Book contents
- The Cambridge Handbook of the Imagination
- The Cambridge Handbook of the Imagination
- Copyright page
- Dedication
- Contents
- Figures
- Contributors
- Acknowledgments
- 1 Surveying the Imagination Landscape
- Part I Theoretical Perspectives on the Imagination
- Part II Imagery-Based Forms of the Imagination
- Part III Intentionality-Based Forms of the Imagination
- Part IV Novel Combinatorial Forms of the Imagination
- Part V Phenomenology-Based Forms of the Imagination
- Part VI Altered States of the Imagination
- 40 Dreaming: Beyond Imagination and Perception
- 41 Dreaming is Imagination Roaming Freely, Based On Embodied Simulation, and Subserved by an Unconstrained Default Network
- 42 Aphantasia
- 43 Hypnosis and Imagination
- 44 Hallucinations and Imagination
- 45 The Psychiatry of Imagination
- 46 Meditation and Imagination
- 47 Flow in Performance and Creative Cognition – An Optimal State of Task-Based Adaptation
- 48 The Force of the Imagination
- Name Index
- Subject Index
- References
47 - Flow in Performance and Creative Cognition – An Optimal State of Task-Based Adaptation
from Part VI - Altered States of the Imagination
Published online by Cambridge University Press: 26 May 2020
Edited by
Book contents
- The Cambridge Handbook of the Imagination
- The Cambridge Handbook of the Imagination
- Copyright page
- Dedication
- Contents
- Figures
- Contributors
- Acknowledgments
- 1 Surveying the Imagination Landscape
- Part I Theoretical Perspectives on the Imagination
- Part II Imagery-Based Forms of the Imagination
- Part III Intentionality-Based Forms of the Imagination
- Part IV Novel Combinatorial Forms of the Imagination
- Part V Phenomenology-Based Forms of the Imagination
- Part VI Altered States of the Imagination
- 40 Dreaming: Beyond Imagination and Perception
- 41 Dreaming is Imagination Roaming Freely, Based On Embodied Simulation, and Subserved by an Unconstrained Default Network
- 42 Aphantasia
- 43 Hypnosis and Imagination
- 44 Hallucinations and Imagination
- 45 The Psychiatry of Imagination
- 46 Meditation and Imagination
- 47 Flow in Performance and Creative Cognition – An Optimal State of Task-Based Adaptation
- 48 The Force of the Imagination
- Name Index
- Subject Index
- References
Summary
The term flow originates from studies on what motivates people to devote more time to activities – across both work and play settings – than could be expected based on external rewards such as money or fame. The main underlying reason appears to be the intrinsically rewarding subjective experience of flow. Flow refers to a psychological state of high but subjectively effortless attention, low self–awareness, sense of control and enjoyment that can occur during the performance of tasks that are challenging but matched in difficulty to the skill level of the person. This chapter gives an introduction to flow that focuses on the prerequisites and phenomenology of effortless attention, and how the flow experience relates to perception, cognition, and action. Flow and creativity are discussed in particular detail, centering on three hypotheses of how flow may relate to creative cognition; as a motivating factor for task engagement and skill acquisition, as a feedback signal for optimal task-based adaptation, and as relying on similar psychological and neural underpinnings. Lastly, the need for more basic research and applied research is discussed – the former on the relation between flow states and the quality of creative performance and the latter on how the concept of flow could be implemented successfully in training and education.
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- Chapter
- Information
- The Cambridge Handbook of the Imagination , pp. 796 - 810Publisher: Cambridge University PressPrint publication year: 2020
References
Beaty, R. E., Kenett, Y. N., Christensen, A. P., et al. (2018). Robust Prediction of Individual Creative Ability from Brain Functional Connectivity. Proceedings of the National Academy of Sciences of the United States of America, 115(5), 1087–1092.CrossRefGoogle ScholarPubMed
Beilock, S. L., Carr, T. H., MacMahon, C., and Starkes, J. L. (2002). When Paying Attention becomes Counterproductive: Impact of Divided versus Skill-Focused Attention on Novice and Experienced Performance of Sensorimotor Skills. Journal of Experimental Psychology-Applied, 8(1), 6–16.CrossRefGoogle ScholarPubMed
Butković, A., Ullén, F., and Mosing, M. A. (2015). Personality and Related Traits as Predictors of Music Practice: Underlying Environmental and Genetic Influences. Personality and Individual Differences, 74, 133–138.Google Scholar
