Enhancing flow states in neurodivergent individuals through cognitive network integration
This article explores the concept of “flow” in the context of neurodivergence, focusing on the interaction between the default mode network (DMN) and task-positive networks (TPNs), particularly in conditions such as autism spectrum condition (ASC) and attention-deficit/hyperactivity disorder (ADHD). Flow, a state of deep immersion and focused engagement, is associated with enhanced performance and satisfaction across activities. The DMN, typically active during rest and self-referential thinking, interacts uniquely with TPNs during flow states, creating a dynamic balance crucial for sustained focus and reduced self-referential thinking. Neurodivergent individuals often exhibit distinct DMN activity patterns, which affect their capacity for achieving flow. For instance, individuals with ADHD may experience flow in stimulating tasks, whereas those with ASC may achieve it in areas of deep interest due to their intense focus. This paper examines the expertise-and-release model in creative flow and transient hypofrontality as a potential mechanism facilitating flow in neurodivergent individuals. It also proposes strategies to enhance flow through personalized cognitive training, specialized task environments, and technology-assisted interventions, aiming to harness neurodivergent strengths and accommodate unique cognitive profiles. This comprehensive analysis deepens understanding of neurodiversity and offers practical applications for improving quality of life and performance in neurodivergent populations.
Ayaz, H., & Dehais, F. (2021). Neuroergonomics. Handbook of Human Factors and Ergonomics. United States: Wiley, p.816-841.
Bailey, C. (2023). Neurodivergent literacies: Exploring autistic adults’ ruling passions’ and embracing neurodiversity through classroom literacies. Literacy, 57(2):120-131.
Beason-Held, L., Beason-Held, L., Kraut, M., & Resnick, S. (2009). Stability of default-mode network activity in the aging brain. Brain Imaging and Behavior, 3:123-131. https://doi.org/10.1007/s11682-008-9054-z
Blumberg, H., Stern, E., Ricketts, S., Martinez, D., Asis, J., White, T., et al. (1999). Rostral and orbital prefrontal cortex dysfunction in the manic state of bipolar disorder. The American Journal of Psychiatry, 156(12):1986-1988. https://doi.org/10.1176/AJP.156.12.1986
Broyd, S.J., Demanuele, C., Debener, S., Helps, S.K., James, C.J., & Sonuga-Barke, EJ.S. (2009). Default-mode brain dysfunction in mental disorders: A systematic review. Neuroscience and Biobehavioral Reviews, 33:279-296. https://doi.org/10.1016/j.neubiorev.2008.09.002
Butnik, S. (2005). Neurofeedback in adolescents and adults with attention deficit hyperactivity disorder. Journal of Clinical Psychology, 61(5):621-625. https://doi.org/10.1002/JCLP.20124
Callara, A.L., Greco, A., Scilingo, E.P., & Bonfiglio, L. (2023). Neuronal correlates of eyeblinks are an expression of primary consciousness phenomena. Scientific Reports, 13(1):12617. https://doi.org/10.1038/s41598-023-39500-z
Carroll, J. (2020). Imagination, the brain’s default mode network, and imaginative verbal artifacts. In: Evolutionary Perspectives on Imaginative Culture. Berlin: Springer, p.31-52.
Carter, C., Perlstein, W., Ganguli, R., Brar, J., Mintun, M., & Cohen, J. (1998). Functional hypofrontality and working memory dysfunction in schizophrenia. The American Journal of Psychiatry, 155(9):1285-1287. https://doi.org/10.1176/AJP.155.9.1285
Chacón, M.P. (2021). High Sensitivity and Mental Health. Italy: Tektime.
Chen, J., & Mokmin, N.A.M. (2024). Enhancing primary school students’ performance, flow state, and cognitive load in visual arts education through the integration of augmented reality technology in a card game. In: Education and Information Technologies. Berlin: Springer, p.1-21.
Chowdhury, D., Banerjee, P., Vice-Chancellor, I.I.L.M., Moreira, A., Narendran, R., Scholar, A.T., et al. (2024). Adaptive Neurosciences and Neuro-Integral Methodology. Bulletin for Technology and History Journal, 24(6): 218-324.
Curtin, P., Neufeld, J., Curtin, A., Austin, C., Isaksson, J., Remnelius, K.L., et al. (2023). Associations between elemental metabolic dynamics and default mode network functional connectivity are altered in autism. Journal of Clinical Medicine, 12(3):1022. https://doi.org/10.3390/jcm12031022
Davidson, C.I. (2020). Thinking up, Writing Down: The Artistic Creativity, Phenomenology and Neurobiology of the Creative Writing Process (Doctoral Dissertation, University of Surrey).
