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Cognitive and behavioural flexibility: neural mechanisms and clinical considerations

Nature Reviews Neuroscience volume 22, pages 167–179 (2021)Cite this article

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Abstract

Cognitive and behavioural flexibility permit the appropriate adjustment of thoughts and behaviours in response to changing environmental demands. Brain mechanisms enabling flexibility have been examined using non-invasive neuroimaging and behavioural approaches in humans alongside pharmacological and lesion studies in animals. This work has identified large-scale functional brain networks encompassing lateral and orbital frontoparietal, midcingulo-insular and frontostriatal regions that support flexibility across the lifespan. Flexibility can be compromised in early-life neurodevelopmental disorders, clinical conditions that emerge during adolescence and late-life dementias. We critically evaluate evidence for the enhancement of flexibility through cognitive training, physical activity and bilingual experience.

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Fig. 1: Core cognitive processes and brain network interactions underlying flexibility in the human brain.
Fig. 2: Brain dynamics underlying individual differences in flexibility.
Fig. 3: Quantifying brain signal variability.

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References

  1. Moradian, N. et al. The urgent need for integrated science to fight COVID-19 pandemic and beyond. J. Transl Med. 18, 205 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Diamond, A. & Lee, K. Interventions shown to aid executive function development in children 4 to 12 years old. Science 333, 959–964 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Burt, K. B. & Paysnick, A. A. Resilience in the transition to adulthood. Dev. Psychopathol. 24, 493–505 (2012).

    Article  PubMed  Google Scholar 

  4. Burke, S. N. et al. What are the later life contributions to reserve, resilience, and compensation? Neurobiol. Aging 83, 140–144 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Scott, W. A. Cognitive complexity and cognitive flexibility. Sociometry 25, 405–414 (1962).

    Article  Google Scholar 

  6. Brown, V. J. & Tait, D. S. Behavioral flexibility: attentional shifting, rule switching, and response reversal. Encycl. Psychopharmacol. https://doi.org/10.1007/978-3-642-27772-6_340-2 (2014).

    Article  Google Scholar 

  7. Miyake, A. et al. The unity and diversity of executive functions and their contributions to complex ‘frontal lobe’ tasks: a latent variable analysis. Cogn. Psychol. 41, 49–100 (2000).

    Article  CAS  PubMed  Google Scholar 

  8. Poldrack, R. A. et al. The cognitive atlas: toward a knowledge foundation for cognitive neuroscience. Front. Neuroinform. 5, 17 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Teuber, H.-L. Unity and diversity of frontal lobe functions. Acta Neurobiol. Exp. 32, 615–656 (1972).

    CAS  Google Scholar 

  10. Badre, D. Opening the gate to working memory. Proc. Natl Acad. Sci. USA 109, 19878–19879 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Chatham, C. H. & Badre, D. Multiple gates on working memory. Curr. Opin. Behav. Sci. 1, 23–31 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Ott, T. & Nieder, A. Dopamine and cognitive control in prefrontal cortex. Trends Cogn. Sci. 23, 213–234 (2019).

    Article  PubMed  Google Scholar 

  13. Banich, M. T. Executive function: the search for an integrated account. Curr. Dir. Psychol. Sci. 18, 89–94 (2009).

    Article  Google Scholar 

  14. Butter, C. M. Perseveration in extinction and in discrimination reversal tasks following selective frontal ablations in Macaca mulatta. Physiol. Behav. 4, 163–171 (1969).

    Article  Google Scholar 

  15. Izquierdo, A., Brigman, J. L., Radke, A. K., Rudebeck, P. H. & Holmes, A. The neural basis of reversal learning: an updated perspective. Neuroscience 345, 12–26 (2017).

    Article  CAS  PubMed  Google Scholar 

  16. Insel, T. R. The NIMH research domain criteria (RDoC) project: precision medicine for psychiatry. Am. J. Psychiatry 171, 395–397 (2014).

    Article  PubMed  Google Scholar 

  17. Saggar, M. & Uddin, L. Q. Pushing the boundaries of psychiatric neuroimaging to ground diagnosis in biology. eNeuro https://doi.org/10.1523/ENEURO.0384-19.2019 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  18. National Institute of Mental Health. National Advisory Mental Health Council Workgroup on Tasks and Measures for Research Domain Criteria. Behavioral assessment methods for RDoC constructs (NIH, 2016).

  19. Cepeda, N. J., Kramer, A. F. & Gonzalez de Sather, J. C. M. Changes in executive control across the life span: examination of task-switching performance. Dev. Psychol. 37, 715–730 (2001).