Clarke, E. F. (1988). Generative Principles in Music Performance. In Sloboda, J. A. (ed.), Generative Processes in Music: The Psychology of Performance, Improvisation, and Composition. New York, NY: Clarendon Press/Oxford University Press, 1–26.Google Scholar
Cseh, G. M., Phillips, L. H., and Pearson, D. G. (2015). Flow, Affect and Visual Creativity. Cognition & Emotion, 29(2), 281–291.CrossRefGoogle ScholarPubMed
Csíkszentmihályi, M. (1990). Flow: The Psychology of Optimal Experience. New York, NY: Harper & Row.Google Scholar
Csíkszentmihályi, M.(1997). Creativity: Flow and the Psychology of Discovery and Invention. New York, NY: HarperPerennial.Google Scholar
Csíkszentmihályi, M.(2014). The Systems Model of Creativity: The Collected Works of Mihaly Csikszentmihalyi. New York, NY: Springer.Google Scholar
Csíkszentmihályi, M., and Getzels, J. W. (1970). Concern for Discovery – An Attitudinal Component of Creative Production. Journal of Personality, 38(1), 91–105.CrossRefGoogle ScholarPubMed
de Manzano, Ö., Cervenka, S., Jucaite, A., et al. (2013). Individual Differences in the Proneness to Have Flow Experiences Are Linked to Dopamine D2-Receptor Availability in the Striatum. NeuroImage, 67, 1–6.Google Scholar
de Manzano, Ö., Theorell, T., Harmat, L., and Ullén, F. (2010). The Psychophysiology of Flow during Piano Playing. Emotion, 10(3), 301–311.CrossRefGoogle ScholarPubMed
de Manzano, Ö., and Ullén, F. (2018). Same Genes, Different Brains: Neuroanatomical Differences between Monozygotic Twins Discordant for Musical Training. Cerebral Cortex, 28(1), 387–394.Google Scholar
Dietrich, A. (2004). Neurocognitive Mechanisms Underlying the Experience of Flow. Consciousness and Cognition, 13(4), 746–761.Google Scholar
Doyon, J., and Benali, H. (2005). Reorganization and Plasticity in the Adult Brain during Learning of Motor Skills. Current Opinion in Neurobiology, 15, 161–167.CrossRefGoogle ScholarPubMed
Eysenck, H. J. (1995). Genius. The Natural History of Creativity. Volume 12. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Feist, G. J. (1999). The Influence of Personality on Artistic and Scientific Creativity. In Sternberg, R. J. (ed.), Handbook of Creativity. Cambridge, UK: Cambridge University Press, 273–296.Google Scholar
Goschke, T., and Bolte, A. (2014). Emotional Modulation of Control Dilemmas: The Role of Positive Affect, Reward, and Dopamine in Cognitive Stability and Flexibility. Neuropsychologia, 62, 403–423.Google Scholar
Gray, R. (2004). Attending to the Execution of a Complex Sensorimotor Skill: Expertise Differences, Choking, and Slumps. Journal of Experimental Psychology-Applied, 10(1), 42–54.Google Scholar
Guilford, J. P., Christensen, P. R., Merrifield, P. R., and Wilson, R. C. (1960). Alternate Uses Manual. Menlo Park, CA: Mind Garden Inc.Google Scholar
Harmat, L., de Manzano, Ö., Theorell, T., et al. (2015). Physiological Correlates of the Flow Experience during Computer Game Playing. International Journal of Psychophysiology, 97, 1–7.CrossRefGoogle ScholarPubMed
Heller, K., Bullerjahn, C., and von Georgi, R. (2015). The Relationship between Personality Traits, Flow-Experience, and Different Aspects of Practice Behavior of Amateur Vocal Students. Frontiers in Psychology, 6, 1901.CrossRefGoogle ScholarPubMed
Herholz, S. C., Coffey, E. B., Pantev, C., and Zatorre, R. J. (2016). Dissociation of Neural Networks for Predisposition and for Training-Related Plasticity in Auditory-Motor Learning. Cerebral Cortex, 26(7), 3125–3134.CrossRefGoogle ScholarPubMed
Jackson, S. A., and Eklund, R. C. (2004). The Flow Scales Manual. Morgantown, WV: Publishers Graphics.Google Scholar
Keller, P. E., Dalla Bella, S., and Koch, I. (2010). Auditory Imagery Shapes Movement Timing and Kinematics: Evidence from a Musical Task. Journal of Experimental Psychology: Human Perception and Performance, 36(2), 508–513.Google Scholar
Lahav, A., Saltzman, E., and Schlaug, G. (2007). Action Representation of Sound: Audiomotor Recognition Network while Listening to Newly Acquired Actions. Journal of Neuroscience, 27(2), 308–314.CrossRefGoogle ScholarPubMed
Land, M. F., and McLeod, P. (2000). From Eye Movements to Actions: How Batsmen Hit the Ball. Nature Neuroscience, 3(12), 1340–1345.CrossRefGoogle ScholarPubMed
MacDonald, R., Byrne, C., and Carlton, L. (2006). Creativity and Flow in Musical Composition: An Empirical Investigation. Psychology of Music, 34(3), 292–306.Google Scholar
Marin, M. M., and Bhattacharya, J. (2013). Getting into the Musical Zone: Trait Emotional Intelligence and Amount of Practice Predict Flow in Pianists. Frontiers in Psychology, 4, 853.CrossRefGoogle ScholarPubMed
