Purpose: Growing evidence reported that patients with comitant exotropia (CE) were accompanied by static cerebral neural activity changes. However, whether the dynamic time-varying of neural activity changes in patients with CE remains unknown.
Methods: A total of 36 patients with CE (25 men and 11 women) and 36 well-matched healthy controls are enrolled in the study. The dynamic amplitude of low-frequency fluctuation (dALFF) combined with the sliding window method was used to assess the dynamic neural activity changes in patients with CE.
Results: Compared with HCs, patients with CE had decreased dALFF values in the right superior parietal lobule (SPL) and right precuneus gyrus (PreCUN). Moreover, we found that the dALFF maps showed an accuracy of 48.61% and an area under the curve of.54 for distinguishing the patients with CE from HCs.
Conclusion: Our study demonstrated that patients with CE showed altered dynamic neural activity changes in the right SPL and right PreCUN, which might indicate the neuropathological mechanism of stereoscopic dysfunction in patients with CE.
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http://dx.doi.org/10.3389/fnhum.2022.944100 | DOI Listing |
J Neural Transm (Vienna)
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Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai 519031, China.
Electroencephalogram (EEG) signals are important bioelectrical signals widely used in brain activity studies, cognitive mechanism research, and the diagnosis and treatment of neurological disorders. However, EEG signals are often influenced by various physiological artifacts, which can significantly affect data analysis and diagnosis. Recently, deep learning-based EEG denoising methods have exhibited unique advantages over traditional methods.
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