De La Serna, J.M., Chacón, M.P., & Chacón, A. (2021). High Sensitivity and Mental Health. Litres. Italy: Tektime.
Desaunay, P., Guillery, B., Moussaoui, E., Eustache, F., Bowler, D.M., & Guénolé, F. (2023). Brain correlates of declarative memory atypicalities in autism: A systematic review of functional neuroimaging findings. Molecular Autism, 14(1):2. https://doi.org/10.1186/s13229-022-00525-2
Di, X., & Biswal, B. (2014). Identifying the default mode network structure using dynamic causal modeling on resting-state functional magnetic resonance imaging. NeuroImage, 86:53-59. https://doi.org/10.1016/j.neuroimage.2013.07.071
Dietrich, A. (2003). Functional neuroanatomy of altered states of consciousness: The transient hypofrontality hypothesis. Consciousness and Cognition, 12:231-256. https://doi.org/10.1016/S1053-8100(02)00046-6
Dietrich, A. (2004). Neurocognitive mechanisms underlying the experience of flow. Consciousness and Cognition, 13:746-761. https://doi.org/10.1016/j.concog.2004.07.002
Dietrich, A. (2006). Transient hypofrontality as a mechanism for the psychological effects of exercise. Psychiatry Research, 145:79-83. https://doi.org/10.1016/j.psychres.2005.07.033
Djebbara, Z., King, J., Ebadi, A., Nakamura, Y., & Bermudez, J. (2024). Contemplative neuroaesthetics and architecture: A sensorimotor exploration. Frontiers of Architectural Research, 13(1):97-111.
Duke, M.M. (2023). Here, then Gone: An Interpretative Phenomenological Analysis of how Young Adults with ADHD Experience Mind Wandering. California: Saybrook University.
Fajardo-Valdez, A., Camacho-Téllez, V., Rodríguez-Cruces, R., García-Gomar, M.L., Pasaye, E.H. and Concha, L. (2024). Functional correlates of cognitive performance and working memory in temporal lobe epilepsy: Insights from task-based and resting-state fMRI. PLoS One, 19(3):e0295142. https://doi.org/10.1371/journal.pone.0295142
Faraone, S.V., Biederman, J. (1998). Neurobiology of attention-deficit hyperactivity disorder. Biol Psychiatry. 44(10):951-8. https://doi.org/10.1016/s0006-3223(98)00240-6
Fink, M., Pasche, S., Schmidt, K., Tewes, M., Schuler, M., Mülley, B., et al. (2023). Neurofeedback treatment affects affective symptoms, but not perceived cognitive impairment in cancer patients: Results of an explorative randomized controlled trial. Integrative Cancer Therapies, 22:15347354221149950. https://doi.org/10.1177/15347354221149950
Fischman, L. (2023). Touching and being touched: where knowing and feeling meet. Frontiers in Psychology, 14:1097402.
Friedrich, E., Sivanathan, A., Lim, T., Suttie, N., Louchart, S., Pillen, S., et al. (2015). An effective neurofeedback intervention to improve social interactions in children with autism spectrum disorder. Journal of Autism and Developmental Disorders, 45:4084-4100. https://doi.org/10.1007/s10803-015-2523-5
George, M., Ketter, T., Parekh, P., Horwitz, B., Herscovitch, P., & Post, R. (1995). Brain activity during transient sadness and happiness in healthy women. The American Journal of Psychiatry, 152(3):341-351. https://doi.org/10.1176/AJP.152.3.341
Greicius, M., Srivastava, G., Reiss, A., & Menon, V. (2004). Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: Evidence from functional MRI. Proceedings of the National Academy of Sciences of the United States of America, 101(13):4637-4642. https://doi.org/10.1073/PNAS.0308627101
Hamilton, A. (2024). The neuroscience of play. In: Seriously Therapeutic Play with LEGO®. London: Routledge, p.31-48.
Heasman, B., Williams, G., Charura, D., Hamilton, L.G., Milton, D., & Murray, F. (2024). Towards autistic flow theory: A non‐pathologising conceptual approach. Journal for the Theory of Social Behaviour, 1-29. https://doi.org/10.1111/jtsb.12427
Horgan, F., Kenny, N., & Flynn, P. (2023). A systematic review of the experiences of autistic young people enrolled in mainstream second-level (post-primary) schools. Autism, 27(2):526-538.
