Contributions of the default mode and central executive networks during posterior cingulate cortex-targeted fMRI neurofeedback in PTSD
Bibliographic record
Abstract
INTRODUCTION: Functional magnetic resonance imaging-based neurofeedback (fMRI-NFB) enables individuals to regulate brain activity implicated in psychopathology, including post-traumatic stress disorder (PTSD). While most fMRI-NFB studies in PTSD target the amygdala, which engages the central executive network (CEN) for top-down regulation, the posterior cingulate cortex (PCC), a core node of the default mode network (DMN), has recently emerged as a promising therapeutic target. However, the relative contributions of intra-network DMN mechanisms versus inter-network CEN engagement during PCC downregulation remain unclear. METHODS: We used independent component analysis (ICA) to examine DMN and CEN functional connectivity during PCC-targeted fMRI-NFB in individuals with PTSD (n = 14) and healthy controls (n = 15) while viewing trauma-related/distressing words. Mixed-design repeated measures ANOVAs assessed within- and between-group connectivity changes, and clinical correlations were explored. RESULTS: During PCC downregulation, PTSD participants exhibited greater DMN connectivity than controls with trauma-related regions, including the precentral gyrus and anterior insula, which correlated with PTSD severity and emotion regulation difficulties. Conversely, CEN connectivity decreased in both groups, with PTSD participants showing progressively reduced connectivity across training. Direct comparisons revealed that DMN connectivity exceeded CEN connectivity with several brain regions, particularly among PTSD participants. CONCLUSION: These findings highlight the predominant role of DMN mechanisms in PCC downregulation in PTSD. The reliance on intra-network DMN processes over CEN-driven regulation underscores distinct network dynamics that may be unique to PCC-targeted fMRI-NFB. These neural mechanistic insights may inform targeted fMRI-NFB protocols to recalibrate altered DMN connectivity and enhance emotion regulation in PTSD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".