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General intelligence is associated with working memory-related brain activity: new evidence from a large sample study

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Abstract

Psychometric intelligence is closely related to working memory capacity. Here we aim to determine the associations of neural activation patterns during the N-back working memory paradigm with psychometric intelligence and working memory performance. We solved the statistical problems of previous studies using (1) a large cohort of 1235 young adults and (2) robust voxel-by-voxel permutation-based statistics at the whole-brain level. Many of the significant correlations were weak, and our findings were not consistent with those of previous studies. We observed that many of the significant correlations involved brain areas in the periphery or boundaries between the task-positive network (TPN) and task-negative network (TNN), suggesting that the expansion of the TPN or TNN is associated with greater cognitive ability. Lower activity in TPN and less task-induced deactivation (TID) in TNN were associated with greater cognitive ability. These findings indicate that subjects with greater cognitive ability have a lower brain response to task demand, consistent with the notion that TID in TNN reflects cognitive demand but partly inconsistent with the prevailing neural efficiency theory. One exception was the pre-supplementary motor area, which plays a key role in cognitive control and sequential processing. In this area, intelligent subjects demonstrated greater activity related to working memory, suggesting that the pre-supplementary motor area plays a unique role in the execution of working memory tasks in intelligent subjects.

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References

  • Baddeley A (2003) Working memory: looking back and looking forward. Nat Rev Neurosci 4:829–839

    Article  CAS  Google Scholar 

  • Basten U, Stelzel C, Fiebach CJ (2013) Intelligence is differentially related to neural effort in the task-positive and the task-negative brain network. Intelligence 41:517–528

    Article  Google Scholar 

  • Buckner RL, Andrews-Hanna JR, Schacter DL (2008) The brain’s default network. Ann N Y Acad Sci 1124:1–38

    Article  Google Scholar 

  • Burgess GC, Gray JR, Conway AR, Braver TS (2011) Neural mechanisms of interference control underlie the relationship between fluid intelligence and working memory span. J Exp Psychol Gen 140:674–692

    Article  Google Scholar 

  • Button KS, Ioannidis JP, Mokrysz C, Nosek BA, Flint J, Robinson ES, Munafò MR (2013) Power failure: why small sample size undermines the reliability of neuroscience. Nat Rev Neurosci 14:365–376

    Article  CAS  Google Scholar 

  • Callicott JH, Mattay VS, Bertolino A, Finn K, Coppola R, Frank JA, Goldberg TE, Weinberger DR (1999) Physiological characteristics of capacity constraints in working memory as revealed by functional MRI. Cereb Cortex 9:20–26

    Article  CAS  Google Scholar 

  • Cattell RB (1971) Abilities: their structure, growth, and action. Houghton-Mifflin, Boston

    Google Scholar 

  • Cona G, Semenza C (2017) Supplementary motor area as key structure for domain-general sequence processing: a unified account. Neurosci Biobehav Rev 72:28–42

    Article  Google Scholar 

  • Diedrichsen J, Shadmehr R (2005) Detecting and adjusting for artifacts in fMRI time series data. Neuroimage 27:624–634

    Article  Google Scholar 

  • Eklund A, Nichols TE, Knutsson H (2016) Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates. Proc Natl Acad Sci 113:7900–7905

    Article  CAS  Google Scholar 

  • Engle RW, Kane MJ, Tuholski SW (1999a) Individual differences in working memory capacity and what they tell us about controlled attention, general fluid intelligence, and functions of the prefrontal cortex. In: Miyake A, Shah P (eds) Models of working memory: mechanisms of active maintenance and executive control. Cambridge University Press, Cambridge, pp 102–134

    Chapter  Google Scholar 

  • Engle RW, Tuholski SW, Laughlin JE, Conway AR (1999b) Working memory, short-term memory, and general fluid intelligence: a latent-variable approach. J Exp Psychol Gen 128:309–331

    Article  CAS  Google Scholar 

  • Gray JR, Chabris CF, Braver TS (2003) Neural mechanisms of general fluid intelligence. Nat Neurosci 6:316–322

    Article  CAS  Google Scholar 

  • Jansma J, Ramsey N, Van Der Wee N, Kahn R (2004) Working memory capacity in schizophrenia: a parametric fMRI study. Schizophr Res 68:159–171

    Article  CAS  Google Scholar 

  • Jung RE, Haier RJ (2007) The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence. Behav Brain Sci 30:135–154

