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Advances in the Neuroscience of Intelligence: from Brain Connectivity to Brain Perturbation

Published online by Cambridge University Press:  06 December 2016

Emiliano Santarnecchi  and
Simone Rossi
Emiliano Santarnecchi*
Affiliation:
Berenson-Allen Center for Non-Invasive Brain Stimulation, Harvard Medical School, Boston (USA)
Simone Rossi
Affiliation:
Department of Medicine, Surgery and Neuroscience, Brain Investigation and Neuromodulation (SiBIN) Lab, University of Siena Deptartment of Medicine, Surgery and Neuroscience, Human Physiology section, University of Siena
*
*Correspondence concerning this article should be addressed to Emiliano Santarnecchi. Berenson-Allen Center for Noninvasive Brain Stimulation. Harvard Medical School. Department of Cognitive Neurology. Beth Israel Deaconess Medical Center. 330. Brookline Avenue, KS-450. 02215. Boston, MA (USA). Phone: Office +1–6670326; Mobile +1–6175169516. E-mail: esantarn@bidmc.harvard.edu
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Abstract

Our view is that intelligence, as expression of the complexity of the human brain and of its evolutionary path, represents an intriguing example of “system level brain plasticity”: tangible proofs of this assertion lie in the strong links intelligence has with vital brain capacities as information processing (i.e., pure, rough capacity to transfer information in an efficient way), resilience (i.e., the ability to cope with loss of efficiency and/or loss of physical elements in a network) and adaptability (i.e., being able to efficiently rearrange its dynamics in response to environmental demands). Current evidence supporting this view move from theoretical models correlating intelligence and individual response to systematic “lesions” of brain connectivity, as well as from the field of Noninvasive Brain Stimulation (NiBS). Perturbation-based approaches based on techniques as transcranial magnetic stimulation (TMS) and transcranial alternating current stimulation (tACS), are opening new in vivo scenarios which could allow to disclose more causal relationship between intelligence and brain plasticity, overcoming the limitations of brain-behavior correlational evidence

Keywords

intelligenceGfnon-invasive brain stimulationplasticityperturbation
Type
Research Article
Information
The Spanish Journal of Psychology , Volume 19 , 2016 , E94
Copyright
Copyright © Universidad Complutense de Madrid and Colegio Oficial de Psicólogos de Madrid 2016 

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References

Achard, S., & Bullmore, E. (2007). Efficiency and cost of economical brain functional networks. PLoS Computational Biology, 3, e17. https://doi.org/10.1371/journal.pcbi.0030017 CrossRefGoogle ScholarPubMed
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, 26, 63–72. https://doi.org/10.1523/JNEUROSCI.3874-05.2006 Google Scholar
Albert, R., Jeong, H., & Barabasi, A. L. (2000). Error and attack tolerance of complex networks. Nature, 406, 378–382. https://doi.org/10.1038/35019019 Google Scholar
Ali, M. M., Sellers, K. K., & Frohlich, F. (2013). Transcranial alternating current stimulation modulates large-scale cortical network activity by network resonance. The Journal of Neuroscience, 33, 11262–11275. https://doi.org/10.1523/JNEUROSCI.5867-12.2013 Google Scholar
Barabasi, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286, 509–512.Google Scholar
