Neuronaukowe podstawy inteligencji

Abdellaoui, A., Dolan, C. V., Verweij, K. J. H., Nivard, M. G. (2022). Gene–environment correlations across geographic regions affect genome-wide association studies. Nature Genetics. https://doi.org/10.1038/s41588-022-01158-0

Ackerman, P. L., Beier, M. E., Boyle, M. O. (2005). Working memory and intelligence: The same or different constructs? Psychological Bulletin, 131(1), 30–60. https://doi.org/10.1037/0033-2909.131.1.30

Adamczyk, A. K., Zawadzki, P. (2020). The memory-modifying potential of optogenetics and the need for neuroethics. NanoEthics, 14(3), 207–225. https://doi.org/10.1007/s11569-020-00377-1

Alavash, M., Lim, S. J., Thiel, C., Sehm, B., Deserno, L., Obleser, J. (2018). Dopaminergic modulation of hemodynamic signal variability and the functional connectome during cognitive performance. Neuroimage, 172, 341–356. https://doi.org/10.1016/j.neuroimage.2018.01.048

Alkire, M. T., Haier, R. J. (2001). Correlating in vivo anaesthetic effects with ex vivo receptor density data supports a GABAergic mechanism of action for propofol, but not for isoflurane. British Journal of Anaesthesia, 86(5), 618–626. https://doi.org/10.1093/bja/86.5.618

Alkire, M. T., Haier, R. J., Fallon, J. H. (2000). Toward a unified theory of narcosis: Brain imaging evidence for a thalamocortical switch as the neurophysiologic basis of anesthetic-induced unconsciousness. Consciousness and Cognition, 9(3), 370–386.

Alkire, M. T., Haier, R. J., Barker, S. J., Shah, N. K., Wu, J. C., Kao, Y. J. (1995). Cerebral metabolism during propofol anesthesia in humans studied with positron emission tomography. Anesthesiology, 82(2), 393–403; discussion 327A. https://doi.org/10.1097/00000542-199502000-00010

Alkire, M. T., Pomfrett, C. J. D., Haier, R. J., Gianzero, M. V., Chan, C. M., Jacobsen, B. P., Fallon, J. H. (1999). Functional brain imaging during anesthesia in humans – Effects of halothane on global and regional cerebral glucose metabolism. Anesthesiology, 90(3), 701–709.

Allegrini, A. G., Selzam, S., Rimfeld, K., von Stumm, S., Pingault, J. B., Plomin, R. (2019). Genomic prediction of cognitive traits in childhood and adolescence. Molecular Psychiatry, 24(6), 819–827. https://doi.org/10.1038/s41380-019-0394-4

Anderson, D. J. (2012). Optogenetics, sex, and violence in the brain: Implications for psychiatry. Biological Psychiatry, 71(12), 1081–1089. https://doi.org/10.1016/j.biopsych.2011.11.012

Anderson, J. W., Johnstone, B. M., Remley, D. T. (1999). Breast-feeding and cognitive development: A meta-analysis. The American Journal of Clinical Nutrition, 70(4), 525–535. https://doi.org/10.1093/ajcn/70.4.525

Anderson, K. M., Holmes, A. J. (2021). Predicting individual differences in cognitive ability from brain imaging and genetics. W: A. K. Barbey, S. Karama, R. J. Haier (red.), Cambridge Handbook of Intelligence and Cognitive Neuroscience (s. 327–348). New York: Cambridge University Press.

Andreasen, N. C., Flaum, M., Swayze, V., Oleary, D. S., Alliger, R., Cohen, G., … Yuh, W. T. C. (1993). Intelligence and brain structure in normal individuals. American Journal of Psychiatry, 150(1), 130–134.

Antal, A., Luber, B., Brem, A. K., Bikson, M., Brunoni, A. R., Cohen Kadosh, R., … Paulus, W. (2022). Non-invasive brain stimulation and neuroenhancement. Clinical Neurophysiological Practise, 7, 146–165. https://doi.org/10.1016/j.cnp.2022.05.002

Arden, R. (2003). An arthurian romance. W: H. Nyborg (red.), The Scientific Study of General Intelligence (s. 533–553). Amsterdam: Pergamon.

