeys composed of neuronal avalanches. Proc. Natl. Acad. Sci. U. S. A. 106 (2009), 15921–15926.
86. Betzel, R.F. et al. (2016) A positive mood, a flexible brain. arXiv. Published online January 28, 2016. https://arxiv.org/abs/1601.07881.
87. Mattar, M.G., et al. The flexible brain. Brain 139 (2016), 2110–2112.
88. Zalesky, A., et al. Time-resolved resting-state brain networks. Proc. Natl. Acad. Sci. U. S. A. 111 (2014), 10341–10346.
89. Zhang, J., et al. Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders. Brain 139 (2016), 2307–2321.
90. Hampshire, A., et al. Fractionating human intelligence. Neuron 76 (2012), 1225–1237.
91. Cole, M.W., et al. Multi-task connectivity reveals flexible hubs for adaptive task control. Nat. Neurosci. 16 (2013), 1348–1355.
92. Braun, U., et al. Dynamic reconfiguration of frontal brain networks during executive cognition in humans. Proc. Natl. Acad. Sci. U. S. A. 112 (2015), 11678–11683.
93. Salthouse, T., Consequences of age-related cognitive declines. Annu. Rev. Psychol. 63 (2012), 201–226.
94. Flynn, J.R., The mean IQ of Americans – massive gains 1932 to 1978. Psychol. Bull. 95 (1984), 29–51.
95. Flynn, J.R., Massive IQ gains in 14 nations – what IQ tests really measure. Psychol. Bull. 101 (1987), 171–191.
96. Flynn, J.R., What is Intelligence? Beyond the Flynn Effect. 2007, Cambridge University Press.
97. Yankner, B.A., et al. The aging brain. Annu. Rev. Pathol. 3 (2008), 41–66.
98. Zamroziewicz, M.K., Barbey, A.K., Nutritional cognitive neuroscience: innovations for healthy brain aging. Front. Neurosci., 10, 2016, 240.
99. Zamroziewicz, M.K., et al. Nutritional status, brain network organization, and general intelligence. Neuroimage 161 (2017), 241–250.
100. Chai, L.R., et al. Evolution of brain network dynamics in neurodevelopment. Netw. Neurosci. 1 (2016), 14–30.
101. Hampshire, A., et al. Network mechanisms of intentional learning. Neuroimage 127 (2016), 123–134.
102. Barbey, A.K., et al. Dorsolateral prefrontal contributions to human intelligence. Neuropsychologia 51 (2013), 1361–1369.
103. Duncan, J., Owen, A.M., Common regions of the human frontal lobe recruited by diverse cognitive demands. Trends Neurosci. 23 (2000), 475–483.
104. Kitzbichler, M.G., et al. Cognitive effort drives workspace configuration of human brain functional networks. J. Neurosci. 31 (2011), 8259–8270.
105. Dehaene, S., et al. A neuronal model of a global workspace in effortful cognitive tasks. Proc. Natl. Acad. Sci. U. S. A. 95 (1998), 14529–14534.