Hosseini, S., Pritchard-Berman, M., Sosa, N., Ceja, A., & Kesler, S. (2016). Task-based neurofeedback training: A novel approach toward training executive functions. NeuroImage, 134:153-159. https://doi.org/10.1016/j.neuroimage.2016.03.035
Jiang, Y., Abiri, R., & Zhao, X. (2017). Tuning up the old brain with new tricks: Attention training via neurofeedback. Frontiers in Aging Neuroscience, 9:52. https://doi.org/10.3389/fnagi.2017.00052
Khalil, R., & Demarin, V. (2024). Creative therapy in health and disease: Inner vision. CNS Neuroscience and Therapeutics, 30(3):e14266.
Lesourd, M., Osiurak, F., Hague, S., Levitre, M., Clément, G., de Bustos, E.M., et al. (2024). Neurocognitive Mechanisms Underlying Action Tool Knowledge Tasks: The Specificity of Tool-Tool Compared to Hand-Tool Manipulation Tasks.
Lloyd-Cox, J. (2024). The Neural and Cognitive Mechanisms Underlying Creative Thinking (Doctoral dissertation, Goldsmiths, University of London).
Lopata, J.A., Barr, N., Slayton, M., & Seli, P. (2022). Dual-modes of creative thought in the classroom: Implications of network neuroscience for creativity education. Translational Issues in Psychological Science, 8(1):79.
Masterpasqua, F., & Healey, K. (2003). Neurofeedback in psychological practice. Professional Psychology: Research and Practice, 34:652-656. https://doi.org/10.1037/0735-7028.34.6.652
Maw, K.J., Beattie, G., & Burns, E.J. (2024). Cognitive strengths in neurodevelopmental disorders, conditions and differences: A critical review. Neuropsychologia, 197:108850.
Megari, K., Frantzezou, C.K., Polyzopoulou, Z.A., & Tzouni, S.K. (2024). Neurocognitive features in childhood & adulthood in autism spectrum disorder: A neurodiversity approach. International Journal of Developmental Neuroscience, 84(6):471-499.
Nejati, V., Fallah, F., & Raskin, S. (2023). Inhibitory control training improves attention deficit-hyperactivity disorder symptoms and externalizing behavior. Clinical Child Psychology and Psychiatry, 28(3):909-923.
Norris, N.G. (2023). How does my student learn? Neurodiversity and the nature of learning in autism. International Journal of Christianity and Education, 27(1):65-87.
Ogrodnik, M., Karsan, S., Malamis, B., Kwan, M., Fenesi, B., & Heisz, J.J. (2024). Exploring barriers and facilitators to physical activity in adults with ADHD: A qualitative investigation. Journal of Developmental and Physical Disabilities, 36(2):307-327.
Parvizi-Wayne, D., Sandved-Smith, L., Pitliya, R.J., Limanowski, J., Tufft, M.R., & Friston, K.J. (2024). Forgetting ourselves in flow: An active inference account of flow states and how we experience ourselves within them. Frontiers in Psychology, 15:1354719.
Peterson, D.R., & Pattie, M.W. (2024). Think outside and inside the box: The role of dual-pathway divergent thinking in creative idea generation. Creativity Research Journal, 36(2):272-290.
Pfefferbaum, A., Chanraud, S., Pitel, A., Müller-Oehring, E., Shankaranarayanan, A., Alsop, D., et al. (2011). Cerebral blood flow in posterior cortical nodes of the default mode network decreases with task engagement but remains higher than in most brain regions. Cerebral Cortex, 21(1):233-244. https://doi.org/10.1093/cercor/bhq090
Picó-Pérez, M., Fullana, M.A., Albajes-Eizagirre, A., Vega, D., Marco-Pallarés, J., Vilar, A., et al. (2023). Neural predictors of cognitive-behavior therapy outcome in anxiety-related disorders: A meta-analysis of task-based fMRI studies. Psychological Medicine, 53(8):3387-3395.
Raichle, M. (2015). The brain’s default mode network. Annual Review of Neuroscience, 38:433-447. https://doi.org/10.1146/annurev-neuro-071013-014030
Ramot, M., Kimmich, S., Gonzalez-Castillo, J., Roopchansingh, V., Popal, H., White, E., et al. (2017). Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback. eLife, 6:e28974. https://doi.org/10.1101/139824
Rządeczka, M., Wodziński, M., & Moskalewicz, M. (2023). Cognitive biases as an adaptive strategy in autism and schizophrenia spectrum: The compensation perspective on neurodiversity. Frontiers in Psychiatry, 14:1291854.
Santarnecchi, E., Momi, D., Sprugnoli, G., Neri, F., Pascual‐ Leone, A., Rossi, A., et al. (2018). Modulation of network‐to‐network connectivity via spike‐timing‐dependent noninvasive brain stimulation. Human Brain Mapping, 39(12):4870-4883.