Arden, R., Chavez, R. S., Grazioplene, R., Jung, R. E. (2010). Neuroimaging creativity: A psychometric view. Behavioral Brain Research, 214(2), 143–156. https://doi.org/10.1016/j.bbr.2010.05.015

Arden, R., Luciano, M., Deary, I. J., Reynolds, C. A., Pedersen, N. L., Plassman, B. L., … Visscher, P. M. (2015). The association between intelligence and lifespan is mostly genetic. International Journal of Epidemiology. https://doi.org/10.1093/ije/dyv112

Ardlie, K. G., DeLuca, D. S., Segre, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., … Consortium, G. (2015). The Genotype-Tissue Expression (GT x) pilot analysis: Multitissue gene regulation in humans. Science, 348(6235), 648–660. https://doi.org/10.1126/science.1262110

Arevalo, A., Abusamra, V., Lepski, G. (2022). Editorial: How to improve neuroscience education for the public and for a multi-professional audience in different parts of the globe. Frontiers in Human Neuroscience, 16, 973893.

Aristizabal, M. J., Anreiter, I., Halldorsdottir, T., Odgers, C. L., McDade, T. W., Goldenberg, A., … O’Donnell, K. J. (2020). Biological embedding of experience: A primer on epigenetics. Proceedings of the National Academy of Sciences, 117(38), 23261–23269. https://doi.org/10.1073/pnas.1820838116

Asbury, K., Fields, D. (2021). Implications of biological research on intelligence for education and public policy. W: A. Barbey, S. Karama, R. J. Haier (red.), The Cambridge Handbook of Intelligence and Cognitive Neuroscience (s. 399–415). New York: Cambridge University Press.

Asbury, K., Plomin, R. (2014). G Is for Genes: The Impact of Genetics on Education and Achievement. Chichester, West Sussex: Wiley-Blackwell.

Asbury, K., Wai, J. (2020). Viewing education policy through a genetic lens. Journal of School Choice, 14(2), 301–315. https://doi.org/10.1080/15582159.2019.1705008

Asbury, K., Wachs, T. D., Plomin, R. (2005). Environmental moderators of genetic influence on verbal and nonverbal abilities in early childhood. Intelligence, 33(6), 643–661.

Ashburner, J., Friston, K. (1997). Multimodal image coregistration and partitioning – A unified framework. Neuroimage, 6(3), 209–217.

Ashburner, J., Friston, K. J. (2000). Voxel-based morphometry – The methods. Neuroimage, 11(6 Pt 1), 805–821.

Aston-Jones, G., Deisseroth, K. (2013). Recent advances in optogenetics and pharmacogenetics. Brain Research, 1511, 1–5. https://doi.org/10.1016/j.brainres.2013.01.026

Atherton, M., Zhuang, J. C., Bart, W. M., Hu, X. P., He, S. (2000). A functional magnetic resonance imaging study of chess expertice. Journal of Cognitive Neuroscience, 105–105.

Au, J., Buschkuehl, M., Duncan, G. J., Jaeggi, S. M. (2016). There is no convincing evidence that working memory training is NOT effective: A reply to Melby-Lervag and Hulme (2015). Psychonomic Bulletin and Review, 23(1), 331–337. https://doi.org/10.3758/s13423-015-0967-4

Au, J., Gibson, B. C., Bunarjo, K., Buschkuehl, M., Jaeggi, S. M. (2020). Quantifying the difference between active and passive control groups in cognitive interventions using two meta-analytical approaches. Journal of Cognitive Enhancement, 4(2), 192–210. https://doi.org/10.1007/s41465-020-00164-6

Au, J., Sheehan, E., Tsai, N., Duncan, G. J., Buschkuehl, M., Jaeggi, S. M. (2015). Improving fluid intelligence with training on working memory: A meta-analysis. Psychonomic Bulletin and Review, 22(2), 366–377. https://doi.org/10.3758/s13423-014-0699-x

Bagot, K. S., Kaminer, Y. (2014). Efficacy of stimulants for cognitive enhancement in non-attention deficit hyperactivity disorder youth: A systematic review. Addiction, 109(4), 547–557. https://doi.org/10.1111/add.12460

Bailey, M. J., Sun, S., Timpe, B. (2021). Prep School for Poor Kids: The long-run impacts of head start on human capital and economic self-sufficiency. American Economic Review, 111(12), 3963–4001. https://doi.org/10.1257/aer.20181801

Barbey, A. (2018). Network neuroscience theory of human intelligence. Trends in Cognitive Sciences, 22(1), 8–20.

