The Underestimated Utility of Resting-state Gamma Oscillations: Both Increase and Decrease of Gamma Discriminates Early-onset Alzheimer's Disease Patients From Healthy Individuals
Conditions: Alzheimer Disease, Early Onset
Sponsor: Görsev Yener, MD, PhD

07/25/2023 
 
THE UNDERESTIMATED UTILITY OF RESTING-STATE GAMMA 
OSCILLATIONS: BOTH INCREASE AND DECREASE OF GAMMA 
DISCRIMINATES EARLY-ONSET ALZHEIMER’S DISEASE PATIENTS FROM 
HEALTHY INDIVIDUALS 
 
 
 

STUDY PROTOCOL: 
● EEG Recording and Analysis 
Instructions Prior to Experiment and EEG Recording Environment 
·         Participants were asked not to consume any caffeine prior to experiments. 
·         EEG was recorded in a sound-attenuated and electrically shielded room. 
EEG Recording Setup 
- 
EEG was amplified using a BrainAmp 32-channel DC amplifier 
- 
EEG was bandpass-filtered between 0.03-70 Hz and digitized at a sampling rate of 
500 Hz (Brain Products GmbH; Gilching, Germany). 
- 
EEG was recorded from 30 Ag/AgCl electrodes (Figure 1). 
- 
Electrodes were positioned on an elastic cap according to the international 10-20 
system (EasyCap; Brain Products GmbH; Gilching, Germany). 
- 
All electrodes were referenced to linked earlobes (A1+A2). 
- 
Electrooculograms (EOG) were recorded from two additional electrodes. 
- 
Electrode impedances were kept below 10 kΩ. 
- 
EEG recordings were performed during morning hours (approximately between 09.00 
to 10.00 am) 
- 
EEG recordings lasted 8 minutes (4 minutes: eyes open & 4 minutes: eyes closed).  
 

 
 
Figure 1. Easycap layout for 30 Electrodes (EasyCap; Brain Products GmbH; Gilching, 
Germany) 
 
EEG Data Preprocessing 
Brain Vision Analyzer v.2.2 (Brain Products GmbH; Gilching, Germany) program was used 
for offline data analysis. EEG preprocessing was employed as below;  
- 
The continuous EEG data were resampled to a 256 Hz sampling rate.  
- 
A band-pass filter at 0.1 with a 12 dB/octave slope and a 50 Hz notch filter was 
applied.  
- 
Vertical and horizontal ocular artifacts were corrected with independent component 
analysis (ICA) with the Infomax algorithm using default parameters.  
- 
Four minutes eyes-closed recordings were segmented into six-second epochs.  

- 
Artifacts that still contaminated the EEG data (i.e., muscle artifacts and drowsiness) 
were semi-automatically rejected based on maximum voltage steps of 50 μV/ms, 
amplitudes exceeding ±70 μV, and activity below 0.5 μV parameters.  
Power Spectral Analysis  
A Fast Fourier Transform (FFT) was applied with  
- 
Maximum resolution power,  
- 
Non-complex output on full-spectrum,  
- 
10% Hanning window function  
Coherence Analysis 
- 
The Laplacian Current Source Density transformation with an 
order of splines 4, the maximal degree of Legendre 
polynomials 10 and 1 e−5 Lambda was applied.  
- 
The FFT with maximum resolution voltage, no window function, and complex output 
on the half spectrum was computed.  
- 
The imaginary part of coherency was used to evaluate connectivity between 
hemispheres, within hemispheres, and midline connectivity. 
● MRI Acquisition 
- 
Philips Achieva 1.5 Tesla scanner was used.  
- 
Scans were performed according to the Alzheimer’s disease Neuroimaging Initiative 
(ADNI, www.adni.loni.usc.edu).  
- 
The pre-processing of images was performed with the SPM12 software package.  
- 
The gray matter volumes and cortical thickness were obtained from the 3D-T1 
weighted TFE sequence (TR: 9ms, TE: 4ms, FOV: 240mm, matrix: 256, slice 
thickness: 1mm, NSA: 1).  
- 
Mean gray matter volumes (GMVs) inside ROIs were estimated using the LPBA40.  
- 
The total intracranial volume (TIV) for each participant is calculated and exported. 
GMVs were normalized according to each individual's TIV to remove the effect of 
different brain sizes.  
 

STATISTICAL ANALYSIS PLAN (SAP) 
● For EEG Analysis: 
The following EEG measures were analyzed using separate repeated-measures ANOVA 
including group as a between-group factor and different within-subject factors for;  
(1) the EEG power [anterior-posterior distribution (frontal, central, parietal, and occipital) 
and laterality (left, midline, and right)];  
(2) EEG intra-hemispheric ICoh measures [region (14-levels) and hemisphere (left and 
right)];  
(3) midline-to-lateral ICoh measures [midline region (4-levels), lateral region (8-levels) and 
hemisphere (2-levels);  
(4) midline-to-midline ICoh measures [midline region (3-levels)];  
(5) inter-hemispheric ICoh measures [region (10-levels)].  
All analyses were performed for total gamma and sub-gamma frequency bands.  
When Mauchly’s test indicated that the assumption of sphericity had been violated, the 
Greenhouse-Geisser correction was applied where ε < 0.75, and the Huynh-Feldt correction 
was applied where ε > 0.75 
● For EEG Analysis: 
GMV measures were analyzed with univariate ANOVA. Age and gender variables were 
included in the analysis as covariates. Bonferroni correction was applied for 54 GMV ROIs. 
The significance level was set to P < 0.0009. 
● For Correlations Analysis: 
Correlations between CSF, NPT, EEG, and MRI parameters were analyzed with Pearson 
correlation analysis. In order to minimize the number of false positives in correlation analysis, 
a Benjamin-Hochberg false discovery rate (FDR) was used to control the type-I error.  
● For Discriminant Analysis: 
The discriminant analysis was performed including the group as the dependent variable and a 
total of four independent variables (three electrode pairs from coherence and one electrode 
from power analysis) to the model. The analysis was performed with the enter method.