    Article  CAS  PubMed  Google Scholar 

  20. Dajani, D. R. & Uddin, L. Q. Demystifying cognitive flexibility: Implications for clinical and developmental neuroscience. Trends Neurosci. 38, 571–578 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Dang, J., King, K. M. & Inzlicht, M. Why are self-report and behavioral measures weakly correlated? Trends Cogn. Sci. 24, 267–269 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Isquith, P. K., Roth, R. M., Gioia, G. A. & Par, S. Behavior Rating Inventory of Executive Function–Adult Version (BRIEF-A) Interpretive Report (Psychological Assessment Resources, 2006).

  23. Gioia, G. A., Isquith, P. K., Guy, S. C. & Kenworthy, L. Behavior rating inventory of executive function. Child. Neuropsychol. 6, 235–238 (2000).

    Article  Google Scholar 

  24. Zelazo, P. D. The Dimensional Change Card Sort (DCCS): a method of assessing executive function in children. Nat. Protoc. 1, 297–301 (2006).

    Article  PubMed  Google Scholar 

  25. Delis, D. C., Kaplan, E. & Kramer, J. H. Delis-Kaplan Executive Function System (American Psychological Association, 2001).

  26. Brooks, B. L., Sherman, E. M. S. & Strauss, E. NEPSY-II: a developmental neuropsychological assessment, second edition. Child. Neuropsychol. 16, 80–101 (2009).

    Article  Google Scholar 

  27. Cambridge Cognition. Intra-Extra Dimensional Set Shift (IED). https://www.cambridgecognition.com/cantab/cognitive-tests/executive-function/intra-extra-dimensional-set-shift-ied/ (2021).

  28. Uddin, L. Q. Salience processing and insular cortical function and dysfunction. Nat. Rev. Neurosci. 16, 55–61 (2015).

    Article  CAS  PubMed  Google Scholar 

  29. Yarkoni, T., Poldrack, R. A., Nichols, T. E., Van Essen, D. C. & Wager, T. D. Large-scale automated synthesis of human functional neuroimaging data. Nat. Methods 8, 665–670 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Seeley, W. W. et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J. Neurosci. 27, 2349–2356 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Uddin, L. Q., Thomas Yeo, B. T. & Nathan Spreng, R. Towards a universal taxonomy of macro-scale functional human brain networks. Brain Topogr. 32, 926–942 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Derrfuss, J., Brass, M., Neumann, J. & von Cramon, D. Y. Involvement of the inferior frontal junction in cognitive control: meta-analyses of switching and Stroop studies. Hum. Brain Mapp. 25, 22–34 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Dajani, D. R. et al. Measuring cognitive flexibility with the flexible item selection task: from MRI adaptation to individual connectome mapping. J. Cogn. Neurosci. 32, 1026–1045 (2020). This functional neuroimaging study in humans demonstrates that flexible item selection directly engages the left IFJ, which influences activity in other cortical and subcortical brain regions supporting cognitive flexibility.

    Article  PubMed  Google Scholar 

  34. Kim, C., Johnson, N. F., Cilles, S. E. & Gold, B. T. Common and distinct mechanisms of cognitive flexibility in prefrontal cortex. J. Neurosci. 31, 4771–4779 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Sundermann, B. & Pfleiderer, B. Functional connectivity profile of the human inferior frontal junction: involvement in a cognitive control network. BMC Neurosci. 13, 119 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Robbins, T. W. Shifting and stopping: fronto-striatal substrates, neurochemical modulation and clinical implications. Philos. Trans. R. Soc. Lond. B Biol. Sci. 362, 917–932 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Banerjee, A. et al. Value-guided remapping of sensory cortex by lateral orbitofrontal cortex. Nature 585, 245–250 (2020).

    Article  CAS  PubMed  Google Scholar 

  38. Ragozzino, M. E. The contribution of the medial prefrontal cortex, orbitofrontal cortex, and dorsomedial striatum to behavioral flexibility. Ann. NY Acad. Sci. 1121, 355–375 (2007). This review summarizes work in rodents delineating limbic, orbitofrontal and striatal contributions to behavioural flexibility.

    Article  PubMed  Google Scholar 

  39. Hampshire, A. & Owen, A. M. Fractionating attentional control using event-related fMRI. Cereb. Cortex 16, 1679–1689 (2006).