Markham, J. A., and Greenough, W. T. (2004). Experience-Driven Brain Plasticity: Beyond the Synapse. Neuron Glia Biology, 1, 351–363.Google Scholar
Martindale, C. (1999). Biological Bases of Creativity. In Sternberg, R. J. (ed.), Handbook of Creativity. Cambridge, UK: Cambridge University Press, 137–152.Google Scholar
McGuire, J. T., and Botvinick, M. M. (2010). The Impact of Anticipated Cognitive Demand on Attention and Behavioral Choice. In Bruya, B (ed.), Effortless Attention: A New Perspective in the Cognitive Science of Attention and Action. Cambridge, MA: MIT Press, 103–120.Google Scholar
Nijstad, B. A., de Dreu, C. K. W., Rietzschel, E. F., and Baas, M. (2010). The Dual Pathway to Creativity Model: Creative Ideation as a Function of Flexibility and Persistence. European Review of Social Psychology, 21, 34–77.Google Scholar
Novembre, G., and Keller, P. E. (2014). A Conceptual Review on Action-Perception Coupling in the Musician’s Brain: What Is It Good For? Frontiers in Human Neuroscience, 8, 603.Google Scholar
Petersen, S. E., van Mier, H., Fiez, J. A., and Raichle, M. E. (1998). The Effects of Practice on the Functional Anatomy of Task Performance. Proceedings of the National Academy of Sciences of the United States of America, 95(3), 853–860.Google Scholar
Pinho, A. L., de Manzano, Ö., Fransson, P., Eriksson, H., and Ullén, F. (2014). Connecting to Create – Expertise in Musical Improvisation Is Associated with Increased Functional Connectivity between Premotor and Prefrontal Areas. Journal of Neuroscience, 34(18), 6156–6163.Google Scholar
Pinho, A. L., Ullén, F., Castelo-Branco, M., Fransson, P., and de Manzano, Ö. (2016). Addressing a Paradox: Dual Strategies for Creative Performance in Introspective and Extrospective Networks. Cerebral Cortex, 26(7), 3052–3063.CrossRefGoogle ScholarPubMed
Raichle, M. E. (2015). The Brain’s Default Mode Network. Annual Review of Neuroscience, 38, 433–447.Google Scholar
Roy, M., Peretz, I., and Rainville, P. (2008). Emotional Valence Contributes to Music-Induced Analgesia. Pain, 134(1–2), 140–147.Google Scholar
Seamans, J. K., and Yang, C. R. (2004). The Principal Features and Mechanisms of Dopamine Modulation in the Prefrontal Cortex. Progress in Neurobiology, 74(1), 1–58.Google Scholar
Ullén, F., de Manzano, Ö., Theorell, T., and Harmat, L. (2010). The Physiology of Effortless Attention. In Bruya, B (ed.), Effortless Attention: A New Perspective in the Cognitive Science of Attention and Action. Cambridge, MA: MIT Press, 205–218.Google Scholar
Ullén, F., Hambrick, D. Z., and Mosing, M. A. (2016). Rethinking Expertise: A Multi-Factorial Gene-Environment Interaction Model of Expert Performance. Psychological Bulletin, 142(4), 427–446.Google Scholar
Ulrich, M., Keller, J., and Gron, G. (2016). Neural Signatures of Experimentally Induced Flow Experiences Identified in a Typical fMRI Block Design with BOLD Imaging. Social Cognitive and Affective Neuroscience, 11(3), 496–507.CrossRefGoogle Scholar
Vanlessen, N., de Raedt, R., Koster, E. H. W., and Pourtois, G. (2016). Happy Heart, Smiling Eyes: A Systematic Review of Positive Mood Effects on Broadening of Visuospatial Attention. Neuroscience & Biobehavioral Reviews, 68, 816–837.Google Scholar
Vuorre, M., and Metcalfe, J. (2016). The Relation between the Sense of Agency and the Experience of Flow. Consciousness and Cognition, 43, 133–142.Google Scholar
Weber, R., Alicea, B., Huskey, R., and Mathiak, K. (2018). Network Dynamics of Attention during a Naturalistic Behavioral Paradigm. Frontiers in Human Neuroscience, 12, 182.Google Scholar
Weber, R., Tamborini, R., Westcott-Baker, A., and Kantor, B. (2009). Theorizing Flow and Media Enjoyment as Cognitive Synchronization of Attentional and Reward Networks. Communication Theory, 19, 397–422.Google Scholar
Willingham, D. B. (1998). A Neuropsychological Theory of Motor Skill Learning. Psychological Review, 105(3), 558–584.Google Scholar
Wulf, G., and Lewthwaite, R. (2010). Effortless Motor Learning?: An External Focus of Attention Enhances Movement Effectiveness and Efficiency. In Bruya, B (ed.), Effortless Attention: A New Perspective in the Cognitive Science of Attention and Action. Cambridge, MA: MIT Press, 75–101.Google Scholar
Wulf, G., and Su, J. (2007). An External Focus of Attention Enhances Golf Shot Accuracy in Beginners and Experts. Research Quarterly for Exercise and Sport, 78(4), 384–389.Google Scholar
Yasuno, F., Suhara, T., Okubo, Y., et al. (2004). Low Dopamine D(2) Receptor Binding in Subregions of the Thalamus in Schizophrenia. American Journal of Psychiatry, 161(6), 1016–1022.CrossRefGoogle ScholarPubMed
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