    Article  Google Scholar 

  • Magistro D, Takeuchi H, Nejad KK, Taki Y, Sekiguchi A, Nouchi R, Kotozaki Y, Nakagawa S, Miyauchi CM, Iizuka K, Yokoyama R, Shinada T, Yamamoto Y, Hanawa S, Araki T, Hashizume H, Sassa Y, Kawashima R (2015) The relationship between processing speed and regional white matter volume in healthy young people. PLoS ONE 10:e0136386

    Article  Google Scholar 

  • Maldjian JA, Laurienti PJ, Kraft RA, Burdette JH (2003) An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. Neuroimage 19:1233–1239

    Article  Google Scholar 

  • Maldjian JA, Laurienti PJ, Burdette JH (2004) Precentral gyrus discrepancy in electronic versions of the Talairach atlas. Neuroimage 21:450–455

    Article  Google Scholar 

  • McKiernan KA, Kaufman JN, Kucera-Thompson J, Binder JR (2003) A parametric manipulation of factors affecting task-induced deactivation in functional neuroimaging. J Cogn Neurosci 15:394–408

    Article  Google Scholar 

  • Mennes M, Kelly C, Zuo XN, Di Martino A, Biswal BB, Castellanos FX, Milham MP (2010) Inter-individual differences in resting-state functional connectivity predict task-induced BOLD activity. Neuroimage 50:1690–1701

    Article  Google Scholar 

  • Murphy S, Norbury R, Godlewska B, Cowen P, Mannie Z, Harmer C, Munafo M (2012) The effect of the serotonin transporter polymorphism (5-HTTLPR) on amygdala function: a meta-analysis. Mol Psychiatry 18:512–520

    Article  Google Scholar 

  • Nachev P, Kennard C, Husain M (2008) Functional role of the supplementary and pre-supplementary motor areas. Nat Rev Neurosci 9:856–869

    Article  CAS  Google Scholar 

  • Neubauer AC, Fink A (2009) Intelligence and neural efficiency. Neurosci Biobehav Rev 33:1004–1023

    Article  Google Scholar 

  • Owen AM, McMillan KM, Laird AR, Bullmore E (2005) N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Hum Brain Mapp 25:46–59

    Article  Google Scholar 

  • Park DC, Lautenschlager G, Hedden T, Davidson NS, Smith AD, Smith PK (2002) Models of visuospatial and verbal memory across the adult life span. Psychol Aging 17:299–320

    Article  Google Scholar 

  • Picard N, Strick PL (1996) Motor areas of the medial wall: a review of their location and functional activation. Cereb Cortex 6:342–353

    Article  CAS  Google Scholar 

  • Plichta MM, Schwarz AJ, Grimm O, Morgen K, Mier D, Haddad L, Gerdes A, Sauer C, Tost H, Esslinger C (2012) Test–retest reliability of evoked BOLD signals from a cognitive–emotive fMRI test battery. Neuroimage 60:1746–1758

    Article  Google Scholar 

  • Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE (2012) Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59:2142–2154

    Article  Google Scholar 

  • Raven J (1998) Manual for Raven’s progressive matrices and vocabulary scales. Oxford Psychologists Press, Oxford

    Google Scholar 

  • Sambataro F, Murty VP, Callicott JH, Tan HY, Das S, Weinberger DR, Mattay VS (2008) Age-related alterations in default mode network: Impact on working memory performance. Neurobiol Aging 31:839–852

    Article  Google Scholar 

  • Schilling C, Kühn S, Paus T, Romanowski A, Banaschewski T, Barbot A, Barker G, Brühl R, Büchel C, Conrod P (2012) Cortical thickness of superior frontal cortex predicts impulsiveness and perceptual reasoning in adolescence. Mol Psychiatry 18:624–630

    Article  Google Scholar 

  • Seitz RJ, Nickel J, Azari NP (2006) Functional modularity of the medial prefrontal cortex: involvement in human empathy. Neuropsychology 20:743

    Article  Google Scholar 

  • Takeuchi H, Taki Y, Hashizume H, Sassa Y, Nagase T, Nouchi R, Kawashima R (2011a) Failing to deactivate: the association between brain activity during a working memory task and creativity. Neuroimage 55:681–687

    Article  Google Scholar 

  • Takeuchi H, Taki Y, Sassa Y, Hashizume H, Sekiguchi A, Fukushima A, Kawashima R (2011b) Verbal working memory performance correlates with regional white matter structures in the fronto-parietal regions. Neuropsychologia 49:3466–3473

    Article  Google Scholar 

  • Takeuchi H, Taki Y, Hashizume H, Sassa Y, Nagase T, Nouchi R, Kawashima R (2011c) Effects of training of processing speed on neural systems. J Neurosci 31:12139–12148

