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Gamma Power during Working Memory in Pre‐symptomatic Alzheimer’s Disease Differs from Normal Healthy Aging
Author(s) -
Arakaki Xianghong,
Liu Quanying,
Fonteh Alfred N,
Harrington Michael G
Publication year - 2020
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2020.34.s1.04743
Subject(s) - working memory , workload , psychology , audiology , medicine , electroencephalography , neuroscience , cognition , computer science , operating system
Background and Objectives Gamma power reduction has been reported in Alzheimer’s disease (AD), and gamma stimulation helps remove amyloid/tau in a preclinical AD model. We hypothesized that gamma power during N‐back working memory testing in pre‐symptomatic AD individuals is lower than in healthy aging, and that gamma power will correlate with n‐back performance. Methods Brain gamma power from elderly study participants were measured during working memory testing with different workload: participants were presented a series of letters and asked to identify letter ‘X’ (0‐back, low workload) or to identify the letter that same as shown 2 letters ago (2‐back, high workload). Participants consisted of two subgroups from cerebrospinal fluid proteins: c ognitively h ealthy with n ormal CSF a myloid/ t au ratio (CH‐NAT, n=10) or p athological CSF a myloid/ t au ratio (CH‐PAT, or pre‐symptomatic AD, n=14) between 63–94 years of age. We compared gamma power, including low gamma band (30–50Hz) and high gamma band (50–80Hz) between two CH groups from electroencephalogram (EEG) at six brain regions including frontal (F); central (C), parietal (P), left temporal (LT), right temporal (RT), and occipital (O) regions. Preprocessing steps included epoching, filtering, re‐referencing, large artifact removal, and time‐frequency analysis. We used simple student two‐sided t‐test to compare gamma power between two groups, and Pearson's linear correlation for the relationship between gamma power and behavioral performance (accuracy (ACC) and response time (RT)). Since this was an exploratory study, a significance level of 0.05 was used for all tests. Results & Discussion During 0‐back compared to CH‐NATs, low gamma in CH‐PATs is higher over F,C regions (p=0.014~0.032). However during 2‐back, low gamma in CH‐PATs is lower over T3,T4 sensors (p=0.044 and 0.028, respectively), and high gamma is lower in P region (p=0.035), compared to CH‐NATs. In addition, only in CH‐NATs low gamma during 2‐back is positively correlated with 0‐back accuracy over F,C,P,LT,RT regions (p=0.0098~0.027, r=0.69~0.77); high gamma during 2‐back is positively correlated with 0‐back accuracy over all regions (p=0.007~0.030, r=0.68~0.78). High gamma during 2‐back is negatively correlated with 0‐back response time over P,RT,O regions (p=0.025~0.037, r=−0.70~−0.66). These results suggest that gamma is compromised in the pre‐symptomatic AD stage. The correlations of gamma with 0‐back accuracy in CH‐NATs but not CH‐PATs indicate gamma played a critical part of performing working memory test (most significantly in the frontal region); we interpret this as diminished capability to hold the testing goal with all other regions involved in CH‐PATs compared to CH‐NATs. Our study further supports a compromised frontal function in pre‐symptomatic AD. The results also support further study of the relationship between gamma and low frequency band power (such as alpha and theta) in pre‐symptomatic AD. Support or Funding Information Acknowledgment Financial support provided by the L.K.Whittier Foundation, NIH R56 Funding 1R56AG063857‐01. Betty Chung and David Buennagel assisted with patient recruitment.