Abnormal neural oscillations depicting excitatory‐inhibitory imbalance are distinctly associated with amyloid and tau depositions in Alzheimer's disease. (December 2021)

• Record Type: Journal Article
• Authors: Ranasinghe, Kamalini G.; Verma, Parul; Cai, Chang; Xie, Xihe; Kudo, Kiwamu; Gao, Xiao; Lerner, Hannah M.; Mizuiri, Danielle; Strom, Amelia; Iaccarino, Leonardo; La Joie, Renaud; Miller, Bruce L.; Tempini, Maria Luisa Gorno; Rankin, Katherine P.; Jagust, William J.; Vossel, Keith A.; Rabinovici, Gil D.; Raj, Ashish; Nagarajan, Srikantan S.
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 4
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.055588
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Excitation‐to‐inhibition (E/I) imbalance is believed to be a key contributor of synaptic and network degeneration in Alzheimer's disease (AD)(Frere and Slutsky, 2018). Extensive preclinical research on transgenic animal models of AD have demonstrated neuronal and circuit level E/I imbalance mediated by amyloid‐beta (Aβ) and abnormally phosphorylated tau proteins (Harris et al., 2020; Palop and Mucke, 2016). However, the mechanisms of E/I imbalance leading to disrupted networks and their relationships to Aβ and tau in humans remain poorly understood. Method: In this multimodal imaging study in patients with AD (n=20 AD patients; n=35 age‐matched controls; Table‐1), we first examined the spectral changes in oscillatory brain rhythms using magnetoencephalography and their relationships to tau and amyloid‐beta (Aβ) accumulation in PET imaging (flortaucipir and 11C‐PiB, for tau and Aβ, respectively). Next, we estimated parameters of a linear neural mass model (Raj et al., 2020) that best fit the observed spectra, and examined the relationships between model parameters for excitatory and inhibitory neural sub‐populations, and tau and Aβ accumulations. Result: We found that neuronal hypoactivity was associated with tau while hyperactivity was associated with Aβ (Figure 1). We also demonstrated E/I imbalance in patients with AD, depicted as abnormal excitatory and inhibitory neuronal parameters in a linear neural mass model that reproduced the empirical macroscopic power spectra (Figure 2). The abnormal excitatory and inhibitory neuronal parameters showed distinct associations with tau and Aβ—higher tau correlated with a longer excitatory time‐constant, whereas higher Aβ correlated with a longer inhibitory time‐constant (Figure 3). Conclusion: The unique contribution of the collective finding in the current study is to demonstrate how abnormalities in the oscillatory power spectrum in AD is mechanistically linked to impaired function of excitatory and inhibitory neuronal populations that are in turn associated with tau and Aβ accumulations. Neural oscillations are modulators of rate and timing of neuronal spiking and have a key role in governing the neuronal excitability (Siegel et al., 2012). The multimodal neuroimaging in AD patients in the current study demonstrate how different frequency oscillations are distinctly affected by Aβ and tau, and offer new perspectives for network stabilizing therapies.