Oscillatory and aperiodic neuronal activity in working memory following anesthesia

The effect of aperiodic components in distinguishing Alzheimer's disease from frontotemporal dementia

Distinguishing between Alzheimer's disease (AD) and frontotemporal dementia (FTD) presents a clinical challenge. Inexpensive and accessible techniques such as electroencephalography (EEG) are increasingly being used to address this challenge. In particular, the potential relevance between aperiodic components of EEG activity and these disorders has gained interest as our understanding evolves. This study aims to determine the differences in aperiodic activity between AD and FTD and evaluate its potential for distinguishing between the two disorders. A total of 88 participants, including 36 patients with AD, 23 patients with FTD, and 29 healthy controls (CN) underwent cognitive assessment and scalp EEG acquisition. Neuronal power spectra were parameterized to decompose the EEG spectrum, enabling comparison of group differences in different components. A support vector machine was employed to assess the impact of aperiodic parameters on the differential diagnosis. Compared with the CN group, both the AD and FTD groups showed varying degrees of increased alpha power (both periodic and raw power) and theta alpha power ratio. At the channel level, theta power (both periodic and raw power) in the frontal regions was higher in the AD group compared to the FTD group, and aperiodic parameters (both exponents and offsets) in the frontal, temporal, central, and parietal regions were higher in the AD group than in the FTD group. Importantly, the inclusion of aperiodic parameters led to improved performance in distinguishing between the two disorders. These findings highlight the significance of aperiodic components in discriminating dementia-related diseases.

Impact of Intraoperative Fluctuations of Cardiac Output on Cerebrovascular Autoregulation: An Integrative Secondary Analysis of Individual-level Data

BACKGROUND

Intraoperative impairment of cerebral autoregulation (CA) has been associated with perioperative neurocognitive disorders. We investigated whether intraoperative fluctuations in cardiac index are associated with changes in CA.

METHODS

We conducted an integrative explorative secondary analysis of individual-level data from 2 prospective observational studies including patients scheduled for radical prostatectomy. We assessed cardiac index by pulse contour analysis and CA as the cerebral oxygenation index (COx) based on near-infrared spectroscopy. We analyzed (1) the cross-correlation between cardiac index and COx, (2) the correlation between the time-weighted average (TWA) of the cardiac index below 2.5 L min-1 m-2, and the TWA of COx above 0.3, and (3) the difference in areas between the cardiac index curve and the COx curve among various subgroups.

RESULTS

The final analysis included 155 patients. The median cardiac index was 3.16 [IQR: 2.65, 3.72] L min-1 m-2. Median COx was 0.23 [IQR: 0.12, 0.34]. (1) The median cross-correlation between cardiac index and COx was 0.230 [IQR: 0.186, 0.287]. (2) The correlation (Spearman ρ) between TWA of cardiac index below 2.5 L min-1 m-2 and TWA of COx above 0.3 was 0.095 (P=0.239). (3) Areas between the cardiac index curve and the COx curve did not differ significantly among subgroups (<65 vs. ≥65 y, P=0.903; 0 vs. ≥1 cardiovascular risk factors, P=0.518; arterial hypertension vs. none, P=0.822; open vs. robot-assisted radical prostatectomy, P=0.699).

CONCLUSIONS

We found no meaningful association between intraoperative fluctuations in cardiac index and CA. However, it is possible that a potential association was masked by the influence of anesthesia on CA.