Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-848d4c4894-xfwgj Total loading time: 0 Render date: 2024-06-19T07:00:06.088Z Has data issue: false hasContentIssue false

5 - Genetic and Experiential Factors in Brain Development

The Examples of Executive Attention and Self-regulation

from Part I - Neurobiological Constraints and Laws of Cognitive Development

Published online by Cambridge University Press:  24 February 2022

By
Michael I. Posner  and
Mary K. Rothbart
Edited by
Olivier Houdé  and
Grégoire Borst
Olivier Houdé
Affiliation:
Université de Paris V
Grégoire Borst
Affiliation:
Université de Paris V
Get access

Summary

Executive attention is a brain network that includes the anterior cingulate cortex (ACC), the anterior insula and adjacent areas of the mid-prefrontal cortex and underlying striatum. In adult studies it is often activated by requiring a person to withhold a dominant response in order to perform a subdominant response (Posner & Rothbart, 2007a, 2007b). The ability to control our thoughts, feelings, and behavior develops over time and is called self-regulation. The self-regulatory view fits well with evidence of brain activation, functional and structural connectivity, and individual differences. Moreover, the self-regulatory view helps us understand how brain networks relate to important real-life functions and provides a perspective on how the shift takes place between infancy, where regulation is chiefly under the control of the caregiver, and later life, where self-control is increasingly important.

Type
Chapter
Information
The Cambridge Handbook of Cognitive Development , pp. 105 - 121
Publisher: Cambridge University Press
Print publication year: 2022

