Targeted limbic self-neuromodulation for alleviating central sensitization symptoms in fibromyalgia

Abstract

Background: Fibromyalgia (FM), involving somatic, cognitive, and affective domains is often regarded as a hallmark central sensitization syndrome. Despite limited current therapeutic options, emerging understanding of its neural underpinnings offers the potential of applying novel neuromodulation strategies. Specifically, limbic dysregulation underlying abnormalities in pain modulation and somatic-affective processing, has been shown to play a key role in FM. Here, we assessed the long-term efficacy of targeted limbic self-neuromodulation for improving clinical disease burden in FM.

Methods: Forty-seven patients with FM participated in a double-blind, randomized, dual-control study employing a novel specialized neurofeedback probe representing amygdala activity. Patients underwent 10 sessions of either genuine neurofeedback training (NFT = 21), or sham neurofeedback training (NFS = 13), or treatment as usual (TAU = 13). Disease severity and symptom burden were assessed using the Symptom Severity Score (SSS), along with other questionnaires administered before and after treatment. A clinical follow-up was performed 10-12 months post-intervention.

Results: NFT led to a significant immediate and long-term reduction in the SSS (F_(2,40) = 7.32, p = 0.00, ηp2 = 0.27) and the Fibromyalgia Impact Questionnaire (FIQ) (F_(2,40) = 9.85, p = 0.00, ηp2 = 0.33), alongside multidomain short- and long-term clinical benefits. NFS resulted in a long-term reduction in pain but did not affect other disease measures or overall disease burden. The TAU group showed no clinical improvements.

Conclusions: Our findings support the intimate involvement of limbic brain areas in the pathophysiology of FM and suggest that targeted neuromodulation offers a novel, mechanism-based approach for managing multidomain symptoms in FM.

Trial registration: This study was preregistered with the National Institutes of Health (NIH).

Registration number: NCT02146495. Name of trial registry: Targeted Limbic Self-modulation as a Potential Treatment for Patients Suffering From Fibromyalgia https://clinicaltrials.gov/study/NCT02146495 .

Keywords: Brain-based therapy; Chronic pain relief; FMRI-informed EEG model; Fibromyalgia management; Non-invasive intervention.

Fig. 1

Experimental Design. A Patients underwent a clinical assessment by a certified specialist and were then randomly assigned to either a treatment-as-usual (TAU) group or an NF intervention group (NFT or NFS). A "Pre-NF" assessment, including clinical evaluations, was conducted, followed by ten sessions of Amyg-EFP-NF training, performed 2–3 times per week. A "Post-NF" assessment, identical to the baseline evaluation, was conducted within 1–2 weeks after the NF course. The entire intervention process lasted 8–10 weeks. The TAU group underwent similar assessments at the beginning and end of a 2–3 month period. A follow-up clinical assessment was conducted 10–12 months later. B NF training protocol: Patients underwent a brief clinical evaluation at the beginning and end of each session. Each session started with a 2-min EEG resting-state recording. Training involved down-regulating the Amyg-EFP signal using a 3D animated scenario of a virtual waiting room that changed based on EFP signal amplitude. Each NF cycle included: Watch (60 s), Regulate (120 s), and Washout (30 s). Each NF cycle included these conditions, repeated twice in each 7-min NF run. The EFP-NF session comprised four NF runs, followed by a 2-min transfer run where patients applied their most effective strategy without feedback

Fig. 2

Feasibility, Immediate and Long-Term Effectivity of Amyg-EFP NF. Several statistical analyses were conducted to assess the immediate and long-term clinical efficacy for each clinical index (A-F). The clinical indices included: A symptom severity score (SSS), B FIQ-final score index, C widespread pain index (WPI), D subjective fatigue (FIQ-fatigue), E affective state (STAI-T), and (F) cognitive symptoms score (SSS-Cog). A linear mixed-model analysis was initially performed to examine the interaction between Group (NFT, NFS, TAU) and measurement time-points (MTP) (pre, post, follow-up), testing between-group differences in overall clinical efficacy. Post-hoc comparisons following ANOVA were then conducted for each group to evaluate immediate improvement (post vs. pre) and long-term effects (follow-up vs. pre). The percentage of symptom improvement over the long term was also calculated for each index and group. The NFT group demonstrated significant long-term effects across all indices. In contrast, the NFS group showed significant long-term effects only for the WPI score, while the TAU group showed none. Significant between-group effects were found for SSS, FIQ-final score, fatigue, and cognitive indices. See Table 2 for detailed results

Fig. 3

Long-Term Clinical Efficacy of Amyg-EFP-NF: Inter-Group Comparisons. A planned contrast analysis was conducted to compare the genuine NF group (NFT) with each control group (NFS and TAU) at long-term follow-up (FU-pre) across all clinical outcomes. A The NFT group showed greater improvement in symptom severity compared to both the NFS and TAU groups. B For the Fibromyalgia Impact Questionnaire (FIQ) final score, the NFT group demonstrated greater improvement than the TAU group, though the difference was not significant when compared to the NFS group. C No significant differences were found between groups regarding the Widespread Pain Index (WPI) score. D The NFT group showed greater improvement in the FIQ-fatigue score compared to both control groups. E There were no significant differences in the STAI-T scores between the groups. F Finally, the NFT group exhibited greater improvement in cognitive scores compared to both the NFS and TAU groups

Fig. 4

Different Dimensions of Amyg-EFP-NF Learning. A Association between Amyg-EFP NF capacity and generalization of Amyg-EFP downregulation learning: A positive correlation was observed exclusively in the NFT group, linking average transfer scores (across all sessions) with the average Amyg-EFP downregulation score (Regulate vs. Watch). B Global learning success: A mixed linear model analysis of Amyg-EFP NF learning trajectory showed a significant Session by Group interaction effect (F_(1,84.34) = 5.39, p = 0.02, 95% CI: 0.0052 to: 0.0683). This result indicated a linear trend in NF learning favoring the NFT group compared to the NFS group. The association between Amyg-EFP-NF downregulation and long-term clinical improvement. A Pearson correlation analysis revealed that successful Amyg-EFP downregulation (average delta; Regulate-Watch) was assosiated with long-term reductions (FU-pre-intervention) in (C) symptom severity (SSS), D cognitive dysfunction, and (E) emotional dysregulation (STAI-T). These correlations were specific to the genuine Amyg-EFP group and were not observed in the NF-sham group