Barbey, A. (2021). Human intelligence and network neuroscience. W: A. Barbey, S. Karama, R. J. Haier (red.), Cambridge Handbook of Intelligence and Cognitive Neuroscience (s. 102–122). New York: Cambridge University Press.

Barbey, A., Karama, S., Haier, R. J. (red.) (2021). Cambridge Handbook of Intelligence and Cognitive Neuroscience. New York: Cambridge University Press.

Barbey, A. K., Colom, R., Paul, E. J., Grafman, J. (2014). Architecture of fluid intelligence and working memory revealed by lesion mapping. Brain Structure and Function, 219(2), 485–494.

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, 135(Pt 4), 1154–1164. https://doi.org/10.1093/brain/aws021

Barbey, A. K., Colom, R., Paul, E., Forbes, C., Krueger, F., Goldman, D., Grafman, J. (2014). Preservation of general intelligence following traumatic brain injury: Contributions of the Met66 brain-derived neurotrophic factor. Plos One, 9(2).

Barnett, W. S., Hustedt, J. T. (2005). Head start’s lasting benefits. Infants and Young Children, 18(1), 16–24.

Bashwiner, D. M. (2018). The neuroscience of musical creativity. W: R. E. Jung, O. Vartanian (red.), The Cambridge Handbook of the Neuroscience of Creativity (s. 495–516). Cambridge: Cambridge University Press.

Bashwiner, D. M., Wertz, C. J., Flores, R. A., Jung, R. E. (2016). Musical creativity „revealed” in brain structure: Interplay between motor, default mode, and limbic networks. Scientific Reports, 6, 20482. https://doi.org/10.1038/srep20482

Bassett, D. S., Yang, M., Wymbs, N. F., Grafton, S. T. (2015). Learning-induced autonomy of sensorimotor systems. Natural Neuroscience, 18(5), 744–751. https://doi.org/10.1038/nn.3993

Basso, A., De Renzi, E., Faglioni, P., Scotti, G., Spinnler, H. (1973). Neuropsychological evidence for the existence of cerebral areas critical to the performance of intelligence tasks. Brain, 96(4), 715–728.

Basten, U., Fiebach, C. J. (2021). Functional brain imaging of intelligence. W: A. Barbey, S. Karama, R. J. Haier (red.), The Cambridge Handbook of Intelligence and Cognitive Neuroscience (s. 235–260). New York: Cambridge University Press.

Basten, U., Hilger, K., Fiebach, C. J. (2015). Where smart brains are different: A quantitative meta-analysis of functional and structural brain imaging studies on intelligence. Intelligence, 51(0), 10–27. https://doi.org/10.1016/j.intell.2015.04.009

Basten, U., Stelzel, C., Fiebach, C. J. (2013). Intelligence is differentially related to neural effort in the task-positive and the task-negative brain network. Intelligence, 41(5), 517–528.

Bates, T. C., Gignac, G. E. (2022). Effort impacts IQ test scores in a minor way: A multi-study investigation with healthy adult volunteers. Intelligence, 92, 101652. https://doi.org/10.1016/j.intell.2022.101652

Bates, T. C., Lewis, G. J., Weiss, A. (2013). Childhood socioeconomic status amplifies genetic effects on adult intelligence. Psychological Science, 24(10), 2111–2116.

Batty, G. D., Deary, I. J., Gottfredson, L. S. (2007). Premorbid (early life) IQ and later mortality risk: Systematic review. Annals of Epidemiology, 17(4), 278–288.