Barabasi, A. L., & Bonabeau, E. (2003). Scale-free networks. Scientific American, 288, 60–69. https://doi.org/10.1038/scientificamerican0503-60 Google Scholar
Bestmann, S., de Berker, A. O., & Bonaiuto, J. (2015). Understanding the behavioural consequences of noninvasive brain stimulation. Trends in Cognitive Science, 19, 13–20. https://doi.org/10.1016/j.tics.2014.10.003 CrossRefGoogle ScholarPubMed
Bruckmann, S., Hauk, D., Roessner, V., Resch, F., Freitag, C. M., Kammer, T., … Bender, S. (2012). Cortical inhibition in attention deficit hyperactivity disorder: New insights from the electroencephalographic response to transcranial magnetic stimulation. Brain, 135, 2215–2230. https://doi.org/10.1093/brain/aws071 Google Scholar
Buzsaki, G., & Draguhn, A. (2004). Neuronal oscillations in cortical networks. Science, 304, 1926–1929. https://doi.org/10.1126/science.1099745 Google Scholar
Canali, P., Sarasso, S., Rosanova, M., Casarotto, S., Sferrazza-Papa, G., Gosseries, O., ... Benedetti, F. (2015). Shared reduction of oscillatory natural frequencies in bipolar disorder, major depressive disorder and schizophrenia. Journal of Affective Disorders, 184, 111–115. https://doi.org/10.1016/j.jad.2015.05.043 Google Scholar
Casali, A. G., Casarotto, S., Rosanova, M., Mariotti, M., & Massimini, M. (2010). General indices to characterize the electrical response of the cerebral cortex to TMS. Neuroimage, 49, 1459–1468. https://doi.org/10.1016/j.neuroimage.2009.09.026 Google Scholar
Casarotto, S., Määttä, S., Herukka, S. K., Pigorini, A., Napolitani, M., Gosseries, O., … Massimini, M. (2011). Transcranial magnetic stimulation-evoked EEG/cortical potentials in physiological and pathological aging. Neuroreport, 22, 592–597. https://doi.org/10.1097/WNR.0b013e328349433a Google Scholar
Chiang, M. C., Barysheva, M., Shattuck, D. W., Lee, A. D., Madsen, S. K., Avedissian, C., … Thompson, P. M. (2009). Genetics of brain fiber architecture and intellectual performance. The Journal of Neuroscience, 29, 2212–2224. https://doi.org/10.1523/JNEUROSCI.4184-08.2009 Google Scholar
Cole, M. W., Yarkoni, T., Repovs, G., Anticevic, A., & Braver, T. S. (2012). Global connectivity of prefrontal cortex predicts cognitive control and intelligence. The Journal of Neuroscience, 32, 8988–8999. https://doi.org/10.1523/JNEUROSCI.0536-12.2012 Google Scholar
Colom, R., Karama, S., Jung, R. E., & Haier, R. J. (2010). Human intelligence and brain networks. Dialogues in Clinical Neuroscience, 12, 489–501.Google Scholar
Deary, I. (2008). Why do intelligent people live longer? Nature, 456, 175–176. https://doi.org/10.1038/456175a CrossRefGoogle ScholarPubMed
Deary, I. J., Penke, L., & Johnson, W. (2010). The neuroscience of human intelligence differences. Nature Reviews Neuroscience, 11, 201–211. https://doi.org/10.1038/nrn2793 Google Scholar
Engel, A. K., Fries, P., & Singer, W. (2001). Dynamic predictions: Oscillations and synchrony in top-down processing. Nature Reviews Neuroscience, 2, 704–716. https://doi.org/10.1038/35094565 Google Scholar
Feurra, M., Bianco, G., Santarnecchi, E., Del Testa, M., Rossi, A., & Rossi, S. (2011). Frequency-dependent tuning of the human motor system induced by transcranial oscillatory potentials. The Journal of Neuroscience, 31, 12165–12170. https://doi.org/10.1523/JNEUROSCI.0978-11.2011 Google Scholar
Feurra, M., Pasqualetti, P., Bianco, G., Santarnecchi, E., Rossi, A., & Rossi, S. (2013). State-dependent effects of transcranial oscillatory currents on the motor system: What you think matters. The Journal of Neuroscience, 33, 17483–17489. https://doi.org/10.1523/JNEUROSCI.1414-13.2013 Google Scholar
