Daban 2026 — Neuro-cognitive trigger model of FM flare-ups

One-paragraph summary

Single-author theoretical paper proposing a dynamics-layer model for FM flare-ups, complementing existing baseline-vulnerability models (central sensitization, predictive_coding_failure). The model: flares emerge from the interaction of (1) sustained cognitive load, (2) persistent emotional background stress, and (3) insufficient neural recovery acting on a neuro-sensitive baseline. Critically, the paper distinguishes baseline neuro-sensitivity (the trait CS or interoceptive-inference deficit captures) from trigger-dependent symptom escalation (the state phenomenon clinically relevant to flares). Recovery failure is identified as an active modulatory factor, not just absence of recovery. The framework generates testable hypotheses suitable for ecological momentary assessment and longitudinal symptom tracking. Conceptually pairs with Strube 2026 (which addresses temporal dynamics in ME/CFS) — Daban supplies the FM-specific dynamics framing.

Claims as triples

• predictive_coding_failure — present_in → widespread_pain [framework-level claim about flare dynamics; confidence: emerging]

Methods note

Single-author theoretical paper. Grounded in established literature on central sensitization, cognitive-load theory, stress neurobiology, and sleep-related recovery mechanisms. Synthesis-only; no new data.

Limitations

• Preprint, single-author, theoretical. Same caveat as Strube 2026 — these are framework papers that reorganize existing data without new data.
• "Cognitive load," "emotional stress," and "neural recovery" are conceptually broad — operationalization for empirical test is non-trivial.
• The trigger-vs-baseline distinction is intuitively useful but the boundary (when does sustained trigger become baseline drift?) is not formally specified.
• No formal computational model — Strube 2026's hierarchical Bayesian formulation is more rigorous on this dimension.

Open questions raised

• What's the cleanest EMA protocol for testing the model? (Q22-related: interoceptive retraining trials might use this design.)
• Does subjective "neural recovery" (sleep quality, cognitive fatigue) map onto biological recovery markers (HRV recovery, glymphatic clearance, immune-cell-cycle resetting)?
• Could combining Daban's trigger-dynamics framing with Strube's hierarchical-Bayesian framework produce a unified model with both formal computational structure and FM-specific dynamics?

Triangulation notes

• Adds the dynamics layer to predictive_coding_failure / interoceptive_inference. The Strube + Herman cluster captures the steady-state deficit; Daban supplies the temporal-modulation framing.
• Highly compatible with the Hou 2026 brain-network findings: FPN-VAN connectivity, alexithymia, and recovery dynamics could all index the same circuit operating under different load conditions.
• Therapeutic implication: stress-reduction + sleep-optimization + cognitive-load management as flare-prevention strategy. Mechanism-anchored rather than just empirical effect.