Beaty, R. E. (2015). The neuroscience of musical improvisation. Neuroscience and Biobehavioral Reviews, 51, 108–117. https://doi.org/10.1016/j.neubiorev.2015.01.004

Beaujean, A. A., Firmin, M. W., Knoop, A. J., Michonski, J. D., Berry, T. P., Lowrie, R. E. (2006). Validation of the Frey and Detterman (2004) IQ prediction equations using the Reynolds Intellectual Assessment Scales. Personality and Individual Differences, 41(2), 353–357. https://doi.org/10.1016/j.paid.2006.01.014

Bejjanki, V. R., Zhang, R., Li, R., Pouget, A., Green, C. S., Lu, Z. L., Bavelier, D. (2014). Action video game play facilitates the development of better perceptual templates. Proceedings of the National Academy Science USA, 111(47), 16961–16966. https://doi.org/10.1073/pnas.1417056111

Bengtsson, S. L., Csikszentmihalyi, M., Ullen, F. (2007). Cortical regions involved in the generation of musical structures during improvisation in pianists. Journal of Cognition Neuroscience, 19(5), 830–842. https://doi.org/10.1162/jocn.2007.19.5.830

Benyamin, B., Pourcain, B., Davis, O. S., Davies, G., Hansell, N. K., Brion, M. J., … Visscher, P. M. (2014). Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Molecular Psychiatry, 19(2), 253–258. https://doi.org/10.1038/mp.2012.184

Berkowitz, A. L., Ansari, D. (2010). Expertise-related deactivation of the right temporoparietal junction during musical improvisation. Neuroimage, 49(1), 712–719. https://doi.org/10.1016/j.neuroimage.2009.08.042

Bernstein, B. O., Lubinski, D., Benbow, C. P. (2019). Psychological constellations assessed at age 13 predict distinct forms of eminence 35 years later. Psychological Science, 30(3), 444–454. https://doi.org/10.1177/0956797618822524

Bhaduri, A., Sandoval-Espinosa, C., Otero-Garcia, M., Oh, I., Yin, R., Eze, U. C., … Kriegstein, A. R. (2021). An atlas of cortical arealization identifies dynamic molecular signatures. Nature, 598(7879), 200–204. https://doi.org/10.1038/s41586-021-03910-8

Biazoli, C. E., Jr., Salum, G. A., Pan, P. M., Zugman, A., Amaro, E., Jr., Rohde, L. A., … Sato, J. R. (2017). Commentary: Functional connectome fingerprint: Identifying individuals using patterns of brain connectivity. Frontiers in Human Neuroscience, 11, 47.

Bishop, S. J., Fossella, J., Croucher, C. J., Duncan, J. (2008). COMT val158met genotype affects recruitment of neural mechanisms supporting fluid intelligence. Cerebral Cortex, 18(9), 2132–2140. https://doi.org/10.1093/cercor/bhm240

Bogg, T., Lasecki, L. (2015). Reliable gains? Evidence for substantially underpowered designs in studies of working memory training transfer to fluid intelligence. Frontiers in Psychology, 5.

Bohlken, M. M., Brouwer, R. M., Mandl, R. C., van Haren, N. E., Brans, R. G., van Baal, G. C., … Hulshoff Pol, H. E. (2014). Genes contributing to subcortical volumes and intellectual ability implicate the thalamus. Human Brain Mapping, 35(6), 2632–2642. https://doi.org/10.1002/hbm.22356

Boivin, M. J., Giordani, B., Berent, S., Amato, D. A., Lehtinen, S., Koeppe, R. A., … Kuhl, D. E. (1992). Verbal fluency and positron emission tomographic mapping of regional cerebral glucose-metabolism. Cortex, 28(2), 231–239.

Bouchard, T. J. (2009). Genetic influence on human intelligence (Spearman’s g): How much? Annals of Human Biology, 36(5), 527–544.

Bouchard, T. J., Jr. (1998). Genetic and environmental influences on adult intelligence and special mental abilities. Human Biology, 70(2), 257–279.