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bakermans-Kranenburg, M. J., & Van Ijzendoorn, M. H. (2006). Gene–environment interaction of the dopamine D4 receptor (DRD4) and observed maternal insensitivity predicting externalizing behavior in preschoolers. Developmental Psychobiology, 48, 406–409.CrossRefGoogle ScholarPubMed
Bakermans-Kranenburg, M. J. Van Ijzendoorn, M. H., Pijlman, F. T. A., Mesman, J., & Juffer, F. (2008). Experimental evidence for differential susceptibility: Dopamine receptor polymorphism (DRD4 VNTR) moderates intervention effects on toddlers externalizing behavior in a randomized controlled trial. Developmental Psychology, 44, 293–300.CrossRefGoogle ScholarPubMed
Beauregard, M., Levesque, J., & Bourgouin, P. (2001). Neural correlates of conscious self-regulation of emotion. Journal of Neuroscience, 21, RC165.CrossRefGoogle ScholarPubMed
Becker, C. O., Pequite, S., Pappas, G. J., Miller, M. B., Grafton, S. T., Bassetti, D. S., & Preciado, V. M. (2016). Accurately predicting functional connectivity from diffusion imaging. arXiv.org > q-bio > arXiv:1512.02602v3.+q-bio+>+arXiv:1512.02602v3.>Google Scholar
Beirowski, B. (2013). Concepts for regulation of axon integrity by enwrapping glia. Frontiers in Cellular Neuroscience, 7, 256.CrossRefGoogle ScholarPubMed
Belsky, J., & Pluess, M. (2009). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 624–652.Google Scholar
Berger, A., Tzur, G., & Posner, M. I. (2006). Infant babies detect arithmetic error. Proceeding of the National Academy of Science USA, 103, 12649–12553.CrossRefGoogle Scholar
Bishop, S. J. (2007). Neurocognitive mechanisms of anxiety. Trends in Cognitive Sciences, 11, 307–316.Google Scholar
Blasi, G., Mattay, G. S., Bertolino, A., Elvevåg, B., Callicott, J. H., Das, S., et al. (2005). Effect of Catechol-O-Methyltransferase val met genotype on attentional control. Journal of Neuroscience, 25, 5038–5045.CrossRefGoogle ScholarPubMed
Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108, 624–652.CrossRefGoogle ScholarPubMed
Brock, S. E., Rothbart, M. K., & Derryberry, D. (1986). Heart-rate deceleration and smiling in 3 month-old infants. Infant Behavior and Development, 9, 403–414.CrossRefGoogle Scholar
Bush, G., Luu, P., & Posner, M. I. (2000). Cognitive and emotional influences in the anterior cingulate cortex. Trends in Cognitive Science, 4, 215–222.CrossRefGoogle Scholar
Cachia, A., Borst, G., Tissier, C., Fisher, C., Plaze, M., et al. (2016). Longitudinal stability of the folding pattern of the anterior cingulate cortex during development. Developmental Cognitive Neuroscience, 19, 122–127.CrossRefGoogle ScholarPubMed
Cachia, A., Borst, G., Vidal, J., Fischer, C., Pineau, A., Mangin, J. F., & Houdé, O. (2014). The shape of the ACC contributes to cognitive control efficiency in preschoolers. Journal of Cognitive Neuroscience, 26, 96–106.Google Scholar
Chrysikou, E. G., Berryhill, M. E., Bikson, M., & Coslett, H. B. (2017). Revisiting the effectiveness of transcranial direct current brain stimulation for cognition: Evidence, challenges, and open questions. Frontiers in Human Neuroscience, 11, 448.Google Scholar
Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 201–215.Google Scholar
Crottaz-Herbette, S., and Mennon, V. (2006). Where and when the anterior cingulate cortex modulates attentional response: Combined fMRI and ERP evidence. Journal of Cognitive Neuroscience, 18, 766–780.CrossRefGoogle ScholarPubMed
Diamond, A., Briand, L., Fossella, J., & Gehlbach, L. (2004). Genetic and neurochemical modulation of prefrontal cognitive functions in children. American Journal of Psychiatry, 161, 125–132.CrossRefGoogle ScholarPubMed
Diatchenko, L., Slade, G. D., Nackley, A. G., Bhalang, K., Sigurdsson, A., Belfer, I., et al. (2005). Genetic basis for individual variations in pain perception and the development of a chronic pain condition. Human Molecular Genetics, 14, 135–143.Google Scholar
Ding, Y. C., Chi, H. C., Grady, D. L., Morishima, A., Kidd, J. R., Kidd, K. K., et al. (2002). Evidence of positive selection acting at the human dopamine receptor D4 gene locus. Proceedings of the National Academy of Sciences (USA), 99, 309–314.CrossRefGoogle ScholarPubMed
Dosenbach, N. U., Fair, D. A., Miezin, F. M., Cohen, A. L., Wenger, K. K. R., Dosenbach, A. T., et al. (2007). Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences (USA), 104, 11073–11078.CrossRefGoogle ScholarPubMed
Duncan, J., Seitz, R. J., Kolodny, J., Bor, D., Herzog, H. Ahmed, A., et al. (2000). A neural basis for general intelligence. Science, 289, 457–460.CrossRefGoogle ScholarPubMed