    Article  CAS  Google Scholar 

  • Takeuchi H, Sugiura M, Sassa Y, Sekiguchi A, Yomogida Y, Taki Y, Kawashima R (2012) Neural correlates of the difference between working memory speed and simple sensorimotor speed: an fMRI study. PLoS ONE 7:e30579

    Article  CAS  Google Scholar 

  • Takeuchi H, Taki Y, Thyreau B, Sassa Y, Hashizume H, Sekiguchi A, Nagase T, Nouchi R, Fukushima A, Kawashima R (2013a) White matter structures associated with empathizing and systemizing in young adults. Neuroimage 77:222–236

    Article  Google Scholar 

  • Takeuchi H, Taki Y, Nouchi R, Sekiguchi A, Hashizume H, Sassa Y, Kotozaki Y, Miyauchi CM, Yokoyama R, Iizuka K (2013b) Resting state functional connectivity associated with trait emotional intelligence. Neuroimage 83:318–328

    Article  Google Scholar 

  • Takeuchi H, Taki Y, Nouchi R, Sekiguchi A, Hashizume H, Sassa Y, Kotozaki Y, Miyauchi CM, Yokoyama R, Iizuka K (2014a) Association between resting-state functional connectivity and empathizing/systemizing. Neuroimage 99:312–322

    Article  Google Scholar 

  • Takeuchi H, Taki Y, Nouchi R, Hashizume H, Sassa Y, Sekiguchi A, Kotozaki Y, Nakagawa S, Nagase T, Miyauchi M, Kawashima C R (2014b) Associations among imaging measures (2): the association between gray matter concentration and task-induced activation changes. Hum Brain Mapp 35:185–198

    Article  Google Scholar 

  • Takeuchi H, Tomita H, Taki Y, Kikuchi Y, Ono C, Yu Z, Sekiguchi A, Nouchi R, Kotozaki Y, Nakagawa S (2015a) Cognitive and neural correlates of the 5-repeat allele of the dopamine D4 receptor gene in a population lacking the 7-repeat allele. Neuroimage 110:124–135

    Article  CAS  Google Scholar 

  • Takeuchi H, Taki Y, Sekiguchi A, Nouchi R, Kotozaki Y, Nakagawa S, Miyauchi CM, Iizuka K, Yokoyama R, Shinada T (2015b) Amygdala and cingulate structure is associated with stereotype on sex-role. Sci Rep 5:1–12

    Google Scholar 

  • Takeuchi H, Taki Y, Nouchi R, Sekiguchi A, Hashizume H, Sassa Y, Kotozaki Y, Miyauchi CM, Yokoyama R, Iizuka K, Seishu N, Tomomi N, Kunitoki K, Kawashima R (2015c) Degree centrality and fractional amplitude of low-frequency oscillations associated with Stroop interference. Neuroimage 119:197–209

    Article  Google Scholar 

  • Takeuchi H, Taki Y, Nouchi R, Yokoyama R, Kotozaki Y, Nakagawa S, Sekiguchi A, Iizuka K, Yamamoto Y, Hanawa S (2017) Global associations between regional gray matter volume and diverse complex cognitive functions: evidence from a large sample study. Sci Rep 7:1–16

    Article  Google Scholar 

  • Tang C, Eaves E, Ng J, Carpenter D, Mai X, Schroeder D, Condon C, Colom R, Haier R (2010) Brain networks for working memory and factors of intelligence assessed in males and females with fMRI and DTI. Intelligence 38:293–303

    Article  Google Scholar 

  • Toffanin P, Johnson A, De Jong R, Martens S (2007) Rethinking neural efficiency: effects of controlling for strategy use. Behav Neurosci 121:854–870

    Article  Google Scholar 

  • 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 15:273–289

    Article  CAS  Google Scholar 

  • Vul E, Harris C, Winkielman P, Pashler H (2009) Reply to comments on “puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition”. Perspect Psychol Sci 4:319–324

    Article  Google Scholar 

  • Waiter GD, Deary IJ, Staff RT, Murray AD, Fox HC, Starr JM, Whalley LJ (2009) Exploring possible neural mechanisms of intelligence differences using processing speed and working memory tasks: an fMRI study. Intelligence 37:199–206

    Article  Google Scholar 

  • Wechsler D (1997) WAIS-III administration and scoring manual. The Psychological Corporation, San Antonio

    Google Scholar 

  • Whitfield-Gabrieli S, Thermenos HW, Milanovic S, Tsuang MT, Faraone SV, McCarley RW, Shenton ME, Green AI, Nieto-Castanon A, LaViolette P (2009) Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc Natl Acad Sci USA 106:1279–1284