Bouchard, T. J., Jr., McGue, M. (1981). Familial studies of intelligence: A review. Science, 212(4498), 1055–1059. https://doi.org/10.1126/science.7195071

Bowren, M., Adolphs, R., Bruss, J., Manzel, K., Corbetta, M., Tranel, D., Boes, A. D. (2020). Multivariate lesion-behavior mapping of general cognitive ability and its psychometric constituents. Journal of Neuroscience, 40(46), 8924. https://doi.org/10.1523/JNEUROSCI.1415-20.2020

Brans, R. G. H., Kahn, R. S., Schnack, H. G., van Baal, G. C. M., Posthuma, D., van Haren, N. E. M., … Pol, H. E. H. (2010). Brain plasticity and intellectual ability are influenced by shared genes. Journal of Neuroscience, 30(16), 5519–5524.

Brem, A. K., Almquist, J. N., Mansfield, K., Plessow, F., Sella, F., Santarnecchi, E., … Honeywell SHARP Team authors. (2018). Modulating fluid intelligence performance through combined cognitive training and brain stimulation. Neuropsychologia, 118(Pt A), 107–114. https://doi.org/10.1016/j.neuropsychologia.2018.04.008

Brodmann, K. (1909). Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues. Leipzig: Barth.

Brody, N. (2003). Construct validation of the Sternberg Triarchic Abilities Test Comment and reanalysis. Intelligence, 31(4), 319–329. https://doi.org/10.1016/S0160-2896(01)00087-3

Bates, T. C., Gignac, G. E. (2022). Effort impacts IQ test scores in a minor way: A multi-study investigation with healthy adult volunteers. Intelligence, 92, 101652. https://doi.org/10.1016/j.intell.2022.101652

Bates, T. C., Lewis, G. J., Weiss, A. (2013). Childhood socioeconomic status amplifies genetic effects on adult intelligence. Psychological Science, 24(10), 2111–2116.

Batty, G. D., Deary, I. J., Gottfredson, L. S. (2007). Premorbid (early life) IQ and later mortality risk: Systematic review. Annals of Epidemiology, 17(4), 278–288.

Beaty, R. E. (2015). The neuroscience of musical improvisation. Neuroscience and Biobehavioral Reviews, 51, 108–117. https://doi.org/10.1016/j.neubiorev.2015.01.004

Beaujean, A. A., Firmin, M. W., Knoop, A. J., Michonski, J. D., Berry, T. P., Lowrie, R. E. (2006). Validation of the Frey and Detterman (2004) IQ prediction equations using the Reynolds Intellectual Assessment Scales. Personality and Individual Differences, 41(2), 353–357. https://doi.org/10.1016/j.paid.2006.01.014

Bejjanki, V. R., Zhang, R., Li, R., Pouget, A., Green, C. S., Lu, Z. L., Bavelier, D. (2014). Action video game play facilitates the development of better perceptual templates. Proceedings of the National Academy Science USA, 111(47), 16961–16966. https://doi.org/10.1073/pnas.1417056111

Bengtsson, S. L., Csikszentmihalyi, M., Ullen, F. (2007). Cortical regions involved in the generation of musical structures during improvisation in pianists. Journal of Cognition Neuroscience, 19(5), 830–842. https://doi.org/10.1162/jocn.2007.19.5.830

Benyamin, B., Pourcain, B., Davis, O. S., Davies, G., Hansell, N. K., Brion, M. J., … Visscher, P. M. (2014). Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Molecular Psychiatry, 19(2), 253–258. https://doi.org/10.1038/mp.2012.184

Berkowitz, A. L., Ansari, D. (2010). Expertise-related deactivation of the right temporoparietal junction during musical improvisation. Neuroimage, 49(1), 712–719. https://doi.org/10.1016/j.neuroimage.2009.08.042

Bernstein, B. O., Lubinski, D., Benbow, C. P. (2019). Psychological constellations assessed at age 13 predict distinct forms of eminence 35 years later. Psychological Science, 30(3), 444–454. https://doi.org/10.1177/0956797618822524

Bhaduri, A., Sandoval-Espinosa, C., Otero-Garcia, M., Oh, I., Yin, R., Eze, U. C., … Kriegstein, A. R. (2021). An atlas of cortical arealization identifies dynamic molecular signatures. Nature, 598(7879), 200–204. https://doi.org/10.1038/s41586-021-03910-8

Biazoli, C. E., Jr., Salum, G. A., Pan, P. M., Zugman, A., Amaro, E., Jr., Rohde, L. A., … Sato, J. R. (2017). Commentary: Functional connectome fingerprint: Identifying individuals using patterns of brain connectivity. Frontiers in Human Neuroscience, 11, 47.