Etkin, A., Egner, T., Peraza, D. M., Kandel, E. R., & Hirsch, J. (2006). Resolving emotional conflict: A role for the rostral anterior cingulate cortex in modulating activity in the amygdala. Neuron, 51, 871–882.Google Scholar
Fair, D. A., Cohen, A. L., Dosenbach, U. F., Church, J. A., Meizin, F. M., Barch, D. M., et al. (2008). The maturing architecture of the brain’s default network. Proceedings of the National Academy of Sciences (USA), 105, 4028–4032.CrossRefGoogle ScholarPubMed
Fair, D. A., Dosenbach, N. U. F., Church, J. A., Cohen, A. L., Brahmbhatt, S., Miezin, F. M., et al. (2007). Development of distinct control networks through segregation and integration. Proceedings of the National Academy of Sciences (USA), 104, 13507–13512.Google Scholar
Fan, J., Gu, X., Guise, K. G., Liu, X., Fossella, J., Wang, H., & Posner, M. I. (2009). Testing the behavioral interaction and integration of attentional networks. Brain and Cognition, 70, 209–220.CrossRefGoogle ScholarPubMed
Fan, J., McCandliss, B. D., Fossella, J., Flombaum, J. I., & Posner, M. I. (2005). The activation of attentional networks. Neuroimage, 26, 471–479.CrossRefGoogle ScholarPubMed
Fan, J., McCandliss, B. D., Sommer, T., Raz, M., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 3, 340–347.CrossRefGoogle Scholar
Fjell, A. M., Walhovd, K., Brown, T., Kuperman, J., Chung, Y., Hagler, D., et al. (2012). Multi-modal imaging of the self-regulating brain. Proceedings of the National Academy of Sciences (USA), 109, 19620–19625.CrossRefGoogle Scholar
Gao, W., Alcauter, S., Elton, A., Hernandez-Castillo, C. R., Smith, J. K., Ramirez, J., & Lin, W. (2014). Functional network development during the first year: Relative sequence and socioeconomic correlations. Cerebral Cortex, 25, 2919–2928.CrossRefGoogle ScholarPubMed
Gao, W., Gilmore, J. H., Shen, D., Smith, J. K., Zhu, H., & Lin, W. (2013). The synchronization within and interaction between the default and dorsal attention networks in early infancy. Cerebral Cortex, 23, 594–603.CrossRefGoogle ScholarPubMed
Gao, W., Lin, W., Grewen, K., & Gilmore, J. H. (2017). Functional connectivity of the infant human brain: Plastic and modifiable. Neuroscientist, 23, 169–184.CrossRefGoogle ScholarPubMed
Green, A. E., Munafo, M. R., DeYoung, C. G., Fossella, J. A., Fan, J., & Gray, J. R. (2008). Using genetic data in cognitive neuroscience: From growing pains to genuine insights, Nature Neuroscience Review, 9, 710–720.CrossRefGoogle ScholarPubMed
Harman, C., Rothbart, M. K., & Posner, M. I. (1997). Distress and attention interactions in early infancy. Motivation and Emotion, 21, 27–43.Google Scholar
Holroyd, C. B., & Coles, M. G. H. (2002). The neural basis of human error processing: Reinforcement learning, dopamine and error-related negativity. Psychological Review, 109, 679–709.CrossRefGoogle ScholarPubMed
Houdé, O., Pineau, A., Leroux, G., Poirel, N., Perchey, G., Lanoë, C., et al. (2011). Functional MRI study of Piaget’s conservation-of-number task in preschool and school-age children: A neo-Piagetian approach. Journal of Experimental Child Psychology, 110, 332–346.Google Scholar
Jaffard, M., Benraiss, A., Longcamp, M., Velay, J.-L., & Boulinguez, P. (2007). Cueing method biases in visual detection studies. Brain Research, 1179, 106–118.Google Scholar
Jones, L. B., Rothbart, M. K., & Posner, M. I. (2003). Development of executive attention in preschool children. Developmental Science, 6, 498–504.CrossRefGoogle Scholar
Kahneman, D. (1973). Attention and Effort. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
Kanske, P., Heissler, J., & Schoenfelder, S. (2011). How to regulate emotion? Neural networks for reappraisal and distraction. Cerebral Cortex, 21, 1379–1388.CrossRefGoogle ScholarPubMed
Kong, A., Thorleifsson, G., Frigge, M. I., Vilhjalmsson, B. J., & Stefansson, K. (2018). The nature of nurture: Effects of parental genotypes. Science, 359, 424–428.CrossRefGoogle ScholarPubMed
Luu, P., Arumugam, E. M. E., Anderson, E., Gunn, A., Rech, D., Turovets, S., & Tucker, D. M. (2016). Slow-frequency pulsed transcranial electrical stimulation for modulation of cortical plasticity based on reciprocity targeting with precision electrical head modeling Frontiers in Human Neuroscience, 10, 377.CrossRefGoogle ScholarPubMed
Markant, J., Cicchetti, D., Hetzel, S., & Thomas, K. M. (2014). Contributions of COMT Val158 Met to cognitive stability and flexibility in infancy. Development Science, 17, 396–411.CrossRefGoogle ScholarPubMed