    Article  PubMed  Google Scholar 

  40. Ghahremani, D. G., Monterosso, J., Jentsch, J. D., Bilder, R. M. & Poldrack, R. A. Neural components underlying behavioral flexibility in human reversal learning. Cereb. Cortex 20, 1843–1852. This functional neuroimaging study reveals how human reversal learning and guidance of actions consistent with current reward contingencies engages the lateral OFC, dorsal anterior cingulate cortex and right inferior frontal cortex.

  41. Chang, C. & Glover, G. H. Time–frequency dynamics of resting-state brain connectivity measured with fMRI. Neuroimage 50, 81–98 (2010).

    Article  PubMed  Google Scholar 

  42. Hutchison, R. M. et al. Dynamic functional connectivity: promise, issues, and interpretations. Neuroimage 80, 360–378 (2013).

    Article  PubMed  Google Scholar 

  43. Calhoun, V. D., Miller, R., Pearlson, G. & Adalı, T. The chronnectome: time-varying connectivity networks as the next frontier in fMRI data discovery. Neuron 84, 262–274 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Nomi, J. S. et al. Chronnectomic patterns and neural flexibility underlie executive function. Neuroimage 147, 861–871 (2017). This dynamic functional connectivity analysis demonstrates that individuals with the propensity to exhibit whole-brain dynamics characterized by attenuated correlations between brain regions and greater functional connectivity variability perform better on the WCST, a test of cognitive flexibility.

    Article  PubMed  Google Scholar 

  45. Chen, T., Cai, W., Ryali, S., Supekar, K. & Menon, V. Distinct global brain dynamics and spatiotemporal organization of the salience network. PLoS Biol. 14, e1002469 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Douw, L., Wakeman, D. G., Tanaka, N., Liu, H. & Stufflebeam, S. M. State-dependent variability of dynamic functional connectivity between frontoparietal and default networks relates to cognitive flexibility. Neuroscience 339, 12–21 (2016).

    Article  CAS  PubMed  Google Scholar 

  47. Vidaurre, D., Smith, S. M. & Woolrich, M. W. Brain network dynamics are hierarchically organized in time. Proc. Natl Acad. Sci. USA 114, 12827–12832 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Medaglia, J. D. et al. Functional alignment with anatomical networks is associated with cognitive flexibility. Nat. Hum. Behav. 2, 156–164 (2018). This multimodal neuroimaging study demonstrates how alignment between functional activation and underlying white matter networks is associated with greater cognitive flexibility across individuals.

    Article  PubMed  Google Scholar 

  49. Cohen, J. R. The behavioral and cognitive relevance of time-varying, dynamic changes in functional connectivity. Neuroimage 180, 515–525 (2018).

    Article  PubMed  Google Scholar 

  50. Yin, W. et al. The emergence of a functionally flexible brain during early infancy. Proc. Natl Acad. Sci. USA 117, 23904–23913 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Cabral, J. et al. Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest. Sci. Rep. 7, 5135 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Ezaki, T., Sakaki, M., Watanabe, T. & Masuda, N. Age-related changes in the ease of dynamical transitions in human brain activity. Hum. Brain Mapp. 39, 2673–2688 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Yin, D. et al. Dissociable changes of frontal and parietal cortices in inherent functional flexibility across the human life span. J. Neurosci. 36, 10060–10074 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Allegra, M. et al. Brain network dynamics during spontaneous strategy shifts and incremental task optimization. NeuroImage 217, 116854 (2020).

    Article  PubMed  Google Scholar 

  55. Saggar, M. et al. Towards a new approach to reveal dynamical organization of the brain using topological data analysis. Nat. Commun. 9, 1399 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Uddin, L. Q. Bring the noise: reconceptualizing spontaneous neural activity. Trends Cogn. Sci. https://doi.org/10.1016/j.tics.2020.06.003 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  57. McIntosh, A. R., Kovacevic, N. & Itier, R. J. Increased brain signal variability accompanies lower behavioral variability in development. PLoS Comput. Biol. 4, e1000106 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Garrett, D. D., Kovacevic, N., McIntosh, A. R. & Grady, C. L. The modulation of BOLD variability between cognitive states varies by age and processing speed. Cereb. Cortex 23, 684–693 (2013). This study illustrates how variability of fMRI signals differs in normal ageing, and specifically highlights the fact that older and slower-performing individuals exhibit reduced variability.

