Neural Correlates of Flow Experiences
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This study investigated the neural correlates of flow states using fMRI. It aimed to test predictions from synchronization theory that flow involves increased activation in attention and reward networks compared to boredom and frustration states. Participants completed tasks designed to induce each state while in the scanner. Preliminary results from one participant found greater activation in attention-related areas like the inferior parietal lobe and reward-related areas like the thalamus during flow vs boredom. Flow vs frustration activated visual cortex areas but no clear reward areas. Further research is needed to fully test the synchronization component of the theory and address limitations like task modality differences.
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Neural Correlates of Flow Experiences
- 1. Neural Correlates of Flow Experiences Richard Huskey Michael Mangus Christian Yoder René Weber http://medianeuroscience.org Department of Communication University of California Santa Barbara
- 2. • • • • • • Six Characteristics of Flow Sense that one’s skills are an adequate fit for the challenge Disappearance of self-consciousness Loss of temporal awareness Pleasant experience that not perceived as taxing Perform the given activity “for its own sake” Intense concentration; “there is no attention left” Csíkszentmihályi, 1990 Department of Communication University of California Santa Barbara
- 3. Problem! • Flow is often heuristically defined • Flow measurement primarily relies on self-report measures Method 1: Poorly Defined Scales Method 2: Experience Sampling Method (ESM) Department of Communication University of California Santa Barbara
- 4. Synchronization Theory of Flow • “Flow is a discrete, energetically optimized, and gratifying experience resulting from the synchronization of attentional and reward networks under condition of balance between challenge and skill” (Weber, Tamborini, Westcott-Baker, & Kantor, 2009, p. 412). • Five assumptions central to sync theory: – Neural networks can oscillate at the same frequency – networks oscillating at the same frequency are said to be in sync – Synchronization is a discrete state – The synchronization of neural networks is energetically cheap – The effect of networks in sync is greater than the sum of individual parts – Flow results from a synchronization of attentional and reward networks under conditions of a balance between challenge/skill Department of Communication University of California Santa Barbara
- 5. Synchronization Theory of Flow • Early Support: – fMRI Attention (Weber, Alicea, & Mathiak, 2009) – fMRI Attention/Reward (Klasen et al., 2012) – fMRI Neural Correlates of Flow (Ulrich, Keller, Hoenig, Waller, Grön, 2013) – STRT Attention (Kantor & Weber, 2009; Weber & Huskey, 2013) – Patch Clamp Attention/Reward (Stanisor et al, 2013) Department of Communication University of California Santa Barbara
- 6. Weber & Huskey, 2013 Overall Model = .928, F(2,119) = 4.626, p = .012 All pairwise comparisons significantly different, p < .033 Overall Model = .68, F(2, 118) = 28.12, p < .001 All pairwise comparisons significantly different, p < .014 Department of Communication University of California Santa Barbara
- 7. The Present Study • This study adapted the Weber & Huskey (2013) protocol to a brain imaging environment and predicts: – Increased activation in alerting (frontal and parietal cortical regions) and orienting networks (superior and inferior parietal lobe regions, the frontal eye fields, and the superior colliculus) during flow compared to boredom and frustration. – Increased activation in reward networks (dopaminergic system, the orbitofrontal cortex, the ventromedial and dorsolateral regions of the prefrontal cortex, the thalamus, and the striatum) during flow compared to boredom and frustration. Department of Communication University of California Santa Barbara
- 8. Boredom 120s 60s rest Instructions Design 30s Flow 120s 60s rest Instructions 30s Frustration 120s 60s rest Instructions 30s Repeat sequence four times total Department of Communication University of California Santa Barbara
- 9. Protocol Primary Task Secondary Task Department of Communication University of California Santa Barbara
- 10. STRT Manipulation Check Department of Communication University of California Santa Barbara
- 11. Analysis • Preprocessing: – Design matrix with 120 s “on” + temporal derivatives + confound Evs – Gamma convolution – McFLIRT + MELODIC ICA – BET + 8 mm smooth + slice time correction + B0 unwarping – Contrasts: • • Boredom (-1), Flow (1) Frustration (-1), Flow (1) – Linear registration to structural scan + nonlinear registration to MNII152 space • Main Analysis: – 3 EVs (one for each contrast) – Fixed Effects – Cluster corrected at Z > 2.3, p < 0.05 Department of Communication University of California Santa Barbara
- 12. Reward: Flow > Boredom Left Thalamus2: z = 3.01 (48,52,41) 1 Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas Department of Communication University of California Santa Barbara
