Preliminary Evidence for Perturbation‐Based tACS‐EEG Biomarkers of Gamma Activity in Alzheimer's Disease

ABSTRACT Background Alzheimer's disease (AD) is characterized by impaired inhibitory circuitry and GABAergic dysfunction, which is associated with reduced fast brain oscillations in the gamma band (γ, 30–90 Hz) in several animal models. Investigating such activity in human patients could lead to the identification of novel biomarkers of diagnostic and prognostic value. The current study aimed to test a multimodal “Perturbation‐based” transcranial Alternating Current Stimulation‐Electroencephalography (tACS)‐EEG protocol to detect how responses to tACS in AD patients correlate with patients' clinical phenotype. Methods Fourteen participants with mild to moderate dementia due to AD underwent a baseline assessment including cognitive status, peripheral neuroinflammation, and resting‐state (rs)EEG. The tACS‐EEG recordings included brief (6′) tACS blocks of gamma (i.e., 40 Hz) stimulation administered through 4 different montages, with Pre/Post 32‐Channels EEG for each block. Changes in tACS‐EEG and rsEEG γ band power with respect to baseline were adopted as a metric of induction and compared with cognitive scores and neuroinflammatory biomarkers. Results We found positive correlations between 40 Hz‐induced γ activity in fronto‐central‐parietal areas and patient cognitive status and negative ones with neuroinflammatory markers. Participants with greater cognitive impairment exhibited less γ induction and higher peripheral neuroinflammation. The same analysis performed with spectral power from baseline rsEEG resulted in no significant correlations, promoting the value of tACS‐based perturbation for capturing individual differences in pathology‐related brain features. Conclusions Our work suggests a link between tACS‐induced γ band spectral power and clinical severity, with weaker γ induction corresponding to more severe clinical/cognitive impairment. This study provides preliminary support for the development of novel physiological biomarkers and therapeutic targets based on disease severity.