    Article  PubMed  Google Scholar 

  59. Garrett, D. D., Kovacevic, N., McIntosh, A. R. & Grady, C. L. Blood oxygen level-dependent signal variability is more than just noise. J. Neurosci. 30, 4914–4921 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Nomi, J. S., Bolt, T. S., Ezie, C., Uddin, L. Q. & Heller, A. S. Moment-to-moment BOLD Signal variability reflects regional changes in neural flexibility across the lifespan. J. Neurosci. https://doi.org/10.1523/JNEUROSCI.3408-16.2017 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Armbruster-Genç, D. J. N., Ueltzhöffer, K. & Fiebach, C. J. Brain signal variability differentially affects cognitive flexibility and cognitive stability. J. Neurosci. 36, 3978–3987 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  62. Garrett, D. D., Epp, S. M., Kleemeyer, M., Lindenberger, U. & Polk, T. A. Higher performers upregulate brain signal variability in response to more feature-rich visual input. Neuroimage 217, 116836 (2020).

    Article  PubMed  Google Scholar 

  63. Snyder, H. R., Miyake, A. & Hankin, B. L. Advancing understanding of executive function impairments and psychopathology: bridging the gap between clinical and cognitive approaches. Front. Psychol. 6, 328 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Lai, C. L. E. et al. Meta-analysis of neuropsychological measures of executive functioning in children and adolescents with high-functioning autism spectrum disorder. Autism Res. 10, 911–939 (2017).

    Article  PubMed  Google Scholar 

  65. Dajani, D. R., Llabre, M. M., Nebel, M. B., Mostofsky, S. H. & Uddin, L. Q. Heterogeneity of executive functions among comorbid neurodevelopmental disorders. Sci. Rep. 6, 36566 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Pennington, B. F. & Ozonoff, S. Executive functions and developmental psychopathology. J. Child. Psychol. Psychiatry 37, 51–87 (1996).

    Article  CAS  PubMed  Google Scholar 

  67. Demetriou, E. A. et al. Autism spectrum disorders: a meta-analysis of executive function. Mol. Psychiatry 23, 1198–1204 (2018).

    Article  CAS  PubMed  Google Scholar 

  68. Landry, O. & Al-Taie, S. A meta-analysis of the Wisconsin Card Sort Task in autism. J. Autism Dev. Disord. 46, 1220–1235 (2016).

    Article  PubMed  Google Scholar 

  69. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5®). (American Psychiatric Association Publishing, 2013).

  70. Lopez, B. R., Lincoln, A. J., Ozonoff, S. & Lai, Z. Examining the relationship between executive functions and restricted, repetitive symptoms of autistic disorder. J. Autism Dev. Disord. 35, 445–460 (2005).

    Article  PubMed  Google Scholar 

  71. Wilkes, B. J. & Lewis, M. H. The neural circuitry of restricted repetitive behavior: Magnetic resonance imaging in neurodevelopmental disorders and animal models. Neurosci. Biobehav. Rev. 92, 152–171 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Uddin, L. Q. Brain mechanisms supporting flexible cognition and behavior in adolescents with autism spectrum disorder. Biol. Psychiatry 89, 172–183 (2021).

    Article  CAS  PubMed  Google Scholar 

  73. Kuntsi, J. & Klein, C. Intraindividual variability in ADHD and its implications for research of causal links. Curr. Top. Behav. Neurosci. 9, 67–91 (2012).

    Article  PubMed  Google Scholar 

  74. Leitner, Y. The co-occurrence of autism and attention deficit hyperactivity disorder in children - what do we know? Front. Hum. Neurosci. 8, 268 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Bloemen, A. J. P. et al. The association between executive functioning and psychopathology: general or specific? Psychol. Med. 48, 1787–1794 (2018).

    Article  CAS  PubMed  Google Scholar 

  76. Sergeant, J. A., Geurts, H. & Oosterlaan, J. How specific is a deficit of executive functioning for attention-deficit/hyperactivity disorder? Behav. Brain Res. 130, 3–28 (2002).

    Article  PubMed  Google Scholar 

  77. Happe, F., Booth, R., Charlton, R. & Hughes, C. Executive function deficits in autism spectrum disorders and attention-deficit/hyperactivity disorder: examining profiles across domains and ages. Brain Cogn. 61, 25–39 (2006).

    Article  PubMed  Google Scholar 

  78. Baez, A. C. et al. Parsing heterogeneity of executive function in typically and atypically developing children: a conceptual replication and exploration of social function. J. Autism Dev. Disord. https://doi.org/10.1007/s10803-019-04290-9 (2019).