Freitas, C., Farzan, F., & Pascual-Leone, A. (2013). Assessing brain plasticity across the lifespan with transcranial magnetic stimulation: Why, how, and what is the ultimate goal? Frontiers in Neuroscience, 7, 42. https://doi.org/10.3389/fnins.2013.00042 CrossRefGoogle ScholarPubMed
Friedman, N. P., Miyake, A., Young, S. E., Defries, J. C., Corley, R. P., & Hewitt, J. K. (2008). Individual differences in executive functions are almost entirely genetic in origin. Journal of Experimental Psychology: General, 137, 201–225. https://doi.org/10.1037/0096-3445.137.2.201 CrossRefGoogle ScholarPubMed
Frohlich, F., & McCormick, D. A. (2010). Endogenous electric fields may guide neocortical network activity. Neuron, 67, 129–143. https://doi.org/10.1016/j.neuron.2010.06.005 CrossRefGoogle ScholarPubMed
Grandy, T. H., Werkle-Bergner, M., Chicherio, C., Lovden, M., Schmiedek, F., & Lindenberger, U. (2013). Individual alpha peak frequency is related to latent factors of general cognitive abilities. NeuroImage, 79, 10–18. https://doi.org/10.1016/j.neuroimage.2013.04.059 CrossRefGoogle ScholarPubMed
Huang, Y. Z., Edwards, M. J., Rounis, E., Bhatia, K. P., & Rothwell, J. C. (2005). Theta burst stimulation of the human motor cortex. Neuron, 45, 201–206. https://doi.org/10.1016/j.neuron.2004.12.033 CrossRefGoogle ScholarPubMed
Jausovec, N., & Jausovec, K. (2000). Differences in event-related and induced brain oscillations in the theta and alpha frequency bands related to human intelligence. Neuroscience Letters, 293, 191–194. https://doi.org/10.1016/S0304-3940(00)01526-3 Google Scholar
Joyce, K. E., Hayasaka, S., & Laurienti, P. J. (2013). The human functional brain network demonstrates structural and dynamical resilience to targeted attack. PLoS Computational Biology, 9, e1002885. https://doi.org/10.1371/journal.pcbi.1002885 CrossRefGoogle ScholarPubMed
Jung, R. E., & Haier, R. J. (2007). The parieto-frontal integration theory (P-FIT) of intelligence: Converging neuroimaging evidence. Behavioral and Brain Science, 30, 135–154. https://doi.org/10.1017/S0140525X07001185 Google Scholar
Kitano, H. (2004). Biological robustness. Nature Reviews Genetic, 5, 826–837. https://doi.org/10.1038/nrg1471 Google Scholar
Koch, G., Di Lourenzo, F., Bonni, S., Ponzo, V., Caltagirone, C., & Martorana, A. (2012). Impaired LTP- but not LTD-like cortical plasticity in Alzheimer’s disease patients. Journal of Alzheimer´s Disease, 31, 593–599.Google Scholar
Komssi, S., Kähkönen, S., & Ilmoniemi, R. J. (2004). The effect of stimulus intensity on brain responses evoked by transcranial magnetic stimulation. Human Brain Mapping, 21, 154–164. https://doi.org/10.1002/hbm.10159 CrossRefGoogle ScholarPubMed
Krause, B., & Cohen, K. R. (2014). Not all brains are created equal: The relevance of individual differences in responsiveness to transcranial electrical stimulation. Frontiers in Systems Neuroscience, 8, 25. https://doi.org/10.3389/fnsys.2014.00025 Google Scholar
Lioumis, P., Kicic, D., Savolainen, P., Mäkelä, J. P., & Kähkönen, S. (2009). Reproducibility of TMS-Evoked EEG responses. Human Brain Mapping, 30, 1387–1396. https://doi.org/10.1002/hbm.20608 CrossRefGoogle ScholarPubMed
Llinas, R., & Ribary, U. (1993). Coherent 40-Hz oscillation characterizes dream state in humans. Proceedings of the National Academic of Sciences, 90, 2078–2081. https://doi.org/10.1073/pnas.90.5.2078 CrossRefGoogle ScholarPubMed
