Gamma power increased in Alzheimer's disease patients in comparison to healthy controls during recognition of facial expressions

Abstract

Background Several researchers have reported the impairment of recognition of facial expressions in Alzheimer’s disease (AD) patients. AD had reduced theta and alpha responses compared to healthy controls during the recognition of facial expressions (Güntekin et al. 2019). Gamma responses also have a crucial role in the recognition of facial expression in healthy young adults (Güntekin and Başar 2014). AD had increased late gamma responses compared to healthy controls during working memory paradigms (Başar et al. 2017). The present study aims to analyze the gamma responses during the recognition of facial expressions in AD and healthy controls. We hypothesized that if the increase of late gamma responses is a general phenomenon in AD patients independent of the stimulation type, we expect to find increase gamma responses in AD patients in comparison to healthy controls. Method EEGs of 40 healthy controls (HCs) and 41 AD patients were recorded during their perception of three different facial expressions (angry, happy, neutral). Event‐related power spectrum and phase locking were analyzed for three different gamma bands (30‐35 Hz, 35‐ 40Hz, 40‐48 Hz) in two different time windows (0‐200 ms, 200‐400 ms). Result The group difference between AD patients and HCs was not significant for the phase‐locking values. AD patients had higher gamma power responses compared to healthy controls in 200‐400 ms time window for 30‐35 Hz(p=0.016), 35‐40 Hz(p=0.018) and 40‐48 Hz (p=0.039). The only significant group difference for the early time window (0‐200 ms) was found for 35‐40 Hz (p=0.046). The figure shows topographical plots of gamma (35‐40 Hz) power for 200‐400 ms time window in patients (upper part) and healthy controls (lower part) for angry, happy and neutral facial expressions. Conclusion The present study showed that the increase of late (200‐400 ms) gamma were independent of stimulus type in AD patients. The increase of gamma power in a 200‐400 ms time window was found in AD patients compared to healthy controls for all three facial expressions. The facial expression recognition in AD patients was differentiated from healthy controls by increased gamma power. Acknowledgments: This work (grant number 218S314) was supported by TUBITAK.

Age-related changes in Higuchi’s fractal dimension in healthy human EEG are anti-correlated with changes in oscillatory power and 1/f slope

“…For example, in depression, both HFD (Akar et al, 2015) and power (Strelets et al, 2007) in gamma band increases, indicating a positive correlation. Similarly, reduced HFD in AD (Smits et al, 2016) and increased gamma power during resting state (van Deursen et al, 2008; Güntekin et al, 2020; Fide et al, 2021) hint at a negative correlation. PCeske and colleagues surveyed several studies and found HFD to be negatively correlated with theta, alpha and beta band power but weakly positively related to gamma band power (Päeske et al, 2023).…”

Facial Expression Recognition Method Combined with Attention Mechanism

“…Information judgment is to study the conveyed meaning by facial expressions (such as happy, angry, or sad). Indication judgment is to study physical signals, which are used to convey information (such as raised cheeks or sunken lips) [15][16][17]. e main disadvantage of the information judgment method is that it cannot explain the full range of facial expressions.…”