    Article  CAS  Google Scholar 

  • Zilles K, Schlaug G, Matelli M, Luppino G, Schleicher A, Qü M, Dabringhaus A, Seitz R, Roland P (1995) Mapping of human and macaque sensorimotor areas by integrating architectonic, transmitter receptor, MRI and PET data. J Anat 187:515

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank Yuki Yamada for operating the MRI scanner, Haruka Nouchi for conducting the psychological tests, all other assistants for helping with the experiments and the study, the study participants, and all our other colleagues at IDAC, Tohoku University, for their support. This study was supported by JST/RISTEX, JST/CREST, a Grant-in-Aid for Young Scientists (B) (KAKENHI 23700306) and a Grant-in-Aid for Young Scientists (A) (KAKENHI 25700012) from the Ministry of Education, Culture, Sports, Science, and Technology. The authors would like to thank Enago (http://www.enago.jp) for the English language review.

Funding

This study was supported by JST/RISTEX, JST/CREST, a Grant-in-Aid for Young Scientists (B) (KAKENHI 23700306) and a Grant-in-Aid for Young Scientists (A) (KAKENHI 25700012) from the Ministry of Education, Culture, Sports, Science, and Technology.

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Authors and Affiliations

  1. Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer (IDAC), Tohoku University, 4-1 Seiryo-cho, Aoba-ku, Sendai, 980-8575, Japan

    Hikaru Takeuchi, Yasuyuki Taki, Yuko Sassa, Susumu Yokota & Ryuta Kawashima

  2. Division of Medical Neuroimaging Analysis, Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan

    Yasuyuki Taki & Atsushi Sekiguchi

  3. Department of Radiology and Nuclear Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan

    Yasuyuki Taki

  4. Creative Interdisciplinary Research Division, Frontier Research Institute for Interdisciplinary Science, Tohoku University, Sendai, Japan

    Rui Nouchi

  5. Human and Social Response Research Division, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan

    Rui Nouchi

  6. Advanced Brain Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan

    Rui Nouchi, Tsuyoshi Araki & Ryuta Kawashima

  7. School of Medicine, Kobe University, Kobe, Japan

    Ryoichi Yokoyama

  8. Division of Clinical Research, Medical-Industry Translational Research Center, Fukushima Medical University School of Medicine, Fukushima, Japan

    Yuka Kotozaki

  9. Department of Functional Human Brain Imaging Science, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan

    Seishu Nakagawa & Sugiko Hanawa

  10. Division of Psychiatry, Tohoku Medical and Pharmaceutical University, Sendai, Japan

    Seishu Nakagawa & Kohei Sakaki

  11. Department of Behavioral Medicine, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan

    Atsushi Sekiguchi

  12. Department of Psychiatry, Tohoku University Graduate School of Medicine, Sendai, Japan

    Kunio Iizuka

  13. Department of Language Sciences, Graduate School of Humanities, Tokyo Metropolitan University, Tokyo, Japan

    Carlos Makoto Miyauchi

  14. Collaborative Research Center for Happiness Co-creation Society through “Ishin-Denshin” Intelligent Communications, Tokyo Institute of Technology, Tokyo, Japan

    Takayuki Nozawa & Ryuta Kawashima

  15. Department of Ubiquitous Sensing, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan

    Shigeyuki Ikeda

  16. Department of Sport Science, School of Science and Technology, Nottingham Trent University, Nottingham, UK

    Magistro Daniele

Authors
  1. Hikaru Takeuchi
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  2. Yasuyuki Taki
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  3. Rui Nouchi
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  4. Ryoichi Yokoyama
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  5. Yuka Kotozaki
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  6. Seishu Nakagawa
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  7. Atsushi Sekiguchi
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  8. Kunio Iizuka
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  9. Sugiko Hanawa
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  10. Tsuyoshi Araki
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  11. Carlos Makoto Miyauchi
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  12. Kohei Sakaki
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  13. Yuko Sassa
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  14. Takayuki Nozawa
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  15. Shigeyuki Ikeda
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  16. Susumu Yokota
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  17. Magistro Daniele
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  18. Ryuta Kawashima
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Corresponding author

Correspondence to Hikaru Takeuchi.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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The authors declare that they have no conflict of interest.

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This study was approved by the Ethics Committee of Tohoku University.

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Informed consent was obtained from all individual participants included in the study.

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Takeuchi, H., Taki, Y., Nouchi, R. et al. General intelligence is associated with working memory-related brain activity: new evidence from a large sample study. Brain Struct Funct 223, 4243–4258 (2018). https://doi.org/10.1007/s00429-018-1747-5

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