Matthews, M., & Fair, D. A., (2015). Research review: Functional brain connectivity and child psychopathology – Overview and methodological consideration for investigators new to the field. Journal of Child Psychology and Psychiatry, 56, 400–414.CrossRefGoogle ScholarPubMed
Morrison, J. H., & Foote, S. L. (1986). Noradrenergic and serotoninergic innervation of cortical, thalamic and tectal visual structures in Old and New World monkeys. The Journal of Comparative Neurology, 243, 117–128.CrossRefGoogle ScholarPubMed
Ochsner, K. N., Bunge, S. A., Gross, J. J., & Gabrieli, J. D. E. (2002). Rethinking feelings: An fMRI study of the cognitive regulation of emotion. Journal of Cognitive Neuroscience, 14, 1215–1229.CrossRefGoogle ScholarPubMed
Parasuraman, R., Greenwood, P. M., Kumar, R., & Fossella, J. (2005). Beyond heritability: Neurotransmitter genes differentially modulate visuospatial attention and working memory. Psychological Science, 16, 200–207.CrossRefGoogle ScholarPubMed
Parkes, L., Fulcher, B., Yücel, M., & Fornito, A. (2018). An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI Neuroimage, 171, 415–436.Google Scholar
Petersen, S. E., & Posner, M. I. (2012). The attention system of the human brain: Twenty years after Annual Review of Neuroscience, 35, 71–89.CrossRefGoogle Scholar
Pfaff, D. W., & Kieffer, B. L. (2008). Molecular and biophysical mechanisms of arousal, alertness, and attention. Annals of the New York Academy of Sciences, 1129, xi.Google ScholarPubMed
Piscopo, D. M., Weible, A. P., Rothbart, M. K., Posner, M. K. I., & Niell, C. M. (2018). Mechanisms of white matter change in mice given low frequency stimulation. Proceedings of the National Academy of Sciences (USA), 115, 6639–6646.Google Scholar
Posner, M. I. (1978). Chronometric Explorations of Mind. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Posner, M. I. (2008). Measuring alertness. Annals of the New York Academy of Sciences, 1129, 193–199.CrossRefGoogle ScholarPubMed
Posner, M. I., & Fan, J. (2008). Attention as an organ system. In Pomerantz, J. R. (ed.), Topics in Integrative Neuroscience (Ch. 2; pp. 31–61). New York: Cambridge University Press.CrossRefGoogle Scholar
Posner, M. I., & Rothbart, M. K. (2007a). Research on attention networks as a model for integration of psychological science Annual Review of Psychology, 58, 1–23.CrossRefGoogle Scholar
Posner, M. I., & Rothbart, M. K. (2007b). Educating the Human Brain. Washington, DC: APA Books.CrossRefGoogle Scholar
Posner, M. I., & Rothbart, M. K. (2018). Parenting and human brain development. In Sanders, M. R., & Morawska, A. (eds.), Handbook of Parenting and Child Development Across the Lifespan (pp. 173–200). New York: Springer.CrossRefGoogle Scholar
Posner, M. I., Rothbart, M. K., Sheese, B. E., & Voelker, P. (2014a). Developing attention: Behavioral and brain mechanisms. Advances in Neuroscience, 2014, 405094.Google Scholar
Posner, M. I., Tang, Y. Y., & Lynch, G. (2014b). Mechanisms of white matter change induced by meditation. Frontiers in Psychology, 5, 1220.CrossRefGoogle ScholarPubMed
Pozuelos, J. P., Paz-Alonso, P. M., Castillo, A., Fuentes, L. J., & Rueda, M. R. (2014). Development of attention networks and their interactions in childhood. Developmental Psychology, 50, 102405–102415.CrossRefGoogle ScholarPubMed
Reinhart, R. M. G. (2017). Disruption and rescue of interareal theta phase coupling and adaptive behavior. Proceedings of the National Academy of Sciences (USA), 114, 201710257.CrossRefGoogle ScholarPubMed
Rothbart, M. K. (2011). Becoming Who We Are. New York: Guilford Press.Google Scholar
Rothbart, M. K., & Rueda, M. R. (2005). The development of effortful control. In Mayr, U., Awh, E., & Keele, S. W. (eds.), Developing Individuality in the Human Brain: A Tribute to Michael I. Posner (pp. 167–188). Washington, DC: American Psychological Association.Google Scholar
Rothbart, M. K., & Sheese, B. E. (2007). Temperament and emotion regulation. In Gross, J. J. (ed.), Handbook of Emotion Regulation (pp. 331–350). New York: Guilford Press.Google Scholar
Rothbart, M. K., Sheese, B. E., Rueda, M. R., & Posner, M. I. (2011). Developing mechanisms of self-regulation in early life. Emotion Review, 3, 207–213.Google Scholar
Rueda, M., Fan, J., McCandliss, B. D., Halparin, J. D., Gruber, D. B., Lercari, L. P., et al. (2004). Development of attentional networks in childhood. Neuropsychologia, 42, 1029–1040.Google Scholar
Sheese, B. E., Rothbart, M. K., Voelker, P., & Posner, M. I. (2012). The dopamine receptor D4 gene 7 repeat allele interacts with parenting quality to predict effortful control in four-year-old children. Child Development Research, 2012, 863242.CrossRefGoogle ScholarPubMed