Massimini, M., Boly, M., Casali, A., Rosanova, M., & Tononi, G. (2009). A perturbational approach for evaluating the brain’s capacity for consciousness. Progress in Brain Research, 177, 201–214. https://doi.org/10.1016/S0079-6123(09)17714-2 CrossRefGoogle ScholarPubMed
Neubauer, A. C., & Fink, A. (2009). Intelligence and neural efficiency. Neuroscience & Biobehavioral Reviews, 33, 1004–1023. https://doi.org/10.1016/j.neubiorev.2009.04.001 CrossRefGoogle ScholarPubMed
Nitsche, M. A., & Paulus, W. (2011). Transcranial direct current stimulation-update 2011. Restorative Neurology and Neuroscience, 29, 463–492. https://doi.org/10.3233/RNN-2011-0618 CrossRefGoogle ScholarPubMed
Oberman, L., Eldaief, M., Fecteau, S., Ifert-Miller, F., Tormos, J. M., & Pascual-Leone, A. (2012). Abnormal modulation of corticospinal excitability in adults with Asperger’s syndrome. European Journal of Neuroscience, 36, 2782–2788. https://doi.org/10.1111/j.1460-9568.2012.08172.x CrossRefGoogle ScholarPubMed
Pascual-Leone, A., Amedi, A., Fregni, F., & Merabet, L. B. (2005). The plastic human brain cortex. Annual Review Neuroscience, 28, 377–401. https://doi.org/10.1146/annurev.neuro.27.070203.144216 Google Scholar
Payton, A. (2009). The impact of genetic research on our understanding of normal cognitive ageing: 1995 to 2009. Neuropsychology Review, 19, 451–477. https://doi.org/10.1007/s11065-009-9116-z Google Scholar
Posthuma, D., Neale, M. C., Boomsma, D. I., & de Geus, E. J. (2001). Are smarter brains running faster? Heritability of alpha peak frequency, IQ, and their interrelation. Behavior Genetic, 31, 567–579.Google Scholar
Reato, D., Rahman, A., Bikson, M., & Parra, L. C. (2010). Low-intensity electrical stimulation affects network dynamics by modulating population rate and spike timing. The Journal of Neuroscience, 30, 15067–15079. https://doi.org/10.1523/JNEUROSCI.2059-10.2010 Google Scholar
Rogasch, N. C., & Fitzgerald, P. B. (2013). Assessing cortical network properties using TMS-EEG. Human Brain Mapping, 34, 1652–1669. https://doi.org/10.1002/hbm.22016 Google Scholar
Rosanova, M., Casali, A., Bellina, V., Resta, F., Mariotti, M., & Massimini, M. (2009). Natural frequencies of human corticothalamic circuits. The Journal of Neuroscience, 29, 7679–7685. https://doi.org/10.1523/JNEUROSCI.0445-09.2009 Google Scholar
Rosanova, M., Gosseries, O., Casarotto, S., Boly, M., Casali, A. G., Bruno, M. A., … Massimini, M. (2012). Recovery of cortical effective connectivity and recovery of consciousness in vegetative patients. Brain, 135, 1308–1320. https://doi.org/10.1093/brain/awr340 Google Scholar
Rossi, S., Hallett, M., Rossini, P. M., & Pascual-Leone, A. (2009). Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research. Clinical Neurophysiology, 120, 2008–2039. https://doi.org/10.1016/j.clinph.2009.08.016 Google Scholar
Rossi, S., & Rossini, P. M. (2004). TMS in cognitive plasticity and the potential for rehabilitation. Trends in Cognitive Science, 8, 273–279. https://doi.org/10.1016/j.tics.2004.04.012 Google Scholar
Rossini, P. M., Burke, D., Chen, R., Cohen, L. G., Daskalakis, Z., Di lorio, R., … Ziemann, U. (2015). Non-invasive electrical and magnetic stimulation of the brain, spinal cord, roots and peripheral nerves: Basic principles and procedures for routine clinical and research application. An updated report from an I.F.C.N. Committee. Clinical Neurophysiology, 126, 1071–1107. https://doi.org/10.1016/j.clinph.2015.02.001 Google Scholar