Bishop, S. J., Fossella, J., Croucher, C. J., Duncan, J. (2008). COMT val158met genotype affects recruitment of neural mechanisms supporting fluid intelligence. Cerebral Cortex, 18(9), 2132–2140. https://doi.org/10.1093/cercor/bhm240

Bogg, T., Lasecki, L. (2015). Reliable gains? Evidence for substantially underpowered designs in studies of working memory training transfer to fluid intelligence. Frontiers in Psychology, 5.

Bohlken, M. M., Brouwer, R. M., Mandl, R. C., van Haren, N. E., Brans, R. G., van Baal, G. C., … Hulshoff Pol, H. E. (2014). Genes contributing to subcortical volumes and intellectual ability implicate the thalamus. Human Brain Mapping, 35(6), 2632–2642. https://doi.org/10.1002/hbm.22356

Boivin, M. J., Giordani, B., Berent, S., Amato, D. A., Lehtinen, S., Koeppe, R. A., … Kuhl, D. E. (1992). Verbal fluency and positron emission tomographic mapping of regional cerebral glucose-metabolism. Cortex, 28(2), 231–239.

Bouchard, T. J. (2009). Genetic influence on human intelligence (Spearman’s g): How much? Annals of Human Biology, 36(5), 527–544.

Bouchard, T. J., Jr. (1998). Genetic and environmental influences on adult intelligence and special mental abilities. Human Biology, 70(2), 257–279.

Bouchard, T. J., Jr., McGue, M. (1981). Familial studies of intelligence: A review. Science, 212(4498), 1055–1059. https://doi.org/10.1126/science.7195071

Bowren, M., Adolphs, R., Bruss, J., Manzel, K., Corbetta, M., Tranel, D., Boes, A. D. (2020). Multivariate lesion-behavior mapping of general cognitive ability and its psychometric constituents. Journal of Neuroscience, 40(46), 8924. https://doi.org/10.1523/JNEUROSCI.1415-20.2020

Brans, R. G. H., Kahn, R. S., Schnack, H. G., van Baal, G. C. M., Posthuma, D., van Haren, N. E. M., … Pol, H. E. H. (2010). Brain plasticity and intellectual ability are influenced by shared genes. Journal of Neuroscience, 30(16), 5519–5524.

Brem, A. K., Almquist, J. N., Mansfield, K., Plessow, F., Sella, F., Santarnecchi, E., … Honeywell SHARP Team authors. (2018). Modulating fluid intelligence performance through combined cognitive training and brain stimulation. Neuropsychologia, 118(Pt A), 107–114. https://doi.org/10.1016/j.neuropsychologia.2018.04.008

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Bruzzone, S. E. P., Lumaca, M., Brattico, E., Vuust, P., Kringelbach, M. L., Bonetti, L. (2022). Dissociated brain functional connectivity of fast versus slow frequencies underlying individual differences in fluid intelligence: A DTI and MEG study. Scientific Reports, 12(1), 4746. https://doi.org/10.1038/s41598-022-08521-5

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Burgaleta, M., Macdonald, P. A., Martinez, K., Roman, F. J., Alvarez-Linera, J., Gonzalez, A. R., … Colom, R. (2013). Subcortical regional morphology correlates with fluid and spatial intelligence. Human Brain Mapping. https://doi.org/10.1002/hbm.22305

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Chabris, C. F., Hebert, B. M., Benjamin, D. J., Beauchamp, J., Cesarini, D., van der Loos, M., … Laibson, D. (2012). Most reported genetic associations with general intelligence are probably false positives. Psychological Science, 23(11), 1314–1323.

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