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Updated: Jan 30, 2026

fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals
Published on: May 23, 2017
Altered intrinsic brain activity in patients with toothaches using the amplitude of low-frequency fluctuations: a
Jun Yang1, Bin Li2, Qiu-Yue Yu2
1Department of Prosthodontics, The Affiliated Stomatological Hospital of Nanchang University, Nanchang, China.
Background:
The results of previous studies have indicated that pain-associated diseases can result in marked functional and anatomical alterations in the brain. However, differences in spontaneous brain activity occurring in toothache (TA) patients remain unclear.
Objective:
This study investigated intrinsic brain activity changes in TA subjects using the amplitude of low-frequency fluctuation (ALFF) technique.
Methods:
A total of 18 patients with TA (eight males, and 10 females) and 18 healthy controls (HCs) who were matched for gender, age, and educational status were enrolled. Resting-state functional MRI was used to examine the participants. Spontaneous cerebral activity variations were investigated using the ALFF technique. The mean ALFF values of the TA patients and the HCs were classified using receiver operating characteristic (ROC) curves. The correlations between ALFF signals of distinct regions of the cerebrum and the clinical manifestations of the TA patients were evaluated using Pearson's correlation analysis.
Results:
Compared with HCs, TA patients showed notably higher ALFF in the left postcentral gyrus, right paracentral lobule, right lingual gyrus, right inferior occipital gyrus, left fusiform gyrus, and right superior occipital gyrus. ROC curve analysis of each brain region showed that the accuracy area under the curve was excellent. In the TA group, the visual analog scale of the left side was positively correlated with the ALFF signal values of the right paracentral lobule (r=0.639, P=0.025).
Conclusion:
Multiple brain regions, including pain- and vision-related areas, exhibited aberrant intrinsic brain activity patterns, which may help to explain the underlying neural mechanisms in TA.
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