Bispectral EEG (BSEEG) quantifying neuro-inflammation in mice induced by systemic inflammation: A potential mouse model of delirium

Autor: Koichi Kaneko, Brandon A. Toth, Kasra Zarei, Uday Singh, Masaaki Iwata, Kalvon T. Steffen, Gordon F. Buchanan, Huxing Cui, Gen Shinozaki, Benton S. Purnell, Hyunkeun Ryan Cho, Rui Li, Shelley Lee, Michael E. Dailey, Johnny R. Malicoat, Kenji Saito, Annice Najafi, Takehiko Yamanashi
Rok vydání: 2021
Předmět:
Zdroj: Journal of Psychiatric Research. 133:205-211
ISSN: 0022-3956
DOI: 10.1016/j.jpsychires.2020.12.036
Popis: Most of the animal studies using inflammation-induced cognitive change have relied on behavioral testing without objective and biologically solid methods to quantify the severity of cognitive disturbances. We have developed a bispectral EEG (BSEEG) method using a novel algorithm in clinical study. This method effectively differentiates between patients with and without delirium, and predict long-term mortality. In the present study, we aimed to apply our bispectral EEG (BSEEG) method, which can detect patients with delirium, to a mouse model of delirium with systemic inflammation induced by lipopolysaccharides (LPS) injection. We recorded EEG after LPS injection using wildtype early adulthood mice (2~3-month-old) and aged mice (18-19-month-old). Animal EEG recordings were converted for power spectral density to calculate BSEEG score using the similar BSEEG algorithm previously developed for our human study. The BSEEG score was relatively stable and slightly high during the day. Alternatively, the BSEEG score was erratic and low in average during the night. LPS injection increased the BSEEG score dose-dependently and diminished the diurnal changes. The mean BSEEG score increased much more in the aged mice group as dosage increased. Our results suggest that BSEEG method can objectively "quantify" level of neuro-Inflammation induced by systemic inflammation (LPS), and that this BSEEG method can be useful as a model of delirium in mice.
Databáze: OpenAIRE