Savickaite, S. (2024). Using Virtual Reality to Explore Individual Differences in Perception Due to Neurodiversity (Doctoral Dissertation, University of Glasgow).
Schauder, K.B., Muller, C.L., Veenstra-VanderWeele, J., & Cascio, C.J. (2015). Genetic variation in serotonin transporter modulates tactile hyperresponsiveness in ASD. Research in Autism Spectrum Disorders, 10:93-100.
Seeburger, D.T., Xu, N., Ma, M., Larson, S., Godwin, C., Keilholz, S.D., et al. (2024). Time-varying functional connectivity predicts fluctuations in sustained attention in a serial tapping task. Cognitive, Affective, and Behavioral Neuroscience, 24(1):111-125.
Senkowski, D., Ziegler, T., Singh, M., Heinz, A., He, J., Silk, T., et al. (2024). Assessing inhibitory control deficits in adult ADHD: A systematic review and meta-analysis of the stop-signal task. Neuropsychology Review, 34(2):548-567.
Spreng, R. (2012). The fallacy of a “task-negative” network. Frontiers in Psychology, 3:145. https://doi.org/10.3389/fpsyg.2012.00145
Tondelli, M., Manigrasso, M., & Zamboni, G. (2024). Impaired self-awareness in Parkinson’s and Huntington’s diseases: A literature review of neuroimaging correlates. Brain Sciences, 14(3):204.
Trambaiolli, L., Kohl, S., Linden, D., & Mehler, D. (2020). Neurofeedback training in major depressive disorder: A systematic review of clinical efficacy, study quality and reporting practices. Neuroscience and Biobehavioral Reviews, 125:33-56. https://doi.org/10.31234/osf.io/5j4wy
Uddin, L., Kelly, A., Biswal, B., Castellanos, F., Milham, M., & Castellanos, X. (2009). Functional connectivity of default mode network components: Correlation, anticorrelation, and causality. Human Brain Mapping, 30:625-637. https://doi.org/10.1002/hbm.20531
van den Engh, M. (2024). “I’ma fish!” Deepening receptivity to neurodiversity: A neuroscientifically informed integration of psychoanalytic psychotherapy, reciprocal prediction, and mindfulness. Neuropsychoanalysis, 26:1-15.
Vatansever, D., Menon, D., Manktelow, A., Sahakian, B., & Stamatakis, E. (2015). Default mode network connectivity during task execution. NeuroImage, 122:96-104. https://doi.org/10.1016/j.neuroimage.2015.07.053
Vinogradov, S., Fisher, M., & De Villers-Sidani, E. (2012). Cognitive training for impaired neural systems in neuropsychiatric illness. Neuropsychopharmacology, 37(1):43-76.
Volkow, N.D., Fowler, J.S., Wang, G.J., Baler, R., & Telang, F. (2009). Imaging dopamine’s role in drug abuse and addiction. Neuropharmacology, 56:3-8.
Wang, Q., Li, H., Li, Y., Lv, Y., Ma, H., Xiang, A., et al. (2021). Resting-state abnormalities in functional connectivity of the default mode network in autism spectrum disorder: A meta-analysis. Brain Imaging and Behavior, 15:2583-2592. https://doi.org/10.1007/s11682-021-00460-5
Wassner, J. (2024). Acceptance and Commitment Therapy with Children: Applications and Strategies for Anxiety, Depression, Autism, ADHD, OCD and More. United States: Jessica Kingsley Publishers.
Wotruba, D., Michels, L., Buechler, R., Metzler, S., Theodoridou, A., Gerstenberg, M., et al. (2014). Aberrant coupling within and across the default mode, task-positive, and salience network in subjects at risk for psychosis. Schizophrenia Bulletin, 40(5):1095-1104. https://doi.org/10.1093/schbul/sbt161
Yoshida, K., Sawamura, D., Ogawa, K., Ikoma, K., Asakawa, K., Yamauchi, T., et al. (2014). Flow experience during attentional training improves cognitive functions in patients with traumatic brain injury: An exploratory case study. Hong Kong Journal of Occupational Therapy, 24:81-87. https://doi.org/10.1016/j.hkjot.2015.01.001
Yuan, Y., Pan, X., & Wang, R. (2021). Biophysical mechanism of the interaction between default mode network and working memory network. Cognitive Neurodynamics, 15(6):1101-1124.
Zhuang, K., Zeitlen, D.C., Beaty, R.E., Vatansever, D., Chen, Q., & Qiu, J. (2023). Diverse functional interaction driven by control-default network hubs supports creative thinking. Cerebral Cortex, 33(23):11206-11224.