- 13. Attention: Flow > Boredom Inferior Parietal Lobe1: z = 4.17 (15,36,49) 1 Secondary Somatosensory Cortex1: z = 3.31 (23,53,45) Cerebellum3: z = 3.73 (38,21,16) Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas Department of Communication University of California Santa Barbara
- 14. Results: Flow > Boredom Frontal Pole1: z = 3.36 (37,90,54) 1 Superior Temporal Gyrus2: z = 3.59 (74,57,33) Paracingulate Gyrus2: z = 3.51 (41,86,32) Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas Department of Communication University of California Santa Barbara
- 15. Attention: Flow > Frustration Visual Cortex (V1)1: z = 3.26 (36,33,39) 1 Visual Cortex (V3)2: z = 2.87 (53,19,33) Visual Cortex (V4)2: z = 3.04 (57,25,33) Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas Department of Communication University of California Santa Barbara
- 16. Attention: Flow > Frustration Lateral Occipital Cortex2: z = 3.14 (32,22,49) 1 Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas Department of Communication University of California Santa Barbara
- 17. Concluding Thoughts • Even with an n=1 study, we see promising results – Flow > Boredom contrast results in activations most closely related to sync theory predictions – Flow > Frustration contrast is less clear – no clear reward activation • Limitations: – – – – Does not test the synchronization component of Sync Theory Differing modality between primary task and secondary task Study design would benefit from increased automation Non-random block order Department of Communication University of California Santa Barbara
- 18. Thank you! http://medianeuroscience.org Department of Communication University of California Santa Barbara
Notas del editor
- We should begin by defining the characteristics of flow experiences. Flow occurs when our skills are perfectly matched to the challenge we are taking on. Sometimes these challenges are as intense as driving a racecar. Other times they are as every-day as cooking dinner. The point is, flow occurs when there is a balance between challenge and skill When we are in flow, we experience a loss of self consciousness. This is like the composer who described an almost out-of-body experience as he watched his hand write music. We also lose track of time. I’m sure we’ve all been doing something enjoyable where we completely forget to monitor time, and are shocked at how much time has passed. Flow is a pleasant experience that we don’t perceive of as taxing. Marathon runners, snowboarders, rock climbers hanging from precarious cliffs; these activities are both emotionally and physically taxing. But, in the moment, we don’t feel these effects. The climber doesn’t feel exhausted until reaching the summit. Flow experiences are gratifying in and of themselves. The enjoyment comes from *doing* the activity, not completing the activity. The last characteristic of flow is that is it is a wholly absorptive experience. In flow, we are so caught up in the experience that we do not have enough attention left to focus on anything else.
- Flow measurement suffers two main issues: Often heuristically defined Primarily relies on self report measures This leads to two problematic measurements of flow: Questionnaires (everyone uses a different one) The ESM… remember pagers? So, why do you care? Several attempts have tried to resolve some of these issues by theorizing the neural correlates of Flow and using cognitive neuroscience to design unobtrusive and online measures of flow.
- In the Communication discipline, flow has been theorized as the outcome of a synchronization between attentional and reward networks under conditions of a balance between challenge and skill. Despite initial support, there still is insufficient evidence to either confirm or falsify the theory. This study attempts to falsify a central premise of Sync theory; that is, that attentional networks are a component of flow experiences. Sync theory is based on an understanding of how complex neurobiological systems exchange information. While a full-scale test of Sync theory likely requires a brain imaging scanner, components of sync theory can be tested individually. This study isolates the assumption that attentional networks are central to flow experiences, and tests the role of attention in flow experiences. Four assumptions of sync theory: 1). Neural networks can oscillate at the same frequency – networks oscillating at the same frequency are said to be in sync Related to information exchange between complex neurobiological systems 2). Synchronization is instantaneous Networks are synchronized or they are not. Just like you are in flow or not. Networks can’t be “more” or “less” in sync just as you can not be “more” or “less” in flow 3). The synchronization of neural networks is energetically cheap Why flow experiences are not perceived as taxing 4). The effect of networks in sync is greater than the sum of individual parts Why the experience of flow as qualitatively different from the individual components of each antecedent. 5). Result of a synchronization of attentional and reward networks under conditions of a balance between challenge/skill Accounts for the wholly absorptive and highly rewarding nature of flow experiences.