Sheese, B. E., Voelker, P. M., Rothbart, M. K., & Posner, M. I. (2007). Parenting quality interacts with genetic variation in dopamine receptor DRD4 to influence temperament in early childhood. Development & Psychopathology, 19, 1039–1046.CrossRefGoogle ScholarPubMed
Shulman, G. L., Astafiev, S. V., Franke, D., Pope, D. L. W., Snyder, A. Z., McAvoy, M. P., & Corbett, M. (2009). Interaction of stimulus-driven reorienting and expectation in ventral and dorsal frontoparietal and basal ganglia-cortical networks. Journal of Neuroscience, 29, 4392–4407.CrossRefGoogle ScholarPubMed
Stiles, J., & Jernigan, T. L. (2010). The basics of brain development. Neuropsychological Review, 20, 327–348.CrossRefGoogle ScholarPubMed
Swanson, J., Oosterlaan, J., Murias, M., Schuck, S., Flodman, P., Spence, M. A., et al. (2000). Attention deficit/hyperactivity disorder children with a 7-repeat allele of the dopamine receptor D4 gene have extreme behavior but normal performance on critical neuropsychological tests attention. Proceedings of the National Academy of Sciences (USA), 97, 4754–4759.CrossRefGoogle ScholarPubMed
Tang, Y.-Y., Lu, Q., Fan, M., Yang, Y., & Posner, M. I. (2012). Mechanisms of wWhite matter changes induced by meditation. Proceedings of the National Academy of Sciences (USA), 109, 10570–10574.CrossRefGoogle Scholar
Tang, Y. Y., Lu, Q., Geng, X., Stein, E. A., Yang, Y., & Posner, M. I. (2010). Short term mental training induces white-matter changes in the anterior cingulate. Proceedings of the National Academy of Sciences (USA), 107, 16649–16652.CrossRefGoogle ScholarPubMed
Thomason, M. E., Brown, J. A., Dassanayake, M. T., Shastri, R., Marusak, H. A., Hernandez-Anrade, E., et al. (2014). Intrinsic functional brain architecture derived from graph theoretical analysis in the human fetus. PLoS ONE, 9, e94423.Google Scholar
Thomason, M. E., Grove, L. E., Lozon, T. A., Vila, A. M. , Ye, Y. Q., Nye, M. J., et al. (2015). Age-related increases in long-range connectivity in fetal functional neural connectivity networks in utero. Developmental Cognitive Neuroscience, 11, 96–104.CrossRefGoogle ScholarPubMed
Thompson, K. G., Biscoe, K. L., & Sato, T. R. (2005). Neuronal basis of covert spatial attention in the frontal eye fields. Journal of Neuroscience, 25, 9479–9487.Google Scholar
Van Dijk, K. R., Sabuncu, M. R., & Buckner, R. L. (2012). The influence of head motion on intrinsic functional connectivity MRI. NeuroImage, 59, 431–438.CrossRefGoogle ScholarPubMed
Van Ijzendoorn, M. H., & Bakermans-Kranenburg, M. J. (2006). DRD4 7-repeat polymorphism moderates the association between maternal unresolved loss or trauma and infant disorganization, Attachment and Human Development, 8, 291–307.CrossRefGoogle ScholarPubMed
Vértes, P. E., & Bullmore, E. T. (2015). Annual research review: Growth connectomics – The organization and reorganization of brain networks during normal and abnormal development. Journal of Child Psychology and Psychiatry, 56, 299–320.CrossRefGoogle ScholarPubMed
Voelker, P., Sheese, B. E., Rothbart, M. K., & Posner, M. I. (2009). Variations in COMT gene interact with parenting to influence attention in early development. Neuroscience, 164, 121–130.CrossRefGoogle ScholarPubMed
Wang, E. T., Kodama, G., Baldi, P., & Moyzis, R. K. (2006). Global landscape of recent inferred Darwinian selection for Homo sapiens. Proceedings of the National Academy of Science (USA), 103, 135–140.CrossRefGoogle ScholarPubMed
Wang, S., & Young, K. M. (2014). White matter plasticity in adulthood. Neuroscience, 276, 148–160.CrossRefGoogle ScholarPubMed
Weible, A. P., Piscopo, D. M., Rothbart, M. K., Posner, M. I., & Niell, C. M. (2017). Rhythmic brain stimulation reduces anxiety-related behavior in a mouse model based on meditation training. Proceedings of the National Academy of Sciences (USA), 114, 2532–2537.CrossRefGoogle Scholar
Winterer, G., Musso, F., Konrad, A., Vucurevic, G., Stoeter, P., Sander, T., & Gallinat, J. (2007). Association of attentional network function with exon 5 variations of the CHRNA4 gene. Human Molecular Genetics, 16, 2165–2174.CrossRefGoogle ScholarPubMed
Wynn, K. (1992). Addition and subtraction by human infants. Nature, 358, 749–750.Google Scholar
Xue, S., Tang, Y. Y., Tang, R., & Posner, M. I. (2014). Short-term meditation induces changes in brain resting EEG theta networks. Brain and Cognition, 87, 1–6.CrossRefGoogle ScholarPubMed
Zhu, M., & Zhao, S. (2007). Candidate gene identification approach: Progress and challenges. International Journal of Biological Studies, 3, 420–427.Google ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×