    Article  Google Scholar 

  79. Di Martino, A. et al. Shared and distinct intrinsic functional network centrality in autism and attention-deficit/hyperactivity disorder. Biol. Psychiatry 74, 623–632 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Dajani, D. R. et al. Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders. Neuroimage Clin. 21, 101678 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  81. Cordova, M. et al. Heterogeneity of executive function revealed by a functional random forest approach across ADHD and ASD. Neuroimage Clin. 26, 102245 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  82. Vaidya, C. J. et al. Data-driven identification of subtypes of executive function across typical development, attention deficit hyperactivity disorder, and autism spectrum disorders. J. Child. Psychol. Psychiatry 61, 51–61 (2020).

    Article  PubMed  Google Scholar 

  83. Mogadam, A. et al. Magnetoencephalographic (MEG) brain activity during a mental flexibility task suggests some shared neurobiology in children with neurodevelopmental disorders. J. Neurodev. Disord. 11, 19 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Steimke, R. et al. Salience network dynamics underlying successful resistance of temptation. Soc. Cogn. Affect. Neurosci. 12, 1928–1939 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  85. Geurts, H. M., Corbett, B. & Solomon, M. The paradox of cognitive flexibility in autism. Trends Cognit. Sci. 13, 74–82 (2009).

    Article  Google Scholar 

  86. Strang, J. F. et al. The Flexibility Scale: development and preliminary validation of a cognitive flexibility measure in children with autism spectrum disorders. J. Autism Dev. Disord. 47, 2502–2518 (2017).

    Article  PubMed  Google Scholar 

  87. Luna, B., Paulsen, D. J., Padmanabhan, A. & Geier, C. The teenage brain: cognitive control and motivation. Curr. Dir. Psychol. Sci. 22, 94–100 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  88. Casey, B. J., Jones, R. & Hare, T. The adolescent brain. The year in cognitive neuroscience. Ann. NY Acad. Sci. 11, 84–94 (2008).

    Google Scholar 

  89. Hauser, T. U., Iannaccone, R., Walitza, S., Brandeis, D. & Brem, S. Cognitive flexibility in adolescence: neural and behavioral mechanisms of reward prediction error processing in adaptive decision making during development. Neuroimage 104, 347–354 (2015).

    Article  PubMed  Google Scholar 

  90. Burrows, C. A., Timpano, K. R. & Uddin, L. Q. Putative brain networks underlying repetitive negative thinking and comorbid internalizing problems in autism. Clin. Psychol. Sci. 5, 522–536 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  91. Akkermans, S. E. A. et al. Frontostriatal functional connectivity correlates with repetitive behaviour across autism spectrum disorder and obsessive–compulsive disorder. Psychol. Med. 49, 2247–2255 (2019).

    Article  PubMed  Google Scholar 

  92. Gu, B.-M. et al. Neural correlates of cognitive inflexibility during task-switching in obsessive-compulsive disorder. Brain 131, 155–164 (2008).

    Article  PubMed  Google Scholar 

  93. Gruner, P. & Pittenger, C. Cognitive inflexibility in obsessive-compulsive disorder. Neuroscience 345, 243–255 (2017).

    Article  CAS  PubMed  Google Scholar 

  94. Weinberger, D. R. Schizophrenia and the frontal lobe. Trends Neurosci. 11, 367–370 (1988).

    Article  CAS  PubMed  Google Scholar 

  95. Cavallaro, R. et al. Basal-corticofrontal circuits in schizophrenia and obsessive-compulsive disorder: a controlled, double dissociation study. Biol. Psychiatry 54, 437–443 (2003).

    Article  PubMed  Google Scholar 

  96. Waltz, J. A. The neural underpinnings of cognitive flexibility and their disruption in psychotic illness. Neuroscience 345, 203–217 (2017).

    Article  CAS  PubMed  Google Scholar 

  97. Hakun, J. G., Zhu, Z., Johnson, N. F. & Gold, B. T. Evidence for reduced efficiency and successful compensation in older adults during task switching. Cortex 64, 352–362 (2015).

    Article  PubMed  Google Scholar 

  98. Spreng, R. N. & Turner, G. R. The shifting architecture of cognition and brain function in older adulthood. Perspect. Psychol. Sci. 14, 523–542 (2019).

    Article  PubMed  Google Scholar 

  99. Heckner, M. K. et al. The aging brain and executive functions revisited: implications from meta-analytic and functional connectivity evidence. J. Cogn. Neurosci. 1–36 (2020).

  100. Naik, S., Banerjee, A., Bapi, R. S., Deco, G. & Roy, D. Metastability in senescence. Trends Cogn. Sci. 21, 509–521 (2017).

