The Neural Correlates of Flow Experiences

University of California Santa Barbara

Department of Communication

Neural Correlates of Flow Experiences

Richard HuskeyMichael MangusChristian Yoder

René Weber

http://medianeuroscience.org

University of California Santa Barbara

Department of Communication

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

University of California Santa Barbara

Department of Communication

Problem!• Flow is often heuristically defined • Flow measurement primarily relies on self-report

measures

Method 2: ExperienceSampling Method (ESM)

Method 1: Poorly DefinedScales

University of California Santa Barbara

Department of Communication

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

University of California Santa Barbara

Department of Communication

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)

University of California Santa Barbara

Department of Communication

Weber & Huskey, 2013

Overall Model = .928, F(2,119) = 4.626, p = .012All pairwise comparisons significantly different, p < .033

Overall Model = .68, F(2, 118) = 28.12, p < .001 All pairwise comparisons significantly different, p < .014

University of California Santa Barbara

Department of Communication

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.

University of California Santa Barbara

Department of Communication

Design

Repeat sequence four times total

Repeat sequence four times total

Boredom    

120s120s

120s120s

120s120s

60s rest60s rest

60s rest60s rest

60s rest60s rest

30s30s

30s30s

30s30s

Instructions 

Flow

Instructions 

Frustration    

Instructions 

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Department of Communication

Protocol

Primary Task

Secondary Task

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Department of Communication

STRT Manipulation Check

University of California Santa Barbara

Department of Communication

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

University of California Santa Barbara

Department of Communication

Reward: Flow > Boredom

1 Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas

Left Thalamus2:z = 3.01 (48,52,41)

University of California Santa Barbara

Department of Communication

Attention: Flow > Boredom

1 Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas

Inferior Parietal Lobe1: z = 4.17 (15,36,49)

Secondary SomatosensoryCortex1: z = 3.31 (23,53,45)

Cerebellum3:z = 3.73 (38,21,16)

University of California Santa Barbara

Department of Communication

Results: Flow > BoredomParacingulate

Gyrus2: z = 3.51 (41,86,32)

1 Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas

Superior Temporal Gyrus2: z = 3.59 (74,57,33)

Frontal Pole1:z = 3.36 (37,90,54)

University of California Santa Barbara

Department of Communication

Attention: Flow > Frustration

Visual Cortex (V1)1:z = 3.26 (36,33,39)

Visual Cortex (V4)2:z = 3.04 (57,25,33)

1 Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas

Visual Cortex (V3)2:z = 2.87 (53,19,33)

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Attention: Flow > Frustration

Lateral OccipitalCortex2: z = 3.14 (32,22,49)

1 Juelich Histological Atlas | 2 Harvard-Oxford Atlas | 3 MNI Structural Atlas

University of California Santa Barbara

Department of Communication

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

University of California Santa Barbara

Department of Communication

Thank you!http://medianeuroscience.org