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A Protocol for the Administration of Real-Time fMRI Neurofeedback Training
Published on: August 24, 2017
Individual-Level Brain Network Predictors and Distinct Reorganization Mechanism in Sound Therapies for Tinnitus
Jiahong Li1,2, Zhaopeng Tong1,2, Weiwei Cai3
1Department of Otolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou City, Guangdong Province, China.
Objective:
To investigate brain network reorganization in tinnitus patients undergoing tailor-made notched music training (TMNMT) or tinnitus retraining therapy (TRT) and assess whether baseline network characteristics predict treatment outcomes.
Study Design:
A randomized, single-blind, controlled trial.
Setting:
The study was conducted at Sun Yat-sen Memorial Hospital.
Methods:
Patients aged 18 to 70 years with tinnitus lasting more than 6 months were randomly assigned to receive either TMNMT or TRT for 3 months. Electroencephalogram (EEG) assessed brain functional and effective connectivity at baseline and after treatment. Additionally, 46 normal controls with a single EEG scan were included for baseline comparison to assess treatment normalization of brain networks.
Results:
A total of 80 patients (TMNMT group: 40 [50.0%]; mean [SD] age: 42.2 [12.0] years; 19 males [47.5%]; TRT group: 40 [50.0%]; mean [SD] age: 41.9 [14.6] years; 21 males [52.5%]) and 46 normal controls (mean [SD] age: 39.37 [12.92] years; 23 males [50.0%]) were analyzed. In tinnitus patients who responded to TMNMT or TRT, tinnitus severity reduction was associated with reorganization of multiple brain networks. Predictive analysis showed that increased effective connectivity from the posterior cingulate cortex and insula to the auditory network predicted TMNMT responders (area under the curve [AUC] = 0.820, 95% CI 0.697-0.944), while increased connectivity from the medial prefrontal cortex to the dorsolateral prefrontal cortex predicted TRT non-responders (AUC = 0.875, 95% CI 0.777-0.974).
Conclusion:
Both TMNMT and TRT induced neural effects on tinnitus. Baseline brain networks distinguished responders from non-responders and predicted treatment outcomes.