    Article  PubMed  Google Scholar 

  101. McDonald, A. P., D’Arcy, R. C. N. & Song, X. Functional MRI on executive functioning in aging and dementia: a scoping review of cognitive tasks. Aging Med. 1, 209–219 (2018).

    Article  Google Scholar 

  102. Robbins, T. W. & Cools, R. Cognitive deficits in Parkinson’s disease: a cognitive neuroscience perspective. Mov. Disord. 29, 597–607 (2014).

    Article  PubMed  Google Scholar 

  103. Lange, F., Seer, C. & Kopp, B. Cognitive flexibility in neurological disorders: cognitive components and event-related potentials. Neurosci. Biobehav. Rev. 83, 496–507 (2017).

    Article  PubMed  Google Scholar 

  104. Townley, R. A. et al. Progressive dysexecutive syndrome due to Alzheimer’s disease: a description of 55 cases and comparison to other phenotypes. Brain Commun. https://doi.org/10.1093/braincomms/fcaa068 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  105. Ueltzhöffer, K., Armbruster-Genç, D. J. N. & Fiebach, C. J. Stochastic dynamics underlying cognitive stability and flexibility. PLoS Comput. Biol. 11, e1004331 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  106. Clark, L., Cools, R. & Robbins, T. W. The neuropsychology of ventral prefrontal cortex: decision-making and reversal learning. Brain Cognition 55, 41–53 (2004).

    Article  CAS  PubMed  Google Scholar 

  107. Evers, E. A. T. et al. Serotonergic modulation of prefrontal cortex during negative feedback in probabilistic reversal learning. Neuropsychopharmacology 30, 1138–1147 (2005).

    Article  CAS  PubMed  Google Scholar 

  108. Cools, R., Barker, R. A., Sahakian, B. J. & Robbins, T. W. L-Dopa medication remediates cognitive inflexibility, but increases impulsivity in patients with Parkinson’s disease. Neuropsychologia 41, 1431–1441 (2003). This study examining patients with Parkinson disease receiving and not receiving dopaminergic medication shows how dopamine influences cognitive flexibility performance.

    Article  PubMed  Google Scholar 

  109. Martino, A. D., Di Martino, A., Melis, G., Cianchetti, C. & Zuddas, A. Methylphenidate for pervasive developmental disorders: safety and efficacy of acute single dose test and ongoing therapy: an open-pilot study. J. Child. Adolesc. Psychopharmacol. 14, 207–218 (2004).

    Article  PubMed  Google Scholar 

  110. Rajala, A. Z., Populin, L. C. & Jenison, R. L. Methylphenidate affects task-switching and neural signaling in non-human primates. Psychopharmacology 237, 1533–1543 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Bell, T., Lindner, M., Langdon, A., Mullins, P. G. & Christakou, A. Regional striatal cholinergic involvement in human behavioral flexibility. J. Neurosci. 39, 5740–5749 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Prado, V. F., Janickova, H., Al-Onaizi, M. A. & Prado, M. A. M. Cholinergic circuits in cognitive flexibility. Neuroscience 345, 130–141 (2017).

    Article  CAS  PubMed  Google Scholar 

  113. Melby-Lervåg, M. & Hulme, C. Is working memory training effective? A meta-analytic review. Dev. Psychol. 49, 270–291 (2013).

    Article  PubMed  Google Scholar 

  114. Johann, V. E. & Karbach, J. Effects of game-based and standard executive control training on cognitive and academic abilities in elementary school children. Dev. Sci. 23, 197 (2020).

    Article  Google Scholar 

  115. Vries, M. de, de Vries, M., Prins, P. J. M., Schmand, B. A. & Geurts, H. M. Working memory and cognitive flexibility-training for children with an autism spectrum disorder: a randomized controlled trial. J. Child. Psychol. Psychiatry 56, 566–576 (2015).

    Article  PubMed  Google Scholar 

  116. Kenworthy, L. et al. Randomized controlled effectiveness trial of executive function intervention for children on the autism spectrum. J. Child. Psychol. Psychiatry 55, 374–383 (2014).

    Article  PubMed  Google Scholar 

  117. Nguyen, L., Murphy, K. & Andrews, G. Cognitive and neural plasticity in old age: a systematic review of evidence from executive functions cognitive training. Ageing Res. Rev. 53, 100912 (2019).

