Poster No:
602
Submission Type:
Abstract Submission
Authors:
Verena Schuster1, Christoph Vogelbacher1, Marlon Westhoff1, Stefan Hofmann1
Institutions:
1Philipps-University, Marburg, Hesse
First Author:
Co-Author(s):
Introduction:
Psychological flexibility refers to the ability to adapt to changing contexts, balance competing desires, and remain open to experiences while staying committed to one's values (Kashdan, 2010). This complex construct has gained attention in psychological and neuroscience research, yet fMRI studies investigating its neural underpinnings remain rare, likely due to its multifaceted nature and emphasis on emotional and behavioral adaptability. This study examines the neural correlates and interregional network dynamics of psychological flexibility during suppression and imagination of personal future threats, using an adapted No-Imagine-Imagine (INI) task (Benoit, 2016) to engage relevant cognitive and emotional processes.
Methods:
Fifty-four participants (33 females, 21 males; mean age = 24.19 years, SD = 2.29, range = 21–31) were included in the study approved by the local Ethics Committee. MRI data were collected using a 3T Siemens Tim Trio scanner with a 32-channel head coil. Functional imaging utilized T2*-weighted echo-planar imaging with multiband sequences for shorter TRs. Participants performed the INI task in a pseudo-randomized block design during fMRI scanning. Preprocessing with fmriprep included motion correction, CompCor noise components, and 8 mm FWHM smoothing. Single-subject contrasts for imagine > suppress and suppress > imagine were calculated using a General Linear Model (GLM). Group analyses employed z-standardized contrasts in a one-sample t-test with clusters (>15 voxels) identified via the DIFUMO atlas (threshold: p < 0.001). Psychological flexibility was assessed with the Acceptance and Action Questionnaire-2 (AAQ-2) (Hayes, 2004; Bond, 2011), with linear regression used to relate brain activity to AAQ-2 scores. Dynamic Causal Modeling (DCM) (Friston, 2003) analyzed interregional connectivity during suppression and imagination, correlating connectivity strengths with AAQ-2 scores.
Results:
During imagination (imagine > suppress), clusters were found in the bilateral posterior cingulate cortex (PCC) and ventromedial prefrontal cortex (vmPFC). Linear regression revealed a significant negative correlation between PCC activity and AAQ-2 scores, indicating higher PCC activity in individuals with greater psychological flexibility (right PCC: slope: -4.97; intercept: 32.13; r: -0.364; p = 0.007; left PCC: slope: -5.94; intercept: 34.91; r: -0.337; p = 0.013). For suppression (suppress > imagine), clusters emerged in the inferior frontal gyrus (IFG), middle frontal gyrus (MFG), superior parietal lobule (SPL), and superior occipital sulcus (SOS), but no significant correlations with AAQ-2 were observed. DCM revealed condition-specific connectivity patterns: positive MFG connections to other regions during suppression and strong PCC-vmPFC coupling during imagination, both with negative self-regulation. However, connectivity parameters were not significantly correlated with AAQ-2 scores.
Conclusions:
This study identifies distinct neural mechanisms underlying psychological flexibility during suppression and imagination of future threats. PCC and vmPFC activity during imagination reflect self-referential and emotional processing, with PCC activity correlating with greater psychological flexibility. Suppression engaged executive control regions (IFG, MFG, SPL), highlighting cognitive inhibition processes. DCM results revealed condition-specific interactions between self-referential and executive control networks. These findings provide insights into adaptive coping strategies and suggest that variability in neural connectivity may shape individual differences in psychological flexibility.
Emotion, Motivation and Social Neuroscience:
Emotion and Motivation Other 1
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 2
Keywords:
Emotions
FUNCTIONAL MRI
MRI
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Task-activation
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
NOTE: Any animal studies without IACUC approval will be automatically rejected.
Not applicable
Please indicate which methods were used in your research:
Functional MRI
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
SPM
Other, Please list
-
fmriprep
Provide references using APA citation style.
Benoit, R.G. (2016). Reducing future fears by suppressing the brain mechanisms underlying episodic simulation. Proceedings of the National Academy of Sciences 113, E8492– E8501.
Bond, F. W. (2011). Preliminary psychometric properties of the Acceptance and Action Questionnaire – II: A revised measure of psychological inflexibility and experiential avoidance. Behavior Therapy, 42, 676–688.
Friston, K.J. (2003). Dynamic causal modelling. Neuroimage19, 1273–4341302.
Hayes, S. C. (2004). Acceptance and commitment therapy, relational frame theory, and the third wave of behavioral and cognitive therapies. Behavior Therapy 35, 639–665.
Kashdan, T.B. (2010). Psychological flexibility as a fundamental aspect of health. Clinical Psychology Review. Nov;30(7):865-78.
No