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Gamma entrainment using 40 Hz sensory stimulation has shown promise in AD mouse models, but inconsistent results in AD patients, possibly due to interspecies and interindividual differences in center frequency (CF). This study aimed to investigate whether gamma rhythms entrained by visual stimulation at an individual's CF can spread better than those at other frequency conditions in older adults. We entrained gamma rhythms in 32 cognitively normal older participants using light flickering at 32 Hz, 34 Hz, 36 Hz, 38 Hz, and 40 Hz. We identified each individual's CF among these five frequencies and compared the spread, strength, and stability of gamma connectivity induced by light stimulation flickering at an individual's CF with those at other frequencies using generalized estimating equation and repeated measures ANOVA. In about two-thirds of the participants, 32 Hz (40.6%) and 34 Hz (28.1%) were identified as CF. The mean spread, strength, and stability of gamma connectivity involving the visual cortex (GC) were higher than those do not involve the visual cortex (GC, p < 0.05). Between the visual cortex and other brain regions, FLS induced with frequencies of high event related spectral perturbation values, including CF and non-center frequency (NCF) 1, generally induced broader, stronger, and more stable gamma connectivity compared to most other NCFs (p < 0.001 when comparing NCFs with either CF and NCF1 for both strength and spread; p = 0.012 when comparing CF and NCF3 for stability). Gamma rhythms entrained by visual stimulation may better spread to other brain regions when its frequency matched to the individual's CF.
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http://dx.doi.org/10.1007/s11357-025-01552-6 | DOI Listing |
Whole-brain models are valuable tools for understanding brain dynamics in health and disease by enabling the testing of causal mechanisms and identification of therapeutic targets through dynamic simulations. Among these models, biophysically inspired neural mass models have been widely used to simulate electrophysiological recordings, such as MEG and EEG. However, traditional models face limitations, including susceptibility to hyperexcitation, which constrains their ability to capture the full richness of neural dynamics.
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