    Article  PubMed  Google Scholar 

  118. Gaál, Z. A. & Czigler, I. Task-switching training and transfer. J. Psychophysiol. 32, 106–130 (2018).

    Article  Google Scholar 

  119. Diamond, A. & Ling, D. S. Conclusions about interventions, programs, and approaches for improving executive functions that appear justified and those that, despite much hype, do not. Dev. Cogn. Neurosci. 18, 34–48 (2016).

    Article  PubMed  Google Scholar 

  120. Firth, J. et al. Effect of aerobic exercise on hippocampal volume in humans: a systematic review and meta-analysis. Neuroimage 166, 230–238 (2018).

    Article  PubMed  Google Scholar 

  121. Meijer, A. et al. Cardiovascular fitness and executive functioning in primary school-aged children. Dev. Sci. https://doi.org/10.1111/desc.13019 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  122. Stillman, C. M., Esteban-Cornejo, I., Brown, B., Bender, C. M. & Erickson, K. I. Effects of exercise on brain and cognition across age groups and health states. Trends Neurosci. 43, 533–543 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Bialystok, E., Craik, F. I. M. & Luk, G. Bilingualism: consequences for mind and brain. Trends Cogn. Sci. 16, 240–250 (2012). This review explores potential mechanisms underlying the effects of bilingualism on cognition in adults.

    Article  PubMed  PubMed Central  Google Scholar 

  124. Carlson, S. M. & Meltzoff, A. N. Bilingual experience and executive functioning in young children. Dev. Sci. 11, 282–298 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  125. Rodríguez-Pujadas, A. et al. Bilinguals use language-control brain areas more than monolinguals to perform non-linguistic switching tasks. PLoS ONE 8, e73028 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  126. Buchweitz, A. & Prat, C. The bilingual brain: flexibility and control in the human cortex. Phys. Life Rev. 10, 428–443 (2013).

    Article  PubMed  Google Scholar 

  127. Hartanto, A., Toh, W. X. & Yang, H. Bilingualism narrows socioeconomic disparities in executive functions and self-regulatory behaviors during early childhood: evidence from the early childhood longitudinal study. Child. Dev. 90, 1215–1235 (2019).

    Article  PubMed  Google Scholar 

  128. Dick, A. S. et al. No evidence for a bilingual executive function advantage in the ABCD study. Nat. Hum. Behav. 3, 692–701 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  129. Nichols, E. S., Wild, C. J., Stojanoski, B., Battista, M. E. & Owen, A. M. Bilingualism affords no general cognitive advantages: a population study of executive function in 11,000 people. Psychol. Sci. 31, 548–567 (2020).

    Article  PubMed  Google Scholar 

  130. Dash, T., Berroir, P., Joanette, Y. & Ansaldo, A. I. Alerting, orienting, and executive control: the effect of bilingualism and age on the subcomponents of attention. Front. Neurol. 10, 1122 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  131. Costumero, V. et al. A cross-sectional and longitudinal study on the protective effect of bilingualism against dementia using brain atrophy and cognitive measures. Alzheimers. Res. Ther. 12, 11 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  132. Gabrys, R. L., Tabri, N., Anisman, H. & Matheson, K. Cognitive control and flexibility in the context of stress and depressive symptoms: the cognitive control and flexibility questionnaire. Front. Psychol. 9, 2219 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  133. Martin, M. M. & Rubin, R. B. A new measure of cognitive flexibility. Psychol. Rep. 76, 623–626 (1995).

    Article  Google Scholar 

  134. Ben-Itzhak, S., Bluvstein, I. & Maor, M. The Psychological Flexibility Questionnaire (PFQ): development, reliability and validity. WebmedCentral Psychol. https://doi.org/10.9754/journal.wmc.2014.004606 (2014).

    Article  Google Scholar 

  135. Kenworthy, L. et al. Preliminary psychometrics for the executive function challenge task: a novel, ‘hot’ flexibility, and planning task for youth. J. Int. Neuropsychol. Soc. 26, 725–732 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  136. Zelazo P. D., C. W. A. Executive function: mechanisms underlying emotion regulation. in Handbook of Emotion Regulation (ed. Gross, J. J.) 135–158 (Guilford, 2007).

  137. Goodkind, M. et al. Identification of a common neurobiological substrate for mental illness. JAMA Psychiatry 72, 305–315 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  138. Huys, Q. J. M., Maia, T. V. & Frank, M. J. Computational psychiatry as a bridge from neuroscience to clinical applications. Nat. Neurosci. 19, 404–413 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Bolt, T., Nomi, J. S., Yeo, B. T. T. & Uddin, L. Q. Data-driven extraction of a nested model of human brain function. J. Neurosci. 37, 7263–7277 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  140. Finc, K. et al. Dynamic reconfiguration of functional brain networks during working memory training. Nat. Commun. 11, 2435 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Allen, E. A. et al. Tracking whole-brain connectivity dynamics in the resting state. Cereb. Cortex 24, 663–676 (2014).