Rushton, J. P., & Ankney, C. D. (2009). Whole brain size and general mental ability: A review. International Journal of Neuroscience, 119, 692–732. https://doi.org/10.1080/00207450802325843 Google Scholar
Santarnecchi, E., Brem, A. K., Levenbaum, E., Thompson, T., Kadosh, R. C., & Pascual-Leone, A. (2015). Enhancing cognition using transcranial electrical stimulation. Current Opinion in Behavioural Sciences, 4, 171–178. https://doi.org/10.1016/j.cobeha.2015.06.003 Google Scholar
Santarnecchi, E., Di Lorenzo, G., Giovannelli, F., Tatti, E., Frugarello, P., Pascual-Leone, A, & Rossi, S. (2016, July). EEG response to brain perturbation correlates with variability in individual cognitive profile. International Society for Intelligence Research Conference 2016. San Petersburgh, Russia.Google Scholar
Santarnecchi, E., Galli, G., Polizzotto, N. R., Rossi, A., & Rossi, S. (2014). Efficiency of weak brain connections support general cognitive functioning. Human Brain Mapping, 35, 4566–4582. https://doi.org/10.1002/hbm.22495 Google Scholar
Santarnecchi, E., Muller, T., Rossi, S., Sarkar, A., Polizzotto, N. R., Rossi, A., & Kadosh, R. C. (2016). Individual differences and specificity of prefrontal gamma frequency-tACS on fluid intelligence capabilities. Cortex, 75, 33–43. https://doi.org/10.1016/j.cortex.2015.11.003 Google Scholar
Santarnecchi, E., Polizzotto, N. R., Godone, M., Giovannelli, F., Feurra, M., Matzen, L., … Rossi, S. (2013). Frequency-dependent enhancement of fluid intelligence induced by transcranial oscillatory potentials. Current Biology, 23, 1449–1453. https://doi.org/10.1016/j.cub.2013.06.022 Google Scholar
Santarnecchi, E., Rossi, S., & Rossi, A. (2015). The smarter, the stronger: Intelligence level correlates with brain resilience to systematic insults. Cortex, 64, 293–309. https://doi.org/10.1016/j.cortex.2014.11.005 Google Scholar
Shafi, M. M., Vernet, M., Klooster, D., Chu, C. J., Boric, K., Barnard, M. E., … Chang, B. S. (2015). Physiological consequences of abnormal connectivity in a developmental epilepsy. Annals of Neurology, 77, 487–503. https://doi.org/10.1002/ana.24343 Google Scholar
Stern, Y. (2009). Cognitive reserve. Neuropsychologia, 47, 2015–2028. https://doi.org/10.1016/j.neuropsychologia.2009.03.004 Google Scholar
Stern, Y. (2012). Cognitive reserve in ageing and Alzheimer’s disease. The Lancet Neurology, 11, 1006–1012. https://doi.org/10.1016/S1474-4422(12)70191-6 Google Scholar
Thut, G., & Miniussi, C. (2009). New insights into rhythmic brain activity from TMS-EEG studies. Trends in Cognitive Science, 13, 182–189. https://doi.org/10.1016/j.tics.2009.01.004 Google Scholar
van den Heuvel, M. P., Stam, C. J., Kahn, R. S., & Hulshoff, Pol H. E. (2009). Efficiency of functional brain networks and intellectual performance. The Journal of Neuroscience, 29, 7619–7624. https://doi.org/10.1523/JNEUROSCI.1443-09.2009 Google Scholar
Vlachos, A., Muller-Dahlhaus, F., Rosskopp, J., Lenz, M., Ziemann, U., & Deller, T. (2012). Repetitive magnetic stimulation induces functional and structural plasticity of excitatory postsynapses in mouse organotypic hippocampal slice cultures. The Journal of Neuroscience, 32, 17514–17523.Google Scholar
Wang, L., Song, M., Jiang, T., Zhang, Y., & Yu, C. (2011). Regional homogeneity of the resting-state brain activity correlates with individual intelligence. Neuroscience Letters, 488, 275–278. https://doi.org/10.1016/j.neulet.2010.11.046 Google Scholar