- In the Communication discipline, flow has been theorized as the outcome of a synchronization between attentional and reward networks under conditions of a balance between challenge and skill. Despite initial support, there still is insufficient evidence to either confirm or falsify the theory. This study attempts to falsify a central premise of Sync theory; that is, that attentional networks are a component of flow experiences. Sync theory is based on an understanding of how complex neurobiological systems exchange information. While a full-scale test of Sync theory likely requires a brain imaging scanner, components of sync theory can be tested individually. This study isolates the assumption that attentional networks are central to flow experiences, and tests the role of attention in flow experiences. Four assumptions of sync theory: 1). Neural networks can oscillate at the same frequency – networks oscillating at the same frequency are said to be in sync Related to information exchange between complex neurobiological systems 2). The synchronization of neural networks is energetically cheap Why flow experiences are not perceived as taxing 3). The effect of networks in sync is greater than the sum of individual parts Why the experience of flow as qualitatively different from the individual components of each antecedent. 4). Result of a synchronization of attentional and reward networks under conditions of a balance between challenge/skill Accounts for the wholly absorptive and highly rewarding nature of flow experiences.
- Weber & Huskey manipulated a video game and applied two measures of flow: a commonly used self-report measure (left chart) and a novel STRT measure of flow (right chart). Results show that, consistent with a limited capacity model of attention, reaction times are longest under flow conditions (relative to boredom and frustration) This result provides support for the attentional component of Sync Theory. What about the reward component?
- We see support for: (1) Attentional components of Sync Theory (2) Reward Components of Sync Theory There is a need to congruently assess attention and reward Accordingly, this study predicts:
- Experimental stimulus = star Reaction. We experimentally manipulate challenge. Explain all three experimental conditions, and give examples for why we did each. Block design: Three conditions (boredom, frustration, flow). Two block per condition, a total of 6 blocks. Each block scans for 4 minutes. 48 trials per block. Each trial displayed for 1500 ms at irregular but non-random intervals per block. Interstimulus interval calculated by taking a sample of normally distributed randomly generated numbers (M = 1969 ms, SD = 1000 ms)
- Experimental stimulus = star Reaction. We experimentally manipulate challenge. Explain all three experimental conditions, and give examples for why we did each. Block design: Three conditions (boredom, frustration, flow). Two block per condition, a total of 6 blocks. Each block scans for 4 minutes. 48 trials per block. Each trial displayed for 1500 ms at irregular but non-random intervals per block. Interstimulus interval calculated by taking a sample of normally distributed randomly generated numbers (M = 1969 ms, SD = 1000 ms)
- What we predicted: Thalamus: component of reward network, switchboard for relaying sensory information (e.g., to attentional networks)
- What we predicted: Inferior parietal lobe: alerting network (endogenous and exogenous alerting) Secondary Somatosensory Cortex: visceral sensation, touch, attention Cerebellum: attention and motor control
- What we didn’t expect: Superior Temporal Gyrus: auditory & speech processing – likely due to different modality in attentional task Paracingulate Gyrus (aPCC): predict future intention of social interactants? (Walter Adenzato, Ciaramidaro, Enrici, Pia, Bara, 2004, Journal of Cognitive Neuroscience) Frontal pole: reasoning, planning, multitasking (Koechlin, 2011 – Trends in Cognitive Sciences), goal directed behavior?
- What we Predicted: Visual Cortex: processing of visual stimuli
- What we Predicted: Visual Cortex: processing of visual stimuli Lateral Occipital Cortex: attention, object recognition Grill-Spector, Kourtzi, Kanwisher, 2001 – Vision Research)
- In the Communication discipline, flow has been theorized as the outcome of a synchronization between attentional and reward networks under conditions of a balance between challenge and skill. Despite initial support, there still is insufficient evidence to either confirm or falsify the theory. This study attempts to falsify a central premise of Sync theory; that is, that attentional networks are a component of flow experiences. Sync theory is based on an understanding of how complex neurobiological systems exchange information. While a full-scale test of Sync theory likely requires a brain imaging scanner, components of sync theory can be tested individually. This study isolates the assumption that attentional networks are central to flow experiences, and tests the role of attention in flow experiences. Four assumptions of sync theory: 1). Neural networks can oscillate at the same frequency – networks oscillating at the same frequency are said to be in sync Related to information exchange between complex neurobiological systems 2). The synchronization of neural networks is energetically cheap Why flow experiences are not perceived as taxing 3). The effect of networks in sync is greater than the sum of individual parts Why the experience of flow as qualitatively different from the individual components of each antecedent. 4). Result of a synchronization of attentional and reward networks under conditions of a balance between challenge/skill Accounts for the wholly absorptive and highly rewarding nature of flow experiences.