    Article  PubMed  Google Scholar 

  142. Berg, E. A. A simple objective technique for measuring flexibility in thinking. J. Gen. Psychol. 39, 15–22 (1948).

    Article  CAS  PubMed  Google Scholar 

  143. Grant, D. A. & Berg, E. A. Wisconsin Card Sorting Test. PsycTESTS Dataset https://doi.org/10.1037/t31298-000 (2014).

    Article  Google Scholar 

  144. Bartolo, R. & Averbeck, B. B. Prefrontal cortex predicts state switches during reversal learning. Neuron 106, 1044–1054 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Kenett, Y. N. et al. Developing a neurally informed ontology of creativity measurement. Neuroimage 221, 117166 (2020).

    Article  PubMed  Google Scholar 

  146. Wu, X. et al. A meta-analysis of neuroimaging studies on divergent thinking using activation likelihood estimation. Hum. Brain Mapp. 36, 2703–2718 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  147. Sunavsky, A. & Poppenk, J. Neuroimaging predictors of creativity in healthy adults. Neuroimage 206, 116292 (2020).

    Article  PubMed  Google Scholar 

  148. Becker, M., Sommer, T. & Kühn, S. Inferior frontal gyrus involvement during search and solution in verbal creative problem solving: a parametric fMRI study. Neuroimage 206, 116294 (2020).

    Article  PubMed  Google Scholar 

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Acknowledgements

This work was supported by the US National Institute of Mental Health (R01MH107549), the Canadian Institute for Advanced Research and a Gabelli Senior Scholar award from the University of Miami to L.Q.U.

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  1. Department of Psychology, University of Miami, Coral Gables, FL, USA

    Lucina Q. Uddin

  2. Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, USA

    Lucina Q. Uddin

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Correspondence to Lucina Q. Uddin.

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Nature Reviews Neuroscience thanks L. Kenworthy, R. Cools and the other, anonymous, reviewer for their contribution to the peer review of this work.

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MRIcron: https://www.nitrc.org/projects/mricron

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University of Miami Brain Connectivity and Cognition Laboratory: https://bccl.psy.miami.edu/

Glossary

Latent variable analysis

A statistical approach for identifying clusters based on a series of continuous variables or indicators. This type of analysis assumes that there are unobserved latent profiles that generate responses on indicator items.

Mental set-shifting

Also referred to as ‘shifting’, this refers to the ability to switch back and forth between multiple tasks.

Prepotent responses

Automatic behavioural responses with which immediate reinforcement is associated. Executive functions are necessary for overriding prepotent responses.

Diagnostic nosology

A system for classification of diseases.

RDoC matrix

The research domain criteria (RDoC) matrix is a tool to help implement the principles of RDoC in research studies.

Construct validity

In psychology, the idea that a test is valid if it measures what it claims to measure or is designed to measure.

Divergent thinking

In the study of creativity, the type of thinking used in an open-ended task, such as coming up with multiple uses for a given object.

Ecological validity

In psychology, the idea that something measured with a laboratory test translates to performance in real-life settings.

Cognitive constructs

In psychology, cognitive constructs are terms used to described mental processes. Examples of cognitive constructs include ‘attention‘, ‘memory’ and ‘perception’.

Extradimensional shifts

In set-shifting tasks, an extradimensional shift is one in which the important aspect of a stimulus switches from one category to another (for example, in a discrimination task, when colour is no longer an informative aspect of the stimulus, and shape becomes the discriminating characteristic).

Hidden Markov models

Statistical models in which the system being modelled is assumed to be a Markov process (where the probability of each event depends on the state in the previous event) with unobservable or hidden states.

Metastability

A state of a dynamical system other than the state of least energy. In a non-linear system such as the brain, ‘metastability’ refers to a state in which signals fall outside their natural equilibrium state, but persist for an extended period of time.

Transfer effects

Phenomena in which training or learning in one context applies to another.

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Uddin, L.Q. Cognitive and behavioural flexibility: neural mechanisms and clinical considerations. Nat Rev Neurosci 22, 167–179 (2021). https://doi.org/10.1038/s41583-021-00428-w

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